configuration management process maturity: …

CONFIGURATION MANAGEMENT PROCESS MATURITY:

DEFINITION AND MATURATION OF CONFIGURATION

MANAGEMENT FOR AEROSPACE AND DEFENCE

INDUSTRIES

A thesis submitted to The University of Manchester for the degree of

Doctor of Philosophy (PhD)

in the Faculty of Engineering and Physical Sciences

2014

Usman Ali

School of Mechanical, Aerospace and Civil Engineering

2

TABLE OF CONTENTS

TABLE OF CONTENTS ................................................................................................... 2

LIST OF FIGURES ........................................................................................................... 7

LIST OF TABLES ............................................................................................................. 9

ABSTRACT ..................................................................................................................... 12

DECLARATION ............................................................................................................. 13

COPYRIGHT STATEMENT .......................................................................................... 14

LIST OF PUBLICATIONS ............................................................................................. 15

ACKNOWLEDGEMENT ............................................................................................... 16

ABBREVIATIONS ......................................................................................................... 17

CHAPTER 1: INTRODUCTION .................................................................................... 19

1.0 Research overview ........................................................................................... 19

1.1 Research problem ............................................................................................. 21

1.2 Research aims and objectives........................................................................... 22

1.3 Research questions ........................................................................................... 23

1.4 Research hypothesis ......................................................................................... 24

1.5 Research strategy ............................................................................................. 25

1.6 Structure of the thesis ....................................................................................... 26

CHAPTER 2: LITERATURE REVIEW ......................................................................... 29

2.0 Introduction ...................................................................................................... 29

2.1 Configuration Management (CM).................................................................... 29

2.1.1 History of CM .............................................................................................. 32

2.1.2 Elements of CM ........................................................................................... 35

2.1.3 CM in Quality perspective ........................................................................... 53

2.1.4 Management of design process with CM ..................................................... 54

2.1.5 CM impacts on customer’s support and satisfaction.................................... 55

Table of contents

3

2.1.6 CM and products reliability and maintainability ......................................... 57

2.1.7 CM activity model ....................................................................................... 58

2.2 Critical success factors and related CM literature............................................ 59

2.3 Barriers to CM implementation ....................................................................... 64

2.4 Maturity models ............................................................................................... 67

2.4.1 SEI maturity models ..................................................................................... 69

2.4.2 CM Capability Model for the medical device industry ................................ 85

2.4.3 Limitation of CM related maturity models .................................................. 87

2.4.4 Research on maturity models in other allied fields ...................................... 88

2.5 Literature search strategy ................................................................................. 98

2.5.1 Keywords ..................................................................................................... 98

2.5.2 Search engines .............................................................................................. 98

2.6 Summary and conclusions ............................................................................... 99

2.6.1 Summary ...................................................................................................... 99

2.6.2 Conclusions ................................................................................................ 101

CHAPTER 3: RESEARCH DESIGN AND METHODOLOGY .................................. 103

3.0 Introduction .................................................................................................... 103

3.1 Research aim and objectives .......................................................................... 104

3.2 Research process ............................................................................................ 104

3.3 Research design and methodology. ................................................................ 107

3.3.1 Research philosophy .................................................................................. 107

3.3.2 Research approaches .................................................................................. 110

3.3.3 Research strategies / methods .................................................................... 117

3.3.4 Research choices ........................................................................................ 119

3.3.5 Time horizon .............................................................................................. 120

3.3.6 Data collection methods / techniques ......................................................... 121

3.3.7 The credibility of research findings ........................................................... 131

3.4 Summary ........................................................................................................ 133

CHAPTER 4: IDENTIFICATION AND ANALYSIS OF CM CSFs ........................... 135

4.0 Introduction .................................................................................................... 135

Table of contents

4

4.1 Research objectives ........................................................................................ 136

4.2 Research methodology ................................................................................... 137

4.3 Findings, analysis, and discussion ................................................................. 138

4.3.1 Descriptive statistics................................................................................... 138

4.3.2 Categorization of CSFs .............................................................................. 141

4.3.3 Inferential statistic ...................................................................................... 145

4.3.4 CM activity model ..................................................................................... 153

4.3.5 Interpretation of CM CSFs groups ............................................................. 155

4.4 Summary and conclusions ............................................................................. 161

4.4.1 Summary .................................................................................................... 161

4.4.2 Conclusions ................................................................................................ 162

CHAPTER 5: BARRIERS AND GOVERNANCE OF THE CM PROCESS .............. 164

5.0 Introduction .................................................................................................... 164

5.1 Research objectives ........................................................................................ 165


5.3 Analysis and discussion ................................................................................. 167

5.3.1 Barriers to Configuration Management implementation ........................... 167

5.3.2 Governance of the Configuration Management process ............................ 189


5.4.1 Barriers in the implementation of CM process .......................................... 195

5.4.2 Governance of CM Process ........................................................................ 196

CHAPTER 6: ANALYSIS OF BARRIERS TO CM IMPLEMENTATION ................ 197

6.0 Introduction .................................................................................................... 197

6.1 Objectives of the research .............................................................................. 198


6.3 Findings, analysis, and discussion ................................................................. 199

6.3.1 Descriptive statistics................................................................................... 199

6.3.2 Factor analysis (categorization of the barriers to CM implementation) .... 203

6.3.3 Inferential statistic ...................................................................................... 209

6.3.4 Interpretation of CM barriers groups ......................................................... 216

Table of contents

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6.4.1 Summary .................................................................................................... 223

6.4.2 Conclusions ................................................................................................ 224

CHAPTER 7: CONFIGURATION MANAGEMENT MATURITY MODEL ............ 227

7.0 Introduction .................................................................................................... 227

7.1 Research Objective......................................................................................... 228

7.2 Research Methodology................................................................................... 229

7.3 Configuration Management Maturity Model ................................................. 230

7.3.1 Identification of key process capabilities ................................................... 231

7.3.2 Establishing goals ...................................................................................... 233

7.3.3 Composition of CMMM ............................................................................ 233

7.3.4 Key focus areas of CMMM........................................................................ 238

7.3.5 Measuring the level of maturity ................................................................. 239

7.4 Validation of CMMM .................................................................................... 249

7.5 CM process maturity ...................................................................................... 256

7.5.1 Level of maturity of Configuration Management practices ....................... 256

7.5.2 Hypothesis validation ................................................................................. 258


7.6.1 Summary .................................................................................................... 260

7.6.2 Conclusions ................................................................................................ 261

CHAPTER 8: SUMMARY, CONCLUSIONS AND RECOMMENDATIONS .......... 263

8.0 Introduction .................................................................................................... 263

8.1 Summary of the research ................................................................................ 263

8.2 Conclusions .................................................................................................... 267

8.2.1 CSFs for the effective implementation of Configuration Management ..... 268

8.2.2 Barriers to Configuration Management implementation ........................... 269

8.2.3 Governance of the Configuration Management process ............................ 271

8.2.4 Configuration Management Maturity Model ............................................. 271

8.3 Limitations of the study ................................................................................. 273

8.4 Contribution of this research .......................................................................... 273

Table of contents

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8.4.1 Academic perspective ................................................................................ 274

8.4.2 Industrial perspective ................................................................................. 276

8.5 Research application ...................................................................................... 277

8.6 Recommendations and further research ......................................................... 278

REFERENCES ............................................................................................................... 280

Appendix A .................................................................................................................... 296

Appendix B .................................................................................................................... 305

Appendix C .................................................................................................................... 308

Appendix D .................................................................................................................... 315

Appendix E .................................................................................................................... 318

Appendix F ..................................................................................................................... 324

7

LIST OF FIGURES

Figure 1-1: The CM Process Ladder (Watt, 2010) .......................................................... 20

Figure 2-1: Configuration Management defined (Watt, 2008; Watt, 2010) .................... 30

Figure 2-2: Configuration Management process model (MIL-HDBK-61, 1997)............ 37

Figure 2-3: Configuration Management identification (MIL-HDBK-61, 1997) ............. 40

Figure 2-4: Detail of baselines (MIL-HDBK-61, 1997) .................................................. 44

Figure 2-5: Product generic phases and baselines (Robert, 2004) ................................... 44

Figure 2-6: Product development cycle (Samaras, 1988) ................................................ 45

Figure 2-7: Life cycle of MoD project (Lester, 2007) ..................................................... 46

Figure 2-8: Simple Change Process (Rowell et al., 2009) ............................................... 48

Figure 2-9: Principles of Change Management System (Ibbs et al., 2001) ..................... 49

Figure 2-10: Statistics of research on members of CCB (Huang and Mak, 1999) .......... 50

Figure 2-11 : Lack of control and its impact on cost (Boznak, 1990a) ............................ 57

Figure 2-12: History of CMMs (Team, 2006) ................................................................. 71

Figure 2-13 : Five levels of SW-CMM (Paulk, Curtis et al. 1993) .................................. 72

Figure 2-14: SE-CMM Model architecture (Bate et al., 1995) ........................................ 77

Figure 2-15 : Improvement path for process capability (Bate et al., 1995) ..................... 77

Figure 2-16: Capability level-1 engineering (Bate et al., 1995) ...................................... 79





Figure 2-21 : Maturity levels of CoPS-RM-CMM (Yeo and Ren, 2009) ........................ 91

Figure 2-22: The four levels of risk maturity (Hillson, 1997) ......................................... 92

Figure 2-23: (PM) 2 model (Kwak and Ibbs, 2006) ......................................................... 94

Figure 2-24: Project Management Maturity Model (Crawford, 2006) ............................ 97

Figure 3-1: The research onion (Saunders et al., 2009) ................................................. 103

Figure 3-2: Research process flowchart ......................................................................... 106

Figure 3-3: Population, sample, and individual cases (Saunders et al., 2003) ............... 127

List of figures

8

Figure 3-4: Sampling techniques (Saunders et al., 2003). ............................................. 128

Figure 4-1: Details of CSFs groups ................................................................................ 143

Figure 4-2: Configuration Management Activity Model ............................................... 155

Figure 6-1: Screeplot, total variance associated with each barrier ................................. 204

Figure 6-2: Three groups of barriers to CM implementation ......................................... 206

Figure 7-1: Configuration Management process capabilities ........................................ 232

Figure 7-2: Configuration Management Maturity Model .............................................. 234

Figure 7-3: Experience of research participants under different categories .................. 251

9

LIST OF TABLES

Table 2-1: CM success factors (areas of importance) ...................................................... 61

Table 2-2: PM CSFs identified across 63 publications (Fortune and White, 2006) ........ 62

Table 2-3: List of PM CSFs (Belassi and Tukel, 1996) ................................................... 63

Table 2-4: List of PM CSFs (Belassi and Tukel, 1996) ................................................... 64

Table 2-5: List of key process areas of SW-CMM (Paulk et al., 1993) ........................... 74

Table 2-6: Capability levels with their common features (Bate et al., 1995) .................. 78

Table 2-7: SE-CMM Process Categories and Process Areas (Bate et al., 1995) ............. 79

Table 2-8 : Details of process areas (TEAM, 2006) ........................................................ 84

Table 2-9 : Capability and maturity levels (TEAM, 2006) .............................................. 85

Table 2-10 : Comparison of CM activities in Medical Device Industry and CMMI

(McCaffery et al., 2008) ................................................................................................... 86

Table 2-11: Maturity stage dimension (Niazi et al., 2005) .............................................. 90

Table 2-12: Critical Success Factors dimension (Niazi et al., 2005) ............................... 90

Table 2-13: Capability Areas of CoPS-RM-CMM (Yeo and Ren, 2009) ....................... 91

Table 2-14: Key PM Processes of (PM) 2 model (Kwak and Ibbs, 2006) ....................... 95

Table 2-15: Major organizational characteristics of (PM) 2

model (Kwak and Ibbs, 2006)

.......................................................................................................................................... 95

Table 2-16: Key focus areas of (PM) 2 model (Kwak and Ibbs, 2006) ............................ 96

Table 3-1: Alternative terms for positivist and phenomenological paradigms (Mangan et

al., 2004)......................................................................................................................... 108

Table 3-2: Key features of the positivist and phenomenological paradigms (Easterby-

Smith et al., 1991). ......................................................................................................... 109

Table 3-3: Classification of the main types of research (Hussey and Hussey, 1997) .... 111

Table 3-4: Differences between deductive and inductive approaches (Saunders et al.,

2003) .............................................................................................................................. 115

Table 3-5: Differences between qualitative and quantitative methods (Ghauri and

Gronhaug, 2005) ............................................................................................................ 116

Table 4-1: List of Critical Success Factors .................................................................... 140

List of tables

10

Table 4-2: Correlation matrix......................................................................................... 142

Table 4-3: Total variance ............................................................................................... 144

Table 4-4: Parallel analysis ............................................................................................ 144

Table 4-5: Comparison of actual eigenvalues with corresponding criterion values ...... 145

Table 4-6: Test of normality .......................................................................................... 148

Table 4-7: Significance of CSFs with academic qualification ....................................... 149

Table 4-8: Mean Rank for academic qualification ......................................................... 149

Table 4-9: Significance of CSFs with CM certification / training ................................. 150

Table 4-10: Mean ranks for CM training ....................................................................... 151

Table 4-11: Significance of CSFs with experience in CM ............................................ 151

Table 4-12: Mean ranks for CM experience .................................................................. 152

Table 4-13: Significance of CSFs with experience in Stakeholder Departments .......... 152

Table 4-14: Mean ranks for experience in stakeholder departments ............................. 153

Table 6-1: Barriers to CM implementation .................................................................... 202

Table 6-2: KMO and Bartlett's Test results ................................................................... 203

Table 6-3: Total Variance Explained ............................................................................. 205

Table 6-4: Correlation matrix for CM barriers .............................................................. 207

Table 6-5: Group of matrix after Varimax rotation ....................................................... 208

Table 6-6: Final statistics of principle component analysis ........................................... 208


Table 6-8: Significance of barriers to CM implementation with academic qualification

........................................................................................................................................ 212

Table 6-9: Mean Rank for academic qualification ......................................................... 213

Table 6-10: Significance of barriers to CM implementation with gender differences .. 213

Table 6-11: Mean Rank for gender differences ............................................................. 214

Table 6-12: Significance of barriers to CM implementation with CM experience........ 214

Table 6-13: Mean Rank for CM experience .................................................................. 215

Table 6-14: Significance of barriers to CM implementation with organizational types 215

Table 6-15: Mean Rank for organizational types ........................................................... 216

Table 7-1: Five point scale in three groups .................................................................... 250

List of tables

11

Table 7-2: Expert opinion on different aspects of Configuration Management Maturity

Model ............................................................................................................................. 252

Table 7-3: Mean values of defence sectors .................................................................... 257


Table 7-5: Group statistics ............................................................................................. 259

Table 7-6: Independent samples test .............................................................................. 259

Table 8-1: Research focus in different research parts .................................................... 264

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ABSTRACT

Name of the University: The University of Manchester

Submitted by: Usman Ali

Degree Title: Doctor of Philosophy

Thesis Title: Configuration Management Process Maturity: Definition and Maturation

of Configuration Management for Aerospace and Defence Industries

Date: 28th

February 2014

This research focuses on the effective implementation and continuous improvement

methodologies for Configuration Management practices within aerospace and defence

industries. The research is conducted mainly to develop a Configuration Management

Maturity Model which is based on Critical Success Factors and Barriers to

Configuration Management implementation. The motives behind this research were the

lack of understanding and problems in the implementation of high-grade Configuration

Management systems as highlighted by other researchers.

The research is conducted in three phases through interviews and questionnaire surveys

with experienced Configuration Management professionals working in aerospace and

defence industries. The first part of this research identifies, prioritizes, and categorizes

the Critical Success Factors for Configuration Management and devises a Configuration

Management Activity Model to help practationers in the effective implementation and

continuous improvement of the process. The second part of the research sets out to

identify and prioritize the obstacles to effective implementation of Configuration

Management practices, categorized these obstacles into more manageable groups of

factors, and analysed the effects of multiple factors on identification and rating of these

barriers. Both studies were conducted through mixed method research with in-depth

interviews followed by questionnaire surveys. The governance aspect of the process is

also investigated to a great deal in the second part through interviews to conclude on

process governance in various setups.

The third part of this research is related to the development of a Configuration

Management Maturity Model. It is important to note that other maturity models on the

topic are generic in nature and emphasis on ‘what’ to implement instead of ‘how’ to

implement which has left a gap of uncertainty that forced us to devise a suitable

framework. The Configuration Management Maturity Model is an assessment tool

which not only provides benchmark information but also helps to identify the strengths

and weaknesses of the process. This maturity framework is unique in its presentation

and unlike previous maturity models, is based on current Configuration Management

practices, Critical Success Factors, and Barriers to Configuration Management

implementation. This maturity model will help organizations to assess their current level

of maturity, identify rational targets for improvements, and will help in providing action

plans for enhancing their configuration management process capability. Like the

previous two studies, this part of the research is conducted through semi-structured

interviews followed by questionniare surveys.

13

DECLARATION

No portion of the work referred to in the thesis has been submitted in support of an

application for another degree or qualification of this or any other university or other

institute of learning.

14

COPYRIGHT STATEMENT

i. The author of this thesis (including any appendices and/ or schedules to this thesis)

owns certain copyright or related rights in it (the “Copyright”) and s/he has given

The University of Manchester certain rights to use such Copyright, including for

administrative purposes.

ii. Copies of this thesis, either in full or in extracts and whether in hand or electronic

copy, may be made only in accordance with the Copyright, Designs and Patents Act

1988 (as amended) and regulations issued under it or, where appropriate, in

accordance with licensing agreements which the University has from time to time.

This page must form part of any such copies made.

iii. The ownership of certain Copyright, patents, designs, trade marks and other

intellectual property (the “Intellectual Property”) and any reproductions of copyright

works in the thesis, for example graphs and tables (“Reproductions”), which may be

described in this thesis, may not be owned by the author and may be owned by third

parties. Such Intellectual Property and Reproductions cannot and must not be made

available for use without the prior written permission of the owner(s) of the relevant

Intellectual Property and/or Reproductions.

iv. Further information on the conditions under which disclosure, publication and

commercialisation of this thesis, the Copyright and any Intellectual Property and/or

Reproductions described in it may take place is available in the University IP policy

(see http://documents.manchester.ac.uk/DocuInfo.aspx?DocID=487), in any relevant

Thesis restriction declarations deposited in the University Library, The University

Library’s regulations (see http://www.manchester.ac.uk/library/aboutus/regulations)

and in The University’s policy on Presentation of Theses.

15

LIST OF PUBLICATIONS

A) Refereed Journal Papers

1. Ali, U., Kidd, C. (2014). Barriers to effective configuration management

application in a project context; an empirical investigation. International

Journal of Project Management, 32(3), 508-518.

2. Ali, U., Kidd, C. (2013). Critical success factors for configuration management

implementation. Industrial Management & Data Systems, 113(2), 250-264.

3. Ali, U., Kidd, C. (2013). Configuration Management Maturation, an Empirical

Investigation. Proceedings of the Institution of Mechanical Engineers, Part

B: Journal of Engineering Manufacture (accepted for publication)

B) Refereed Conference Papers

1. Ali, U., Kidd, C. (2012). Understanding the obstacles to configuration

management success. 26th

IPMA World Congress, Greece.

2. Ali, U., Kidd, C. (2013). Configuration Management Process Capabilities.

Procedia CIRP, 11, 169-172.

16

ACKNOWLEDGEMENT

I am grateful to almighty Allah for giving me the strength and ability to successfully

complete this research work. Without Allah’s countless blessings and mercy, none of

this would have been possible.

I owe my deepest gratitude to so many people whose help, guidance, support,

contribution, and invaluable assistance provided me the opportunity for timely

completion of my PhD research.

I have no words to thank and pay my gratitude to my mother for her unending love,

prayers, undivided support, interest and encouragement. Without her inspiration,

prayers, love, and encouragement; none of my achievements would have been possible. I

would like to thank to my brothers and sisters for their support, help and prayers for my

success. I also wish to express my love and gratitude to my wife for her patience,

support, and understanding throughout my research.

I would like to express my appreciation and thanks to Mr Callum Kidd and Dr. Robert

Young for their motivation, abundant help, and incessant guidance. It is because of their

motivation, tremendous contribution, and continuous support which helped me in the

successful completion of this research.

My thanks also goes to my colleagues back home especially Tahira Kalsoom, Ashfaq

Ahmed, Gulistan Khan, Syed Muddasar Gillani, Naseer Ahmed and Shaikha AlSanad,

Dr. Khalid Mahmood, Dr. Ashfaq Khan, Abdulrahman Alghamdi at The University of

Manchester whose support and companionship made my stay comfortable and helped

me in the accomplishment of my research. I also extend my special thanks to all my

friends and well wishers whose support and guidance has been instrumental in

completion of my PhD but I failed to mention their names.

I would also like to convey my special thanks to Higher Education Commission (HEC)

of Pakistan for providing me the opportunity in pursuing my studies.

17

ABBREVIATIONS

ACM Association of Configuration Managers

ANA Army, Navy, and Air Force

CCB Configuration Control Board

CDR Critical Design Review

CIs Configuration Items

CM Configuration Management

CMM Capability Maturity Model

CMMI Capability Maturity Model Integration

CMPIC Configuration Management Process Improvement Centre

CoPS-RM-CMM Risk Management Capability Maturity Model for Complex

Product Systems

CPD Continuing Professional Development

CSA Configuration Status Accounting

CSFs Critical Success Factors

DoD Department of Defence

ECOs Engineering Change Orders

ECPs Engineering Change Proposals

EIA Electronic Industries Alliance

ERP Enterprise Resource Planning

FCA Functional Configuration Audit

HW Hardware

IEEE Institute of Electrical and Electronics Engineers

IPD-CMM Integrated Product Development Capability Maturity Model

IPPD Integrated Product and Process Development

ISO International Organization for Standardization

IT Information Technology

KM Knowledge Management

KPA Key Process Areas

MIL-STD Military Standard

MoD Ministry of Defence

Abbreviations

18

NASA National Aeronautics and Space Administration

PCA Physical Configuration Audit

PDM Product Data Management

PLM Product Lifecycle Management

PM Project Management

(PM)2 Project Management Process Maturity

PMBoK Project Management Body of Knowledge

PMI Project Management Institute

QM Quality Management

SDR System Design Review

SE-CMM Systems Engineering Capability Maturity Model

SEI Software Engineering Institute

SPI Software Process Improvements

SSR Software Specification Review

SW Software

SW-CMM Capability Maturity Model for Software

TQM Total Quality Management

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CHAPTER 1

INTRODUCTION

1.0 Research overview

Achieving process excellence is not a short term goal but takes time through incremental

and progressive improvement methodologies. It is only through enormous efforts, great

dedication and planning which helps organizations to achieve their objectives. Leading

industries of the world dominate the market by launching state-of-the-art products and

enhance customer satisfaction through continuous improvement in quality of their

products. The production of such products by these industries is only possible through

organized processes run by dedicated, efficient and trained work force. It is pertinent to

note that industries which produce quality products have excellent processes in terms of

planning, product design & development, engineering, manufacturing, marketing and

administration (Toro and McCabe, 1997).

Extensive literature is available on process improvement methodologies in the form of

maturity models. The concept of process maturity was rationalized by Crosby (1997)

through the development of five layers quality management maturity grid to help

managers in maturing their quality processes. Deming (1986) and Juran (1988)

highlighted the significance of this concept through their works on continuous process

improvement practices for the development of quality management system. The concept

was further signified by Radice et al. (1985) through developing maturity model within

IBM and Humphrey (1989) through a five layers process maturity framework in

software organizations. The software engineering institute at Carnegie Mellon

University further developed the concept by introducing various maturity models.

This concept is not limited to any specific industry or field but its significance is evident

from extensive literature in diverse areas such as Project Management (e.g. Crawford,

Chapter 1: Introduction

20

2006; Jugdev and Thomas, 2002; Kwak and Ibbs, 2002), Risk Management (e.g.

Hillson, 1997; Yeo and Ren, 2008), Requirements Engineering (e.g. Beecham et al.,

2005), safety (e.g. Filho et. al., 2010), Knowledge Management (e.g. Kulkarni and

Freeze, 2004; Paulzen and Perc, 2002), and IT (e.g. Gottschalk and Solli-Sæther, 2006)

etc. Moreover, around 150 business maturity models are available in the market (Spanyi,

2004)) whereas 30 alone are evident in the field of Project Management (Grant and

Pennypacker, 2006).

Figure 1-1: The CM Process Ladder (Watt, 2010)


21

It is important to highlight that Configuration Management (CM) has remained an

integral part of the Capability Maturity Model for Software (e.g. Paulk et. al., 1993),

Systems Engineering Capability Model (e.g. Bate et al., 1995), and Capability Maturing

Model Integration (e.g. Team, 2006). The study of McCaffery and Coleman (2007)

highlight the maturity of Configuration Management process in medical device

industries while Watt (2010) pointed towards the maturity ladder (figure 1-1) while

formulating the measuring methodologies for continuous improvements of the process.

The process improvement methodologies in the form of maturity models highlighted by

these studies are tenable but have specific limitations in its own. Such models, if

generated through valid requirements could be an effective tool for progressive

improvements of the process. These models are useful only if detailed practices at each

level are known and have adequate measuring methodologies.

1.1 Research problem

Configuration Management is never practiced to its full potential and is always

undermined at all levels of organizations and implemented in a haphazard way which are

the main problems to its effective implementation and continuous development faced by

industries (Burgess et al. 2005). It is important to note that since the literature in the field

of CM is extremely limited as compared to other allied fields, professionals in the field

have never benefited from advancement in process improvements methodologies made

over the years in other allied fields like Project Management, Knowledge Management,

and Quality Management. Literature suggest that processes can be largely facilitated by

identifying process related critical success factors and barriers to its implementation and

defining path of maturation based on these factors as highlighted by Niazi et al. (2005)

and Yeo and Ren (2008). To help professional in the field, this research is targeted on

multiple issues with core objective is to enhance the applications of CM in both

aerospace and defence industries.

Detailed search of the peer reviewed journals and practitioner’s literature highlight no

formal study on critical success factors and barriers in the field of Configuration


22

Management which are the basic requirements for developing maturity models as

highlighted by Niazi et al. (2005) and Yeo and Ren (2008). The importance of research

on Critical Success Factors and barriers is evident from extensive research in other allied

professional activities like Project Management (PM), Quality Management (QM) and

Knowledge Management (KM). There are more than seventy studies highlighted on

Critical Success Factors in PM by Fortune and White (2006); Belassi and Tukel (1996),

and Baccarini and Collins (2003) while seven within Knowledge Management by Wong

(2005) whereas the studies of Bhat and Rajashekhar (2009) and Sebastianelli and

Tamimi (2003) in Quality Management, Riege (2005) and Sun and Scott (2006) in

Knowledge Management, Atkinson et al. (2006) in Project Management , and Da-Silva

(2012) in Business Process Management shows the importance of research on barriers.

The studies on maturity models related to Configuration Management (e.g. Bate et al.,

1995; McCaffery and Coleman, 2007; Paulk et. al., 1993; and Team, 2006) proposes a

standardized approach for maturity but recent studies (e.g. Niazi et al., 2005; Yeo and

Ren, 2008) recommends that maturity models should be based on critical success factors

and barriers. This approach seems logical since the implementation requirements and

improvement priorities for Configuration Management could never be the same for other

disciplines (e.g. requirements management, risk management, and product integration)

and can only be fixed through CM specific critical success factors and barriers.

Moreover the maturity guidelines are generic in nature, ignored the governance aspects

of the process and put emphasis on ‘what’ to implement instead of ‘how’ to implement

which left a gap of uncertainty to effective maturity concepts of the process.

1.2 Research aims and objectives

The aim of this research is to highlight and evaluate practitioners’ perception on critical

success factors and critical barriers and develops a roadmap to achieve excellence in the

implementation and continuous development of Configuration Management process in



23

The overall objectives of this research are as follows:

• To identify, prioritises, and categorises critical success factors for Configuration

Management and analyse the influence of multiple parameters such as academic

qualification, work experience, training, and experience in particular stakeholder

departments on the practitioner’s perception on the criticality of these critical success

factors.

• To identify barriers associated with managing Configuration Management

application, prioritize them on the basis of their criticality, categorize them into more

manageable groups of factors, and analyse the effects of multiple factors e.g.

academic education, gender differences, CM experience and types of organization on

the perception of CM practitioners in the process of application and rating the

highlighted barriers.

• To investigate the governance of the Configuration Management process in


• To develop a Configuration Management Maturity Model for the effective

implementation and continuous development of Configuration Management as a

process.

1.3 Research questions

The research questions for this research are as follows,

• What are the critical success factors for the effective implementation of the

Configuration Management process in aerospace and defence industries?

• What obstacles are perceived as the real barriers in implementation and success of

Configuration Management practices in aerospace and defence industries?


24

• What is the perception of Configuration Management practitioners regarding the

organizational structure for Configuration Management in aerospace and defence

industries that could help in the effective implementation of Configuration

Management practices?

• What is the perception of Configuration Management practitioners regarding

continuous improvements of the Configuration Management process? According to

their views, how could a Configuration Management Maturity Model be that could

achieve standards of excellence in aerospace and defence industries?

1.4 Research hypothesis

The research hypotheses to be tested in this study are as follows:

Hypotheses 1

There is a difference in the identification of Critical Success Factors for the

implementation of best CM practice, based on a practitioner’s academic

qualification, work experience, qualification / training, and experience in key

stakeholder departments.

Hypotheses 2

The identification and ranking of barriers to Configuration Management

acceptance and application, from the perspective of a CM practitioner, will be

directly influenced by their academic education, gender difference, CM

experience, and typology of organization.

Hypotheses 3

There is a significant difference in the maturity levels between aerospace and

defence industries.


25

1.5 Research strategy

The research strategy adapted for this research is outlined in detail in Chapter 3;

however, its brief outlines are below.

• It was important to grasp the theoretical perspective on the important aspects of this

research (i.e. Configuration Management, critical success factors, barriers, and the

maturity concept) which was possible only through detailed literature review.

Although the academic literature on Critical Success Factors, barriers, and maturity

frameworks specific to Configuration Management is limited, the studies in other

allied fields like Quality Management, Project Management, and Knowledge

Management etc. provided great deal to focus in the right direction. The literature

review was followed by feedback from practitioners on the research topics to know

their point of views.

• The first part of this research is based on mixed method research where data was

collected through interviews and questionnaire survey. To come up with a set of

success factors, in-depth interview were arranged with CM subject matter experts.

Three CM practitioners with more than thirty years of experience were consulted

through emails. Data from the two sources was combined with available literature to

finalize an initial list of success factors. The refined list of success factors was

finalized and their importance was highlighted with the help of a short statement.

The list was forwarded to a group of thirteen CM subject experts in the form of a

questionnaire in a meeting of the ‘Association of Configuration Managers’ (ACM) at

The University of Manchester for review and comments. The final questionnaire was

sent to CM professionals working in aerospace and defence sectors for the required

objectives. The questionnaire survey helped to establish the validity of the findings

obtained through interviews and conclusion on the designed hypothesis.

• The second part of this research is based on mixed method research to increase the

reliability and validity of findings. The barriers to Configuration Management were


26

identified through an open question in a questionnaire survey where 64

questionnaires were received followed by seven semi-structured interviews with CM

experts of four different industries. The data from both forms of studies was grouped

and analysed carefully to avoid possibilities of ignoring or repeating factors where

nineteen factors were finalized for final questionnaire survey which was conducted

to validate initial findings and verify the designed hypothesis. The questionnaire was

divided in two sections. The first section focussed on gathering background

information whereas the second part was related to barriers where respondents’

opinions were asked on a series of statements. Respondents of the questionnaire

survey were asked to mark trueness of each statement on a five-point scale. The

target population was the personnel from aerospace and defence industries where a

total of 187 valid questionnaires were used to analyse the stated hypothesis.

• The third part of this research is related to the development of Configuration

Management Maturity Model which is developed with the help of semi-structured

interviews. These interviews were conducted with six Configuration Management

professionals after critical analysis of the literature on maturity models, critical

success factors, and barriers to Configuration Management implementation followed

by two questionnaire surveys. The first questionnaire survey is related to model

validation while the second questionnaire survey is related to measuring the maturity

levels of the Configuration Management practices in different organization to see the

working of developed maturity model.

1.6 Structure of the thesis

The Thesis is organised in the following eight chapters:

Chapter 1 – Introduction: This chapter briefly highlight an overview of the research,

research problems, aim and objectives of the research, research questions, and

hypotheses. It also briefly highlights the research methodology and the structure of the

thesis.


27

Chapter 2 – Literature review: This chapter presents the literature review on the topics

covered in this research i.e. critical success factors, barriers to Configuration

Management implementation, and maturity models. In order to understand the

Configuration Management concept, a detailed overview on the topic is provided at the

outset to understanding the base practices of Configuration Management. Since the

academic literature on Configuration Management and related topics is limited, the

literature in other allied fields like quality management, knowledge management, and

project management helped us to streamline this research.

Chapter 3 - Research design and methodology: This chapter presents the research

philosophies, approaches, strategies, techniques and procedures to address the research

questions and conclude on the research hypothesis. It is also important to note that the

rationale for the selection of right research methods is also presented.

Chapter 4 – Identification and analysis of CM CSFs: This chapter discuss in detail

the identification and analysis of the critical success factors for the implementation of

Configuration Management practices. The primary objective of this chapter is to

establish a set of CSFs and analyze practitioners’ perceptions on CSFs based on their

work experience, qualification/training, experience of stake holders departments, and

type of organization.

Chapter 5 – Barriers and governance of the CM process: This chapter highlight the

interviews discussion to investigate the barriers to Configuration Management and the

governance aspects of the process.

Chapter 6 – Analysis of barriers to CM implementation: This chapter highlight in-

depth analysis of the barriers to Configuration Management implementation. The

analysis supports that how the barriers to Configuration Management have been

finalized and analyzed to conclude on designed hypothesis.


28

Chapter 7 – Configuration Management Maturity Model

This chapter presents in detail the structure of Configuration Management Maturity

Model and the way it will be used to measure the maturity of Configuration

Management practices within organizations.

Chapter 8 – Summary, conclusions, and recommendations:

This chapter presents the summary of the research and conclusions made in all three

parts of this research. The limitations of this research and recommendations for future

research are also presented in this chapter.

29

CHAPTER 2

LITERATURE REVIEW

2.0 Introduction

This chapter presents the literature review on four important topics i.e. Configuration

Management, Critical Success Factors, Barriers to CM implementation, and maturity

models.

2.1 Configuration Management (CM)

It is important to know how the term Configuration Management is defined in the

literature before explaining its multiple aspects.

According ISO (2003):

‘Configuration Management is a management activity that applies technical

and administrative direction over the life cycle of a product, its

configuration items, and related product configuration information’.

According to Watt (2008) and Watt (2010)

‘Configuration Management is a communication bridge between design

engineers and rest of the world’. This is shown through a graphical

representation in figure 2-1.

Chapter 2: Literature review

30

Figure 2-1: Configuration Management defined (Watt, 2008; Watt, 2010)

According to the National Consensus Standard for Configuration Management EIA-649

(2011):

‘A management process for establishing and maintaining consistency of a

product’s performance, functional, and physical attributes with its

requirements, design and operational information throughout its life’.

Configuration Management is a management discipline that controls definition of a

product or system from concept till disposal. CM is used to ensure that products and

systems fulfil their defined functional and physical requirements and that any changes to

these requirements are tightly controlled, carefully identified, and accurately recorded

(Samaras, 1988). With obvious returns in terms of reducing the total time for product

development, minimizing the overall cost, and enhancing product quality, CM has

become a vital part of the project delivery strategy. However, CM practices have been

undermined by industries and implemented in a chaotic way even in the presence

organized standards (Burgess et al., 2005). CM is based on sound business strategies to

establish product configurations, identify and manage changes to product configuration,

account for all approved changes and maintain the integrity of the configuration through

reviews and audits which helps in validating and verifying compliance with

requirements. Turner (1997) put this into a PM perspective as thus ‘CM is not a radical


31

discovery that revolutionises the way the facility is developed and maintained. It is a set

of good working practices for coping with uncertainty and change and gaining

commitment of the projects participants as the design evolves’.

Configuration Management, after inception from US department of defence in 1950’s,

has become a standard practice within many different organizations and is used for

supporting product development activities. The aim of CM is to identify, control,

account, and validate the functional and physical characteristics of a product.

Configuration Management plays an influential role in a project or product life cycle but

is not accountable for every aspect of a project or product. Configuration Management is

not a project management; rather an element of it (Burgess et al., 2003; Thompson,

1997). Configuration Management is not fully utilized to its potential but is treated like

that of quality management in Western organisations till its improved awareness in

1980’s (Burgess et al., 2005). In fact, there is similarity in the development between

quality and CM in which quality ascended from a culture of quality control, through

assurance and then on to management whereas CM is entrenched in a culture of control /

assurance.

CM was first introduced in the 1950/60’s by the US Department of Defence where its

need was instigated due to lack of data uniformity and change control issues in the race

for a successful missile launch in the 1950’s (Samaras, 1988). In the 1990’s, CM was

more evident in commercial sectors to help them with through life management of

product and system status. During this time, International Organization of

Standardization issued ISO-10007 in 1994 which was the first guideline on CM with a

major reflection being its inclusion in the requirements based aerospace standards such

as AS-9100. CM has remained one of the major process areas throughout the process

maturity models developed by the Software Engineering Institute. CM is not limited to

just the aerospace and defence sectors but is practiced in other sectors for example

conventional power generation, petrochemical, construction, nuclear, and shipbuilding

(Fowler, 1992; Gonzalez and Zaalouk, 1997) and has played a vital part in business

process improvements across the board (Gonzalez and Zaalouk, 1997).


32

To many, CM is integral element of the project management (PM) which in itself is a

barrier to effective application of CM. Many studies have identified that the CM process

extends beyond the project, across engineering, support and disposal. Application of a

common process is crucial in ensuring conformance. Consistent and repeatable

processes and methodologies are required for effective management of a project to deal

with the constraints of scope, time, cost and quality and to guarantee project success.

CM is essential for the PM professional to actively support the project direction and

infrastructure (PMI, 2007). CM is a through life activity, which invariably extends

beyond the traditional project lifecycle, and is encapsulated in a variety of engineering,

project management and manufacturing management methods (Burgess et al., 2003). It

is a continuous activity to establish and maintain integrity of an evolving product /

system throughout the lifecycle, whereas PM is mainly concerned with the definition

and execution of the lifecycle at a project level. CM is an integral part of the System

Engineering function (Team, 2006; Sage and Rouse, 2009) whereas PM, engineering

management, quality management, and logistics management are principal stakeholders

in the possession of the CM process (Kidd and Burgess, 2007).

The implementation of Configuration Management requires dedicated efforts to have

positive effect on the overall design process. Top management support plays a vital role

and is the driving force behind the effective implementation of the CM process. It is

important to establish comprehensive Configuration Management policies in the preview

of latest international standards to ease the implementation of CM practices. This can be

done by educating the CM personnel and functional stakeholders on the benefits of CM

practices through continuous training programmes. It is essential to note that there is no

final step in the Configuration Management process improvements and needs constant

and devoted efforts (Hancock, 1993).

2.1.1 History of CM

The concept of Configuration Management was first evidence by Henry Ford in the

early 1900's in order to organize the production of the first automobile (Bazelmans,

1985) but as a term was initially introduced by the US defence industries in 1950s


33

(Thompson, 1997). The design and manufacturing process of complex products which

was once understood and managed by single individuals became hard to control by them

and hence the need of an independent process was emerged to organize the design and

development of a product (Thompson, 1997). In 1950s the deficiency in the race of

missile launch was apparent where related industries were facing problems like:

• Prototype were either expended or destroyed

• Adequate records of part number identification was not available

• No change criteria existed

• Design documents did not reflect changes

• Produced articles not identified

Following is a brief history of Configuration Management transformation summarized

from the book of Samaras (1988).

The discipline was initially introduced through ANA (Army, Navy, and Air Force)

Bulletin No 390 issued in 1957. This document introduced and established “Engineering

Change Proposal” methodology that provided a unique and uniform system of change

incorporation within products. The next document was ANA Bulletin 391a where new

guidelines were added to the existing change control system. These two bulletins were

merged in a single document in 1963 with a new number i.e. ANA Bulletin 445. ANA

Bulletin 445 was superseded by MIL-STD-480 which was a comprehensive document

on the management of changes.

The US Air Force was involved in the generation of their own standard for

Configuration Management to manage their products. After extensive debate with

industry surveys, management consultation, and large expenditures AFSCM 375 was

introduced and changed with the consultation of industries and a final standard was

published in 1962 with a revised number i.e. AFSCM 375-1 which was further revised

in November 1963 to incorporate information regarding baselines. The document was

extensively revised in June 1964 which superseded about 61 government specifications,


34

bulletins, and standards. At the same time DOD directive 3200.9 was issued covering

the concept formulation and contract definition. The National Aeronautics and Space

Administration (NASA) issued their own standard on Configuration Management in

May, 1964 entitled Apollo Configuration Management Manual, NPC 511-1 that was

almost similar to AFSCM 375-1. In 1965 the Army Material Command issued

Configuration Management regulations, AMCR 11-26. From 1965 to 1967 Navy

generated three different documents (ASWSPO 5200.4, NAVMAT INSTR 5000.6, and

NAVMAT INSTR 4130.1) related to Configuration Management for the management of

their products. In 1967, several documents have superseded AFSCM 375-1 and many

other standards e.g. MIL-STD-480, DOD-STD-1679, and DOD-STD-2167. Meanwhile

NASA issued Handbook 8040.2 and GMI 8040.1A while private industry issued several

other publications.

In 1968 to reduce the proliferation of Configuration Management instructions, DOD

issued a directive to all agencies to stop issuance of any further standard on

Configuration Management. DOD formalized a team of experts to work on the

establishment and review of Configuration Management standard which will be equally

applicable to all agencies. In 1968, DOD issued his first directive on Configuration

Management 5010.19 which was applicable to all agencies alone with guidelines

5010.21 for the use of 5010.19. 5010.19 revised in 1979 to restrict the use of 2010.21

and again in 1987 with few changes. Later on the term DOD was replaced with term

MIL and all documents were reissued.

In 1991, MIL-STD-973, a comprehensive standard on Configuration Management

system for both hardware and software was issued by DOD which was their last

standard on the subject. The same has been cancelled in 2000 with a purpose to expand

the Configuration Management practices from defence to commercial industries. MIL-

HDBK-61 and EIA.649 were issued for general guidelines before the cancellation of

MIL-STD-973. Even though MIL-STD-973 has been cancelled long ago but is still in

use in many industries for guidance. ISO issued guidelines on Configuration

Management in 1994 with a title ISO 10007, the same was revised in 2003 and in 2008.


35

IEEE issued standard guidelines on software Configuration Management in 1988. After

the cancellation of MIL-STD-973, different books on Configuration Management have

been published and are available in the market.

Credit goes to the US Department of Defence for establishing and organizing

Configuration Management as a process. Even though their standards are no longer

applicable, but are still useful and provide help to the beginners of this field.

2.1.2 Elements of CM

General principles and practices of Configuration Management have not changed over

the years. Basic Configuration Management practices as outlined thirty years back in

different defence standards are in the main unchanged. These principles and practices

have been reemphasised and rearranged in current literature with new insights.

Principles of Configuration Management are the same but their implementation

procedures are different in different industries. Configuration Management have been

divided into different elements or processes. Since the field has not been changed over

the years, there are no significant changes in high level definitions. Following is the

stance of the literature (standards, books, and research papers) on CM elements.

According to MIL-STD-973 (1992), MIL-HDBK-61 (1997), and Samaras (1988) the

elements of Configuration Management are:

• Configuration identification

• Configuration control

• Configuration status accounting

• Configuration audits

According to EIA-649 (2011) the elements of Configuration Management are:


36

• CM planning and management


• Configuration change management


• Configuration verification & audit

According to ISO (2003) the elements of Configuration Management are:

• Configuration Management planning


• Change control


• Configuration audit

According to Guess (2006) the elements of Configuration Management are:

• Requirements Management

• Change Management

• Release Management

• Data Management

• Records Management

• Document and Library Control

• Enabling Software Tools

The activities of these elements are not independents in nature but have strong

dependencies on each other. Example of the same could be seen in figure 2-2 where

relationship and dependencies of the five elements of Configuration Management

process are shown. It is important to note that the output of these activities in the form of

approved data is transferred to data management for control and record keeping.


37

Figure 2-2: Configuration Management process model (MIL-HDBK-61, 1997)

2.1.2.1 Management and planning

Management and Planning is responsible for achieving an effective, predictable, and

repeatable Configuration Management process over the life cycle of a product (EIA-649,

2011). Management and planning tries to integrate distributed task across organization,

coordinate among them, and support the overall objectives of Configuration

Management process. It establishes and controls the mission, vision, and policies for

Configuration Management within an organization. On the basis of these established

policies, comprehensive Configuration Management procedures and instructions are


38

generated whereas management and planning helps in the implementation of these

established guidelines within all projects of an organization. It is responsible for

managing and organizing the necessary resource in terms of infrastructure requirements,

human resource requirement, software tools requirements, or knowledge improvement

through training. The governance of a process plays an important role in efficient

working of any process. According to Felix and Monroy (2009) it is important to set

responsibilities of each Configuration Management entity, draw boundaries in terms of

scope of work and methodologies for each individual, establishing internal structure and

organization, and effective running of Configuration Management process. Management

and Planning and its relation with four major elements of Configuration Management is

shown in figure 2-2.

The Configuration Management Plan is a vital document for the execution of

Configuration Management process within a project. Provisions of guidelines on the

generation and implementation of this document is the responsibility of management and

planning. The CM Plan issues policies on how different elements of Configuration

Management would be implemented in specific projects. Configuration Management

Plan defines the necessary procedures, responsibilities of all functional stakeholders, and

provides related templates or examples of what is expected within a project (James et al.,

1999). Configuration Management Plan can restrict certain activities within specific

projects which are not necessary and otherwise mentioned in the companywide

procedures.

The effective implementation of a Configuration Management process depends mainly

on the way it is organized and represented at organizational level and the effectiveness

of the roles and responsibilities for individuals who are responsible for the execution of

this process. It is the organizational structure of a process which plays an important role

in its overall implementation and explains how specific tasks are divided, grouped and

coordinated. The organizational structure prevents chaos through a set of reporting

relationships and communication channels (Aquinas, 2009). It is important to note that

there is not a single best structure that could suite the implementation of that process in


39

all circumstances but is based on many other factors e.g. number and size of projects and

the overall composition of that organization and have their own advantages and

disadvantages.

A suitable organizational structure will play a major part in the implementation and

continuous improvement of any process. The limited literature in the field of

Configuration Management has hardly touched this subject and needs some discussion

to help organizations in better implementation of the Configuration Management

process. On the other hand extensive literature is available on organizational structure

which is largely boosted through the studies of Mintzberg (1979) and Miller et al. (1984)

by identifying common organisational structures. The concept of organizational

structure is recently summarized by Aquinas (2009) which gives a sound knowledge and

understanding of the topic in the context of previous research. This study of Aquinas

(2009) has categorized organizational structures into four major types i.e. functional,

divisional, hybrid, and matrix which also highlight that how Mintzberg’s and Miller’s

configurations fits under these four types of organizational structures.

2.1.2.2 Configuration identification

Configuration identification is the basic foundation of Configuration Management.

According to EIA-649 (2011), configuration identification is the basis from which

configuration of products are defined and verified; products and documents are labelled;

changes are managed; and accountability is maintained. Configuration identification is

the basic part of the process where in the event of any irregularities, it is impossible to

establish correct association between parts within a product, correlate changes within

parts and documents, identify and induce comparison between status reports, and

validate requirements through audits. Detailed activities of configuration identification

are shown in figure 2-3.


40

Figure 2-3: Configuration Management identification (MIL-HDBK-61, 1997)

2.1.2.2.1 Product structure

Product structure; also called product architecture or product family tree; highlights the

relationship between configuration items, assemblies, and their individual parts.

According to EIA-649 (2011), product structuring is a technique for organizing the

composition of a product. Product Structure is a tree-like representation of a complete

product which is usually drawn on paper from top-to-bottom, left-to-right or right-to-

left.


41

2.1.2.2.2 Configuration item (CI)

According to Samaras (1988) configuration item are defined as:

‘An aggregation of Hardware or software, or any of its discrete portions, which satisfies

an end use function and is designated by the Government for Configuration

Management. CIs may vary widely in complexity, size and type, from an aircraft,

electronic or ship system to a test meter or round of ammunition. During development

and initial production, CIs are only those specification items that are referenced directly

in a contract (or an equivalent in-house agreement). During the operation and

maintenance period, any reparable item designated for separate procurement is a

configuration item’.

Selection of Configuration Items is not an easy task. According to Lyon, (2008),

Configuration Item is one of the more confusing topics of CM. CI segregates major units

of a product into identifiable subsets to effectively manage the physical and functional

characteristic of those units (MIL-HDBK-61, 1997). Each configuration item is

associated with a set of configuration documentation. These documents vary widely in

variety from status reports like production reports, change status reports, and physical

and functional configuration audit reports to performance specification; detailed

manufacturing documents like bills of materials, part list, assembly drawing, detailed

component drawings, assembly instructions, and so on.

Decision on items to be a CI is entirely flexible as there are no binding on the

organizations and they can select as many CI’s on the basis of their internal policies. But

mainly in engineering and manufacturing development phase, deliverable and

independently installable units of the product are identified as CIs which requires

significant management attention but during deployment and operational support,

individual items which need logistic support and procurement are designated as

configuration items (MIL-HDBK-61, 1997). The decision on the selections of CIs which

will work as Line Replaceable Units are easy but for those which falls in another CI or


42

assembly is difficult and needs consideration of different factors. The factors which must

be considered before the selection of a CI are well elaborated by MIL-HDBK-61, (1997)

and Samaras (1988):

2.1.2.2.3 Product identification

According to EIA-649 (2011), all products should assign unique identifiers to

distinguish between products, segregate products configuration, determine source of a

product, and to retrieve correct product information. Product and related documentation

are assigned unique identification number and specific titles (EIA-649, 2011; Lyon,

2008; MIL-HDBK-61, 1997; Samaras, 1988; Watts, 2008) are assigned Serial / Lot / or

batch numbers in conjunction with part numbers for their traceability at customer

premises.

2.1.2.2.4 Product documentation

Product documentation highlights the physical, functional, and performance,

characteristics of that product. Necessary information about a product could be obtained

from configuration documentations. Each document carries a unique document number,

title, and issue or revision number which are under configuration control (EIA-649,

2011; MIL-HDBK-61, 1997; Samaras, 1988; Watts, 2008). Documents carry different

signature which highlights authenticity of the document.

2.1.2.2.5 Serial, lot, and batch numbers

Serial Numbers are allocated to individual units of a product whenever there is a need to

distinguish one unit of the product from another (EIA-649, 2011; Lyon, 2008; Watts,

2008). Lot and Batch numbers are allocated to a group of similar units when it is

unnecessary or impractical to identify individual units with serial numbers but rather

necessary to associate units to a process, date, event, or test (EIA-649, 2011). It is

important to note that specific activities during production processes are recorded and


43

maintained in the form of Build History Dossiers against each serial, lot, or batch

number(s).

2.1.2.2.6 Part marking

Independently movable units need necessary information which must be available on the

unit for identification and traceability. Usually this include, part number, serial number,

part title, and manufacturer logo. Part markings should be part of the technical data pack

of the product before printing on the actual part (Watt, 2008). These markings of the

product should always be done according to organization policy (Lyon 2004).

2.1.2.2.7 Phases and baselines

Phase is milestones which needs to be achieved during the product life cycle (Watts

2008) while baseline is a set of document(s) formally designated and fixed at a specific

time during a CI’s life cycle (Samaras 1988). Each phase or milestone is planted in the

project/product life cycle to achieve planned goals or objectives. Each milestone is

represented by a document or set of documents called baseline which represents the

activities performed in that specific phase. It should be noted that there are various

phases and baselines in each product life cycle.

Baselines are the outputs of activities performed during a phase which are internally

established by the organization or externally imposed by the customer. A Baseline is a

set of documents which are required to be checked by the customer. A summary of

baselines have been highlighted in figure 2-4 (MIL-HDBK-61). This shows three

external baselines i.e. Functional Baseline, Allocated Baseline, and Product Baseline is

are required to be checked by the external agency while one internal baseline i.e.

Development Baseline is checked by contractors which can sometimes be externally

imposed by the external agency.


44

Figure 2-4: Detail of baselines (MIL-HDBK-61, 1997)

Figure 2-5: Product generic phases and baselines (Robert, 2004)


45

Figure 2-4 is a single representation of a product life cycle. Another generic product

lifecycle presented by Robert (2004) is shown in figure 2-5. The cells in the row

describe the phases while each square in column at the bottom highlights individual

baseline. Ellipses show three reviews i.e. System Design Review (SDR), Software

Specification Review (SSR), and Critical Design Review (CDR) and two audits i.e.

Functional Configuration Audit (FCA), and Physical Configuration Audit (PCA).

Samaras (1988) described a comprehensive product development cycle. He explained

the Product Development Life Cycle in terms of four major phases and three main

baselines. Full scale development phase is further divided into four phases and three

internal baselines. This is a comprehensive model that covers all aspects of the product

development cycle and is shown in figure 2-6.

Figure 2-6: Product development cycle (Samaras, 1988)

The MoD project life cycle is shown in figure 2-7 which highlights three main features

i.e. project life cycle, product life cycle, and extended life cycle (Lester, 2007).

It should be noted that there is no one project / product life cycle which could be

responsible to manage the activities of a product from initiation till disposal of a project /

product. Project / product life cycle may change with the requirements of the product.


46

According to Field and Keller (1998) ‘there is no single life cycle that applies to all

projects’.

Figure 2-7: Life cycle of MoD project (Lester, 2007)

2.1.2.3 Configuration change management

Configuration change management is a process responsible for managing changes and

variances to the physical and functional characteristics of a product. It is a process to

manage preparation, justification, evaluation, coordination, disposition, and

implementation of proposed engineering changes and deviations to effected

configuration items (MIL-HDBK-61, 1997). Engineering changes are the changes and

modifications in forms, fits, materials, dimensions, functions, etc of a product or

component which can be as simple as documentary amendments or as complicated as

the entire redesign of a products and manufacturing processes (Huang and Mak, 1999).

Change Management is required to maintain the integrity of the product (Mannan et al.,

1998).

Engineering changes usually starts at the beginning of product life cycles when

documents are generated and need change as build of the products are updated according

to the customer requirements. Changes are huge in numbers during development phase

where requirements are changing quite rapidly and slow down as the product passes to

production phase. Consequences of changes are different within these phases. Design

changes after full scale development phase might be ten times as expensive to design

changes at the initial design phase (Huang and Mak, 1999).


47

Change management plays an important role in the product development and has been

considered the corner stone for an organization to compete in the market (Loch and

Terwiesch, 1999). Single change can affect different assemblies and items and

propagates unexpectedly which can easily destabilize an organization (Jarratt et al.,

2004). Rowell et al. (2009) highlighted the same that a single change can create multiple

threats and effects and also multiple causes can create a single effect. Effective control

of these effects and threats can be minimized through effective close loop change

management system.

The change process does not receive due importance in a production organization since

it is considered to be responsible for obstructing smooth product manufacturing (Wright,

1997), excessive development costs, and product lead time (Loch and Terwiesch, 1999).

It is important to note that without proper change control system, the changes are not

organized and the documents do not highlight the as-built configuration of the product

(Castor, 2007).

Extensive literature is available on change management having diverse views on the

configuration change management process. Organizations might have different change

management processes where some might have established formal processes with

dedicated staff while others might have quite ad hoc systems (Huang et al., 2003).

Change process starts with the initiation of a change and end with incorporation of

changes in products and related documents. Change process mainly depends upon the

product development phase, size of the product, size of the organization, communication

channel, inner departmental cooperation, and available information system (Tavcar and

Duhovnik, 2005).

According to Huang and Mak (1999), the engineering change process usually involves

four phases i.e. identification, evaluation, implementation, and auditing while Rowell et

al. (2009) emphasized on the five steps as highlighted in figure 2-8. Ibbs et al. (2001)

highlighted that five principles should be kept in mind while considering a change

management system i.e. promote a balanced change culture, recognize change, evaluate


48

change, implement change and continuously improve from lessons learned. The same

has been shown in figure 2-9.

Figure 2-8: Simple Change Process (Rowell et al., 2009)

Whatever a change process would be, the objective should be change identification and

successful implementation of the same within the product. Best organizations have

effective system for the identification, segregation, evaluation, and implementation of

the changes. They always strive to improve their system in the long run to remove

hindrances from change control and implantation system.


49

Figure 2-9: Principles of Change Management System (Ibbs et al., 2001)

The Change Control Board is an important element of the change control process.

Change Control Board is a group of people who are solely responsible for the planning

and disposition of changes. The composition and structure of the board may vary

according to the type of project and product life-cycle phase; however, it shall comprise

persons who are involved in the product from all functional stakeholders. The study of

Huang and Mak (1999) can be used as reference on the composition of change control

board which refer to the members of the board in multiple organizations compiled

through survey research methodology and is shown in figure 2-10. The vertical axis

shows the members who have attended the board meetings while horizontal line shows

the percent companies responded for the member to have in the board. Composition of

the board is mainly decided by the project manager or head of the organization and

documented in the concerned CM Plan.


50

Figure 2-10: Statistics of research on members of CCB (Huang and Mak, 1999)

2.1.2.4 Configuration status accounting (CSA)

Configuration status accounting is responsible to identify, create, and organize reports of

the Configuration Management activities. CSA is a gateway to complete, accurate, and

timely information of physical and functional characteristics of a CIs throughout the

product life cycle. It is an important activity to reach the right information in complex

projects in no time because according to Badiru (1988) and as highlighted by Burgess et

al. (2003) that about 30% of the time of a project member is usually spent to search the

right information. The same is also mentioned by Smith (1991) that about 80 % of the

average person’s time is spent on collecting and handling data while the rest is spent on

the actual work by using that data.

The worth of CSA is not recognized in majority aerospace industries and hence not

implemented in its full strength (Burgess et al., 2003). Burgess et al. (2003) observed


51

that CSA is considered a time consuming and costly activity and do not receive due

favour at the early development phase of the product where data can be easily

accumulated but considerable time is spent in the final stages of product where need of

product reporting arise.

Systematic and progressive approach is necessary to highlight the importance and to

implement CSA in these industries. A stepwise approach for the implementation of CSA

is an effective way to implement this area in more professional way in these industries.

The approach may start with basics and ends with full implementation of CSA process

to acquire their desired results.

2.1.2.5 CM audits and reviews

CM audits and reviews are responsible for the verification and validation of a product

before its release to the customer(s) for use. Configuration audit and reviews are

performed to verify that physical and functional requirements of a product have been

achieved and incorporated in the design and are documented in configuration

documentation. Audits and reviews are performed by the end of different phases to form

specified baselines. Baselines are released after successful completion of CM reviews

and audits.

There are of various types of reviews [e.g. according to Samaras (1988) they are system

requirements review, system design review, software specification review, preliminary

design review, critical design review, test readiness review, and formal qualification

review] which are conducted after specific phases within product development cycle to

evaluate the current design process and make recommendations if necessary. There are

two types of Configuration Audits (EIA-649, 2011; Hass, 2002; ISO, 2003; MIL-

HDBK-61, 1997; MIL-STD-973, 1992; Samaras, 1988), i.e. Physical Configuration

Audit (PCA) and Functional Configuration Audit (FCA). These audits are conducted as

a final check before the products are delivered to the customers. Audits are mostly done

by the owner of the product and have no representatives from the customer as they do

have in case of reviews.


52

Audits are conducted in four major steps. Planning is the first and most important of

these steps. Audits are planned in advance before their execution in the form of PCA

Plan & FCA Plan. Audits are then accomplished as per plan in one or several different

settings. Audits activities and results are summarised in the form of Post Audit Reports.

The fourth and final step is to see the progress of accomplishment of the action items

which have been highlighted during audits.

2.1.2.6 Data management

Data Management is the management of product configuration related data generated

from concept till disposal of a product. Data Management is mainly responsible for

archiving of master documents; issuance, and retrieval of these documents within and

outside organization. Besides product documentation, data management may maintain

and control organizational policies and working procedures. The data management is

very difficult to manage without suitable data management system.

Documents are controlled both in the form of hard paper and electronic media.

Electronic copies are maintained with dedicated software usually with Product Lifecycle

Management (PLM) or Product Data Management (PDM) software. There are multiple

software available in the market designed to manage Configuration Management data.

While controlling electronic documents, optimum care is taken for maintaining the

identification of files, its correct versions, and relationship with product and associated

documents. Correct identification and version control of documents are important for

maintaining status of documents. These activities are important to access and archive the

data and manage related changes. Locating the correct data at minimum time is only

possible through a strong status management system. Data Management ensures access

to the right data by the right individual in minimum time and is important for supporting

the product life cycle activities. It ensures the accessibility of data to those individuals

who are only entitled for its use.


53

Data Management plays a vital role in maintaining a proper relationship between data

and product configuration. Documents carrying the following information which are

used by data management for establishing a proper relationship:

• Project / Project Related Information

• Changes Designators

• Associated Products & Documents Information

• Item Serial / Lot / Batch Number

• Status of the data, i.e. working, released, submitted, approved, or achieved

2.1.3 CM in Quality perspective

Configuration Management is a process designed to harmonize the product development

process. Experience shows that what we plan to built does not correspond in totality with

the designers intentions to build. This deviation is some time highlighted with minor

inadequacy in the original design during production and is fixed but usually appears a

major departure from the original design objectives and create major issues.

Configuration Management as a process is designed to reduce and remove such

inadequacies and ensure that as design configuration is the same to the as built

configuration and is a major concern of the quality control and quality assurance to

validate and conform the same.

Fowler (1993) highlighted that TQM and CM enhance productivity and are responsible

to reduce the total cost of the product. Fowler (1993) admitted that since customer

satisfaction is the prime objective of both, appraisal and prevention costs tend to rise

modestly but failure cost tend to reduce much more which results in reduction of the

total costs. Fowler (1993) highlighted a strong correlation between TQM and CM where

TQM is supporting tool enforcing a culture to increase customer relations, develop a

system for monitoring changes to requirements, enforce on supplier’s identification and

traceability, and control of processes. These areas are effectively identified and

controlled through CM. Configuration Management is an effective tool for information


54

handling and documentation control and therefore helps organizations to have effective

control on the inputs and outputs of their processes. Configuration Management has

been declared as a powerful tool to boost up quality of a product and improve

productivity (Stevens and Wright, 1991).

There is a strong correlation between ISO 9000 Quality Management System and the

CM process. Some of the clauses of ISO 9000 Quality Management System [e.g.

Control of documents (4.2.3), Control of records (4.2.4), Design and development (7.3),

Identification and traceability (7.5.3), Control of non-conforming products (8.3)] have a

direct relation with Configuration Management process. There are some additional

clauses of ISO 9000 which do address Configuration Management process. This

relationship shows that effective implementation of Configuration Management within

an organization can have strong impacts on enhancing supporting processes and

ultimately improving the quality of products.

2.1.4 Management of design process with CM

Configuration Management has a major role in controlling and maintaining the design

process of a product (Fowler, 1993). Configuration Management is directly related with

the design process and has major impacts in streamlining the design activities.

According to Hancock (1993) and Hancock (1994) the CM concept is very important to

improve the design control techniques. Design process starts with concept exploration,

passes through different phases and finalizes initially at the production phase and finally

ends on the disposal of the product. CM controls the design process by establishing

unique baselines at the end of each phase which are checked and verified through

different reviews. These baselines highlight the design of a product at specific point in

time and can be changed by the designer through a controlled process.

CM Personnel supports designers during identification, control, reporting, verifying and

validating their design process. Good communication between the two creates positive

results on the overall productivity and quality of the organization. But this looks a hard

job as highlighted by Fowler (1993) as this is not always the case as convincing


55

designers and other agencies with CM advantages is an intricate process as most of them

consider this process merely an expensive and obstructive bureaucratic activity. The

functional stakeholders must be convinced that how CM can improve quality, reduce

waste, streamline schedules and enhance the productivity of their processes. CM rewards

can be achieved if supporting departments are motivated and have a full belief on CM

advantages.

It is important to maintain strict relationships between product and its related documents

during the design phase which is the main objective behind CM. Configuration

Management is a key to process improvement which tries to build close associations

between product and its data (Buckley, 1993). With a good CM process, we can control

our design process and provide a good foundation in the form of design documents to

build quality products according to customer’s requirements.

2.1.5 CM impacts on customer’s support and satisfaction

Configuration Management helps organizations to fulfil customer’s requirements from

concept till operations of a product. Requirements specification is considered as the most

important document for the generation of system specifications. System specifications,

design alternatives, and feasibility reports are prepared on the basis of requirement

specification. The functional requirements review is conducted at the end of concept

phase to ensure that customer requirements have been incorporated in the design

approach and will serve per requirements (Samaras, 1988). The purpose of this step on

requirements specification right from concept phase is to enhance customer satisfaction

in the long run.

It is important that customers should be part of the detail design review and

organizations should take their consent before going for the qualification prototypes

(Samaras, 1988). This is necessary because most of the design decisions are completed

during this phase and is important to have customer satisfaction in the design at this

point in time as it is very difficult to reverse the design once the designers opt for the

next phase. It is also important to note that in the majority cases the ‘integrated support


56

analysis’ starts during the detail design phase to finalize the support side of the products.

Design and development of the ground support and operational equipments are started

mostly in parallel with product development and are covered by the Configuration

Management process.

Products may change not only in the design and development but also in the operational

phase when retrofits are required to fix bugs or enhance the functionality against

customer requirements. These Changes are classified in two categories i.e. Class-1

changes and Class-2 changes (Jones, 1992). Class1 changes also called major changes,

effects the fit, form, and function of the products while all other changes that do not

affect the form, fit, and function of the product are Class-2 or minor changes (Jones,

1992). According to Configuration Management principles, Class-1 changes should

always be approved and incorporated in the design with the consent of customers.

Changes have a potential to cause immense damage to company finances and customer

satisfaction hence prior approval should be sort before its implementation (Jones, 1992).

CM process plays a major part in the maintenance and modification of a product during

the operational phase. It is important to note that kit preparation and installation is a

major activity in modification and retrofits of any product where selection of right kit on

the basis of proper documentation plays a vital role. Any minor mistake at this level can

jeopardize the life of the product and can extremely effect customer relation (Jones,

1992). Control of all records related to maintenance and modification is maintained

through set guidelines established through CM process in the form of ‘maintenance and

modification history dossiers’ for each CIs, assemblies, or components.

Implementation of Configuration Management process from customer perspective is a

challenging task. Support process needs visibility throughout product life cycle

especially in the operational phase which can be achieved through effective CM process.

It is of extreme importance to understand, accept, and integrate customer support

interests throughout the CM process which is a key factor to both customer satisfaction

and organizational survival (Jones, 1992).


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2.1.6 CM and products reliability and maintainability

Successful organizations can dominate the market through low product prices, better

time to market, superior product quality, and reliability and maintainability of the

product. According to Boznak (1990a), effective control on product development

through Configuration Management ensures the predictability of achieving reliability

and maintainability goals. Product development process should have a clear visibility of

the parts and information flow which if unavailable or unclear can severely affect the

integrity of the product. Clear and authentic information establishes a foundation for

significant improvement to product reliability and maintainability (Boznak, 1990b).

Figure 2-11 : Lack of control and its impact on cost (Boznak, 1990a)

Organization having poor control on development process results in escalation of

changes on approach to product finalization. This rise in changes results in longer time

to market for new product, boost manufacturing cost, and creates the reliability and

maintainability concerns. By applying the concept of Configuration Management,


58

Japanese companies have dominated the market as compared to the US companies

through their effective control on changes in product development cycle. This

comparison and the rise of the cost through unmanaged activities is presented by Boznak

(1990a) and is shown in the graph in figure 2-11.

2.1.7 CM activity model

Activity models which are mostly conceptual in nature represent a set of activities

organized in a logical sequence with clear dependencies to handle information for the

desired outputs. This concept is explored mainly in the form of human activity model by

Checkland, (1981) who in turn drew on the ideas of Churchman (1971) and Jenkins

(1969) which is also explained by Fortune and White (2006) and White and Fortune

(2009) in the form of formal system model by emphasising on projects. It is important to

emphasis on the CM activity model which needs to be based on factors necessary for

establishing, maintaining, and continuously improving the CM process. It is important to

note that limited academic literature on Configuration Management has never

emphasized on this concept whereas the available models could create misunderstanding

through the use of specific terminologies because of their origin with systems thinking

and project management. It is important to work on CM activity model and make it

easier for the use of CM practitioners to provide them with tangible basis for comparison

with their existing practices to highlight ways of improvements.

The most important aspect to know is that ‘there are not valid models and invalid ones,

only defensible conceptual models and ones which are less defensible! But at least it is

possible to check that conceptual models are not fundamentally deficient, and this is

done by checking the model against a general model of any human activity system’

(Checkland, 1981). To ensure that such models are free from any fundamental

deficiencies and make it more effective while implementation, it is important to adopt

the principals of soft system model building methodologies highlighted by Checkland,

(1979). In the soft systems methodology, models are not part of the world and hence

cannot be tested by checking how well they represent it; they are only pertinent to debate

about the real world and are used in a repeated learning process (Checkland, 1995).


59

2.2 Critical success factors and related CM literature

The concept of critical success factors is mostly linked with the research of Daniel

(1961) on ‘Management Information Crisis’ but defined for the first time by Rockart

(1979) as ‘Critical Success Factors thus are, for any business, the limited number of

areas in which results, if they are satisfactory, will ensure successful competitive

performance for the organization. They are the few key areas where "things must go

right" for the business to flourish. Critical success factors are areas of activity that

should receive constant and careful attention from management. Critical success

factors, however, are the areas in which good performance is necessary to ensure

attainment of those goals’. Critical Success Factors outline key areas of managerial

success and has been used by management to measure and improve processes in sectors

like finance, information system, and manufacturing industries (Li et al., 2005).

Based on the seminal research ‘Chief Executive Define their Own Data Needs’ by

Rockart (1979), research in numerous sectors has been done on areas critical to project /

process outcomes and those that need special attention from top management to achieve

and ensure the success of a project / process within organizations. Critical Success

Factors include imperative issues necessary for an organization’s activities to flourish

with time. Importance of research on CSFs could be seen from the extensive literature

available in diverse fields such as, construction projects, construction partnering,

information systems projects, new product development, agile software projects,

education, data management, quality engineering, and project management.

The importance of research in the field of Critical Success Factors (CSFs) has become

evident through extensive research in other allied fields like Quality Management (QM),

Project Management (PM) and Knowledge Management (KM). For example more than

seventy studies have been identified on CSF’s in PM by Belassi and Tukel (1996),

Baccarini and Collins (2003), and Fortune and White (2006); while seven studies within

knowledge management by Wong (2005). Research on CSFs and critical barriers (CBs)

establish a baseline to formulate a means for the maturity of process (Niazi et al., 2005).


60

According to Yeo and Ren (2008), process maturity is mainly dependent on key

capability areas obtained from CSFs and CBs. Identification of CSFs helps individuals

to work on areas responsible for the success of a process, provide an opportunity to

avoid barriers, establishes direction to achieve goals, and offer a means of measuring the

effectiveness of their processes.

A detailed search of the peer reviewed journals and practitioner literature highlights no

formal study on the subject in the field of Configuration Management. Some researchers

believe that in the presence of such an extensive literature on CSFs in areas such as PM

or QM, it is fruitless to further explore the subject within CM. But, in reality there is no

single study that could be used as a baseline to help CM practitioners in the maturity of

the CM process although some studies (table 2-1) highlight some areas of importance.

Being a technical management discipline it is logical that some of the areas will be

critical for both CM and PM e.g. resource requirements, management support etc., but

many other PM factors identified by studies presented in table 2-2, table 2-3, and table

2-4 have limited direct correlation on the overall performance of CM operation e.g.

market intelligence, technical uncertainty innovation, accurate initial cost estimates,

strong business case.


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Key Important Factors References

management support (Guess, 2006; MIL-HDBK-61, 1997;

Samaras, 1988)

CM specialists, simplest CM process (Samaras, 1988)

Good standards (Guess, 2006; Hancock, 1993; MIL-HDBK-

61, 1997;)

CM planning (Guess, 2006; Sachs, 2009)

Efficient software tool (Fowler, 1993; Guess, 2006)

Effective communication

(Guess, 2006; Jarratt et al., 2011; Tavcar

and Duhovnik, 2005; Yeh and Tai-Hsi,

2005; Wasmer et al. 2011)

Proper resources allocation (MIL-HDBK-61, 1997; Gonzalez and

Zaalouk, 1997; Guess, 2006)

Training (Samaras, 1988; Hancock 1993; Gonzalez

and Zaalouk, 1997; Guess, 2006)

Cooperation

(Gonzalez and Zaalouk, 1997; Guess, 2006;

Jarratt et al., 2011; MIL-HDBK-61, 1997;

Samaras, 1988)

Good leader (Guess, 2006; Watts, 2008)

Team work (Sachs, 2007)

Creative and committed professional (Sachs, 2010)

Continuous improvement (Guess, 2006; Hancock, 1993)

Table 2-1: CM success factors (areas of importance)


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Critical Factor Counts of Citations

Support from senior management 39

Clear realistic objectives 31

Strong/detailed plan kept to date 29

Good communication & feedback 27

User/client involvement 24

Skilled/suitably qualified/sufficient staff/team 20

Competent project manager 19

Strong business case/sound basis for project 19

Sufficient/well allocated resources 16

Good Leadership 16

Proven/familiar technology 15

Realistic schedule 14

Risk addressed/assessed/managed 14

Project sponsor/champion 13

Effective monitoring / control 12

Adequate budget 12

Organisational adaptation/culture/structure 11

Good performance by suppliers/contractors/consultants 10

Planned close down/review/acceptance of possible failure 10

Training provision 9

Political stability 7

Correct choice/past experience of project management

methodology/tools 6

Environmental Influences 6

Past experience (learning from) 5

Project size (large)/level of complexity (high)/number of

people involved (too many)/duration (over 3 years) 4

Different viewpoints (appreciating) 3

Table 2-2: PM CSFs identified across 63 publications (Fortune and White, 2006)


63

Study 1 Study 2 Study 3 Study 4

Define goals Make project

commitments

known

Project summary Project manager's

competence

Select project

organizational

philosophy

Project authority

from the top

Operational concept Scheduling

General

management

support

Appoint competent

project manager

Top management

support

Control systems and

responsibilities

Organize and

delegate authority

Set up

communications

and procedures

Financial support Monitoring and

feedback

Select project team Set up control

mechanisms

(schedules, etc.)

Logistic

requirements

Continuing

involvement in the

project

Allocate sufficient

resources

Progress meetings Facility support

Provide for control

and information

mechanisms

Market intelligence

(who is the client)

Require planning

and review

Project schedule

Executive

development and

training

Manpower and

organization

Acquisition

Information and

communication

channels

Project review

Table 2-3: List of PM CSFs (Belassi and Tukel, 1996)


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Study 5 Study 6 Study 7

Clear goals Top management support Project objectives

Goal commitment Client consultation Technical uncertainty

innovation

On-site project manager Personnel recruitment Politics

Adequate funding to

completion

Technical tasks Community involvement

Adequate project team

capability

Client acceptance Schedule duration urgency

Accurate initial cost

estimates

Monitoring and feedback Financial contract legal

problems

Minimum start-up

difficulties

Communication Implement problems

Planning and control

techniques

Trouble-shooting

Task (vs. social orientation) Characteristics of the

project team leader

Absence of bureaucracy Power and politics

Environment events

Urgency

Table 2-4: List of PM CSFs (Belassi and Tukel, 1996)

2.3 Barriers to CM implementation

CM Barriers refer to those potential actions, phenomenon, or influences which hamper

and prevent successful implementation of the process in achieving its objectives.

Detailed literature review highlights that research based studies on barriers to CM

implementation are limited in comparison with other allied fields like Quality


65

Management and Knowledge Management. To the best of my knowledge based on the

available literature, there is no formal study found with the aim to explore barriers to

CM implementation. However, studies in other allied fields like Project Management

(Atkinson et al., 2006), Quality Management (e.g. Bhat and Rajashekhar, 2009;

Sebastianelli and Tamimi, 2003), Knowledge Management (e.g. Riege, 2005; Sun and

Scott, 2006), and Business Process Management (Da-Silva., 2012) provided a great deal

of scope while developing this study.

Burgess, et al. (2003); Burgess et al. (2005) and Huang and Mak (1999) could be

considered the most significant studies which have supported this research in many

aspects but have specific limitations. These studies have targeted specific elements of

CM instead of targeting CM as a generic and holistic process. For example the study of

Burgess et al. (2003) deals mainly to Configuration Status Accounting while the study of

Huang and Mak (1999) is related Configuration Change Control and hence can’t be

considered a representative view of the CM process as a whole. Burgess et al. (2005)

covers the status of CM implementation within one multi-national aerospace programme

which highlighted some of the obstacles to CM implementation.

The study of Burgess et al. (2003) highlights the implementation status of Configuration

Status Accounting within the aerospace sector. According to this study, CM planning

which is the most influential aspect of the process is a major concern for organizations

since it is rarely given the due importance. There are some other factors which have

significant effects on the outcome of this activity e.g. perceived lack of CM value, lack

of dedicated CM staff and an engendered belief that CM is not a cost effective process.

This study is based on the assumption that standards for CM are well understood and

prevalent which could be considered a major limitation of the study. This as a whole is

believed to be one of the most crucial areas in CM implementation (Samaras, 1984)

which can affect the overall performance of the process and hence cannot be ignored.

Further to this, a recent study by Wu et al. (2012) states that CM standards are not well

understood or adopted, especially where there is no contractual obligations.


66

The study of Huang and Mak, (1999) is related to the influential factors of engineering

change management. According to the authors, the most influential factors to effective

change implementation are poor communication, high uncertainty in planning and

priorities, reluctance and indifference toward the process, complex and confusing

organizational structures, lack of cooperation, an overly bureaucratic process

infrastructure, lack of simplicity, isolated automation of the process, scarce resources

that are exacerbated by constant fire fighting, lack of involvement from stakeholders,

lack of engagement of CM practitioners in decision making and narrowing of human

skills.

The study of Burgess et al. (2005) is an overview of current status of CM applications in

the aerospace sector, from the perspective of one major collaborative programme, which

highlights some major obstacles to CM implementation. It claims that CM is not

considered a vigorous discipline, having poor recognition, and instead of a single

process it is viewed as the interaction of many processes all embedded within other

functions. According to this study, CM as a generic process across the full life cycle is

missing at present. It is believed that the lack of poor CM recognition is linked with lack

of management support, lack of training, and lack of CM career progression.

Fowler (1996) has also highlighted some major issues in the effective implementation of

CM within shipbuilding organizations. Fowler (1996) further highlighted that although

CM is considered a powerful tool focusing on waste-reduction, quality and the

preservation of design intent, the problems associated with CM implementation should

not be misjudged even in the presence of defined CM principles, practices, and

standards. Even though some aspects may vary according to the nature, structure,

function and objectives of a particular organization; there are some general soft skill

issues with CM implementation. These behavioural issues include lack of sufficient

human resource to introduce CM concepts, unfamiliarity with CM concepts, the

existence of a diverse range of perceptions, and hesitation in accepting the ownership

and commitment to the CM process.


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There are some other studies on multiple issues within CM- although limited- have

highlighted barriers to CM success e.g. lack of resources, lack of standardization, lack of

management support, and lack of user’s acceptance and involvement (Gonzalez and

Zaalouk, 1997), cooperation and coordination, lack of communication (Jarratt et al.

2011), and lack of user friendly software tools (Guess, 2006).

The literature on barriers to CM implementation does not reflect one single study

dedicated to CM implementation barriers. Some of the studies mentioned above do

reflect some barriers but critical review suggests that several highlighted barriers are

based on a particular researcher’s own perception since they believe that the process is

not practiced to its full potential because of a variety of perceived reasons. Little cross

industry research based on collected data has been carried out in some of these studies.

This is a major failing of a phenomenological approach to research, and reflects a

particular bias, especially where the outcome is to promote a particular methodology. It

is also essential to note that many barriers presented in this research have not been

reflected before, for example extreme project pressures, poorly defined CM

requirements and process, lack of flexibility in CM process, lack of authority to

implement CM principles / policies, lack of CM awareness in Customer worlds, and

outdated CM process.

2.4 Maturity models

Maturity is the state or quality of being mature, full development, or perfected condition

whereas maturity of a process is the stage where it is perfectly implemented to achieve

its desired objectives. Maturity Models on the other hand represent theories on how to

evolve the capabilities of an activity in steps along an anticipated, desired, or logical

maturation path and are used to assess the as-is situations to guide improvement

initiatives and to control progress (Röglinger et. al., 2012). It is logical that in the real

world it is not possible to achieve a fully matured process or activity hence it make sense

to highlight stages for improvements and develop paths for achieving those stages to

help individuals in obtaining a certain level of maturity.


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Apparently the concept of process improvement was initiated by Walter Shewhart

through his work on Statistical Quality Control back in 1930s (Team, 2006) which was

formalized through the developments of quality management concepts and practices

where efforts were made to enhance the quality of products / services. It was Crosby

(1997) who developed the five layer Quality Management maturity grid to help

managers to mature their processes. Deming (1986) and Juran (1988) further highlighted

the significance of this concept through their works on continuous process improvement

practices for the development of Quality Management system. The concept is further

signified by Radice et al. (1985) through developing maturity model within IBM and

Humphrey (1989) with a five layers process maturity framework in software

organizations. The Software Engineering Institute (SEI) further developed the concept

by introducing multiple maturity models which were finally combined in the form of

capability maturing model integration (Team, 2006).

The significance of research on the topic could be seen from extensive literature in

multiple areas. According to Spanyi (2004), approximately 150 business maturity

models are available where as 30 alone are working in the field of Project Management

(Grant and Pennypacker, 2006). This shows that the maturity concept is not limited to

SEI initiatives to software sectors but has spread to almost all sectors of knowledge like

project management (e.g. Crawford, 2006; Jugdev and Thomas, 2002; Kwak and Ibbs,

2002), risk management (e.g. Hillson, 1997; Yeo and Ren, 2008), requirements

engineering (e.g. Beecham et al., 2005b), safety (e.g. Filho et. al., 2010;), knowledge

management (e.g. Kulkarni and Freeze, 2004; Paulzen and Perc, 2002), and IT

(Gottschalk and Solli-Sæther, 2006) etc.

Recent research on maturity models has changed the traditional concept of developing

these models. Andersen and Jessen, (2003) developed a model for projects maturity in

organization based on attitude, knowledge, and actions parameters while describing

organizational maturity into three layers i.e. Project, Programe, and Portfolio

Management. Niazi et al. (2005) emphasis on the identification of critical success factors

and critical barriers while generating maturity models while Yeo and Ren (2008)


69

emphasis on process capabilities which are based on the critical success factors and

barrier to process implementation. Beecham and Rainer, (2005b) introduced the

requirements process improvements model based on previous literature and problems

highlighted by professionals through forty-five focused groups in the software

development process. These studies has given a new dimension to this research

CM has remained an integral part of the Capability Maturity Model for software (Paulk

et. al., 1993), Systems Engineering Capability Model (Bate et al., 1995), and Capability

Maturing Model Integration (Team, 2006). The other independent study on the subject is

the development of CM maturity model for medical device industries (McCaffery and

Coleman, 2007). The objectives of these studies are to use it as a reference point to

mature the CM process; however these studies are similar in nature and are not

comprehensive and lack important information. These studies suggest a standardized

approach to mature the process areas of an organization but recent research of Niazi et

al. (2005) and Yeo and Ren (2008) recommends that maturity frameworks should be

based on critical success factors and barriers to its implementation. Moreover these

studies are based on ‘what’ instead of ‘how’ (Jugdev and Thomas, 2002; Niazi et al.,

2005) which forced us to come-up with a framework which emphasis that how to

implement the key aspects of this process to mature an organization’s CM process.

This seems logical since the implementation requirements and improvement priorities

for Configuration Management could never be the same to that of requirements

management, risk management, and product integration and could only be fixed on the

basis of CM specific Critical Success Factors and Barriers to its implementation.

Moreover the maturity guidelines are generic in nature, has ignored the governance

aspects of the process, and emphasis on ‘what’ to implement instead of ‘how’ to

implement which leave a gap of uncertainty to effective maturity of a process.

2.4.1 SEI maturity models

It was the Software Engineering Institute (SEI) who developed the concept of maturity

models and provided foundation for further research. The Software Engineering Institute


70

with mitre corporation started the development of a process maturity framework back in

1986 (Paulk et al., 1993). The Software Engineering Institute released a brief description

of the process maturity framework and a maturity questionnaire in 1987. In the next four

years SEI evolved the software process maturity framework into the Capability Maturity

Model for Software (CMM). The first released document of CMM (Version 1.0) was

used by the software community during 1991 and 1992 which was updated (Version 1.1)

and released in February, 1993 (Paulk et al., 1993).

The release of CMM were followed by the release of two important maturity models i.e.

Systems Engineering Capability Maturity Model (SE-CMM) and the Integrated Product

Development Capability Maturity Model (IPD-CMM). The three Models i.e. the

Capability Maturity Model for Software (SW-CMM), the SE-CMM and IPD-CMM

were combined into Capability Maturing Model Integration SM

(CMMI SM

) (Team,

2006). CMMI model architecture has been improved and was developed for three main

areas, i.e. development, services, and acquisition. CMMI for Development consists of

two models i.e. CMMI for Development with Integrated Product and Process

Development (IPPD) and CMMI for Development without IPPD. Both models share

much of their materials, however, CMMI for Development with IPPD contains

additional goals and practices that cover IPPD (Team, 2006). The history of Capability

Maturity Model by SEI has been indicated in the figure 2-12.

It is important to have a look on those SEI maturity models where CM is the key process

element. This would help to clear our thoughts, understand its working mechanism, and

the pros and cons of these models. It is important to discuss the three maturity models

where CM is one of the key process areas. The three maturity models are the capability

maturity model for software, the systems engineering capability maturity model, and the

capability maturity model integration. The discussion on these maturity models are

presented below.


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Figure 2-12: History of CMMs (Team, 2006)

2.4.1.1 Capability maturity model for software (SW-CMM)

The Capability Maturity Model is a software process capability improvements

framework designed for software organizations and has been evolved from process

maturity framework developed by SEI in 1987 on the requirements of federal

government (Paulk et al., 1993). SW-CMM is a staged model having five levels of

maturity i.e. (1) initial, (2) repeatable, (3) defined, (4) managed, and (5) optimizing.

Each of these levels is assessed according to its capabilities in several key process areas

(KPA). The five staged Capability Maturity Model is shown in figure 2-13.

Each of the five maturity levels has defined characteristics and is outlined below.

i. Initial

Organizations at initial level have more ad-hoc processes and mostly chaotic.

Only few processes are defined and the success of the process depends more on

individual efforts.


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ii. Repeatable

Organizations at Repeatable Level have most essential processes are in place.

Duplication of efforts found in current projects which have been implemented

and are learnt from previous successful projects.

iii. Defined

Organizations at Defined Level are well documented, standardized, and

integrated, process activities.

iv. Managed

Organizations at this level could have abilities to quantitative measure their

software process and product quality

v. Optimizing

Optimized Organization continuous improves their processes.

Figure 2-13 : Five levels of SW-CMM (Paulk, Curtis et al. 1993)


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Each maturity level is composed of several key process areas which are further

organized by common features. Each common feature consists of several key practices.

Implementation of these key practices accomplishes the goals of the key process areas.

2.4.1.1.1 Key Process Areas

There are eighteen key process areas designated to different maturity levels of SW-

CMM (Paulk et al., 1993). The key process areas are distributed in different levels where

it is necessary to accomplish six key process areas at maturity level two, seven at

maturity level three, two at maturity level four, and three at maturity level five. There is

no key process which is specified to level one of SW-CMM. Detail of these key process

areas are listed in the table 2-5.

2.4.1.1.2 Common Features

These key process areas are organized by common features. Common features highlight

that whether the implementation and institutionalization of key process areas are

effective, repeatable, and lasting. The five common features have been listed below

(Paulk et al., 1993):

i. Commitment to perform

ii. Ability to perform

iii. Activities performed

iv. Measurement and analysis

v. Verifying implementation

2.4.1.1.3 Key practices

Each key process area has been explained in terms of key practices. The objective of

these key practices is to satisfy the overall objectives of each process areas. Key Practice

is usually a single sentence, sometimes followed by a detailed description, which


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describes the fundamental policies, procedures, and activities of the key process area.

Detailed description is frequently referred to as sub-practices.

CAPABILITY

LEVEL

CAPABILITY

NAMES KEY PROCESS AREAS

1 Initial -------------

2

Repeatable a. Software Configuration Management

b. Software Quality Assurance

c. Software Subcontract Management

d. Software Project Tracking And Oversight

e. Software Project Planning

f. Requirements Management

3

Defined a. Peer reviews

b. Intergroup Coordination

c. Software Product Engineering

d. Integrated Software Management

e. Training Program

f. Organization Process Definition

g. Organization Process Focus

4 Managed a. Software Quality Management

b. Quantitative Process Management

5

Optimizing a. Process Change Management

b. Technology Change Management

c. Defect Prevention

Table 2-5: List of key process areas of SW-CMM (Paulk et al., 1993)

2.4.1.1.4 CMM implementation

SW-CMM has been effectively used in the past by organizations for software process

assessment and software capability evaluation. Software assessments and evaluations


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were mainly done by a team of specialized persons against a maturity questionnaire

(Zubrow et al., 1994). After in-depth interviews which were followed from a response

analysis on questionnaire, findings were compiled based on the SW-CMM.

Improvements were suggested on the KPA profile which was generated on the findings

from both questionnaires and interviews.

2.4.1.1.5 CM as a key process area

The Capability Maturity Model for software was designed to enhance the maturity of an

organization where each process area was explained in terms of its requirements without

any independent maturity path for any specific process area. Configuration Management

is one of the key process areas where four goals are highlighted related to the

implementation of the major elements of the process. A critical review of the model

highlights the necessary requirements but lags sufficient information on providing path

for the maturity of the process. In other words there are materials on what to implement

but lags on how to implement the listed criteria to achieve the required objectives.

It is also important to note that this model only highlights a five stage maturity path for

an organization based on eighteen process areas where Configuration Management is

one of them. This is not a maturity model for maturing the Configuration Management

practices but only highlight some basic criteria necessary to fully implement the process.

The Configuration Management process area has been described in terms of unique

goals, commitments, abilities, activities, measurements, and verification statements

where some basic requirements are missing (e.g. the governance of the process).

Moreover, there are only eight questions available in the SW-CMM questionnaire to

measure the CM process (Zubrow et al., 1994) which not is sufficient for the

measurement of any significant process in the preview of latest available literature.

2.4.1.2 Systems engineering capability maturity model (SE-CMM)

The Systems Engineering Capability Maturity Model (SE-CMM) was developed by SEI

to support and improve the systems engineering discipline in organizations. SE-CMM is


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a multipurpose framework and was designed for obtaining different objectives in

different circumstances. First, SE-CMM was a useful guide for individual systems

engineering practitioners; secondly, it acted as a productivity improvement tool for their

parent organizations; and thirdly it was a good choice as a tool for supplier selection by

any organization (Bate et al., 1995). SE-CMM was divided in two main areas i.e. basic

systems engineering elements (the domain side) and process management focused

elements (the capability side). The domain and capability side of the SE-CMM has been

shown in the figure 2-14.

2.4.1.2.1 Capability portion

The Systems Engineering Capability Maturity Model (SE-CMM) has grouped the

process capability into three tires i.e. capability levels, common features, and generic

practices. Capability levels are the increasing levels of process maturity having some

common features. Each common feature consists of several generic practices. Fulfilment

of these generic practices for each process area was responsible for increasing the level

of capability for each process area. There are five capability levels (figure 2-15) and

eleven common features (table 2-6) mentioned in the Systems Engineering Capability

Maturity Model (Bate et al., 1995).

2.4.1.2.2 Domain portion

The SE-CMM explains the systems engineering domain by using process areas. Each

process area further includes several base practices and explanatory notes. There are 18

process areas which are grouped into three process categories i.e. Engineering, Project,

and Organization (Bate et al., 1995). Each process area can be improved through a step

wise approach as shown in figure 2-15. Details of process categories and process areas

are given in the table 2-7 below.


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Figure 2-14: SE-CMM Model architecture (Bate et al., 1995)

Figure 2-15 : Improvement path for process capability (Bate et al., 1995)


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Capability

Level Capability Names Common Features

1 Performed

Informally a. Base practices performed

2 Planned and

Tracked

a. Planning Performance

b. Disciplined Performance

c. Verifying Performance

d. Tracking Performance

3 Well Defined a. Defining a Standard Process

b. Perform the Standard Process

4 Quantitatively

Controlled

a. Establishing Measurable Quality Goals

b. Objectively Managing Performance

5 Continuously

Improving

a. Improving Organizational Capability

b. Improving Process Effectiveness

Table 2-6: Capability levels with their common features (Bate et al., 1995)

2.4.1.2.3 Improving systems engineering maturity

One of the possible outlays for improving the system engineering maturity within an

organization is shown in the following five figures. An organization will be called at

“Capability Level-1 Engineering” if the engineering process is at level one. The

organization can proceed to “Capability Level-2 Engineering” if the project process of

an organization reaches level one. The organization can reach to “Capability Level-3

Engineering” if the project process obtains capability level two and organization process

obtains level one. Similarly, the organization can attain the “Capability Level-4

Engineering” if both the project process and organization process reach capability level

three. Finally the organization can obtain “Capability Level-5 Engineering” of both the

project process and organization process achieves capability level four.


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Engineering Process

Areas

Project Process Areas Organizational Process

Areas

Analyze Candidate

Solutions Ensure Quality Coordinate with Suppliers

Derive and Allocate

Requirements Manage Configurations

Define Organization's

Systems Engineering

Process

Evolve System

Architecture Manage Risk

Improve Organization's

Systems Engineering

Processes

Integrate Disciplines Monitor and Control

Technical Effort

Manage Product Line

Evolution

Integrate System Plan Technical Effort

Manage Systems

Engineering Support

Environment

Understand Customer

Needs and Expectations

Provide Ongoing

Knowledge and Skills

Verify and Validate

System

Table 2-7: SE-CMM Process Categories and Process Areas (Bate et al., 1995)

Figure 2-16: Capability level-1 engineering (Bate et al., 1995)


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2.4.1.2.4 CM process within SE-CMM

Configuration Management has been explained in Process-09 of the SE-CMM under the

heading of Manage Configurations. Five base practices have been identified to explain

the term of Configuration Management. By fulfilling these base practices in its totality,

we can achieve Level-1 of CM Process. To achieve the next levels for this process we

have to fulfil the requirements of related general practices.

There are some limitations in the CM process as explained in the SE-CMM. First of all,

it should be noted that the five base practices of CM as explained in SE-CMM do not

explain this process area in its totality. Secondly, the general practices are same for all

eighteen process areas to mature a specific process. The assumptions behind this

approach is that all process have similar requirements to mature and might be facing the

same problem during its implementation, hence needs a similar approach to overcome

those problems. This needs further research to come on conclusion that whether this

assumption is true or not.

2.4.1.3 Capability Maturity Model Integration (CMMI)

The Capability Maturity Model Integration (CMMI) is a process improvement maturity

model for the development of products and services. CMMI addresses development,


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maintenance and acquisition activities that cover the product lifecycle from conception

through delivery and maintenance. There are three CMMI modules as listed below.

• CMMI for development

• CMMI for services

• CMMI for acquisition

The CMMI for development is the point of interest because Configuration Management

is one of the major process areas explained.

2.4.1.3.1 CMMI for development

CMMI for Development has been developed to help organizations in improving their

development and maintenance processes for both products and services. CMMI for

development V1.02 was initially released in 2000, updated to V1.1 in 2002, and V1.2 in

2006. The purpose CMMI for development is to cope with the problem of using multiple

Capability Maturity Models. The CMMI for Development was built by integrating the

three major capability maturity models i.e. Capability Maturity Model for Software,

Systems Engineering Capability Maturity Model, and Integrated Product Development

Capability Maturity Model (Team, 2006). It is important to note that all the previous

three capability maturity models are no more valid to use.

CMMI uses two different representations for process improvement i.e. continuous and

staged (TEAM, 2006). The continuous representation facilitates an organization to select

a process or group of process areas for improvements. Continuous representation uses

capability levels to characterize improvements to an individual process area. The staged

representation is characterized by maturity levels and uses predefined sets of process

areas to define an improvement path for an organization.

There are twenty two process areas which have been grouped into four categories. Each

process area has been assigned to a specified capability level. There are seven processes


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associated to maturity level two, eleven processes to maturity level three, and two

processes each to maturity level four and five. Details of these process areas along their

maturity level and groups are shown in table 2-8.

Each process area can be matured to Capability Level-5 (continuous representation) by

fulfilling the requirements of six capability levels (table 2-9). For process maturity, an

initial requirement is to fulfil specific goals and specific practices related to that process

area. After fulfilling these basic requirements, a process can be matured by fulfilling the

generic goals and generic practices. Group of processes can be matured to a Maturity

Level-5 (staged representation) by fulfilling the requirements of five Maturity Levels

(table 2-9). Organization can select any number of processes in the staged representation

as per their ability to enhance a group of processes.

To enhance the overall maturity level of an organization it should be noted that to

achieve maturity level 2, all process areas assigned to maturity level 2 must achieve

capability level 2 or higher while to achieve maturity level 3, all process areas assigned

to maturity levels 2 and 3 must achieve capability level 3 or higher. To achieve maturity

level 4, all process areas assigned to maturity levels 2, 3, and 4 must achieve capability

level 3 or higher while to achieve maturity level 5; all process areas must achieve

capability level 3 or higher (TEAM, 2006).

2.4.1.3.2 CM Process in CMMI for development

According to CMMI for Development, CM Process can be enhanced to capability Level-

5 through continuous representation. The approach of enhancement presented in CMMI

is similarly to that of SE-CMM. The basic differences are in the terms generic goals and

generic practices which are used for common features and generic practices respectively.

Also, the base practices, as explained in the SE-CMM do not explain the CM process in

its totality; but in CMMI, these have been fully explained under the headings of Specific

Goals and Specific Practices of CM.


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PROCESS AREA PROCESS

CATEGORIES

MATURITY

LEVEL

Requirements Management Engineering 2

Project Planning Project Management 2

Project Monitoring and Control Project Management 2

Supplier Agreement Management Project Management 2

Measurement and Analysis Support 2

Process and Product Quality Assurance Support 2

Configuration Management Support 2

Requirements Development Engineering 3

Technical Solution Engineering 3

Product Integration Engineering 3

Verification Engineering 3

Validation Engineering 3

Organizational Process Focus Process Management 3

Organizational Process Definition +IPPD Process Management 3

Organizational Training Process Management 3

Integrated Project Management +IPPD Project Management 3

Risk Management Project Management 3

Decision Analysis and Resolution Support 3

Organizational Process Performance Process Management 4

Quantitative Project Management Project Management 4

Organizational Innovation and Deployment Process Management 5

Causal Analysis and Resolution Support 5

Table 2-8 : Details of process areas (TEAM, 2006)


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LEVELS

CONTINUOUS

REPRESENTATION

(CAPABILITY LEVELS)

STAGED

REPRESENTATION

(MATURITY LEVELS)

Level 0 Incomplete N/A

Level 1 Performed Initial

Level 2 Managed Managed

Level 3 Defined Defined

Level 4 Quantitatively Managed Quantitatively Managed

Level 5 Optimizing Optimizing

Table 2-9 : Capability and maturity levels (TEAM, 2006)

It is important to note that the whole model is based on generic practices and base

practices concept. The model has similar limitations as highlighted in the previous two

models of the same family which are not based on critical success factors and barriers to

a specific process but has followed the general trend already in use. It is evident that

these are not research models which are generated by targeting specific areas or

processes but has followed a general trend by targeting an overall organization. The

model does highlighted some areas in general but has not specified them specific to a

process which could be summarized like ‘the model does say what to do but lacking in

conveying the message of how to do it’ e.g. the model is talking about measuring the

CM process at level four but does not highlight what to measure and that how it will

benefit in the improvement of the process.

2.4.2 CM Capability Model for the medical device industry

McCaffery and Coleman (2007) developed a Configuration Management Capability

Model which is specifically dedicated to CM improvement process in the medical device

industry. This model is based on the comparison of Configuration Management


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activities in medical device industry to that of capability maturity model integration CM

process. The studies of McCaffery et al. (2008) and McCaffery and Coleman (2007)

highlighted that medical device industry only implement seventeen out of thirty eight

CMMI practices with two additional practices which are not mentioned in CMMI

guidelines. Details on the number of practices specific to three goals are show in table 2-

10.

CMMED

goal

CMMI

activities

CMMI

activities to

meet medical

device

requirements

Additional

activities to

meet medical

device

requirements

Goal 1 17 6 1

Goal 2 9 8 1

Goal 3 12 3 0

Total 38 17 2

Table 2-10 : Comparison of CM activities in Medical Device Industry and CMMI

(McCaffery et al., 2008)

Configuration Management Capability Model for medical device industry consists of six

capability levels (McCaffery and Coleman 2007). The Level-0 of the CMMI is replaced

with Level-Med in this capability model while the rest five levels are unchanged to that

of CMMI. According to McCaffery, nineteen specific practices and five general

practices are at Level-Med, twenty one specific practices are at level one, five general

practices are at level two, two general practices are at level 3, two general practices are

at level four, and two general practices are at level five.

The model of McCaffery and Coleman (2007) is nothing more than a comparison of the

CM practices as used in medical device industry with that of CM process area in CMMI

model to come-up with Capability Model for Medical Device Industry. There is no


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significant difference between the two models except the explanation of the terms

specific to medical industry. The model does not cover any specific problem that

management do face during the CM implementation within medical device industries.

Also, there is no special emphasis on the success factors which are critical to be

implemented for the success of CM within these industries.

It is important to note that all CMMI CM specific processes are at capability level one

but nineteen specific practices of CM regarding medical device industry are at Level-

Med in this model without any specific reason. It is also to note that five of the general

practices are at capability Level-Med which is against CMMI concept where no generic

goal exists at this level as there is no reason to institutionalize a partially performed

process. It is logical to give reasons for deviation if you are following a specific

approach as a whole.

CM implementation strategies are different in different industries which are mostly

dependent on the size of the organization, type of products, and scope of work. Due to

these factors, the capability model; which is an improvement model, must have some

differences in the maturity process. Capability Models should be based on the factors

which boost the organization to mature the process. These factors are the critical success

factors which are responsible for a process to mature. Furthermore it is important to have

the knowledge of the factors which are creating problems in the improvement process of

Configuration Management so that organization could be able to look for any remedial

actions and guide their process to maturity.

2.4.3 Limitation of CM related maturity models

Existing Configuration Management related maturity models does cover the following

main aspects:


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• There is a general view that previous maturity models are based on ‘what to

implement’ instead of ‘how to implement’ things (Jugdev and Thomas, 2002; Niazi

et al., 2005) to mature a process which leads researchers to work on the issue.

• Critical Success Factors and Barriers to a process / system play a key role while

developing maturity models (Niazi et al., 2005); Yeo and Ren, 2008) but these

aspects are totally ignored while developing CM related maturity models which may

affect the maturity concept in the field.

• It is important to mention the improvement priorities for the maturity of any process

while attempting a process maturity. This is no where present in these process

maturity models.

• Most maturity guidelines are generic and are applicable to all process areas of an

organization. These guidelines should be specific to a process so that concerned

individuals could easily implement the same.

• Most importantly, previous maturity models (SE-CMM or CMMI) are system

engineering based models which are specifically designed for those 18 or 22 process

areas to mature an overall organization. These maturity models work well if we

consider an overall organization but do not provide a clear picture when come to

independent process maturity.

2.4.4 Research on maturity models in other allied fields

Despite the development of different maturity models on multiple aspects by the SEI,

significant research has taken place in the last two decades in multiple fields which show

the importance of the topic and the limitation of the SEI models. It is widely believed

that these studies are based on ‘what’ instead of ‘how’ (Jugdev and Thomas, 2002; Niazi

et al., 2005) and forced researchers to come-up with different frameworks which

emphasise how to implement the key aspects to mature their processes.


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There is a wide range of research on the issue where approximately 150 business

maturity models are available where as 30 alone are working in the field of Project

Management (Grant and Pennypacker, 2006) and is extended to other areas e.g.

requirements engineering (e.g. Beecham et al., 2005b), safety (e.g. Filho et. al., 2010),

knowledge management (e.g. Kulkarni and Freeze, 2004; Paulzen and Perc, 2002), and

IT (Gottschalk and Solli-Sæther, 2006) etc. It is important to review some of the

frequently highlighted studies in these diverse areas before initiating any further research

on the topic which could help in answering the limitation highlighted by previous

researchers in the previous studies. Some of the studies are given below which have

helped in the development of this research.

2.4.4.1 Maturity model for software process improvement

The study of Niazi et al. (2005) highlights a maturity model for software process

improvements which is mainly based on critical success factors and barriers to software

process improvements. The structure of the maturity model in built upon three

dimensions i.e. maturity stage dimension, critical success factors dimension, and

assessment dimension. The maturity stage dimension has four maturity levels and is

shown in table 2-11. The CSFs dimension has four maturity levels which are based on

critical success factors and barriers to software process improvements which are

categorized in into three categorize i.e. awareness, organizational, and support shown in

table 2-12. Each Critical Success Factor and Barriers are highlighted with the help of

five statements or practices which needs to be measured on a scale from 1 to 10. It is

important to note that to achieve any maturity level, all critical success factors and

barriers that belong to that maturity level should have an average score of 7 or above.


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Table 2-11: Maturity stage dimension (Niazi et al., 2005)

Maturity Stage Front-end category Back-end category

4 -Optimising Support Awareness

Organizational

3 - Defined Organizational Awareness

2 - Aware Awareness

1 - Initial

Table 2-12: Critical Success Factors dimension (Niazi et al., 2005)

2.4.4.2 Risk management capability maturity models

The Study of Yeo and Ren (2009)

Yeo and Ren (2009) developed a risk management capability maturity model for

complex product systems (CoPS) Projects (CoPS-RM-CMM) to provide a framework to

help CoPS producers and project teams to standardize their current approach in risk

management against different risk management scenarios. The CoPS-RM-CMM has

been divided into two components i.e. maturity levels and capability levels. There are

five maturity levels and ten capabilities (based on success and risk factors) which are


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further divided into three main areas. Details of Capability and Maturity of CoPS-RM-

CMM are shown in figure 2-21.

Figure 2-21 : Maturity levels of CoPS-RM-CMM (Yeo and Ren, 2009)

Category Key Capability Areas

Organization

Organization Culture

Stakeholder coalition

Leadership

Organization structure and support

Process

Risk planning and identification

Risk analysis

Risk mitigation

Process integration and improvement

Project management process

Technology Technology

Table 2-13: Capability Areas of CoPS-RM-CMM (Yeo and Ren, 2009)

CoPS-RM-CMM uses a questionnaire-based appraisal method to assess the risk

management capability maturity of a real-life CoPS projects (Yeo and Ren, 2009). Risk


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management capabilities in table 2-13 are converted into series of questions or

statements suitable for questionnaire survey purposes. The response on each question is

based on Five Point Likert Scale from 1 to 5. The maturity of a key capability area is the

average score of its items and provides quantitative results. Using this method, we can

identify which capability areas are weak as well as the appropriate suggestions for

improvements based on model.

The Study of Hillson (1997)

Hillson (1997) generated a four levels risk maturity models as shown in the figure 2-22.

The attributes of the typical organization at each maturity level is defined under four

different attributes i.e. culture, process, experience, and application which help

organization to compare their risk management processes against a clear criteria. The

study has also defied comprehensive guidelines for progressing between different

maturity levels.

Figure 2-22: The four levels of risk maturity (Hillson, 1997)

2.4.4.1 Project Management maturity models

Extensive research is available on maturity models in the field of project management. It

is important to have an overview of some latest maturity model which are highly

referred in the literature. Review of literature suggests that there is no one way to define


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the maturity process for a specific discipline. The studies described here have a different

approach for the maturity of project management activity within organization which

shows the diversity and extent of variation in the subject.

The study of Andersen and Jessen (2003)

The study of Andersen and Jessen (2003) is unique in its concept on the subject of

maturity when compared to other similar studies. The maturity of projects are discussed

in three different dimensions i.e. attitude, knowledge, and actions. Each of the three

dimensions is measured on four different dimensions adopted from multiple research

studies. The ladder of maturity defined by Andersen and Jessen (2003) is in three steps

which start at the basic level from Project Management (the management of individual

projects), proceed to the next level i.e. Program Management (program is a collection of

projects related to some extent to a common objective), and finalizes at the third level

i.e. portfolio Management (the management of a number of projects or programs that do

not necessarily share a common objective).

A questionnaire survey was conducted containing a list of 36 questions based on the

theoretical framework from three dimensions i.e. attitude, knowledge, and actions. The

questionnaire was tested on 59 middle managers and project managers attending the

master of management program in project management. The levels of maturity were

calculated based on the statistical analysis and recommendations were made.

The Study of Kwak and Ibbs (2002)

The Project Management Process Maturity (PM)2 Model developed by Kwak and Ibbs

(2002) aims to integrate previous PM practices process and maturity models to improve

the project management effectiveness. This is a more detailed model which was initially

developed be Ibbs and Kwak (1997).The model is based on the discussions with PM

professionals and review of the literature to capture the different aspects of maturity

concept. This maturity model has nine PM knowledge areas (project scope management,


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project time management, project cost management, project quality management, project

human resource management, project communications management, project risk

management, and project procurement management) and five PM processes (initiating

process, planning process, executing process, controlling process, and closing process).

There are five maturity levels (figure 2-23) where each level contains key PM process

(table 2-14), organization’s characteristics (table 2-15, and focus areas (table 2-16). Each

level of the model has different characteristics of the nine knowledge areas and five

processes.

Figure 2-23: (PM) 2 model (Kwak and Ibbs, 2006)


95

Table 2-14: Key PM Processes of (PM) 2 model (Kwak and Ibbs, 2006)

Table 2-15: Major organizational characteristics of (PM) 2

model (Kwak and Ibbs, 2006)


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Table 2-16: Key focus areas of (PM) 2 model (Kwak and Ibbs, 2006)

The Study of Crawford (2006)

The model developed by Crawford (2006) utilizes the PMBOK Guide’s nine knowledge

areas and patterned similar to that of SEI’s CMMs. The model is shown in figure 2-24

having specific characteristics for each of the level. This study have emphasized on three

special components i.e. project office, management oversight, and professional

development beside other parameters. The assessment of maturity is defined in four

ingredients i.e. interviews, artefact collection and evaluation, survey input, and

benchmark comparison to established standards.


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Figure 2-24: Project Management Maturity Model (Crawford, 2006)

The list of such maturity models is not short. Some of the models highlighted above are

included to give an idea of the different concepts. There are other studies which has

supported this research in the development of CM maturity model. The studies which

are important to mention are the maturity grid to enhance the maturity of requirements

engineering by Beecham et al. (2005b), maturity model on requirements engineering

introduced by Sawyer et al. (1997), software testing maturity model developed by

Burnstein et al. (1996), model to assess testing process maturity introduced by Burnstein

et al. (1998), maturity model for offshore organizational management by Strutt et al.

(2006), safety culture maturity model by Filho et al. (2010), Maintainer’s education and

training model by Kajko-Mattsson et al. (2001), maturity model for IT outsourcing


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relationships Gottschalk and Solli-Saether (2006), maturity model for Knowledge

Management by Paulzen and Perc (2002), maturity model for performance measurement

systems developed by Wettstein and Kueng (2002), and documentation maturity model

introduced by Huang and Tilley (2003).

2.5 Literature search strategy

The literature highlighted above is obtained by using multiple keywords in different

search engines. Details of the keywords and search engines are given below.

2.5.1 Keywords

Following keywords were used throughout this research to obtain the literature

highlighted above.

Configuration management, Software Configuration Management, Configuration

Management in Aerospace and Defence Industries, Configuration Management Critical

Success Factors, Barriers to Configuration Management implementation, Critical

Success Factors, Process Barriers, Process Capabilities, Project Management Critical

Success Factors, Maturity Model, Process Maturity, Process Improvement, Project

Management, Quality Management, Inferential Statistic, Parametric Tests, Non

Parametric Tests, Governance, Types of Organizational Structures.

2.5.2 Search engines

Following are the major search engines which were used to search the required literature

on multiple topics within this research.

• http://scholar.google.co.uk/

• http://www.sciencedirect.com/

• apps.webofknowledge.com (http://wokinfo.com)


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• www.engineeringvillage.com

• http://www.scopus.com/home.url

• http://www.scienceresearch.com/scienceresearch/

• http://search.proquest.com/abiglobal/index

• http://www.sciencedirect.com

• http://web.b.ebscohost.com/ehost/search/advanced?sid=9da71bd8-6aa8-43f4-be6f-

94a48b33e6f7%40sessionmgr115&vid=2&hid=108

• http://wok.mimas.ac.uk/

2.6 Summary and conclusions

2.6.1 Summary

This chapter summarize the theoretical and practitioners’ perspectives on the topics

covered in this research. It has been observed that the academic literature on

Configuration Management is extremely limited whereas defence related standards have

dominated the field. There are some studies available but have specific limitations in

terms of their focus and their scope of the discipline. The majority of the studies purely

focus specific areas like change management and status accounting and not

Configuration Management in general. To establish a solid foundation in terms of the

literature, other allied fields (e.g. knowledge management, quality management, and

project management etc.) are studied to have a good theoretical background.

The literature on maturity models (e.g. Bate et al., 1995; TEAM, 2006) suggests the

importance of base practices. The base practices explain the necessary elements of a

process which are compulsory to implement for the effective implementation of the

process. The base practices of Configuration Management are comprehensively covered

in the literature (EIA-649, 2011; Guess, 2006; MIL-HDBK-61, 1997; MIL-STD-973,

1992; PMI, 2007; Samaras, 1988; Watt, 2008) with little changes over the years. The

first section of this chapter is dedicated to Configuration Management which highlight

the strength of the literature on the base practices of the process. It is important to note


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that the literature is an overview of the process base practices where as detailed base

practices could be obtained by picking any latest source document conforming to the

standards of CM.

The research on Critical Success Factors for the implementation of Configuration

Management is a major part of this research and its literature is covered in the second

section of this chapter. The review of the literature highlights no formal study on critical

success factors in the field of Configuration Management, however, limited literature in

the form of case studies and research theories are available on the success and failures or

problems in the implementation of Configuration Management. On the other hand

extensive literature is available on the subject in other allied field like project

management and knowledge management etc. which provided the required help in

establishing a strong foundation and guide to achieve the objectives.

It was important to discuss the studies on Barriers to Configuration Management

implementation as highlighted in the third section of this chapter. Detailed search of the

peer reviewed journals and practitioner literature highlights that research based study on

the topic is unexpectedly and extremely scare in comparison with other allied processes

like quality management and knowledge management whereas no formal study is found

with the aim to explore barriers to CM implementation. Some studies have supported the

need for this research in many aspects but have specific limitations on their own e.g.

instead of targeting CM as a holistic and generic process, these studies have targeted

specific elements of CM execution. Because of the limited studies on the topic, other

allied studies in the areas of Quality Management, Knowledge Management, project

Management, and Business Process Management provided a great deal of scope in this

area of study.

The last section of discussion in this chapter is related to the literature on maturity

models. It was important to know why the notion of maturity was introduced and

developed over time? And how the maturity of Configuration Management process is

defined and analysed? It has learnt that even the concept was introduced by Crosby


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(1997); the Software Engineering Institute (SEI) further developed the concept by

introducing multiple maturity models where some were finally combined in the form of

capability maturing model integration. CM has remained an integral part of the

capability maturity model for software, systems engineering capability model, and

capability maturing model integration. These studies suggest a similar pattern to mature

the process areas of an organization whereas other latest studies recommends that

maturity frameworks should be based on critical success factors and barriers to its

implementation which looks logical since the implementation requirements and

improvement priorities could never be the same for different processes. Moreover these

maturity models are generic in nature, have ignored the governance aspects, and are

based on what to implement instead of how to implement which is a gap of uncertainty

to effective process improvement methodologies which needs to be addressed.

2.6.2 Conclusions

The literature suggest that industries are facing difficulties in the implementation of CM

practices (Burgess et al. 2005) despite efforts to enhance CM practices through Maturity

Models (e.g. McCaffery and Coleman, 2007; Paulk et al. 1993; Team, 2006). The

objectives of these studies were to effectively implement and continuously develop the

CM process; however these studies are similar in nature, lack some important

information, suggest one standardized approach of maturity for different process areas,

and are based on ‘what’ instead of ‘how’ to implement the maturity concepts (Jugdev

and Thomas, 2002; Niazi et al., 2005). Moreover, recent research of Niazi et al. (2005)

and Yeo and Ren (2008) recommends that maturity frameworks should be based on

critical success factors and barriers to its implementation which seems logical since the

implementation requirements and improvement priorities for CM could never be the

same to that of other process areas and could only be fixed on the basis of CM specific

critical success factors and barriers to its implementation. Because of the major

deficiencies highlighted above by Jugdev and Thomas, (2002) and Niazi et al., (2005)

and some new incites presented by Niazi et al. (2005) and Yeo and Ren (2008) forced us

to present a new model which emphasis on how to implement the key aspects of this


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process to mature an organization’s CM process. Since there were no formal studies on

CM related CSFs and Barriers, it was important to explore these areas and provide the

necessary foundation for the development of Configuration Management Maturity

Model.

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CHAPTER 3

RESEARCH DESIGN AND METHODOLOGY

3.0 Introduction

This chapter describes the research philosophy, approach, and strategies applied to

address the research problems as outlined in Chapter 1. All materials have been

presented to illustrate the way in which the data is collected to answer the research

questions as presented in Chapter 1. The research process is generally conceived in

terms of research philosophy, research approaches, strategies chosen and different tools

and techniques used to achieve the research objectives. The research process which has

been presented here is captured from the research onion developed by Saunders et al.

(2009) and is shown in figure 3-1.

Figure 3-1: The research onion (Saunders et al., 2009)

The research process has been explained in six layers. The first layer of this “Research

Onion” highlights research philosophies while the second describes the research

Chapter 3: Research design and methodology

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approaches followed by research strategies. The fourth layer is the choices in which a

researcher has a choice to define specific research methods while the fifth is the time

horizons and the sixth and last layer is the techniques and procedures applied to conduct

a research.

3.1 Research aim and objectives

It is important to reflect back upon the research aims and objectives presented in Chapter

1 before explaining the selected research methodology and methods. The aim of this

research is to highlight and evaluate practitioners’ perception on critical success factors

and critical barriers and develops a roadmap to achieve excellence in the implementation

and continuous development of Configuration Management process in aerospace and

defence industries. The core objective of this research was to develop maturity model for

the effective implementation and continuous development of Configuration

Management process. To achieve this objective it was important to give special

consideration to critical success factors, barriers to Configuration Management

implementation, and governance aspects of the process. It was therefore necessary to

identify, prioritize, and categorize both critical success factors and barriers to

Configuration Management and investigate the governance aspects of the process both

in aerospace and defence industries.

The proceeding sections present in detail the research methodologies which are

discussed in the context of the research aim and objectives by examining the most

appropriate techniques for this research.

3.2 Research process

This section highlights the sequence of studies conducted in this research and are

summarized in the form of a flowchart in figure 3-2. Since Critical Success Factors and

Barriers to a process provide baseline guidelines for the maturity of any existing process

(Niazi et al., 2005; Yeo and Ren, 2008), this research is divided into three parts i.e.


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identification of CM CSFs, barriers to CM implementation, and developing the CM

maturity model. The first part of this research was designed to achieve the first objective

and hypothesis highlighted in sections 1.2 and 1.4 respectively. In-depth interview were

arranged with five CM subject matter experts followed by an emails consultation with

three CM practitioners with more than thirty years of CM experience. The success

factors from the two activities were combined with the available literature in the form of

a questionnaire and forwarded to a group of thirteen CM subject experts in a meeting of

the ‘Association of Configuration Managers’ (ACM) at The University of Manchester,

UK for their critical review. The final questionnaire (Appendix A) was then sent to CM

professionals from aerospace and defence companies where 94 received questionnaires

were used for further analysis. The results, analysis, and discussion, of the first phase are

fully described in Chapter 4.

The second part of this research was designed to achieve the second and third objectives

presented in section 1.2 and second hypothesis highlighted in section 1.4. To identity

and analyse the barriers to CM implementation and discuss the governance aspects of

the process, in the second phase of the research, seven semi-structured interviews with

CM experts of four different industries were conducted. A comprehensive questionnaire

was generated from the critical analysis of the data obtained from seven semi-structured

interviews and an open ended question on barriers to CM implementation through 64

questionnaires from the first part of my research. The questionnaire (Appendix C) was

submitted to CM professionals from aerospace and defence companies where feedback

of a total of 187 questionnaires were included in the final analysis to decided on the

second hypothesis presented in section 1.4. It is important to note that identification of

barriers to CM implementation were accomplished through 64 questionnaires and seven

interviews while governance aspects of the process was covered in the seven interviews

and are covered in Chapter 5. The results, analysis and discussions related to the second

hypothesis are described in Chapter 6.


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Figure 3-2: Research process flowchart


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To achieve the fourth objective presented in section 1.2 and third hypothesis described

in section 1.4, in the third part of this research, semi-structured interviews were arranged

followed by two questionnaire surveys after critical analysis of the selected studies for

an initial model. The semi-structured interviews conducted with six CM experts of four

aerospace and defence organization were followed by two questionnaire surveys which

were conducted to achieve the establish objectives. The first questionnaire survey was

related to model validation (Appendix E) while the second survey was related to

measuring the process maturity (Appendix F). A total of 50 responses on model

validation questionnaire while 52 responses on process maturity questionnaire were

received which were used for later analysis to achieve the desired objectives. The

results, analysis, and discussion related to the third part of this research are presented in

Chapter 7.

3.3 Research design and methodology.

The six areas of research described by Saunders et al. (2009) presented in figure 3-1 are

research philosophy, research approach, research strategies, research method choices,

time horizons, and techniques and procedures. These areas have been summarized in the

following sections in which each section presents a brief explanation of the research

paradigm along with its rationale for this research.

3.3.1 Research philosophy

The term research philosophy relates to the development of knowledge and the nature of

that knowledge (Saunders el al., 2009). According to Saunders el al. (2009); there are

three major ways of thinking (ontology, epistemology, and axiology) to look at four

research philosophies (positivism, realism, Interpretivism, and pragmatism) used in

management research. It is difficult to decide which research philosophies would best fit

a research but rather reflects that one will be touching most of the philosophies at the

same time. Selecting a particular research philosophy mainly depends on research’s way

of thinking about the development of knowledge and has a great effect on the outcomes


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of a specific research. Selection of a particular research philosophy can be accomplished

by emphasizing on the type research questions, by studying research philosophies

previously selected in the same area of knowledge, and by studying the literature on

research methodologies in a specific subject. On the basis of these guidelines, following

two epistemological research philosophies have been selected for this research. It is hard

to say that all other research philosophies have been ignored and were not under

consideration but are touched in bits and pieces as the research proceeded.

• Positivism

• Phenomenology / Interpretivism

These two terms have been used through different names by different researchers which

have been summarized and are listed below in table 3-1. Brief explanations of these two

terms are given in the following sections to strengthen our stance of why they have been

selected.

Positivist Paradigm Phenomenological Paradigm

Quantitative Qualitative

Objectivist Subjectivist

Scientific Humanistic

Experimentalist Interpretivist / Hermeneutic

Traditionalist

Hypothetico deductive Inductive

Social Constructionism

Table 3-1: Alternative terms for positivist and phenomenological paradigms (Mangan et

al., 2004)

In a positivist paradigm the researcher play a role of an observer or objective analyst by

making independent interpretations about the data which is obtained without his

involvement and interactions with the object (Hussey and Hussey, 1997; Saunders et al.


109

2003). Since there is no direct interaction of the researcher with the object, a refined

structured research methodology is required to get quantifiable data for the statistical

analysis to deduce theories. ‘Positivism is an epistemological position that advocates the

application of the methods of the natural sciences to the study of social reality and

beyond’ (Bryman and Bell, 2007). Positivistic Paradigm uses the research concept of

natural sciences in the field of social sciences (Hussey and Hussey, 1997). It uses

experimental and quantitative methods to test hypothetical-deductive generalizations.

Positivism is a research method that focuses on generating supposedly objective data,

usually in the form of statistics to generalize a research (McNEILL, 1990).

Positivist paradigm Phenomenological paradigm

Basic beliefs: The world is external and

objective

Observer is independent

Science is value-free

The world is socially

constructed and subjective

Observer is part of what

observed

Science is driven by human

interests

Researcher

should:

Focus on facts

Look for causality and

fundamental laws

reduce phenomena to

simplest elements

formulate hypotheses and

then test them

Focus on meanings

Try to understand what is

happening

Look at the totality of each

situation

Develop ideas through

induction from data

Preferred

methods

include:

Operationalising concepts

so that they can be

measured

Taking large samples

Using multiple methods to

establish different views of

phenomena

Small samples investigated in

depth or over time

Table 3-2: Key features of the positivist and phenomenological paradigms (Easterby-

Smith et al., 1991).


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Phenomenological paradigms deal with the action and behaviour which are produced

from within human mind and where the interrelationship of the researcher and the object

was impossible to separate (Hussey and Hussey, 1997). It deals with understanding of

behaviour from the participant’s subjective frames of reference where research methods

are selected to explain and interpret events from the perspectives of the object.

Phenomenological research is mainly related to highlight the actual feelings of

participants and see the world from their standpoint (McNEILL, 1990). According to

McNEILL, (1990) phenomenological research has given rise to ethnographic studies,

particularly the technique of participant observation. Data collected within this type of

research is in qualitative form rather than quantitative and mainly concentrates on

wording rather than on numbers or statistics. The key features of the two paradigms have

been summarised in the table 3-2.

According to Saunders et al, (2003), in a practical world, management research rarely

falls into only one philosophical paradigm and is often a mixture of positivist and

phenomenological. This is not because of the difficulty to decide between the merits and

demerits of the two approaches but instead that sometimes it is the requirement of

specific research to include elements of both research paradigms. By comparing the

table 3-1 and looking on research problems as outlined in Chapter 1, phenomenological

philosophy seems to be the best option for this research. However, it was necessary to

prove some of the areas through statistical analysis which necessitates the need to adapt

a positivist, quantitative approach. To conclude, it was necessary to use both these two

philosophies to answer the research questions presented in chapter 1. This would be

further established when the justification for the research approaches is presented and

explained in the next sections.

3.3.2 Research approaches

Different kinds of research approaches are reflected in the literature which are divided

into four major areas as outlined in the table 3-3. One of the different views about these

research approaches is by dividing any specific research into empirical / non-empirical


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approach (Veal, 2006). It should be noted that any particular research can be based on

empirical approach, non-empirical approach, or a combination of the two.

Type of Research Basis of Classification

Exploratory, Descriptive, Analytical or

Predictive Research

Purpose of the Research

Quantitative or Qualitative Research Process of the Research

Deductive or Inductive Research Logic of the Research

Applied or Basic Research Outcome of the Research

Table 3-3: Classification of the main types of research (Hussey and Hussey, 1997)

3.3.2.1 Non-empirical research

Non-empirical research is not based on new evidence from the real world but is based on

data previously accumulated for quite different purpose (Clarke, 2003) while according

to Veal, (2006), non-empirical research is purely a theoretical research. The pre-existing

body of knowledge plays a vital role in the research of a particular area. This previous

knowledge can be used as a basis for further research and gives important information

about the history of particular field. Some of the research may be entirely non-empirical

in nature and are based on searching and reviewing the previous literature. There are

different views on the types of non-empirical research e.g. according to Clarke (2003),

non-empirical research includes the following main areas.

• Review of existing literature

• ‘Scholarship’, varying interpretation

• Conceptual research

• Futurism, especially Delphi rounds

• Scenario-building

• Game-playing or role-playing


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• Analytical and simulation modelling

According to Guo and Sheffield (2008), non-empirical research includes:

• Literature review

• Theory building

• Computer simulation

It is important to note that that research is incomplete and unauthentic without a review

of existing literature because it establishes a foundation for addressing the research

problems. All the three major studies in this research i.e. identification of critical success

factors, barriers to CM implementation, and establishing a CM maturity model is based

on comprehensive literature review hence could be part of the non-empirical approach.

3.3.2.2 Empirical research

Empirical research ‘involves the collection and/or analysis of data – quantitative or

qualitative, primary or secondary’ (Veal, 2006). It is defined as ‘data based on

observation or experience’ (Hussey and Hussey, 1997). Empirical evidence is very

important to present regardless of the purpose of that research (Hussey and Hussey,

1997). Empirical Research is very important for gathering and analysis of data through

observation or experience (Easterby-Smith et al., 1991). It should be noted that empirical

research is based on the data collected from the real world.

There are two primary dimensions for empirical research which can be evaluated for use

in management studies. These do not necessarily represent a simple either choice, but

should rather be seen as the extent to which elements of the approach apply. Since most

of the authors have explained the research approach by considering these two basic

classification areas, hence we have described the research process by taking the

following two areas into consideration for the clarity of this research.


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• Deductive / Inductive approach (Saunders et al., 2003)

• Qualitative / Quantitative approach (Creswell and Clark, 2007; Easterby-Smith et al,

1991; Patton, 1987)

It is most important to summarize that this research was designed to take into account

both the non-empirical and empirical research approaches. The non-empirical approach

was used as bases for structuring and execution of the empirical research activities.

3.3.2.2.1 Deductive / Inductive

Deductive research approach is a more scientific research methodology in which theory

is developed, hypothesis is deduced and tested, specific outcomes are examined, and if

required theory is modified in the light of findings (Saunders et al., 2003). Deductive

approach is also called top-down approach and works from general to more specific

where a theory is established, hypothesis is deduced, observations are established, and

finally hypothesis is tested with some data to validate and confirm the original theory

(Trochim, 2008). Inductive approach, on the other hand, works opposite to that of

deductive approach where data is collected and theory is developed as a result of the

data analysis (Saunders et al., 2003). Inductive approach, also called bottom-up

approach, start with some sort of observations which leads us to specific pattern and

enables us to establish some tentative hypothesis which finally facilitate us to have some

general conclusions or theory (Trochim, 2008). The major differences between the two

approaches are summarised in the table 3-4.

To get benefit out of the two research approaches it is important to use both research

methodologies in combination as highlighted by Saunders et al. (2003) that ‘Not only is

it perfectly possible to combine approaches within the same piece of research, but in our

experience it often advantageous too’. Different methods can be used for different

research studies; some follow interviews (inductive) to get the feel of the key issues of

the research followed by questionnaire (deductive) to test specific hypotheses while


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others follow both the interviews and questionnaires to get an in-depth view and motives

and testing of hypotheses.

3.3.2.2.2 Quantitative / Qualitative approach

Qualitative research deals with the analysis of data such as words, pictures, or objects. In

this type of research, researcher is closely involved with the subject and compiles data

through his direct involvement in the research environment. Qualitative research reflects

less tangible aspects of a research subject, e.g. values, attitudes, and perception.

Qualitative research has been formulated to help researchers to understand people and

the social and cultural contexts in which they live (Myers and Avison, 2002). Qualitative

research is a complicated process and has no hard and fast rules about how to do it

(Oates, 2006). According to Patton (1987) ‘Qualitative methods consist of three kinds of

data collection: (1) in-depth, open-ended interviews; (2) direct observation; and (3)

written documents, including such sources as open-ended written items on

questionnaires, personal diaries, and program records’. According to Ghauri &

Gronhaug (2005), the three components of qualitative research are data obtained for

interviews and observation, the techniques to conceptualize and analyse the data to

arrive at findings or theories, and reports (written or verbal). Qualitative research is used

to reveal the human experience, behaviour and functions and is suitable for research on

organizations, groups, and individuals (Ghauri & Gronhaug, 2005).

Quantitative research on the other hand uses numerical data to obtain information about

a specific research topic. It is more objective in nature and emphasis on collection and

analysis of numerical data. According to Patton, quantitative methods ‘use standardized

measures that fit diverse opinions and experiences into predetermined response

categories’ (Patton, 1987). This is a very structured research method where results are

easily formulated and statistically presented but is hard to design initially.

Implementation of quantitative methods can be find in social sciences include survey,

laboratory experiments, formal methods (e.g. econometrics) and numerical methods

such as mathematical modelling where the structured data is subjected to scientific


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techniques for appropriate analysis to test the validity of hypothesis (Yin, 1994; Myers

and Avison, 2002).

Deduction Emphasises Induction Emphasis

• Scientific Principles

• Moving from theory to data

• The need to explain casual relationship

between variables

• The collection of quantitative data

• The application of controls to ensure

validity of data

• The operationalisation of concepts to

ensure clarity of definition

• A highly structured approach

• Researcher independence of what is

being researched

• The necessity to select samples of

sufficient size in order to generalise

conclusions

• Gaining an understanding of the meaning

human attach to events

• A close understanding of the research

context

• The collection of qualitative data

• A more flexible structure to permit

changes of research emphasis as the

research progresses

• A realization that the researcher is part of

the research

• Less concern with the need to generalise

Table 3-4: Differences between deductive and inductive approaches (Saunders et al.,

2003)

Both qualitative and quantitative approaches have been used by both positivist and

phenomenological researchers in different research strategies (Oates, 2006). A

combination of both research strategies has greater advantage instead of using each

research strategy independently as highlighted by Creswell and Clark (2007) that ‘The

use of quantitative and qualitative approaches in combination provides a better

understanding of research problems than either approach alone’. This type of research

approach is called a Mixed Method Research and is available in the literature with

different names i.e. ‘Multitrait / Multimethod Research’, ‘Integrated or Combined’,

‘Quantitative and qualitative Methods’, ‘Hybrids’, ‘Methodological Triangulation’, or


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‘Mixed Methodology’ (Creswell and Clark, 2007). In summary, quantitative research is

objective, deductive, generalizable and deals with numbers while qualitative research is

subjective, inductive, not generalizable, and mainly consists of words. Summary of the

main features of qualitative and quantitative research is shown in the table 3-5.

In light of the above discussion and keeping in view the strengths and weaknesses of

qualitative and quantitative approach, a Mixed Method Research, which refers to the use

of more than one method for gathering data (Creswell and Clark, 2007; Denzin, 1970)

was deemed suitable for this research. Qualitative approach is used to explore the views

of the practitioners and to get the motives behind the reasoning while quantitative

approach has been used to focus on certain areas and investigate the relationships and /

or difference using statistical techniques. Another main motive behind mixed method

research is to validate my results through triangulation which is one way of determining

whether the findings from different studies converge to common grounds.

Qualitative Methods Quantitative Methods

• Emphasis on Understanding

• Focus on Understanding from

Respondent’s/informant’s point of

view

• Interpretation and rational approach

• Observations and measurements in

natural settings

• Subjective ‘insider view’ and

closeness to data

• Explorative orientation

• Process oriented

• Holistic perspective

• Generalization by comparison of

properties and contests of individual

organism

• Emphasis on testing and verification

• Focus on facts and/or reasons for

social events

• Logical and critical approach

• Controlled measurement

• Objective ‘outsider view’ distant

from data

• Hypothetical-deductive; focus on

hypothesis testing

• Result oriented

• Particularistic and analytical

• Generalization by population

membership

Table 3-5: Differences between qualitative and quantitative methods (Ghauri and

Gronhaug, 2005)


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The next section discusses the various research strategies / methods along with the

details of the research strategy adopted for this research.

3.3.3 Research strategies / methods

There are various research strategies which are in use in management research. Some of

these research strategies are clearly related to deductive (quantitative) approach while

the others belong to inductive (qualitative) approach. These strategies can be used alone

or in combination with each others to fulfil the requirements of any specific research.

The list these research strategies are given below.

• Experiment

• Survey

• Case Study

• Grounded Theory

• Ethnography

• Action Research

• Cross-sectional and Longitudinal studies

• Exploratory, descriptive and explanatory studies

The research strategies which have been adopted for this research are discussed in great

details in the next sections.

3.3.3.1 Survey

The survey is an important research strategy in business and management research,

usually associated with a deductive approach (Saunders et al. 2003). The survey is not a

method but a research strategy where researchers can use a whole range of methods

(questionnaires, interviews, documents, and observation) within the strategy to

accomplish the research (Denscombe, 1998). ‘Surveys refer to a method of data

collection that utilizes questionnaires or interview techniques for recording the verbal

behaviour of respondents. The survey is an effective tool to get opinions, attitudes and


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descriptions as well as for getting cause-and-effect relationships’ (Ghauri and

Gronhaug, 2005). Survey highlights the human response where basic data is

accumulated by talking to people, either face to face, by means of telephone, over

internet or by written questionnaire (Jankowicz, 2004). The purpose of survey is to get

information from a small set of peoples / population specific to an area or expended to a

large region (Easterby-Smith et al., 1991). Selection of this defined population, called

sample, is the most important and critical stage of the survey. Another important action

during survey is the selection of suitable method for conducting the survey where

interviews and questionnaires are the two important means to get information from the

participants by asking similar questions from all individuals in the sample.

According to Ghauri and Gronhaug, 2005), whether a questionnaire method is selected

to get data by postal mail from the respondent or interviews are arranged by asking

questions during face-to-face meeting, each method has their pros and cons. Different

issues like research problems and objectives, samples size location, availability of funds

and complexity of information may restrict the selection of any specific method. Postal

surveys are less expensive but time consuming as compared to face-to-face interviews.

Moreover there may be a high rate of non-response in postal surveys while there is a risk

of interviewer bias.

In the first part i.e. the identification and analysis of CM CSFs, a mixed method research

approach is used to gather information for this research. Multiple techniques were

followed to make this study more robust and useful where data was collected through

unstructured interviews either face to face or through telephone, emails, and by written

questionnaire as a means of performing effective survey research. Unstructured

interviews were suitable since the main objective was to take control of the situation and

know respondent’s opinions and motives about specific topics which generates with the

discussion process. Followed by interviews, questionnaire was designed based on the

findings of interviews, email discussions and literature review with aim to test the

designed hypothesis and rank the level of impact of highlighted variables.


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In the second study on the identification of barriers to CM implementation, again a

mixed method research approach is used to validate my results through triangulation.

The research process is divided into three phases where in the first phase, research

participants were asked through an open question to identify factors which they believe

are the most obvious barriers in the implementation of Configuration Management. The

replies received through 64 questionnaires were grouped into multiple factors for further

analysis. In the second phase of the research seven semi-structured interviews with CM

experts of four different industries were conducted. The third phase of this research was

based on a questionnaire survey to validate my findings and verify the designed

hypothesis. A total of 187 responses were received which were used to finalize the list of

barriers and establish the designed hypothesis.

The third part of this research related to developing Configuration Management Maturity

Model; semi-structured interviews were conducted followed by two questionnaire

surveys. A total of six semi-structured interviews were conducted with CM experts of

four different aerospace and defence organization which were recorded for later analysis.

Interviews were followed by two questionnaire surveys which were conducted to

achieve the establish objectives. The first questionnaire survey was related to model

validation while the second survey was related to measuring the process maturity. A

total of 50 responses on model validation questionnaire while 52 responses on process

maturity questionnaire were received which were used for later analysis to achieve the

desired objectives.

The details about the concept of interviews and questionnaire are presented in sections

3.3.6.1 & 3.3.6.2 respectively which highlights the data collecting methods / techniques.

The next section for discussion covers brief introduction on research choices, time

horizons, and data collection techniques.

3.3.4 Research choices


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As mentioned before, this research has been conducted by a mixed method approach to

answer the research questions as highlighted in Chapter 1. The survey is the only

research strategy which has been considered suitable to answer the research questions as

described in chapter 1.

3.3.5 Time horizon

The time horizon is the duration to perform specific research which depends on the types

of research questions. Some research needs less time to get ideas of a particular event

called cross-sectional studies while other needs to study groups of events over a long

period of times called longitudinal studies.

3.3.5.1 Cross-sectional studies

Cross-sectional studies are conducted when there is a limitation of time and resources

and where data is collected just once within a short span of time to get a snapshot of the

ongoing process before it is analysed and reported (Hussey and Hussey, 1997). These

studies often use questionnaires and survey techniques (Easterby-Smith et al., 1991;

Thomas, 2004). Instead of having some limitations with such studies, it gives important

information in no time. On the positive node, cross-sectional studies are inexpensive and

are conducted simultaneously but on the negative node, firstly, it does not give

information on the sampling size to represent the total population for reliable results,

secondly it provide no guidelines on how to isolate the subject study with the areas

which are in close correlation, and finally it does not mention that why such correlation

exist (Hussey and Hussey, 1997).

3.3.5.2 Longitudinal studies

Longitudinal research is a research methodology where researcher investigates a case

over time, anything from a month to several years, analysing continuous and change

processes and relationships (Oates, 2006). Longitudinal studies are conducted to find the


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dynamics of the problem by investigating similar set of peoples or situations

continuously within specified time frame or several times on different occasions (Hussey

and Hussey, 1997). In such studies repeated observations are taken to find the relative

stability of the phenomenon and to observe changes if exists. Longitudinal study is a

series of studies on similar subjects over a long period of time where each study has

been linked to previous and discussing the deviations of parameters over time. This

research methodology establish a chain of studies on a single subject and as the chain

extends to some level, grounded theory is generated at the end (Hussey and Hussey,

1997)

Looking at the brief introduction of the above two types of studies, this research falls in

the category of cross-sectional study. One reason is the time constraints and secondly

this study is not concentrating to investigate a similar topic over the period time to

observe changes but rather to get a snapshot of observations and understanding on the

research topic.

3.3.6 Data collection methods / techniques

The selection of precise data collection methods is the most critical phase during any

research process. Getting the right data in the right format from the right individuals put

positive effects on the final results of any research. Generally researchers concentrate on

the data collection techniques without giving enough consideration to the different

research methodologies as highlighted by the upper cores of the research onion as

highlighted in figure 3-1 which most of the time indirect researcher from the real outputs

and incur considerable delays in their research process. It is important to mention the

data collection methods / techniques as highlighted by Hussey and Hussey, (1997)

presented below before explaining any particular methods used in this research.

• ‘Critical Incident technique – ‘It is a procedure for gathering certain important

facts concerning behaviour in defined situations’.


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• Diaries – ‘is a daily record of events or thoughts and is typically used to capture and

record what people do, think and feel’.

• Focus Groups – ‘are used to gather data relating to the feelings and opinions of a

group of people who are involved in a common situation’.

• Interviews – ‘are a method of collecting data in which selected participants are

asked questions in order to find out what they do, think or feel. Interviews make it

easy to compare answers and may be face-to-face, voice-to-voice or screen-to-

screen; conducted with individuals or a group or individuals’.

• Observations – ‘can take place in a laboratory setting or natural setting. There are

two ways in which observation can be conducted: non-participant and participant

observation’.

• Protocol Analysis – ‘is a data collection method used to identify the mental process

in problem solving. The aim is to ascertain the way that people behave and think in a

particular situation. The researcher gives some form of written problem to a

practitioner who is experienced in that field. The participant then solves the

problem, but verbally explains the way he or she is tackling it. This is allows the

researcher to record the process. Sometimes the participant generates further

questions and these can for the basis for subsequent analysis and research’.

• Questionnaires – ‘A questionnaire is a list of carefully structured questions, chosen

after considerable testing, with a view to eliciting reliable responses from a chosen

sample. The aim is to find out what a selected group of participants do, think or

feel’.

This research adapts a mixed method research methodology as discussed in section

3.3.2.2. The data collections techniques in this research are interviews and questionnaire

surveys which are discussed in the following sections.


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3.3.6.1 Interview

An interview is a particular type of conversation between persons, with some

assumptions (normally unspoken) that do not apply to normal conversation, where one

person undertakes an interview for the required information from selected participant(s)

(Oates, 2006). Interview is a method of collecting data in which selected set of peoples

are asked questions in order to find expert opinions on the topic of interest; and can be

either positivistic or phenomenological depending on the method of conducting

interviews (Hussey and Hussey, 1997).

There are three types of interview as listed below (Denscombe, 1998; Hussey and

Hussey, 1997; Oates, 2006).

• Structured Interviews

• Semi-Structured Interviews

• Unstructured Interviews

Structured interviews are conducted on pre-determined and standardized questions

where questions are asked from the respondent and his response is recorded on a

standardised format while in semi-structured interviews the researcher have a list of

questions that may vary from interview to interview and new question can be added

according to situations as interview proceeds and finally the unstructured interviews,

where there is no specific set of questions designed for the interview but have a broad

area in mind for discussion to get the desired outputs from a set of selected peoples

(Saunders et al., 2003).

To identify a set of success factors in the first phase, unstructured interviews were

arranged with five CM subject matter experts. The highlighted success factors were

recorded on the diary after discussing the different aspects of each factor. Three CM

practitioners with more than thirty years of experience were consulted through emails.

Data from the two sources were combined with available literature to finalize an initial


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list of twenty-one success factors. In the second phase of the research seven semi-

structured interviews with CM experts of four different industries were conducted. Each

interview was recorded for later analysis. Interviews were analysed several times and

highlighted barriers were downloaded where cross comparison was done with identified

barriers through questionnaire study. The data was grouped and analysed carefully to

avoid possibilities of ignoring or repeating factors where nineteen factors were finalized

for the final survey. In the third and final part of this research six semi-structured

interviews were conducted with CM experts of four different organizations where each

interview was recorded for latter analysis.

3.3.6.2 Questionnaire

‘A questionnaire is a pre-defined set of questions (sometimes called items), assembled in

a pre-determined order’ (Oates, 2006). Questionnaires are usually connected with

survey research strategy and are associated both with positivistic and phenomenological

methodologies. Questionnaire consists of clearly and carefully structured questions to

find out the feeling of a selected group of peoples about the topic under research which

are usually based on previous studies (Hussey and Hussey, 1997). Being a cheaper way

to get the required information in less time, questionnaires are the most popular method

of data collection but the low response rate on the other hand is the main drawback and

therefore needs a lot of hard work in the design process to make it more effective for the

data collection (Hussey and Hussey, 1997; Saunders et al., 2003). Best questionnaires

can be designed by focusing four major areas i.e. questionnaire focus, question

phraseology, the form of response, and the question sequencing and overall presentation

(Gill and Johnson, 2002).

There are two main type of questionnaires design i.e. open and close (Easterby-Smith et

al., 1991; Ghauri and Gronhaug, 2005; Hussey and Hussey, 1997; Oates, 2006; Saunders

et al., 2003). In open-ended questions respondents have full rights to write in the empty

space available by the end of each question while in closed questions, respondents are

bound to select an answer from the given choices provided by the researcher at the end


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of each question. Mostly the researchers adopt closed questions while using positivistic

research methodology and open ended questions in case of phenomenological research

methodology (Saunders et al., 2009).

Questionnaires are either self-administered or researcher administered (Oates, 2006;

Saunders et al., 2009). Self-administered questionnaires are filled by the respondents in

the absence of researcher while researcher administered questionnaires are filled by the

researchers during their meeting with research participants while asking the questions

directly and recording at the same time. Self-administered questionnaires are usually

sent and received back from respondents either through internet or in the hard copy.

In the first part of this research i.e. identification and finalization of critical success

factors for CM implementation, a questionnaire survey (Appendix A) was conducted to

validate the findings (finalized through five in-depth interviews, email conversations

with three CM experts, and literature review) and verify the designed hypothesis. The

questionnaire was produced to collect responses on the basis of a Likert-Type scale,

running from 1 (strongly disagree) to 5 (strongly agree) on each success factor. The

target population was CM professionals from aerospace and defence companies where

as the Association of Configuration Managers (ACM) was used as a platform to obtain

the data. A total of 94 received questionnaires were used to finalize the factors on the

basis of their mean values and establish the designed hypothesis.

In the 2nd

part of this research i.e. identification and finalization of barriers to CM

implementation, a questionnaire survey (Appendix C) was conducted to validate the

findings (obtained from the initial questionnaire and seven semi-structured interviews)

and verify the established hypothesis. The questionnaire was divided into two sections.

The first section focussed on gathering background information while the second part

was related to barriers where respondents’ opinions were asked on a series of statements.

Respondents of the questionnaire survey were asked to mark trueness of each statement

based on their organization by using a five-point scale (1 = not at all true, 2 = slightly

true, 3 = somewhat true, 4 = mostly true, 5 = completely true). To facilitate respondents

and improve the response rate, a web based questionnaire was designed and the link was


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sent by email to all respondents. A total of 187 received questionnaires were used to

finalize the barriers on the basis of their mean rank values and establish the designed

hypothesis.

In the 3nd part, two questionnaire surveys were conducted at the same time after six

interviews; first to validate the developed maturity model while the other was to measure

the maturity levels of the CM practices of different organization to see the working of

designed maturity model. The validation questionnaire (Appendix E) was divided into

three sections. The first section focused on general information while the second section

was related to detail discussion on the Configuration Management Maturity Model to

give insight of the model to research participants. In the third and final section,

seventeen statements were provided with a five point scale from 1 (strongly disagree) to

5 (strongly agree). The process maturity questionnaire (Appendix F) was divided into

two sections where the first section was related to the general information while the

second section consisted of thirty-five processes against a four point scale (static,

reactive, proactive, and dynamic). To facilitate respondents and improve the response

rate, a web based questionnaires were designed and the link were sent by email to all

respondents. A total of 50 received questionnaires for the first questionnaire survey

(validation of the Configuration Management Maturity Model) and 52 received

questionnaires for the second questionnaire survey (Configuration Management process

maturity) were used for further analysis to achieve the desired objectives.

3.3.6.3 Sampling

After identifying a research problem and selecting appropriate research philosophy,

research approach, research strategies, and data collection methods, the next important

step is the selection of peoples/case/elements from where the information/data will be

collected. It is best to approach each individual and collect the required data but most of

the time it is quite difficult not only because of the time it needs but also the resources it

requires. To handle such difficulties during the collection and analysis of data, sampling

concept has been introduced in the research process.


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‘Sampling can be defined as the deliberate choice of a number of unites (companies,

departments, people)’ (Jankowicz, 2004). Sampling saves time and money by

investigating sample instead of population (Ghauri and Gronhaug, 2005). The full set of

cases from where the sample is selected is called the population which may consist of

people, firms, products, and so on. The relationship between population, sample, and

cases or elements has been presented in the figure 3-3.

Figure 3-3: Population, sample, and individual cases (Saunders et al., 2003)

Sampling is divided into the following two main categories i.e. probability sampling and

non-probability sampling (Ghauri and Gronhaug, 2005; Jankowicz, 2004; Oates, 2006;

Saunders et. al., 2003) which can be used together in any single research (Ghauri and

Grønhaug, 2005; Saunders et. al., 2003). The two broad categories of sampling are

divided into many different types and are presented in the figure 3-4.


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Figure 3-4: Sampling techniques (Saunders et al., 2003).

3.3.6.3.1 Population

Population is the group of interest of the researcher on the basis of which the researcher

would like to generalize the results of his study (Fraenkel and Wallen, 2006). The

population could either be an actual population (also called target population) or

accessible population. The target population is a population to which a researcher would

be unable to generalise while accessible population is a population where he is able to

generalise his research (Fraenkel and Wallen, 2006). It is also important to note that

target population is the researcher’s ideal choice while the accessible population is his

realistic choice. The accessible population for this research is the CM professionals

working in aerospace and defence sectors.

In the first part, questionnaire was administered to CM professional from aerospace and

defence companies whereas the Association of Configuration Managers (ACM) was

used as a platform to obtain the data. In the second part, questionnaire was administered

to CM professional from aerospace and defence companies where the Association of

Configuration Managers (ACM) and Configuration Management Process Improvement


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Centre (CMPIC) resources were used to obtain the required responses. In the third part

of this research the two questionnaire surveys were conducted with the members ACM,

CMPIC and CM professionals from researcher own organization. It is impossible to

identify neither the exact number of CM professionals in aerospace and defence

industries nor even the members of ACM and CMPIC because of the confidentiality of

data.

Different sampling techniques (highlighted above) have been used for the sample

selection which are described below

3.3.6.3.2 Sampling techniques

The sampling techniques which have been adapted in this research are given below.

• Convenience sampling

Convenience sampling is a non-probability sampling technique in which cases are

selected because of their convenient accessibility and readily availability to the

researcher.

• Judgemental or purposive sampling

Judgmental sampling also called purposive sampling, is a non-probability sampling

technique where the participants are selected based on their knowledge and purpose of

the study. This type of sampling is often selected when the cases are more informative

(Saunders et al., 2003)

3.3.6.3.3 Sample size

Suitable sample size has greater effects on the final outcome of any research since

generalizations are made on the data which have been obtained from the selected

samples. Larger sample size means less probability of any error in the output of a


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research as compared to smaller sample size. Large sample size increases the validity of

any research but needs enough time and money for the collection and analysis of data.

This shows a real problem in the decision on adequate and sufficient sample size for any

research where unfortunately there is still no clear cut answer for this problem (Fraenkel

and Wallen, 2006).

Sample selection is a complex subject but researcher can select any sample size by

keeping in mind the following considerations (Hussey and Hussey, 1997).

• The type of statistical analysis you want to make

• The variation in results with a variation in sample size (greater variation means

greater sample size)

• The tradition of sample size selection in a particular research area

The research methods which involves interview, sample size is enough when the

collected data reaches to the point of ‘saturation’; the point at which no new information

or themes are experienced in the data (Fraenkel and Wallen, 2006). Another point of

consideration is that usually data obtained from less number of respondents with huge

experience is given more preference then the data which is obtained from greater

number of respondents with less experience in that specific field. This highlights that the

quality of the final research is more dependent on the overall quality of the sample then

the quantity as highlighted by McCracken (1988) that “less is more” which means that it

is best to work more and with greater care with fewer and experienced people than less

with more people.

The sample selection was done in consultation with supervisor by keeping in view the

requirements highlighted above and emphasising on not to comprise on the quality of

resulted data. In the first phase of this research in-depth interviews were arranged with

five CM subject matter experts whereas three CM practitioners with more than thirty

years of experience were consulted through emails. A list of success factors was

finalized and their importance was highlighted with the help of a short statement. The


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list was forwarded to a group of thirteen CM subject experts in a meeting of the

‘Association of Configuration Managers’ (ACM) at The University of Manchester, UK

for critical review and marking. The questionnaire was than distributed to around 380

research participants either personally in hard copies or by their work emails (obtained

from ACM data base). To maintain legitimacy of the received data only those

questionnaires were included for analyses which are obtained for identified research

participants.

In the second part of this research seven semi-structured interviews with CM experts of

four different industries were conducted to identify a list of barriers to CM

implementation. The questionnaire was than finalized and administered to 550 CM

professional from aerospace and defence companies. In the third and final part of this

research six semi-structured interviews were conducted followed by questionnaire

survey which was sent to approximately 200 members of ACM and CMPIC and CM

professionals from researcher’s own organization.

3.3.7 The credibility of research findings

The most crucial part during research is ensuring its reliability and validity. According

to Saunders et al. (2003) it is important to concentrate on two important parameters i.e.

research design reliability and validity to avoid any single opportunity of getting the

wrong answer. These parameters are discussed below.

‘Reliability refers to the consistency of the scores obtained - how consistent they are for

each individual from one administration of an instrument to another and from one set of

items to another’ (Fraenkel and Wallen, 2006). Reliability of a research means the

repeatability of the same in another research in similar situations (Hussey and Hussey,

2003; Saunders et al., 2003). A research would be reliable if anyone uses the findings of

your research under the same constraints get similar results each time. Positivist

viewpoint of the reliability is that same results should be obtained on different occasions


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on measure while phenomenological view point is that similar observations be made on

different occasion by different researchers (Easterby-Smith et al., 1991).

There are three types through which we can check the reliability of any research

(Malhotra, 2004).

• Test-Retest Reliability

Here the same type of research instrument is sent to the respondent after some time

and the variation in both is checked and analysed

• Alternative-Forms Reliability

Here two different types of measuring scale are developed for same research

instrument and both are processed with a time difference to same respondent and the

variations are analysed.

• Internal Consistency Reliability

Here every item is correlated with every other item across the entire sample and the

average inter-item correlation is taken as the index of reliability (Hussey and Hussey,

1997).

‘Validity has been defined as referring to the appropriateness, correctness,

meaningfulness, and usefulness of the specific inferences researches made based on the

data they collect’ (Fraenkel and Wallen, 2006). Validity is concerned with the extent to

which the research results accurately represent what is happening in the situation i.e.

whether the results are really what the researcher think or claim it will (Hussey and

Hussey, 1997). In other words validity highlights that whether the data gives the true

reflection of research performed. If the data is reliable the inferences made may or may

not be valid but on the other hand an unreliable data could not provide valid inferences


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(Fraenkel and Wallen, 2006). To enhance the validity of their research, researchers can

collect the three types of validity i.e. content validity, criterion validity, and construct

validity (Fraenkel and Wallen, 2006).

To ensure the quality of this research, mixed method research also called triangulation

was used which according to Hussey and Hussey (1997) increases the reliability and

validity of any research. To establish the validity of the research, first of all questions

were discussed with the supervisors and pilot studies were done through CM experts to

ensure that questions make sense and are relevant and focused on the research topic.

Where possible, interviews were recorded for later analysis which allowed us to

concentrate more on the discussion rather than taking notes. The questionnaire surveys

were piloted from CM professionals and experts to ensure the content validity whereas

the Cronbach’s Alpha coefficient was calculated to check the reliability of

questionnaires by using the internal consistency method. The Cronbach’s Alpha

Coefficient needs to be 0.7 and above to validate the test of internal consistency (Pallant,

2010). In the first part of this research, the Cronbach’s Alpha obtained after 94 responses

is 0.877 whereas for the second part of this research questionnaire it is 0.904 after 187

responses which are well above the recommended value of 0.7 shows a high internal

consistency between items within these research questionnaires. In the third part of our

research the Cronbach’s Alpha after 52 responses for process maturity is .969 while that

for model validation is .908 after 50 responses shows a high internal consistency

between items within these two questionnaires.

3.4 Summary

This chapter outline the research methodologies which have been implemented in this

research. The flow of this chapter is presented by explaining the five major areas of

‘research process onion’ outlined by Saunders et al. (2003). Different research

philosophies have been explained while its relation with this research is outlined in great

detail. Detail and the relationship of research approaches i.e. deductive/inductive or

quantitative/qualitative with this research have been explained in great deals. The mixed


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method research comprising of interviews followed by questionnaire surveys to test the

outlined hypotheses of the research is discussed.

Different sampling techniques along with a valid justification with reference to each

study have been discussed. However, the emphasis of sample selection was basically on

two important aspects i.e. the experience and the exposure of the respondents in the light

of the research problems.

Realising the importance of research reliability and validity, every efforts have been

done to ensure the clarity and relevancy of the questionnaires and interviews guides to

the research questions and to reflect the detail parameters which were required for the

analysis of this research.

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CHAPTER 4

IDENTIFICATION AND ANALYSIS OF CM CSFs

4.0 Introduction

This chapter outlines research in the identification and analysis of Critical Success

Factors for the implementation of Configuration Management process in aerospace and

defence industries conducted from January 2011 to July 2001. The importance of

research in the field of Critical Success Factors (CSFs) has become evident through

extensive research in other allied fields like Project Management (PM), Knowledge

Management and Quality Management (QM). This is evident from the fact that more

than seventy studies have been highlighted on CSF’s in PM by Belassi and Tukel

(1996), Baccarini and Collins (2003), and Fortune and White (2006); while seven

studies within Knowledge Management by Wong (2005). Research on CSFs and Critical

Barriers (CBs) establish a baseline to formulate means for the maturity of process (Niazi

et al., 2005). Process maturity is mainly dependent on key capability areas extracted

from CSFs and CBs (Yeo and Ren, 2008). Identification of these CSFs helps

practitioners to work on areas responsible for the success of a process, provide an

opportunity to avoid barriers, establishes direction to achieve the required goals and

offer means to measure the effectiveness of their processes.

The studies of Niazi et al. (2005), Fortune and White (2006) and Yeo and Ren (2008)

provide fundamental guidelines for maturity of any existing process. Niazi et al. (2005)

stress on the identification of CSFs and CBs and propose to measure each factor through

outline guidelines for improvements. The research of Yeo and Ren (2008) not only

highlights the importance of CSFs and CBs but also stresses the extraction of key

capability areas. The study of Fortune and White (2006) is related to the identification of

CSFs, extraction of key capability areas, and emphasize on formal system models to

evolve and mature a particular system or process.

Chapter 4: Identification and analysis of CM CSFs

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Extensive literature review suggests no formal study on Critical Success Factors in the

field of CM. However, limited literature in the form of case studies and research theories

are available on the success and failures in the implementation of CM. Many of these

informal studies suffered from funding bias and were carried out in order to promote

specific tools or training packages. These studies have very much focussed on what

constituted success or failure rather than the factors themselves. What these studies did

demonstrate however was that there were some key themes that arose again and again. A

detailed review of these themes helped us in identifying the potential Critical Success

Factors. These success and failure factors along with expert opinions from CM

professionals obtained through different research methodologies are the foundation for

the execution of this research work.

With the help of mixed method research with in-depth interviews followed by a

questionnaire survey, twenty-one CSFs were identified with the help of CM

professionals working in the leading aerospace and defence industries. Descriptive

statistics were used to find the significance of these factors where high Mean Values (4≤

Mean Values ≤ 5) highlight its importance in the implementation of CM process.

Inferential statistics were used to find the significance of a CM practitioner’s education,

experience, training, and experience in stakeholders departments in the ranking of these

CSFs.

Note: It is important to mention that material presented in this chapter is also

published in our journal publication i.e. “Ali, U., Kidd, C. (2013). Critical

Success Factors for Configuration Management implementation. Industrial

Management & Data Systems, 113(2), 250-264”

4.1 Research objectives

To ensure capability and maturity of the CM process within aerospace and defence

industries, this research identifies and prioritizes the CM CSFs, categorizes these factors

into key process management areas, and presents a CM activity model to help CM


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professionals in the implementation and continuous improvement of the process. It is

also important to see the influence of multiple parameters such as academic

qualification, work experience, training, and experience in stakeholder departments on

the practitioner’s perception on the criticality of CM CSFs. To analyse the influence of

these factors, the following hypothesis was developed:

Hypothesis: There is a difference in the identification of Critical Success

Factors for the implementation of best CM practice, based on a practitioner’s

academic qualification, work experience, qualification / training, and

experience in key stakeholder departments.

4.2 Research methodology

Mixed method research is used to collect information for this research. Various research

techniques were followed to make this study more practical and robust. The survey

research method is used as highlighted by Jankowicz (2004) where data was collected

through interviews, emails, and by questionnaire. Mixed method research also called

triangulation was used to validate the outputs of the research which is commonly used to

increase the validity and reliability of the research (Hussy and Hussy, 1997).

To finalize a set of success factors, in-depth interview were arranged with five CM

professionals with vast experience in the implementation of the process. Followed by

interviews, the issue was discussed with three CM professionals with more than thirty

years experience through emails. The data collected from the available literature and the

two sources mentioned above were combined to finalize an initial list of success factors.

A refined list of success factors was finalized and their importance was highlighted with

the help of a short statement. The list was presented to a group of thirteen CM

professionals for critical review in a meeting of the Association of Configuration

Managers (ACM) at The University of Manchester. A questionnaire (Appendix A) was

then produced to collect responses on the basis of a Likert-Type scale, running from 1

(strongly disagree) to 5 (strongly agree) on each success factor. A pilot study was


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conducted where the same questionnaire was delivered to a list of sixteen CM

professionals to ensure that the questionnaire is phrased correctly and also observe the

difficulty and problems during the response process. With some minor changes in the

received ten responses were made while all success factors were retained in the final

questionnaire for survey.

The sample size was selected for this research through judgemental and convenience

sampling strategies to avoid any compromise on the quality of data. The target

population was CM professionals from aerospace and defence companies where as the

Association of Configuration Managers (ACM) helped us in getting the required data.

The questionnaire was distributed personally in hard copies through head of the CM

facilities in some organizations while to others by their work emails (obtained from

ACM data base). The received 94 questionnaires were used for further analysis to verify

the designed hypothesis.

4.3 Findings, analysis, and discussion

4.3.1 Descriptive statistics

Descriptive statistics is used to describe and summarize a set of data instead of finding

the internal behaviour and making inferences to generalize the conclusions. It helps

researchers by arranging huge data through simple summaries in a rational way by

presenting relationships across different parameters. Descriptive statistics emphasis on

the combination of graphical and numerical summaries to present the actual behaviour

of data and measure specified parameters.

Descriptive statistics uses statistical measures like mean, median, mode, variance, and

standard deviation etc to describe details of the data. Graphical representation e.g.

histogram etc. can also be combined with numerical calculation to display the data’s

overall pattern and help researcher to easily understand the general behaviour of data.

Descriptive statistics gives specific information related to:


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• Mean, Skewness, and Kurtosis of CSFs

• Biographical details

• Qualification details

• Job Experience details

The required information highlighted above will be discussed as we proceed further

while discussing multiple issues in coming sections. Related to biographical details of

the research participants, out of five research participants in the interviews four were

males while one were female. The email conversations were done with three CM subject

experts who were males while out of ninety four research participants in the

questionnaire study, 70 (74.5 %) were males while 24 (25.5 %) were females.

4.3.1.1 Finalization and ranking of CSFs

The initial list of twenty-one success factors identified through mixed method research

as highlighted in section 4.2 were sent to CM practitioners in the form of a questionnaire

for further analyses. Data received from the questionnaire survey were subject to

descriptive statistics using SPSS to decide on the significance of factors in the

implementation of Configuration Management with the help of its mean values. All

twenty-one factors were retained as Critical Success Factors on the basis of their high

mean values (4≤ Mean Values ≤ 5) which established the importance of these factors in

the implementation of the Configuration Management practices. Mean values are shown

against each factor for all twenty-one CSFs in table 4-1 below.


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Symbol Success Factors

Mean Value

(statistic)

Skewness

(statistic)

Kurtosis

(statistic)

CSF1 Management support 4.78 -3.989 22.871

CSF2 CM organization 4.46 -1.459 2.098

CSF3 Effective leadership 4.55 -1.652 2.913

CSF4 Clear vision, mission, and policies for CM

process 4.67 -1.208 .420

CSF5 CM planning 4.64 -1.298 .749

CSF6 Competent CM practitioners 4.61 -.874 -.375

CSF7 Professional development 4.34 -1.616 4.602

CSF8 Effective support from the stakeholders 4.62 -.736 -.894

CSF9 Adequate resources allocation 4.23 -1.172 1.384

CSF10 Organizational culture 4.52 -.847 -.246

CSF11 User friendly software (tool) for CM 4.16 -.748 -.123

CSF12 Effective control of CM process at vendor

premises 4.26 -.552 .421

CSF13 Effective communication of CM with

stakeholders 4.48 -.470 -.796

CSF14 Previous CM experience 4.35 -.785 .347

CSF15 Continuous improvement in CM practices 4.47 -.101 -1.477

CSF16 Committed and focused CM practitioners 4.28 -.820 .416

CSF17 Team work 4.39 -.274 -.764

CSF18 Equal career progression opportunities for

CM staff 4.10 -1.186 1.855

CSF19 Flexibility in CM practices 4.20 -1.005 1.811

CSF20 Recognition of CM employees efforts 4.18 -1.064 2.107

CSF21 Politics free projects environment 4.03 -.459 -.690

Table 4-1: List of Critical Success Factors


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Table 4-1 also highlight some important information like skewness, and kurtosis which

are obtained from descriptive statistics on the data received from ninety four respondents

on twenty one success factors as continuous variables. Skewness and Kurtosis provides

important information in the decision process of which statistical technique could be

used i.e. either parametric or nonparametric technique. Skewness tells us about the

symmetry of distribution while kurtosis gives information of how peaked or flat a

distribution is. Looking into the data suggest that our distribution does not look normal

as most of the values are out of range from +1 and -1 where for a perfect normal

distribution both skewness and kurtosis should be zero (0) (Pallant, 2010).

4.3.2 Categorization of CSFs

The Critical Success Factors have been organized into seven categories as shown in

figure 4-1 by critically analysing the studies of human activity model (Checkland, 1981),

the formal system model (Fortune and White, 2006), and the requirements of the CM

activity model. Factor Analysis was not selected to group these factors since the data

failed to meet essential assumptions required before conducting any factor analysis. To

adopt factor analysis approach, it is important to have a strong correlation among the

factors that can be checked through correlation coefficients (shown in table 4-2) which

should be above 0.3. Factor analysis is not appropriate if a weaker correlation above this

exist (Pallant, 2010). Factor analysis was not considered appropriate since less than 35

percent of the values are above 0.3 in the correlation matrix obtained from factor

analysis (table 4-2). Furthermore, parallel analysis done by using Monte Carlo

simulation also suggests the same. This process suggest comparison of the first

eigenvalue obtained from factor analysis (table 4-3) with the corresponding first value

obtained by parallel analysis (table 4-4) and maintains the component where the actual

eigenvalue is larger than the criterion value from parallel analysis; if it is less, then it is

rejected (Pallant, 2010). Results in table 4-5 recommend maintaining one group of

factors of all twenty-one factors and do not allow further grouping based on their

inherent relationships.


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CSF1 CSF2 CSF3 CSF4 CSF5 CSF6 CSF7 CSF8 CSF9 CSF10 CSF11 CSF12 CSF13 CSF14 CSF15 CSF16 CSF17 CSF18 CSF19 CSF20 CSF21

CSF1 1.000 .436 .161 .192 .152 .136 .188 .266 .266 .161 .100 .219 .279 .039 .143 .259 .179 .192 .069 .208 .104

CSF2 .436 1.000 .472 .538 .270 .215 .515 .269 .397 .255 .396 .199 .396 .252 .273 .492 .305 .265 .077 .273 .226

CSF3 .161 .472 1.000 .280 .302 .369 .347 .399 .412 .313 .404 .138 .339 .456 .291 .483 .401 .141 .132 .505 .295

CSF4 .192 .538 .280 1.000 .287 .344 .353 .291 .269 .353 .294 .315 .364 .118 .299 .326 .299 .231 .174 .271 .286

CSF5 .152 .270 .302 .287 1.000 .343 .348 .335 .282 .277 .167 .223 .415 .054 .252 .294 .312 .247 -.021 .141 .176

CSF6 .136 .215 .369 .344 .343 1.000 .234 .230 .131 .346 .403 .353 .420 .147 .282 .252 .231 .204 .043 .348 .235

CSF7 .188 .515 .347 .353 .348 .234 1.000 .320 .357 .322 .255 .284 .430 .144 .306 .278 .264 .131 .114 .137 .199

CSF8 .266 .269 .399 .291 .335 .230 .320 1.000 .276 .378 .367 .328 .496 .266 .155 .341 .190 .208 .067 .261 -.045

CSF9 .266 .397 .412 .269 .282 .131 .357 .276 1.000 .360 .327 .289 .295 .348 .134 .499 .352 .185 .047 .364 .159

CSF10 .161 .255 .313 .353 .277 .346 .322 .378 .360 1.000 .258 .287 .400 .126 .277 .181 .304 .238 .230 .283 .255

CSF11 .100 .396 .404 .294 .167 .403 .255 .367 .327 .258 1.000 .197 .357 .348 .316 .444 .291 .273 .005 .460 .066

CSF12 .219 .199 .138 .315 .223 .353 .284 .328 .289 .287 .197 1.000 .307 .038 .275 .119 .246 .336 .139 .286 .061

CSF13 .279 .396 .339 .364 .415 .420 .430 .496 .295 .400 .357 .307 1.000 .369 .290 .376 .410 .249 .166 .333 .253

CSF14 .039 .252 .456 .118 .054 .147 .144 .266 .348 .126 .348 .038 .369 1.000 .378 .402 .358 .025 .120 .520 .341

CSF15 .143 .273 .291 .299 .252 .282 .306 .155 .134 .277 .316 .275 .290 .378 1.000 .246 .420 .101 .340 .312 .297

CSF16 .259 .492 .483 .326 .294 .252 .278 .341 .499 .181 .444 .119 .376 .402 .246 1.000 .528 .291 .116 .509 .236

CSF17 .179 .305 .401 .299 .312 .231 .264 .190 .352 .304 .291 .246 .410 .358 .420 .528 1.000 .191 .150 .322 .297

CSF18 .192 .265 .141 .231 .247 .204 .131 .208 .185 .238 .273 .336 .249 .025 .101 .291 .191 1.000 .065 -.056 .399

CSF19 .069 .077 .132 .174 -.021 .043 .114 .067 .047 .230 .005 .139 .166 .120 .340 .116 .150 -.056 1.000 .103 .163

CSF20 .208 .273 .505 .271 .141 .348 .137 .261 .364 .283 .460 .286 .333 .520 .312 .509 .322 .399 .103 1.000 .288

CSF21 .104 .226 .295 .286 .176 .235 .199 -.045 .159 .255 .066 .061 .253 .341 .297 .236 .297 .065 .163 .288 1.000

Table 4-2: Correlation matrix

Chapter 4: Identification and Analysis of CM CSFs

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Factor analysis is also sometimes not selected to group factors because at times when

applied to a similar set of factors by three different individuals it may yield different

groups of factors which would discredit its use (Darlington, 2012). Since there is no one

complete and fixed way to group such factors and is mainly dependent on the

researcher’s interpretation (Darlington, 2012), consensus was made on the seven groups

of factors on above guidelines and are shown in figure 4-1.

Figure 4-1: Details of CSFs groups


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Component Initial Eigenvalues

Extraction Sums of Squared

Loadings

Total % of

Variance

Cumulative

% Total

% of

Variance

Cumulative

%

1 6.559 31.234 31.234 6.559 31.234 31.234

2 1.653 7.870 39.104 1.653 7.870 39.104

3 1.443 6.871 45.975 1.443 6.871 45.975

4 1.236 5.884 51.859 1.236 5.884 51.859

Note: Data goes up to component 21 but not required to highlight here

Table 4-3: Total variance

Table 4-4: Parallel analysis


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Component Actual eigenvalue from

factor analysis

Criterion value from

parallel analysis Decision

1 6.559 1.9351 accept

2 1.653 1.7736 reject

3 1.443 1.6376 reject

Table 4-5: Comparison of actual eigenvalues with corresponding criterion values

4.3.3 Inferential statistic

Inferential statistics, also called statistical induction, is used to draw conclusion about

the whole population by studying the internal behaviour of sample(s). Unlike descriptive

statistics which is used to describe and summarize the actual data, inferential statistics is

used to make inferences from the same data to a more generalized condition. Inferential

statistics are mostly used to test some hypothesis. These hypothesises are usually

established to find similarities or differences between groups or factors on the basis of

internal behaviour of the data.

Choosing the right statistical technique is the most difficult part of any research (Pallant,

2010) which is mainly because there is no universal decision tree to help researcher to

choose the right statistical test (Kinner and Gray, 2000). It is the variations in the types

of research which makes the selection of right statistical test a tedious job. Selecting the

right statistical tests mainly depends on the type of research questions, the included scale

in questionnaire, the variables to be analysed, the assumptions met by the data for

specific statistical techniques, and the nature of data itself (Pallant, 2010).

This part of research was designed to finalize the Critical Success Factors and find the

effects of CM professionals work experience, qualification/training, experience in

stakeholders departments, and experience in the stakeholders departments on the level of

importance of Critical Success Factors. To validate the hypothesis as outlined in section


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4.1, the objective was to analyze the data received on the basis of four categorical and

twenty-one continuous variables. To compare and analyze the inherent relationship

between continuous variables (CSFs) with categorical variable of two or more groups,

Kruskal Wallis test (a nonparametric test) was decided to be applied.

By keeping in mind the type of outputs and the extent of relationships between

dependent and independent variables, the Kruskal-Wallis Test was selected by keeping

in mind the different parameters like design of the questionnaire, number of

questionnaire received, and the trend that we got after initial analysis of the data.

Parametric tests are the more powerful statistical tests and are preferred by most of the

researchers but have been ignored because these tests make more assumptions regarding

the data which needs to be satisfied before conducting these tests. Nonparametric tests,

On the other hand, do not make enough assumptions regarding the data, but do not

provide the full details of the inherent characteristics of the data.

Parametric Tests are based on two important assumptions; firstly the data should be

normally distributed and secondly the data should have homogeneity of variance or

homoscedasticity or population with similar variance (Erceg-Hurn and Mirosevich,

2008). Violation of these assumptions has substantial effects on the results of parametric

test (Erceg-Hurn and Mirosevich, 2008). Non-parametric tests, on the other hand do not

make assumptions about the population distribution whether normal or not (Motulsky,

1995).

Choosing between parametric and nonparametric tests is a difficult task but sometimes

few parameters make it very easy. Parametric test should be used if one is sure that the

data are sampled from population that follows a Normal / Gaussian distribution

otherwise select a nonparametric test if the outcome is based on rank or a score and the

population is clearly not Gaussian / Normal and some values are "off the scale," that is,

too high or too low (Motulsky, 1995).


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To summarize the discussion, nonparametric tests were selected for the analysis of data

within this research because the data did not meet the stringent requirements of

parametric tests. Following are the reason for this decision:

i. The data in this research does not fulfil the assumption of normality which is usually

measured by any of the following two methods.

a. Normality is mainly assessed by checking the values of skewness and kurtosis. If

absolute value of skewness or kurtosis is less than three times of the standard

error of the skewness or kurtosis then the data is termed as not skewed or

kurtosis and distribution will be called normal which has been violated by the

data as show in table 4-1. Another condition is that if the value of skewness and

kurtosis is between -1 and +1 then data is neither skewed nor kurtosis and the

distribution is normal which is again violated by the data as shown in table 4-1.

Hence we can easily conclude that the data is not normally distributed.

b. Normality can also be checked by the tests for normality where two types of test

can be used i.e. Kolmogorov-Smirnov Test (when the sample size is greater than

50) and Shapiro-Wilk Test (if the sample size is smaller then 50). The principle

for the data to be normally distributed is if the significance value is greater than

0.05; which has been violated by the data as shown in table 4-6, hence the

nonparametric test has been chosen for the analysis of data.

ii. Non parametric techniques have been chosen as the data obtained was ordinal i.e.

ranked data (Motulsky, 1995).

4.3.3.1 Participants perceptions regarding CM CSFs

Kruskal Wallis test is used to come up with conclusions on the hypothesis outlined in

section 4.1. Non-parametric tests are suitable in cases where the data fail the test of

normality (Pallant, 2010) and the data is ranked or discreet (Motulsky, 1995). It is


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important to select the right statistical test on the basis of normality of the data as the

violation of this assumption can substantially affect the results of parametric test (Erceg-

Hurn and Mirosevich, 2008). One way to check the normal distribution of data is to

calculate sig. values through Kolmogorov-Smirnov or Shapiro-Wilk Tests which if

greater than 0.05 show that the data is normally distributed (Pallant, 2010). Since the sig.

values for all seven groups and its group average are below 0.05 as shown in table 4-6

and the obtained data is discreet, Kruskal Wallis test is selected for further analysis.

Kolmogorov-Smirnov Shapiro-Wilk

Statistic df Sig. Statistic df Sig.

G-1 .146 94 .000 .917 94 .000

G-2 .225 94 .000 .880 94 .000

G-3 .255 94 .000 .816 94 .000

G-4 .154 94 .000 .902 94 .000

G-5 .106 94 .011 .966 94 .016

G-6 .333 94 .000 .707 94 .000

G-7 .190 94 .000 .836 94 .000

Group Average .099 94 .024 .964 94 .010

Table 4-6: Test of normality

4.3.3.1.1 Significance of CSFs with academic qualification

Kruskal Wallis test has been used to determine any significant difference in the

perception of participants based on their academic qualification. Results of the test

obtained through SPSS software are presented in table 4-7. The results confirm that

Asymp. Sig. for each of the seven groups and its group- average is more than .05 which

highlight that there is no significant differences in perception of CM practitioners on the


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basis of their academic qualification hence we reject the hypothesis as outlined in

section 4.1 for academic qualification.

Group G-1 G-2 G-3 G-4 G-5 G-6 G-7 Groups

-Avg

Asymp. Sig. 0.638 0.466 0.652 0.526 0.738 0.880 0.925 0.639

Table 4-7: Significance of CSFs with academic qualification

The outputs in table 4-7 could be explained with the help of mean rank values generated

by the same test. In the case of significance, the difference between the mean rank

values is greater between the groups and the parameter having greater mean rank value

shows its importance over others. Since there is no significant difference in the

perception of CM professionals on the basis of their academic qualification, the mean

rank values of individuals having master degrees, bachelor degrees, HND/HNC, and

other degrees as shown in table 4-8 are quite close to each other hence justify my

previous result highlighted above.

Academic Qualification N Mean Rank

Groups-Avg

Bachelor Degree 33 38.11

Master Degree 20 46.15

HND / HNC 19 38.45

Other 8 41.13

Table 4-8: Mean Rank for academic qualification


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4.3.3.1.2 Significance of CSFs with CM certification / training

There will be a significant difference in the perception of CM professional on the basis

of their CM certification / training if the significance value obtained from Kruskal-

Wallis test is less than 0.05. The significance values for all seven groups and their

groups-average is shown in table 4-9 which are less than 0.05, meaning that there is a

significant difference in the perception CM professionals based on CM certification /

training in identifying and rating the CM CSFs. On the basis of these results we accept

the hypothesis as outlined in section 4.1 which concludes that CM certification / training

plays a vital role in the implementation of CM practices.


-Avg

Asymp. Sig. 0.011 0.000 0.001 0.001 0.033 0.003 0.01 0.001

Table 4-9: Significance of CSFs with CM certification / training

The outputs in table 4-9 can be explained with the help of mean rank values generated

by the same test. The mean ranks are given in table 4-10 shows that employees having

CM certification or training (training obtained from professional CM training institutes)

give more importance to these factors than those having either non-assessed training

(organization or on-job training) or no training at all (mean rank value of employees

having assessed training is 60.91 which is greater than the mean rank value of

employees having either non-assessed or no training which is around 39). This shows

the importance and positive outcome of dedicated CM training and education.


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CM Training N Mean Rank

Groups-Avg

Assessed CM Certification / Training 37 60.91

Non-Assessed CM Certification / Training 16 39.16

No CM Certification / Training 41 38.66

Table 4-10: Mean ranks for CM training

4.3.3.1.3 Significance of CSF with experience in Configuration Management

Kruskal-Wallis test results shown in table 4-11 highlight that the significance value for

Critical Success Factors groups are less than 0.05 hence we can say that there is a

statistical significant difference in the perception of CM professions to identify and rank

these CSFs based on their previous experience in CM. On the basis of these results we

accept the hypothesis outlined in section 4.1 for experience in CM.


-Avg

Asymp. Sig. 0.031 0.000 0.002 0.004 0.000 0.001 0.019 0.000

Table 4-11: Significance of CSFs with experience in CM

Mean ranks of above seven CSFs has been highlighted in table 4-12 below explain that

respondents with higher Configuration Management experience have high mean ranks

than those with less experience. This shows that experience has positive effects on the

implementation of Configuration Management process as they know the significance of

the areas which are important for CM implementation process. Individual with high CM

experience give more credence to these factors then with less expertise.


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CM Experience N Mean Rank

Groups-

Avg

Less Than 5 Years 33 32.32

Between 5 to 10 Years 23 46.87


15 Years or Above 27 59.48

Table 4-12: Mean ranks for CM experience

4.3.3.1.4 Significance of CSFs with experience in stakeholder departments

The significance of CSFs with experience in stakeholder departments can be checked

through the significance values as highlighted in table 4-13 obtained by applying

Kruskal-Wallis Test. Since no value is less than 0.05 hence it can be concluded that

there is no significant difference in the perception of practitioner’s views about the CSFs

score with experience in stakeholder departments. On the basis of these results, we reject

the hypothesis as outlined in section 4.1 for experience in other discipline i.e. quality,

design, and project management.


-Avg

Asymp. Sig. 0.503 0.856 0.201 0.993 0.730 0.784 0.82 0.85

Table 4-13: Significance of CSFs with experience in Stakeholder Departments


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Experience in stakeholder

departments N Mean Rank

Groups-

Avg




15 Years and Above 20 34.13

Table 4-14: Mean ranks for experience in stakeholder departments

Table 4-14 shows the mean ranks for experience in stakeholder departments. The mean

rank values of employees having different experiences in different departments (quality,

design, project management, support, and manufacturing) are in the range of 32 and 37

which are again too close to each other and hence assumes no significant differences in

the perceptions of employees for these categories.

The results in sections 4.3.3.1.1, 4.3.3.1.2, 4.3.3.1.3, and 4.3.3.1.4 are not surprising

since it is believed that experience and professional training in CM plays an essential

role in the implementation of Configuration Management (Samaras, 1988; Burgess et

al., 2005; Guess, 2006). It is understandably true that since CM has been comparatively

ignored in the past by academia (Burgess et al., 2005) hence academic qualification

should not influence these factors. Furthermore, no significant difference is evident from

either these results or literature in the ranking of Critical Success Factors for CM

applications based on professional’s work experience in different types of stakeholder

departments.

4.3.4 CM activity model

The Configuration Management Activity Model is a logical representation of the key

factors necessary for establishing, maintaining, and continuously improving the CM


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process. It is designed to inform the CM professionals with most essential factors

necessary for establishing and maintaining best CM process and to facilitate them to

identify the actual or potential weaknesses in their Configuration Management practices.

The Configuration Management Activity Model combines the core concepts of the

Formal System Model (Fortune and White, 2006) also called the Human Activity Model

(Checkland, 1981) and is designed on the principals of soft system model building

methodologies by Checkland, (1979). Any such model is ideal and represents a robust

system that is capable of a purposeful activity without failure.

The problem with any existing model is the use of specific terminologies because of

their origin with systems thinking and PM which creates confusion during

implementation. The aim behind the Configuration Management Activity Model is to

make it easier for the use of CM practitioners and provide them a solid basis for

comparison with their existing practices to identify areas of improvements. This model

is quite simple but is different from the existing Formal System Models and uses CM

specific terminologies and is built on the basis of existing research and expert opinions.

To show the utility and usefulness of this model, it is important to address weaknesses in

the existing CM process and compare them with key process areas of the Configuration

Management Activity Model as shown in figure 4-2 with details in section 4.3.5 will

provide guidance on the missing links.

It is important to note that ‘There are not valid models and invalid ones, only defensible

conceptual models and ones which are less defensible! But at least it is possible to check

that conceptual models are not fundamentally deficient, and this is done by checking the

model against a general model of any human activity system’ (Checkland, 1981). In the

soft systems methodology, models are not part of the world and hence cannot be tested

by checking how well they represent it; they are only relevant to discuss the real world

and are used in a cyclic learning process (Checkland, 1995).

The Configuration Management Activity Model has a core decision making system with

decision taker(s) who are responsible for managing the process and implementation of


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the CM strategies with the help of effective communication channels both from top to

bottom and bottom to top and a designated boundary. Decision takers are not only

responsible for monitoring the process but to ensure that sufficient resources are

available for the execution of Configuration Management strategies. Communication

plays an important role in the execution and monitoring of the process and is mostly

effected by the environment. The environment encapsulated the other six activities, have

a critical role in the execution of the CM process. Organizations need to pay special

attention to all seven areas which would help them with superior CM processes to fulfil

customer requirements and produce quality products.

Figure 4-2: Configuration Management Activity Model

4.3.5 Interpretation of CM CSFs groups

Further discussion on the significance of CM CSFs groups in the implementation of CM

process is given below.


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4.3.5.1 Decision taker(s)

Decision taker(s) emerges from four CSFs i.e. management support, competent CM

practitioners, effective leadership, and previous CM experience. Top management

ensure the provisioning of required resources and defining the organizational role of the

process, whereas process leadership certify the effective usage of resources to carry out

the process and achieve the required objectives. Employee’s competencies and previous

experience help leadership to ensure that process is implemented according to

established guidelines which are mapped towards the vision and mission of the process.

Management support plays a vital role in establishing CM as a core business process of

the organization (Guess, 2006) whereas, leadership on the other hand, plays an essential

part for any core business process where CM needs to be established as one of those

core business processes for continuous improvement in an organization (Guess, 2006).

Both management support and effective leadership has an important role to the success

of any system or process (Carlos, 2011). It is also to note that to achieve success;

leadership is always backed by capable and experienced employees to accomplish the

desired tasks. Competency is the ability of an individual to execute his/her duties

properly where-as experience makes one capable to avoid paths to failure and guide the

process to accomplish the desired objectives which results in saving both money and

time.

4.3.5.2 Execution strategies

Execution strategies have three CSFs i.e. vision, mission and policies for CM process,

flexibility in CM practices and effective control of CM process at vendor premises.

Effective implementation of any process needs to have a clear vision (to answer the

question of where a process is going?), mission (to answer the question of why the

process exists?), and policies (to answers the questions of what and how to implement?).

It helps owners of the process and all functional stakeholders to adjust themselves

according to the rules and to achieve the desired goals and objectives.


157

It is important to observe the performance of CM process of subordinate activities such

as subcontractors, suppliers (EIA-649, 2011) where in most cases, a vendor’s CM

process is often overlooked. It is only through an effective control of CM process at a

vendor’s premises which make us capable to manage the use of unacceptable parts and

avoid compromise on the overall quality of products. It is the responsibility of

management to ensure the potential of vendors in terms of quality, production, and CM

process before contracting for any design and development activities.

The rigidity in CM practices creates inconvenience to users and hence the CM

implementation strategies need to be flexible to easily adopt according to different

requirements. On the other hand, products complexity plays a major role in the

implementation strategies of change management (Jarratt et al., 2011) where it is

believed that requirements of complex projects (e.g. space shuttle) cannot be matched

with small products (e.g. ball point pens), hence the CM process should never be too

rigid and users may provide flexibility to decide on CM requirements according to the

nature of the products.

4.3.5.3 Performance monitoring

Performance monitoring consists of two CSFs i.e. CM Planning and continuous process

improvement. The importance of continuous improvement methodologies is evident

from the fact as highlighted by Guess (2006) that when organizations operate in a

corrective action mode, places its survival in risk since they spend their resources and

time in overcoming intermittent failures. Since tremendous efforts have been made to

automate the process by introducing new tools and techniques, it is essential to

emphasise continuous improvement of the CM practices to maintain alignment with

changing demands of the environment. It is significant to note that there is no final step

in the CM process implementation and continuous improvement and hence development

programs should be in place through the provision of suitable resources (Hancock,

1993).


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According to Sachs (2009) CM planning plays an important part in the success of any

project and has a major contribution in organization's effectiveness and productivity.

CM planning not only ensures the implementation of CM practices but makes sure the

required consistency between the product’s configuration, product definition, and that

the CM records is maintained throughout the product-life-cycle (EIA-649, 2011). It is an

utmost requirement for organizations to have effective CM planning methodologies for

measuring the performance and effectiveness of their CM process.

4.3.5.4 Resources allocation

There are three CSFs under resources allocation i.e. adequate resources allocation, user

friendly software (tool) for CM and professional development. Adequate resources

(human and financial etc.) play a key part in implementation and continuous

improvement of the CM process (Gonzalez and Zaalouk, 1997; Guess, 2006). The recent

research on barriers to CM implementation presented in Chapter 5 and 6 suggest that

lack of resources (human resource and necessary budgets) are the main concerns of the

owners of this process which exists because the CM process has never given the

necessary importance by top management.

On the other hand, professional development plays a significant role in the success of a

process which improves the capability, capacity, and performance of individuals

involved in the process implementation. This issue is also highlighted in literature which

suggests CM training as a burning issue in organizations. Since Configuration

Management is largely ignored by academia (Burgess et al., 2005), recruiting competent

individuals is always an issue. Because of these reasons, special emphasis is required on

professional training programmes to maintain the required competencies across

organization.

CM software in the form of PLM and PDM toolsets has done a great job in the

automation of Configuration Management practices but still have some major concerns

highlighted in the literature since most of these software tools are not user friendly


159

(Guess, 2006) and as being off-the-shelf and not designed according to one’s own

requirements which create problems during implementation. It is essential to note that

user friendly software, if in-line with organizational CM process, could play a major part

in the effective implementation and development of the CM process.

4.3.5.5 Effective environment

Effective environment has six CSFs i.e. organizational culture, effective support from

the stakeholder, recognition of CM employee’s efforts, team work, equal career

progression opportunities for CM staff, and politics free projects environment.

Organization culture is the combination of values, core beliefs, behaviour model, and

represents the value system of the company that becomes the employees' behavioural

norm (Ying-Yung, 2006). Extensive literature on organizational culture reflects its

significance on the outputs of any process within organizations.

Teamwork plays an essential role because when everyone is working together, the

results are always better to any individual’s accomplishment (Sachs, 2007). On the other

hand according to Jarratt et al. (2011) people’s lack of interest and poor cooperation

within stakeholder is believed to be a main obstacle in configuration change

management. Supportive attitude and politics free environment helps in the effective and

on-time communication between functional stakeholders and CM. CM is seen as a

communication bridge between design engineering and the rest of the world (Watts,

2010); where lack of interest and concerns from any side could affect the desired outputs

of the process.

Organizations face problems to hold back experienced and competent employees due to

lack of recognition and career progression. Lack of recognition and career progression is

a major concern in aerospace industries and has largely affected the overall

implementation of the CM process (Burgess et al., 2005). This issue will never help

organizations to retain their employees and as such practitioners will switch to

alternative fields having better career developments and opportunities.


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4.3.5.6 Communication

The only Critical Success Factor in this group is effective communication which plays a

positive role in the implementation and continuous development of the CM practices and

helps to reduce product development cycle time through better decisions. According to

Tavcar and Duhovnik (2005) and Wasmer et al. (2011), up-to 40 % of time reduction

has been reported in the implementation of engineering changes through timely

communication. It is observed that two third of changes could be prevented with the help

of improved communication where failure in this could result in a large number of

changes through decisions on obsolete data (Jarratt et al., 2011). It is believed that

changes in product characteristics on customer requirements result an exponential

growth in the volume of information which needs to be properly communicated through

an effective product configuration system to handle such information (Yeh and Tai-Hsi,

2005).

4.3.5.7 Process boundary

Process boundary is composed of two CSFs i.e. committed and creative employees and

proper CM organization. Committed and creative employees are among the most

valuable business assets that provide organizations an edge over its competitors. Best

CM practices are the result of creative and committed professionals who always evaluate

and communicate what works and what doesn’t work (Sachs, 2010). CM organizational

structure on the other hand plays an important role in the CM process implementation. It

is important to note that decision on the type of CM organization depends on many

factors such as the number, size and complexity of projects and availability of the

required resources.


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4.4.1 Summary

The main objective of this research was to identify, prioritize, and categorize the critical

Success Factors for Configuration Management and devise a Configuration Management

activity model to help practitioners in the effective implementation and continuous

improvement of the process with reference to aerospace and defence industries. The

motivation behind this study was twofold; first as no formal research has been identified

in general on this imperative topic to act as a baseline for process improvement of CM

and secondly to provide guidelines to CM practitioners for the effective implementation

of process as CM has not been fully established and recognized within aerospace and

defence industries after 60 years from inception even with apparent recognition by

different international standards.

Mixed method research was chosen with supervisor consent to finalize the list of Critical

Success Factors where inputs of as many participants were difficult to obtain through

any other research methodology with available resources. The identification of critical

success factors for CM implementation was a challenging task and was successfully

done through comprehensive literature review and discussion with Configuration

Management experts through interviews, emails and phones. After presenting the

identified list of twenty-one factors to a group of CM subject specialists with CM

experience ranging from 5 to 30 years in a meeting of Association of Configuration

Managers in The University of Manchester, all twenty-one factors were retained for the

final questionnaire and were forwarded to CM professionals in aerospace and defence

industries.

On the basis of descriptive statistics, all twenty-one factors included in the questionnaire

survey were finalized critical for the successful implementation of Configuration

Management in aerospace and defence industries based on their mean values (4≤ Mean

Values ≤ 5) as highlighted in table 4.1. Inferential statistics were applied to determine


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the effects of different parameters on Critical Success Factors in the implementation

process of CM. Two important results have been obtained from these inferential

statistics. One is the experience in Configuration Management while the other is

Configuration Management certification / training where variations are observed due to

these factors in the perception of CM practitioner.

The main focus of this research was to finalize and prioritize factors which are critical

for the implementation of the Configuration Management process within aerospace and

defence industries. Descriptive statistics was used to finalize and prioritize the CM

Critical Success Factors while inferential statistics was applied to assess the variations in

the perception of CM practitioners based on their academic qualification, work

experience, qualification / training, and experience in key stakeholder departments.

4.4.2 Conclusions

This study identifies and prioritizes Critical Success Factors for the effective

implementation and continuous development Configuration Management practices in

aerospace and defence companies based on the views of CM professionals. Importance

is given to find any significant differences in the perception of practitioner’s academic

qualification, work experience, qualification / training, and experience in stakeholders

departments. The groups of factors were then populated in the form of an activity model

to highlight the importance of these factors in the implementation of Configuration

Management process. The research is conducted with experienced CM professionals to

ensure the usefulness and effectiveness of the study.

A number of studies have been identified in CSFs in other allied fields but no single

study is known to describe the Critical Success Factors for Configuration Management.

This research contributes to the knowledge by presenting the Critical Success Factors for

the effective implementation of Configuration Management within aerospace and

defence industries. The main objective of this study was to provide a benchmark in the

shape of Critical Success Factors. These Critical Success Factors will help Configuration


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Management practitioners to know the most important reference points, guide them to

work in the right direction for their goals and help them to measure the effectiveness of

their Configuration Management practices.

A total of twenty-one factors are finalized as Critical Success Factors and ranked on the

basis of importance for the implementation of Configuration Management. The

importance of these factors could be judged from their high mean values shown in table

4-1 while literature supports the significance by emphasising the importance of these

factors in the implementation Configuration Management practices. Significant

difference is found in Configuration Management professionals perception’s on the basis

of their experience in Configuration Management and Configuration Management

certification and training on the ranking of Critical Success Factors which presents the

importance of these two areas in the implementation process.

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CHAPTER 5

BARRIERS AND GOVERNANCE OF THE CM PROCESS

5.0 Introduction

This chapter investigate the data obtained through a questionnaire survey administered

from April to July 2011 and interviews conducted in December 2011 and January 2012.

These interviews are continuation of research on barriers to Configuration Management

implementation initiated through a questionnaire survey. These interviews helped us by

providing a channel to extensively discuss the issues with CM professional and get their

expert opinion to ensure that identified barriers are the true representation of the

Configuration Management practices in aerospace and defence industries. The purpose

behind these interviews were twofold, first to explore the barriers in the effective

implementation of CM process and second to define mechanisms for the governance of

this process.

Judgemental and convenience sampling strategies were adopted to select a sample size

for the interviews. Judgemental or purposive sampling was used to avoid any

compromise on the quality of data where interviewees were selected on the basis of their

experience in the field of Configuration Management. Convenience sampling was used

by keeping in mind the easily and readily availability of the sample. Interviewees were

shortlisted and finalized with the help of supervisor by taking multiple parameters into

account i.e. experience in CM, role of the individual in the implementation process of

CM, and the type of industries they belong.

Analysis of data received from sixty-four questionnaires and seven semi-structured

interviews conducted with CM experts in four aerospace and defence organizations a list

of nineteen barriers were finalized. The second part of interviews which included

discussion on the Configuration Management concludes that CM organizational

Chapter 5: Barriers and governance of the CM process

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structure within organization could varies with many factors e.g. composition of the

actual organization, the number and size of individual projects etc. It is also concluded

that the most suitable organizational structure for Configuration Management process

would be either functional or matrix to ensure consistency of CM principals from project

to project.

Note: It is important to mention that some of the material presented in this chapter

is also published in the following publications.

• Ali, U., Kidd, C. (2013). Barriers to effective Configuration Management


Journal of Project Management (DOI reference:

10.1016/j.ijproman.2013.06.005)

• Ali, U., Kidd, C. (2012). Understanding the obstacles to Configuration

Management success. 26th IPMA World Congress, Greece.

5.1 Research objectives

The objectives were to answer the following research questions as outlined in chapter

one.

• What obstacles are perceived as the real barriers in implementation and success of

Configuration Management practices in aerospace and defence industries?

• What is the perception of Configuration Management practitioners about

organizational structure for Configuration Management in aerospace and defence

industries that could help in the implementation of Configuration Management

practices?


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This research was conducted through a questionnaire survey followed by semi-

structured interviews. Through an open-ended question in a questionnaire survey, CM

practitioners were asked to address problems which they believe are the real obstacles in

the implementation of CM process. Questionnaire was divided into four sections. The

first three sections were part to my research on critical success factors while the last

section was related to this part of the research. A number of barriers were identified as

barriers to CM implementation on the basis of sixty-four questionnaires.

The questionnaire survey was followed by semi-structured interviews. To effectively

conduct these interviews and get the desired results, interview guide (Appendix B) was

designed by keeping in mind the research questions as outlined in chapter one and were

refined several times before interviews. The interview guide was updated by

incorporating questions according to situations as interviews proceeded. The interview

guide was divided into five different sections where the first three sections were to

support the fourth and fifth sections which were related to barriers in the implementation

of CM process and CM governance respectively. Interviews were analysed several times

and the results were compared with the data obtained from the questionnaire survey

where nineteen barriers were finalized.

This research is based on judgemental and convenience sampling techniques.

Judgemental and convenience sampling techniques were applied as it provide us the

flexibility to choose appropriate sample which can be accessed easily and conveniently

and also fulfils the required objectives (Saunders et al. 2009). By keeping in view the

objectives of this research, sample was selected from different organizations to ensure

that output of the research is unbiased and cover the views of different environments.

Interviewees were selected from four different aerospace and defence industries having

experience ranging from 5 to 35 years in the field of Configuration Management. In the

first phase, two interviews were conducted at The University of Manchester with CM


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professionals. The interview guide was updated on the basis of responses to questions to

ensure quality of outputs in coming interviews. In the second phase four interviews were

conducted in one organization to get their expert opinion on the issues addressed in the

interview guide while seventh interview was conducted on telephone. Findings of the

interviews are presented in the coming sections i.e. barriers in implementation of CM

process and CM governance.

5.3 Analysis and discussion

This section describes the analysis of data received through a questionnaire survey and

semi-structured interviews. Details of the quotes are provided to explain and support

further discussion. This section is further divided into the following two main sections:

• Barriers to Configuration Management implementation

• Governance of the Configuration Management process

5.3.1 Barriers to Configuration Management implementation

One of the research questions as highlighted above is to identify barriers in the

implementation of Configuration Management process. It is important to know the root

causes which affect the efficiency of a process implementation in most efficient and

effective way. The aim of this research was to get CM practitioner’s views based on

their work experience in different projects environment on the issues which has affected

the implementation of the CM process.

The data was collected through a questionnaire survey and semi-structured interviews on

barriers to Configuration Management implementation within aerospace and defence

industries. The purpose of questionnaire survey was to get responses from as many

research participants which was not feasible through any other research method because

of the time and resource constraints. On the basis of open ended question to highlight the

barriers in the effective implantation of Configuration Management process, a number of


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responses were received from sixty-four CM professionals working in major aerospace

and defence industries. Interviews were conducted to further investigate the subject and

highlight obstacles which the practitioners are facing in the implementation of the CM

process.

After detail analysis of the data, several factors were extracted and were discussed with

supervisor in several meetings. A list of nineteen factors were finalized on the basis of

data received from two source of data i.e. questionnaire survey and semi-structured

interview. Details of the extracted obstacles to CM implementation are given below.

• Lack of top management support

• Lack of centralized body for the governance of CM

• Lack of CM training across organization

• Lack of authority to implement CM principles / policies

• Implementation cost outweigh CM benefits

• Lack of recognition and underestimating the importance of CM at every level of the

organization

• Lack of career progression for CM professionals

• Poorly defined CM requirements and process

• Lack of maintaining consistency in CM activities across projects

• Lack of flexibility in CM process

• Outdated CM process

• Lack of current CM Plans

• Lack of CM process across life-cycle

• Lack of CM awareness in customer world

• Lack of effective communication

• Lack of effective CM tools

• Lack of resources

• Lack of support from stakeholders

• Extreme projects pressures


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The most important issue as highlighted during interviews was that most of the barriers

have strong connections with each others; where ignoring one specific factor results with

many other obstacles in the implementation process. Analysis of data showed that

identification of these factors was influenced by many factors like respondents

experience and type of organizations and the nature of complexity of the products

research participants were involved. These issues will be further analyzed in the next

phase of this research. Details of the factors highlighted above on the basis of data

received from the two research methods are given below.

5.3.1.1 Lack of top management support

Lack of management support is frequently highlighted in the received data both through

questionnaires and interviews. On the other side literature also back this issue where

lack of management support is considered one of the main issues in the CM

implementation (Burgess et al., 2005). It is important to present the received data in their

original quotes to support this discussion. The data received through questionnaires

presents a strong position on the lack of support from the top management where several

quotes are presented below obtained through a question asked to present barriers to CM

implementation.

• ‘It is very easy for senior management to blame Configuration Management or

quality assurance teams for the lack of proper control of products or data assets,

when in fact there has been a blatant disregard for following process. This is why it

is essential that CM has the necessary status / authority within an organisation to

ensure that CM processes are followed’.

• ‘Management not ensuring CM Plans, policies, work instructions are understood

and / or followed by the stakeholders’.

• ‘Lack of senior management vision and understanding of the importance of CM in

supporting project management’


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• ‘Managers and higher project Managers do not understand what they want reported

and how it should help them?’

• ‘When top management doesn't consider the practice of CM to be as critical as other

teams in the organization’.

• ‘Lack of support for CM methodologies from every level (top management –

stakeholders)’.

• ‘The failure by management to understand the consequence of poor CM practice’.

• ‘Lack of CM awareness / importance at top management level’.

• ‘Management not giving enough credence to CM’.

This data obtained through questionnaire is equally supported by participants in

interviews by highlighting it as one of the main barrier in the implementation CM

process. According the research participants, CM has never received the due importance

at every level of the organization which is highlighted below:

‘Lack of leadership support often ties in with poor requirements and poor process

because unless you have leadership saying you will do CM, its critical for our business.

A project has no incentive to actually deliver it themselves because typically the project

stops its product delivery and almost all of the CM benefits or product lifecycle

management, fixing faults, managing risks when its coming to life support, and the

project does not really care about that, there job is to deliver product. So your company

top-down needs to be saying we are doing this for overall benefits and it’s not used an

individual, if we get these benefits, its downs stream so that top management

understanding of what they want? Why they want it? And, how would it benefit them?

And then promoting that to the company is really important’ [Sic]


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‘I don’t think they really know who we are and what we doing. I guess, I think it all

comes back to this that we are the one who delay things, who block things, what we can

do to improve things?. They are not interested in we are in a change board process, they

are not so interested in that as a department.’ [Sic]

5.3.1.2 Lack of centralized body for the governance of CM

It is believed that if Configuration Management is projectized there is every possibility

that this process will not deliver the desired results and inconsistencies in practices will

arise from project to protect. The issue has been highlighted by various participants

through questionnaire which is reflected below.

• ‘No centralized corporate body for governance of CM / PLM standard processes

across corporation / divisions result in islands of technology and wasted IT dollars

replicating / reinventing CM / PLM systems and processes’

• ‘There should be a core CM team within every organisation ensuring that correct

CM practices and discipline is being recorded and completed throughout the

organisation’

• ‘Decentralisation and matrixing of CM staff tends to lead to lack of cross

fertilisation of skills’

• ‘Configuration Management lost in integration with Project Management’

This issue was highlighted in great depth by almost all participants during interviews

and emphasised more on a core and centralized body for CM within organization which

has been reflected below.

‘I think one of the problem we have is that we are projectized, so we have different

projects, different teams, and our department look after different projects, and we have


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got three different teams and one team split into twos, and so that means we do things in

four different ways’ [Sic]

‘I think lack of centralization is a problem, if I do a little bit of change coordination on

the project I work on, the project (abc), because we don’t have a change controller, but I

couldn’t go and pickup and help in projects (xyz) because everybody does it different’

[Sic]

‘You can have decentralized staff working in projects but they need to be a centralized

body for process and standards and monitoring their staff can show they are working for

those standards. If your organization is fully decentralized, you would have no

consistency. I think there is a risk if the organization is fully centralized its seen as a

black box, the projects don’t know what’s going on, they don’t engaged very much and

then they often do their own things because they don’t see how CM benefits them’ [Sic]

5.3.1.3 Lack of CM training across organization

Lack of CM knowledge across organization is another important barrier highlighted

frequently by individuals in this research and has also been identified as a barrier

previously by Burgess et al. (2005) on his research in the implementation of CM within

aerospace industries. It is highlighted by the respondents through the questionnaire

survey as:

• ‘CM cannot be understood by many people. Lack of education and training by many

disciplines by the users and their leaders’

• ‘Lack of knowledge within the engineering lifecycle new areas of the business e.g.

support and disposal, bid winning and requirements capture’

• ‘Senior managers should understand the principles of CM and should mandate there

us by all employees’


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• ‘Non-education of project managers and senior management as the pit-falls of

ignoring Configuration Management’

• ‘CM personnel need to have CPD which is recognised by the business and is

industrially recognised’

• ‘CM Training of other stakeholder [engineering (HW & SW), procurement, PM,

Business & Finance etc.]’

• ‘Training of stakeholders and lack of funding resources’

• ‘Lack of fully trained and CM knowledgeable people’

• ‘Top management knowledge on CM’

• ‘CM training seen as not value added’

It is equally supported by the respondents in interviews where they highlighted the need

for effective CM training and can be seen from their statements below.

‘One of our biggest problem is that peoples don’t understand what Configuration

Management is? And why we do it? And why it is important?, and the image that we just

do the paper work, and we block everything that they want to do with the projects and

we delay things and we just cause troubles for peoples rather than providing the

answers that they want’ [Sic]

‘CM training across the board is an absolute barrier. CM teams are often quite well

trained but CM should be part of the core training everyone gets in have to do their day

jobs’ [Sic]

‘One of the barriers is the lack of CM knowledge within engineering functions. We got a

big amount of knowledge of engineering techniques, but realization of the concepts into


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product is outside of the knowledge of most of the engineering sort of stuff, so we have a

lot number of engineering leaders grownup as dedicated engineers, have worked in

development areas and design areas and gone to chief engineer type levels and they

fully understand the responsibilities they have got, we offer as part of our design

organization approval, we offer an X position to the authorities which fully explains the

responsibilities of these peoples and how they have to control a product but the detail

knowledge of how does that control happen is kind of missing’ [Sic]

‘It is always a need to do more training. When you are doing a day job, may be you

don’t have enough time to training but having said that certainly in my experience we

put a lot of priority on ensuring that as much training is available the team organization

had access to and try to encourage the team members to support this training activity,

but in the real world you can never do enough’ [Sic]

‘Lack of training is a very big barrier because how could you expect from somebody

make you a cup of tea if they don’t know how to do it, simple analogy, if you are not

trained to do something then it is very difficult to do it properly and get it right’ [Sic]

5.3.1.4 Lack of authority to implement CM principles / policies

Configuration Management is no more new to organizations after its inclusions in

multiple standards as compliance requirements but process executers still have problems

with its implementation and seek the required authority to implement the same. The way

it is highlighted by one of the respondents through a questionnaire ‘Project managers

undermine CM principles and believe that they can do all without CM’ shows the

limited authority of CM professionals towards CM applications within projects. This

issue is also highlighted by interviewees as a concern in the implementation process of

Configuration Management in their organization as:

‘We have lack of authority to implement CM principles. When we try and stand our

ground and say this is the crack way to manage the change that you are asking for, they


175

say no we want to do this way because it is cheaper, quicker, whatever, and the real

thing which frustrate you when you got two standards in series and becomes four, eight,

and sixteen standards after some time’ [Sic]

‘In theory we own the process, but I don’t think the business sees it owning the process’

[Sic]

‘There are companies I know where deliverables are owned and managed by other

functions such as project management or by quality so the company have the authority

to ensure that these Configuration Management activities are undertaken and the

deliverables are produced but they don’t always allocate that to Configuration

Management team and that is why you often see poor quality deliverables and poor

quality process’ [Sic]

5.3.1.5 Implementation cost outweigh CM benefits

It is evident from participant’s remarks that implementation cost of CM within projects

is another main concern for management especially in small projects where exhaustive

requirements is put forward to control the projects. It was pointed that this issue can be

addressed if CM policies could have the required flexibilities in requirements

downloading phase of the projects. Implementation cost was highlighted as one the

concern by professionals in the questionnaire study as.

• ‘Lack of funding. CM can be overlooked at estimate stage and in some cases cuts

completely in order to lower an estimate. This is a false economy as these projects

are normally the ones that end up with huge rework costs or an inability to actually

reproduce a build’

• ‘CM process does equate their effort as cost benefit centre. CM is mostly viewed as

an overhead and block of progress’


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• ‘CM not seen as saving cost’

The issue was highlighted within interviews which are highlighted in the following

paragraphs.

‘I think that’s one of the big problems as what I am saying that CM is predominantly

based on reducing risks, so how much does it costs us? Because that is a function not

only of Configuration Management but also of quality also of safety, even if you could

measure that risk and say this will cost my business, however which portion belongs to

which function and at that point it’s really hard to understand the full benefits’ [Sic]

‘With defence you have these key deliverables you must deliver to your customer- you

must deliver the design baseline, you must deliver the functional baseline, you must

deliver a product baseline, you must deliver CM Plan - these are pretty much

contractual for every defence project. You actually have a lot more visibility of CM

because the project is got on their schedule, I must got these things out which CM will

produce for me so I see less arguments about the cost of CM in defence because the

project managers got list of deliverables he has the CM personnel do for or she for that

matter and there is more visibility because those deliverables are upfront where

somewhat like aerospace, I will deliver a baseline but I will deliver it to internal

customer which then goes to e.g. technical publication, which then goes to our external

customer, we don’t have that direct customer relationship, so it’s not as obvious what

the benefit of your deliverables is.‘ [Sic]

5.3.1.6 Lack of recognition and underestimating the importance of CM at every

level of the organization

Whatever may be the reasons for underestimating the importance of CM within

organizations, it has been reflected a major concern in the CM community. Even after

seven decades of its conception, CM has not yet got the due status within organizations


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which is visible from the research participant’s comments through the questionnaire

survey below.

• ‘Configuration is not important until something goes wrong (It is seen as a

necessary evil)’

• ‘Poor perception of personnel involved in the CM environment as to its importance’

• ‘Project Managers undermine CM principles and believe that they can do all

without CM’

• ‘Mid-level and senior management do not understand the "real" role of CM’

• ‘CM is just to be tolerated - not embraced’

• ‘It is expected to be done cheaply’

• ‘Role of CM not understood’

• ‘Ignorance of others’

The issue is also highlighted by interviewees as follow.

‘You have a lack of respect for CM leadership by the wider projects, so the peoples who

are the directors and responsible for the profit, make or conceive decisions based on

product out-of-the-door and don’t consider the impact of those decisions because they

haven’t got a deep understanding, a wider understanding of the issues’ [Sic]

‘There is a lack of recognition and underestimating the importance of CM at every level

of organization’ [Sic]


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5.3.1.7 Lack of career progression for CM professionals

Lack of career progression for CM is one of the three barriers identified by (Burgess et

al., 2005) in his research on Configuration Management practices in aerospace sectors. It

is highlighted by the research participants as:

‘CM does not connect with other disciplines in engineering for instance, so you wouldn’t

expect to become a configuration engineer normally and that be lead into designer or

become a stress engineer so I think people feel to grow up in configuration discipline, if

you want to move on to a different career path you have got to stop and take a different

career path it’s not a progression’ [Sic]

‘Lack of career progression, until very recently’ [Sic]

5.3.1.8 Poorly defined CM requirements and process

Poorly defined CM requirements and process is the second major concern within CM

community after lack of management support which is frequently highlighted by the

respondents through both in questionnaire survey and interviews. It is evident from the

replies highlighted below through questionnaire survey as follow.

• ‘No customer / agency mandate of approved regulatory or defence 'standards' to

mandate corporations to have a Configuration Management division / dept / group’

• ‘Documents are not correctly identified, structured and/or linked to the physical

items. The result of this is the time wasted in either finding the correct docs or

reviewing unnecessary documents’

• ‘Organisations believe that CM stands for Change Management therefore ignoring

all other Configuration Management requirements’


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• ‘MOD Def Standards are too complex and rigid and explanation is not clear or

defined’

• ‘Un-implementable process and process not fully known and documented’

• ‘Approval process is too long and cumbersome’

• ‘Inadequate workflow design’

It is believed that CM requirements are process is poorly presented within organization.

Even though international standards are available but only highlight a generalize view of

the process which does not guarantee the implementation of an effective CM process.

There is still a need for a centralized team to take the task for downloading the CM

guidelines which could be understandable and implementable. The issue was highlighted

by interview participants as follow.

‘Poorly defined requirements for CM, so if an organization does not understand what

CM they want? Why they want it? And, how would it benefit them? Than your CM

process is always guaranteed not to work by the time you get it. From that your next

sequential one tends to be, poorly defined process; so I worked in several organizations

that planned to be CM at my level three, what actually you got lot of heroes and very

erratic process or process erratically acquired, so you didn’t have consistent process,

you didn’t have well defined process, normally it was huge global process, and at the

point you got into the detail, everybody did their own things on their own project, and it

is very hard to have a transferable skills. So you often find there is existing process but

there is no consistency which for CM is quite a challenge than’ [Sic]

‘Lack of simplified and updated CM standards, lack simplified CM procedures, lack of

adequate and updated CM plans, and lack of CM process across product life and

outdated CM process have been a problem’ [Sic]


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5.3.1.9 Lack of maintaining consistency in CM activities across projects

Lack of consistency within CM practices was also highlighted as one of the barriers by

many research participants. A respondent through a questionnaire highlighted the issue

as ‘within the same company people can still work differently because there can still be

a lack of communication’. The reason behind inconsistencies in CM process across

projects as highlighted by respondents in interviews is the lack of maintaining

centralized CM process within organizations. This can be seen from the comments as

highlighted below.

‘Maintaining consistency of CM process is an issue; we suffered it right down from

various authorities. There is no legislative requirements for Configuration Management,

so the relative authorities don’t ask for Configuration Management process, our

organization does have anywhere in the process, I think, that this is the Configuration

Management process, so the way it is explained is in terms of delivering product,

delivering engineering information, delivering data, controlling requirements. So we

struggle with consistency because each product interpret those requirements slightly

differently and out of that, spills of slightly different Configuration Management, not

necessarily process but certainly practices’ [Sic]

‘For each of the project the organizational structure was somewhat different and we

also find that they deviated dependent on their project to the generic process and that

couldn’t be managed as a top level, that was done via subset of documents for each of

the project, so instead of having one generic Configuration Management process that

was enforced on the project they tend to have a diluted view of the all’ [Sic]

‘Lack of maintaining consistency is a big problem, again, as every project does it

differently’ [Sic]

‘If you look that one project and one team that are doing the specific role, not all of

those fully understand in exactly the same manner as the rest of the team what they


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supposed to be doing. It’s maintaining consistency among the staff you are working

with, and this is only because you don’t have a centralized body or centralized person’

[Sic]

‘Every time when new project comes along; they say we do it slightly differently, so they

have been allowed to do so and the problem now is that we have multiple processes. It

comes back to this that we don’t have the power, we don’t have the control, I mean, the

product change board is how we change everything we live the project change board,

we own it, but we don’t chair it’ [Sic]

5.3.1.10 Lack of flexibility in CM process

It is a feeling that CM process is quite rigid as highlighted by respondents with

questionnaire survey through remarks like “Non-flexible corporate governance” and

“Rigidity / inflexibility of CM process” The issue is highlighted by interviewees as.

‘We are quite good, we can bend the rules should we need to, sometimes we do and

catch things up latter’ [Sic]

‘Sometimes, I think the problem is often the CM processes are too flexible and when they

are tightening-up they are too inflexible. I would say it is a risk around CM effectiveness

overall’ [Sic]

‘We do like flexibility mainly because I think we don’t practice high enough capability

Configuration Management, so the processes we have got, we say are a little bit

desperate and we have got variations in practices but we are relying on them completely

so whatever type of change we do to product we have to use the same process as it is

written’ [Sic]


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5.3.1.11 Outdated CM process

‘Outdated configuration procedures, need to keep up with new ideas’, as a barrier,

highlighted by one of the respondent in the implementation of Configuration

Management process through a questionnaire. The same is highlighted within interviews

as.

‘Again, defence particularly (xyz document) is a terrible document that makes reference

to specific templates that you will never do it right now’ [Sic]

‘The CM standards, either they are not explicit or detailed enough or there is a need to

be updated but haven’t been updated’ [Sic]

5.3.1.12 Lack of current CM Plans

This research indicates that CM plans are not given enough importance within

organizations which is vital to govern the CM process of individual project. CM plans

are either not existed or not updated according which could create multiple problems in

the implementation of CM process. This has been highlighted during interviews as.

‘It’s often the case that some CM Plans lacked behind the actual point in which the

projects moving in the project life cycle’ [Sic]

‘The problem is that you will find lot of companies will develop quite a good CM plans

and they will issue it and people will work to it but then five years latter you look at that

CM plan and it is probably still in issue one but the organization has evolved so it has

not kept up-to-date. So in general they start-up in good way but don’t maintain that and

then becomes an issue then’ [Sic]

‘We don’t have as many plans, the only plans I tend to see are plans relating to projects

going through the project change process and they are rubbish because they make plans


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and then say, right we are going to do this development work by this date and they never

stick to it’ [Sic]

5.3.1.13 Lack of CM process across the life-cycle

It is believed that a major concern to effective Configuration Management

implementation is not giving the due considerations in early phases of the projects i.e.

concept and development and after sale i.e. maintenance and modifications. It is

highlighted by respondents in the questionnaire study as:

• ‘Delay in involving Configuration Management process on any given project’

• ‘Involving CM too late in the lifecycle of the project / product’

• ‘Absence of CM during development’

According to research participants in interviews, it is highlighted that CM process can

play a more important role in the post delivery process but has not been actively

involved as highlighted from the following comments.

‘Once we delivered our product to the customer, our CM process is didn’t covered in

too much detail the continuous CM activity once the product have been delivered to the

customer, but I have no good reasons for that. But in most recent time the contractor has

a great more involvement with the product post delivery then we have to become more

involved in Configuration Management in the post delivery phase’ [Sic]

‘Lack of Configuration Management involvement across life-cycle is a barrier because

you are not identifying what you want to control upfront, you always plan catch-up

things later which is not easy’ [Sic]


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5.3.1.14 Lack of CM awareness in customer world

Configuration Management can be used by external customer as a tool to ensure the

quality of products which they are going to develop or purchase. Even after extensive

development in knowledge proliferation there are still a lack of CM awareness in the

customer world which is highlighted by one the participant in questionnaire survey as

‘There is a lack of knowledge about product Configuration Management requirements

from a customer’s perspective when that product requires full support from the supplier;

Lack of CM awareness and cost within the customer world’.

Lack of CM awareness in customer world is highlighted in interviews as follow.

‘I have certainly found that in MOD environment, there is a lack of understanding of

CM and how should it be applied within their environment, it just cause problem, so I do

find that a big barrier’ [Sic]

‘There is hardly any specialists, if we haven’t any specialists, I am sure most of the

companies haven’t got specialists’ [Sic]

5.3.1.15 Lack of Communication

Communication was highlighted as an issue in the implementation of CM process by

some of the respondents and was thus included here. It was highlighted through

questionnaire study that ‘within the same company people can still work differently

because there can still be a lack of communication’ and ‘the need to keep information

real-time is not considered important by groups that create the initial items / sites that

require tracking’. In the interview two of the respondents replied as follow.

‘Communication is a barrier for CM but not more so for other areas like project

management, quality, and other part of the infrastructure’ [Sic]

‘It’s a bit of a mix I would say, as people don’t understand what we do’ [Sic]


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5.3.1.16 Lack of effective CM tools

One of the highly marked barriers within this research is the lack of effective CM tools

(software). There might be several reasons for this as identified by the respondents

through questionnaire as follow.

• ‘Most CM tools are designed by those who do not perform day-to-day CM activities

and hence create problems during implementation’

• ‘CM can only be effective if given the right tools, proper recognition and a top down

approach from the board’

• ‘Databases designed by people who do not have to use them on a daily basis’

• ‘continual changes of buzz words each time a new database is introduced’

• ‘Toolsets contain more workarounds than detailling the CM Process’

• ‘Tool functionality specified by CM and not prescribed by IT’

• ‘Poor investment in the implementation and use of CM tools’

• ‘Up to date CM tools not being utilized with the Command’

• ‘CM tools implemented with the out of the box solution’

• ‘Too many different tools without interface/integration’

• ‘ERP support tool’

In the interviews it was highlighted as:


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‘Poor tools implementation - old or non-functional tools- CM tools and other tools

where you got data and multiple systems no tie-up between your systems, you then have

vary many manual processes which either you have data inaccuracies or no bodies

understand where defined anything, and that’s a bit that most often generate the

perceptions of CM is not working - and that’s the biggest one you will see you always

that usually the reasons for that really is poor requirements and no buy in processes and

wrong data is coming in, people are not managing it correctly. People think it’s not

important so by the time it hit the tool, the data in the tool is very poor. If your tool is not

user friendly or your tool have poorly implemented process, that will then generate tools

problems - about 80 percent of what subscribed to be a tool problems is a process

problems and the training problem and not a tool issues’ [Sic]

‘CM tools e.g. PDM and now PLM; some tools ask the golden things, that they will do

everything, we know that, but four five six years in, we are still developing the system, so

none of them have ever truly being fit for purpose’

5.3.1.17 Lack of resources

The most obvious barrier in terms of resources is issues with human resources to do the

job that often ties in with lack of funds within projects. It is highlighted by respondents

through questionnaire as.

• ‘Lack of support in resources to implement CM effectively in personnel and

equipment’

• ‘Budget for CM for projects underestimated’

• ‘Continuous improvement of CM process is often difficult when also progressing CM

tasks for a product with a challenging programme e.g. with funding, timescale or

resource limitations’


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It is equally considered as a barrier in the implementation process within interviews by

respondents as.

‘We struggle a bit to get the required resource. Actually we are quite a large

configuration organization but relative to design outputs and relative to development

activities going on, I think Configuration Management is possibly under resource. We

have got the core Configuration Management team that really look after particularly

accounting and change process and all of the other sort of areas of Configuration

Management of development vehicle and Configuration Management of requirements.

It’s done by the people around the business and it’s done by mostly one or two peoples

in the area’ [Sic]

‘Lack of resources comes into everything, doesn’t it? There is never enough people to do

the job’ [Sic]

5.3.1.18 Lack of support from stakeholders

Lack of support from stakeholders is rightly identified by respondents because if one is

not accepting the importance of a process it is not possible to have their positive support.

It is believed that there is still a lack of knowledge of CM practices which is one of the

reasons of ignoring the importance of these practices. Lack of support from stakeholders

is identified by the respondents through questionnaire survey as follow.

• ‘Lack of adherence to processes by stakeholders’

• ‘Lack of dedicated staff for CM in program management’

• ‘Constant 'fire-fighting' by programme’

Lack of support from stakeholders is equally supported and identified as a barrier within

interviews. It is highlighted by the respondents as follows.


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‘CM is an obstacle to achieve in the maximum output; they don’t realize that good CM

will actually give them maximum output with maximum integrity’ [Sic]

‘There is a lack of support because of the lack of understanding I think. Because if they

understood what we are trying to do, they will support us’ [Sic]

‘Lack of support from stakeholders is a barrier. That’s your leadership point of lack of

commitment from stakeholders’ [Sic]

5.3.1.19 Extreme projects pressures

It is identified in the interviews by the research participants that programme

management never wait to fulfil the requirements of Configuration Management

activities and adopts short cuts or bypass them. It is highlighted by the respondents as

follow.

‘Programme pressure, communication, resources in all its various aspects where it is

funding, people, tools, facilities are barriers but programme pressures are probably

significant’ [Sic]

‘Project pressures is a big problem, they never wait especially when it is urgent jobs’

[Sic]

‘Projects pressure is a barrier but it does not need to be a barrier if your process is well

defined and flexible. Again, it’s an excuse not a barrier - I think that project deadlines

and projects pressure are barriers because the importance of CM is not understood, so

it’s not a barriers in its own right but is frequently causes failure to the CM process’

[Sic]


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5.3.2 Governance of the Configuration Management process

The literature suggests that the governance aspect of Configuration Management is

missing in its limited academic literature. On the other hand extensive literature on the

subject shows its critical importance in the success of organizations. It is important to

note that Configuration Management has never given the due credence within

organization and hence faces considerable resistance while implementation. To avoid

such resistance and ensure its effective implementation it is necessary to have a strong

organizational basis of the process. It is important to highlight that Configuration

Management is always believed as a rigid discipline which have never provided the

room of flexibility for projects based on their different requirements and hence

considerable difference is found in the Configuration Management practices from

project to project within same organization. The objectives of this discussion is to come-

up with conclusions on the effective governance methodologies for Configuration

Management which could help standardization and effective implementation of the

process across the projects.

Governance issues were discussed in great deals to come up with conclusions on

different aspects on how to run a CM organization within aerospace and defence

industries. Interviewee were asked multiple question as outlined in the interview guide

in appendix B and many other were added as the interviews proceeded to reach on

conclusions. Output of these interviews has been analysed in different headings below.

5.3.2.1 CM organization

Respondents were asked to explain the CM structure within their organization and the

appropriateness of that structure in their views. They were further asked to highlight that

how the CM discipline should be governed within organizations on the basis of their

experience and how to ensure the accountability and responsibility issues of the process.

The research participants views were distributed towards three organizational structure

i.e. functional (centralized), divisional (projectized), and matrix. In their views it is


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difficult to advise which structure would be best to govern their CM process and should

be decided by keeping in view different requirements e.g. the number of projects, size of

projects, and the organizational setup. Their comments have been downloaded below for

better understanding of the governance process within organizations.

‘We did have a dedicated CM organization; it was always linked into the technical

organization headed by the Chief Engineers. We have head of projects and chief

engineer, chief engineer was the engineering manager, and Configuration Management

organization was one of his responsibilities. We had a chief engineer for each project,

so we had a project based Configuration Management system. Across all products we

had a functional department that looked the activities across all the project areas, and

one of the aspects of this functional area was to ensure that there are aligned activates

across all the projects’ [Sic]

‘We did have an engineering director and then we have a CM process owner and then

we have all the projects underneath him. The configuration manager of each projects

were about the same level as the CM process owner but only his say was that you will

use the generic CM process and you will use these golden roles and you will do this and

you will do that’ [Sic]

‘If you have a good centralized structure in place then you got somebody at the very top

level who is responsible for all your CM activities and can make sure that each of the

projects underneath that umbrella is operating correctly. If you got another like the

hybrid type of environment which is similar to we have, all we could do is say this is the

procedure you should be following, these are the golden rules you must follow, they still

developed how they operated themselves, they still utilized a very generic CM process,

but it was very different in the way they applied it’ [Sic]

‘Personally, and it is a personal view, there should be a CM directorate, so for my point

of view you need a CM director with a central CM functioning team underneath him to

make sure that all the activities, all the processes, and all the practices are going on and


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that aren’t diluted so much that you don’t recognized any more. There should be

somebody in place, a director is in place that will make sure that funding is available for

CM, that the correct training is in place, there is a career structure for people if they

want a career in CM and that all the projects are operating under the same umbrella

under the banner in the correct manner’ [Sic]

‘Depends on the company and the products they are producing so if you got a company

which producing a lot of small products then you may have a multi project

Configuration Management organization, if you have big project then you need a

dedicated CM team for that’ [Sic]

‘We have a very regulated industry, so very active business lots of pressure, we spend

our own money our own private R&D money, so there is a lot of pressure, much of a

time to deviate and find quick routs quick answers cheap answers, so I think

Configuration Management has to be a really hard policing activity, controlling activity,

so what we find from our experiences if we go completely projectized, if we put the

configuration team under the project chief engineer or chief design engineer they tend to

adopt practices that are suitable for that project to deliver its product which is not

necessarily the right thing in the long term. The most beneficial thing to do so certainly

we prefer a centralized Configuration Management team that is not directed by the

projects’ [Sic]

“A centralized CM function which defines processes, standards, answers the key

questions and decentralized CM staff delivering that process within projects, so co-

located with projects” [Sic]

On the basis of comments, there is no one best way to govern a CM process and presents

more variations in the structuring of the process across organizations. Most of the

peoples favoured a functional (centralized) organization to have consistency in their CM

practices. It can be concluded that for defence organizations which are involved in the

development and production of huge projects, they should be a matrix type of CM

organization to maintain consistency in the CM process within different projects and


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organization which are involved in the development and production of various small

projects, function organization will suite them best by keeping in mind the cost and

consistency issues of the process. It is further highlighted that in both cases it is the CM

head that will be both accountable and responsible for the implementation and

consistency of the CM process within organizations.

5.3.2.2 CM roles / appointments within organization

In all the seven interviews no two organizations have similar roles / appointments for the

execution of Configuration Management process within their setup. This shows that

organizations are still in the transition phase to establish their CM process and define the

roles / appointments to fit their process. Different appointments came across under

discussion like configuration specialist, configuration manager, and change manager etc

at different level. It is highlighted by interviewee as follow.

“It depends on how you opt to set your organization basically, but I mean, I would

expect that on a centralized function you will have a Configuration Management

director; underneath him you will have a core team and that might be perhaps four or

five configuration specialists or offices or whatever you want to call them, and

underneath that you got all the configuration managers of each of the project and they

will then set their own team underneath them to manage their activities, to make sure

they go correctly” [Sic]

“We call them configuration engineers; it’s our generic terminology, they live within a

competency structure which our company treat for its product definition type peoples

and certainly we need for configuration specialist which is a high level of professional

capability but not necessarily leadership management type capabilities” [Sic]

“We had a configuration manager and then under the configuration manager we

typically had a change manager, we had status accounting & verification manager, so

the job titles related to the activities and responsibilities they were given” [Sic]


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It is difficult to comment and devise roles for CM personnel that would fit different

types of defence industries. But on the basis of expert opinion of research participants

and assuming a defence industry which is involved in the development and production

activities of multi-type projects having a matrix type of CM structure; it would be

advisable to have a CM director, Configuration Management specialists, Configuration

Management officer, and Configuration Management staff / coordinators to execute

different activities.

5.3.2.3 Qualification for CM roles / appointments

It has been highlighted throughout this research that Configuration Management is never

given the due importance and ignored in term of resources especially qualified human

resource. Multiple participants in this research highlighted this issue and insisted on the

employment of technical staff to execute the Configuration Management activities as

highlighted by one of the participant as ‘engineers could perform the duties of CM, and

this is true depending on the complexity and the time-constraints of any project. It's been

my observation that the consistency and accuracy of CM would be performed to the

extent of an Engineer's integrity, directly proportionate to the Engineer's belief /

commitment to CM principals and practices’ [Sic]

It is until very recently that organizations mostly valued CM training and experience,

and not any academic qualification where peoples were recruited based on their

elementary levels of academic educations. But the things have changed in organization

and are taking graduates in engineering for Configuration Management roles and

appointments. These issues have been highlighted in the following paragraphs.

‘There is lots of different things you can consider is qualifications and some bit of a

training etc. At the moment I don’t believe there is a specific qualification for

Configuration Management but things are changing now but in general what the

company should be doing is looking for the right kind of training and development and


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even certification to give people a level of knowledge that will enable them to

successfully do their job and a feel that they have gained a level of knowledge’ [Sic]

‘Traditionally configuration engineer is HNC qualified. We expect mechanical and

production engineering at analytical level and we are trying to recruit engineers as a

configuration managers, configuration engineers of any engineering discipline’ [Sic]

5.3.2.4 CM rules and regulations

In response to question of who should define the CM rules and regulations and from

where these should be reviewed and approved? Almost everyone replied that it should

be the direct head of Configuration Management function within that organization. One

of the replies to the question is ‘The one who owns the process at the top, the dedicated

head of function’ [Sic]

The replies are the true representation of the actual practices, since, in project based CM

organization, where CM manager own the process and have no centralized setup to

govern the CM rules and regulation, respondents highlighted inconsistencies in the CM

process from project to project. On the basis of this discussion, this problem could be

eliminated by having centralized governing body to take charge of the rules and

regulations of the CM process and ensure its implementation in projects within

organizations.

5.3.2.5 CM control at vendors premises

In view of the CM professionals, it is the concerned configuration manager who should

deal with vendors on the issues related to configuration control of that project but in

actual it is quite varied in various organizations. In some organizations it is done by the

quality staff and in some the concerned project manager. On the basis of responses, it

can be summed that since it is only configuration managers who have the full


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background of the issues; should deal with Configuration Management issues with

vendors.


The main objective of these interviews were two fold, first to finalize the list of barriers

to Configuration Management implementation and second to discuss the governance

issues of Configuration Management and come up with a suitable organizational

structure which could best suite the implementation of consistent Configuration

Management process. To achieve the objectives, questionnaire was sent to CM

professional in different aerospace and defence industries from where a total of sixty-

four questionnaires were received followed by seven semi-structured interviews, which

were conducted with Configuration Management professionals from four different

aerospace and defence industries. The conclusions on results of these interviews are

summarized in the following two headings.

5.4.1 Barriers in the implementation of CM process

On the basis of analysis of data received from sixty-four questionnaire and seven semi-

structured interviews, the following list of nineteen factors termed as barriers to

Configuration Management implementation were extracted.

• Lack of top management support

• Lack of centralized body for the governance of CM

• Lack of CM training across organization

• Lack of authority to implement CM principles / policies

• Implementation cost outweigh CM benefits

• Lack of recognition and underestimating the importance of CM at every level of the

organization

• Lack of career progression for CM professionals

• Poorly defined CM requirements and process


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• Lack of maintaining consistency in CM activities across projects

• Lack of flexibility in CM process

• Outdated CM process

• Lack of current CM Plans

• Lack of CM process across life-cycle

• Lack of CM awareness in customer world

• Lack of effective communication

• Lack of effective CM tools

• Lack of resources

• Lack of support from stakeholders

• Extreme projects pressures

5.4.2 Governance of CM Process

Governance of the CM process was only discussed in interviews where different areas

related to the governance of CM process i.e. CM organization, CM roles and

appointments within organization, CM rules and regulations, CM control at vendors

premises within defence setup were discussed in great details. It was observed that these

issues may vary from organization to organization and are varies with many other

factors such as the size and number of projects and the geographical locations of

different departments of organization.

In view of Configuration Management professionals from the four organizations, they

are in favour of either a functional or matrix CM setup where they have dedicated staff

to execute the CM principals and maintain consistency in CM process from project to

project. They further highlighted that CM personnel should be more technical and

should have engineering background at least for Configuration Management officers or

engineers level and above. They further summarized that control of the CM process at

vendors should only be handled by concerned CM officer of that project as he is the only

right person to discuss and resolve the issues with vendors.

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CHAPTER 6

ANALYSIS OF BARRIERS TO CM IMPLEMENTATION

6.0 Introduction

This chapter further investigates the obstacles to Configuration Management (CM)

implementation in aerospace and defence industries. This part of the research is

conducted through a questionnaire survey from April 2012 to September 2012. It is

believed that CM is not practiced to its full potential and is treated the way Quality

Management was neglected in the West prior to its belated recognition (Burgess et al.,

2005). Burgess et al. (2005) believes that achieving highly quality CM system is not

simple and needs further research to investigate the obstacles involved in implementing

high-grade CM systems. To investigate the issue, this research is designed with the aim

to statistically investigate barriers in the effective implementation of the CM process in

aerospace and defence industries. This study has confirmed some barriers associated

with managing CM application, prioritized them with the help of differential statistics,

categorized them into more manageable groups of factors through factor analysis and

have analysed the effects of multiple factors e.g. academic education, gender

differences, CM experience and types of organization on the perception of CM

professionals in the process of identification and rating these factors through inferential

statistics.

Through a questionnaire survey, nineteen (19) barriers are finalized and prioritized on

the basis of their mean values which are grouped in three groups (i.e. ‘managerial and

organizational barriers’, ‘planning and process barriers’, and ‘implementation barriers’).

Significance is found in the CM practitioner’s perceptions based on the typology of

organizations in which they work.

Chapter 6: Analysis of barriers to CM implementation

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Note: It is important to mention that material presented in this chapter is also

published in my following publications.

• Ali, U., Kidd, C. (2013). Barriers to effective Configuration Management


Journal of Project Management (DOI reference:

10.1016/j.ijproman.2013.06.005)

• Ali, U., Kidd, C. (2012). Understanding the obstacles to Configuration

Management success. 26th

IPMA World Congress, Greece.

6.1 Objectives of the research

The objectives were to prioritize the barriers to CM applications with the help of

differential statistics, categorize them into more manageable groups of factors through

factor analysis, and analyse the effects of multiple factors e.g. academic education,

gender differences, CM experience and types of organization on the perception of CM

professionals in the process of identification and rating these factors through inferential

statistics. To analyse the effects of these multiple factors, following hypothesis was

developed which is then evaluated by using inferential statistics.

Hypothesis: The identification and ranking of barriers to Configuration

Management acceptance and application, from the perspective of a CM

practitioner, will be directly influenced by their academic education, gender

difference, CM experience, and typology of organization.


A questionnaire survey is used to validate the initial findings finalized on the basis of the

first questionnaire survey followed by semi-structured interviews as presented in

Chapter 5 and verify the designed hypothesis outlined in section 6.1 above. The

questionnaire (appendix C) was divided in two sections. The first section focussed on

gathering background information whereas the second part was related to barriers where

respondents’ opinions were accumulated on a series of statements. Research participants


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were asked to mark trueness of each statement based on their organization by using a

five-point scale (1 = not at all true, 2 = slightly true, 3 = somewhat true, 4 = mostly true,

5 = completely true). Before the sending the questionnaire for the required responses, in

the first phase five CM professionals were asked to comment on the readability,

comprehensiveness, and accuracy of the questionnaire. After some changes, in the

second phase, questionnaire was sent to fifty-two CM professionals where a total of

thirty-five questionnaires were received without any changes. The Cronbach’s Alpha

coefficient was calculated to check the reliability of questionnaire by using internal

consistency method which is 0.91 after thirty-five responses. The questionnaire survey

was continued since the Cronbach Alpha of 0.7 and above conform the test of internal

consistency (Pallant, 2010) which means that the scale is free from any random error and

is reliable for research. The overall Cronbach Alpha coefficient is 0.904, is well above

the recommended value of 0.7 shows a high internal consistency between nineteen items

in the research questionnaire.

To facilitate respondents and improve the response rate, a web based questionnaire was

designed and the link was sent by email to all respondents. For high degree of legitimacy

of received data, judgemental sampling is used where only identified CM professionals

were contacted to provide their views on the issue. The received 187 questionnaires

were used for further analysis to establish the designed hypothesis. It is important to note

that the research participants targeted in this research were CM professionals from


6.3 Findings, analysis, and discussion

6.3.1 Descriptive statistics

Descriptive statistics is used to summarize a set of data by presenting the relationships

across multiple parameters. Unlike inferential statistics, descriptive statistics is used to

describe and summarize a set of data instead of studying the internal behaviour and

make inferences to generalize conclusions. Descriptive statistics uses combination of


200

numerical summaries and graphical techniques to present the behaviour of data for

measuring the required parameters.

In descriptive statistics the outputs are summarized in the form of statistical measures

e.g. mean, median, mode, variance, and standard deviation. The outputs can be viewed

both in the forms of tables or graphics (e.g. histogram etc.) which help researchers to

easily understand the general behaviour of the data. Descriptive statistics is used to

summarize information for the following outputs:

• Mean of the data

• Biographical details

• Qualification details

• Job Experience details

Descriptive statistics is used in combination with inferential statistics to highlight the

importance of specific parameters. The required information highlighted above are

presented in coming sections of this chapter and are not included here to avoid

repetition. Details of descriptive statistics are available in different sections i.e. mean of

the data is shown in section 6.3.1.1, biographical details in section 6.3.3.1.2,

qualification details in section 6.3.3.1.1, and job experience details in section 6.3.3.1.3.

6.3.1.1 Identification and prioritization of barriers to CM implementation

On the basis of literature review, an initial questionnaire (appendix A) where an open

ended question was asked about the barriers to CM application and semi structured

interviews, nineteen barriers are finalized which were further validated through the

second questionnaire survey (appendix C). Since configuration managers perceive the

existence of barriers to CM, in general, the responses highlight that these barriers are not

widespread and are more visible in aerospace sectors. It is understandably true and

validates my initial interview’s findings since it is believed that in industries like defence

where CM is being fully followed while its performance is monitored from the top

which is also obvious from the fact that majority of the CM standards have been issued


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from defence and hence suit their environment. It is observed that aerospace sectors

have rated the CM barriers more than any other business which means that there may be

more importance for CM issues.

The identified nineteen barriers is a combination of both previously highlighted and

newly identified barriers which are shown in table 6-1. The barriers presented in the

existing research studies (e.g. lack of management support, lack of training, lack of

communication, lack of resources, and lack of stakeholder’s support) are prevalent in

nature which are not only reflected in the literature of CM but also in other allied fields

like Knowledge Management and Quality Management. Some of the barriers (e.g. lack

of flexibility, extreme project pressures, lack of authority to implement CM principles,

poorly defined CM requirements and process, lack of CM awareness in Customer

worlds, and outdated CM process) are presented for the first time and will need special

consideration to address. Analysis of these barriers shows that most of the barriers are

closely related while some are considered the root cause for many other barriers e.g. lack

of training, lack of CM planning, lack of management support etc. and hence need extra

care to address.

Descriptive statistics is used to rank all nineteen barriers on the basis of their mean

values as shown in table 6-1 in descended order based on their mean values. The barriers

having the same mean values are ranked first based on their high marking as either

mostly or completely true received through the questionnaire survey. Even through some

of the barriers are at top while others at the bottom, but the most important aspect to note

is the mean values presented in table 6-1 which are very close to each other and suggest

that there are no major differences in the perception of professionals for these factors as

barriers to CM implementation.


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Table 6-1: Barriers to CM implementation

Symbol Barriers to CM implementation Mean Value

B3 Lack of CM training across organizations 3.41

B17 Lack of resources 3.39

B6 Lack of recognition and underestimating the importance of

CM at every level of organization 3.34

B16 Lack of effective CM tools 3.33

B7 Lack of career progression for CM professionals 3.33

B5 Implementation costs outweigh CM benefits 3.25

B19 Extreme projects pressures 3.25

B9 Lack of maintaining consistency in CM activities across

projects 3.20

B4 Lack of authority to implement CM principles / policies 3.19

B1 Lack of top management support 3.06

B18 Lack of support from stakeholders 3.02

B14 Lack of CM awareness in customer world 3.01

B15 Lack of effective communication 2.97

B13 Lack of CM process across the lifecycle 2.96

B2 Lack of centralized body for the governance of CM 2.94

B8 Poorly defined CM requirements and process 2.94

B12 Lack of current CM Plans 2.51

B10 Lack of flexibility in CM process 2.42

B11 Outdated CM process 2.36


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6.3.2 Factor analysis (categorization of the barriers to CM implementation)

Factor analysis is a data reduction technique which identifies and explores the inherent

relations among a large set of variables and summarize them into smaller sets of factors

based on their inherent relationship. Factor analysis is an ideal technique for reducing

various items into manageable frameworks (Norusis, 2008). Factor analysis can be used

in hypothesis testing or finding relationship within a group of variables (Bartholomew et

al., 2011).

One of the important methods of factors analysis i.e. principal component analysis; is

used to group the nineteen barriers into small sets of factors based on their inherent

relationship. Principal component analysis is mainly used in factor analysis where

original variables are transformed into smaller sets of linear combinations, with all of the

difference in variables being used as compared to other factor analysis approaches where

factors are estimated through mathematical model by only analysing the shared variance

(Pallant, 2010).

Kaiser-Meyer-Olkin Measure of Sampling Adequacy. .893

Bartlett's Test of Sphericity

Approx. Chi-Square 1456.152

df 171

Sig. .000

Table 6-2: KMO and Bartlett's Test results

It is essential to do some compulsory checks before choosing factor analysis. The first

and most important check is to have a large sample size. There is little agreement among

researchers on suitable sample size (Pallant, 2010) but according Tabachnick and Fidell

(2001) reliable results could be obtained in most cases if the sample size is 5 to 1 ratio:

i.e. 5 cases for each item to be factor analysed. Following a suitable sample size, it is

essential to confirm the suitability of data for factor analysis by using three mandatory

checks (Pallant, 2010). Firstly, inspection of the Pearson Product-Moment Correlation

Coefficient Matrix is important which revealed the presence of many coefficients of 0.3


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and above as shown in table 6-4. Secondly, the Bartlett’s Test of Sphericity which is

used to identify if variables are uncorrelated is significant [significance value needs to

less than 0.05 which is 0.000 (table 6-2) in this study]. Thirdly, the Kaiser-Meyer-Olkin

(KMO) value is 0.893 (table 6-2) which exceeds the recommended value of 0.6 meaning

that factor analysis is recommended for the sample data.

Principal component analysis (table 6-3) shows the presence of three components with

eigenvalues exceeding 1, presenting 36.919 %, 10.305 %, and 6.406 % of the variance

respectively. It is important to note the screeplot shown in figure 6-1 which highlights an

apparent break after the third component which suggests retaining three components for

further investigation i.e. managerial and organizational barriers, planning and process

barriers, and implementation barriers and are shown in figure 6-2. Since the Kaiser’s

criterion which recommends retaining of factors having eigenvalues of 1.0 or above and

Catell’s scree test which recommends retaining all factors above breaking in the plot as

shown in figure 6-1 (Pallant, 2010) confirm that the three-factor-model should be

adequate for my research analysis.

Figure 6-1: Screeplot, total variance associated with each barrier


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Co

mp

on

en

t

Initial Eigenvalues Extraction Sums of

Squared Loadings

Rotation Sums of Squared

Loadings

Total % of

Variance

Cumulative

%

Total % of

Variance

Cumulative

%

Total % of

Variance

Cumulative

%

1 7.015 36.919 36.919 7.015 36.919 36.919 3.953 20.808 20.808

2 1.958 10.305 47.224 1.958 10.305 47.224 3.154 16.600 37.407

3 1.217 6.406 53.631 1.217 6.406 53.631 3.082 16.223 53.631

4 .972 5.113 58.744

5 .918 4.832 63.576

6 .872 4.589 68.165

7 .730 3.845 72.009

8 .698 3.673 75.683

9 .642 3.378 79.061

10 .599 3.152 82.213

11 .530 2.791 85.004

12 .489 2.572 87.576

13 .409 2.154 89.729

14 .407 2.141 91.870

15 .370 1.949 93.819

16 .342 1.801 95.621

17 .309 1.628 97.249

18 .289 1.524 98.772

19 .233 1.228 100.000

Table 6-3: Total Variance Explained


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Figure 6-2: Three groups of barriers to CM implementation


207

B1 B2 B3 B4 B5 B6 B7 B8 B9 B10 B11 B12 B13 B14 B15 B16 B17 B18 B19

B1 1.000

B2 .461 1.000

B3 .622 .517 1.000

B4 .537 .505 .562 1.000

B5 .395 .440 .434 .529 1.000

B6 .571 .517 .585 .581 .621 1.000

B7 .272 .354 .369 .330 .358 .381 1.000

B8 .137 .315 .256 .363 .356 .340 .363 1.000

B9 .284 .380 .332 .315 .378 .372 .390 .631 1.000

B10 .175 .200 .239 .254 .217 .225 .200 .420 .386 1.000

B11 .182 .284 .336 .309 .275 .369 .284 .465 .326 .395 1.000

B12 .135 .293 .237 .283 .301 .261 .162 .467 .415 .398 .459 1.000

B13 .231 .336 .285 .155 .290 .299 .221 .376 .401 .408 .285 .438 1.000

B14 .189 .300 .215 .302 .366 .335 .213 .283 .253 .233 .297 .434 .328 1.000

B15 .166 .248 .205 .304 .200 .328 .255 .356 .397 .233 .302 .354 .218 .451 1.000

B16 .117 .171 .180 .137 .118 .160 .212 .247 .288 .376 .266 .236 .263 .312 .384 1.000

B17 .278 .290 .358 .259 .347 .320 .274 .348 .376 .278 .297 .303 .287 .323 .280 .464 1.000

B18 .233 .325 .354 .282 .376 .380 .396 .327 .350 .300 .287 .373 .355 .437 .418 .391 .556 1.000

B19 .230 .328 .302 .366 .324 .376 .257 .338 .393 .272 .258 .388 .371 .344 .362 .297 .453 .613 1.000

Table 6-4: Correlation matrix for CM barriers


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Group 1 Group 2 Group 3

B1 .789

B6 .781

B3 .773

B4 .751

B2 .666

B5 .658

B7 .439

B8 .770

B12 .675

B10 .663

B9 .634

B11 .633

B13 .547

B18 .778

B17 .680

B16 .672

B19 .643

B14 .560

B15 .560

Table 6-5: Group of matrix after Varimax rotation

Groups Eigenvalues Percentage of

Variance

Cumulative

Percentage of

Variance

1. Managerial and Organizational Barriers 7.015 36.919 36.919

2. Planning and Process Barriers 1.958 10.305 47.224

3. Implementation Barriers 1.217 6.406 53.631

Table 6-6: Final statistics of principle component analysis


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At the end, varimax rotation was applied on the data to present the loadings pattern of all

nineteen factors in three groups for easy interpretation. The data in table 6-5 shows that

extracted data after Varimax rotation is consistent where each of the barriers weighs

heavily on only one of the three groups and hence verified the decision of maintaining

only three groups of factors. The final statistics of Principle Component Analysis after

Varimax rotation in table 6-6 show that the three factors extracted comprise 53.631 % of

the variance.

6.3.3 Inferential statistic

Inferential statistics, also called statistical induction are used to draw conclusion about

the whole population by studying the internal behaviour of a sample. Unlike descriptive

statistics which describe and summarize the actual data, inferential statistics is used to

make inferences from the same data to a more generalized condition. Inferential

statistics are mostly used to test some hypothesis. These hypothesises are usually

established to find similarities or differences between groups or factors on the basis of

internal behaviour of the data.

Choosing the right statistical technique for the analysis of data is the most difficult part

for any research (Pallant, 2010). This is mainly because of the unavailability of any

universal decision tree to help researcher to choose the right statistical test (Kinnear,

2000) and the variations in the types of research studies. Selecting the right statistical

tests mainly depends on the type of research questions, the included scale in

questionnaire, the variables to be analysed, the assumptions met by the data for specific

statistical techniques, and the nature of data itself (Pallant, 2010).

There are two types of statistical techniques (i.e. parametric and non-parametric) which

can be used to investigate the hypothesis as outlined in section 6.1. The selection of the

right statistical technique between the two is based on some important assumptions.

Violation of these assumptions has substantial effects on the final outputs (Erceg-Hurn

and Mirosevich 2008). Parametric tests are used if the data is normally distributed and


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present homogeneity of variance or homoscedasticity i.e. population with similar

variance (Erceg-Hurn and Mirosevich, 2008) while non-parametric tests do not make

assumptions about the population distribution whether they are normal or not (Motulsky,

1995). Parametric test should be used if one is sure that the data are sampled from

population that follows a normal / gaussian distribution otherwise use a non-parametric

test if the data is ranked or discreet (usually the case with Likert scale) and the

population is not normally distributed and some values are "off the scale," that is, too

high or too low to measure (Motulsky 1995). Parametric tests are more powerful

statistical tests and are preferred by most of the researchers because of the detailed

outputs but are ignored because of its stringent assumptions regarding the data while

nonparametric tests, on the other hand, do not make such assumptions but do not provide

the full details of the inherent characteristics of the data.

Non-parametric tests i.e. Mann-Whitney-U and Kruskal Wallis tests are carried out to

analyze participant perceptions based on their academic education, gender differences,

CM experience, and types of organization on three groups of CM barriers because the

data has not fulfilled the stringent requirements of parametric tests.. Mann-Whitney-U

and Kruskal Wallis Tests gives reliable results if the data is not normally distributed

(Pallant, 2010) or the data received is ranked or discreet (usually the case with Likert

scale) (Motulsky, 1995). Following is the detailed discussion on why Mann-Whitney-U

and Kruskal Wallis tests are used for the analysis of data?

i. The data has not fulfilled the assumption of normality which is usually checked

by the tests for normality where two types of test can be used i.e. Kolmogorov-

Smirnov Test (when the sample size is greater than 50) and Shapiro-Wilk Test (if

the sample size is smaller then 50). The principle for the data to be normally

distributed is if the significance value is greater than 0.05; which has been

violated by the data as shown in table 6-7, hence the nonparametric test has been

chosen for the analysis of data.


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ii. Non-parametric techniques have been chosen as the data obtained was ordinal

i.e. ranked or discreet (Motulsky, 1995).



G-1 .121 187 .000 .967 187 .000

G-2 .081 187 .005 .984 187 .032

G-3 .096 187 .000 .979 187 .007

Group Average .075 187 .012 .989 187 .170


Since the data is ranked or discreet and is not normally distributed hence non-parametric

tests i.e. Mann-Whitney-U and Kruskal Wallis tests are used for data analysis. Mann-

Whitney-U and Kruskal Wallis tests are used to investigate the effects of categorical

variables (academic education, gender difference, CM experience, and typology of

organization) on perception of CM practitioners while identifying continuous variables

(nineteen barriers as highlighted in table 6-1).

6.3.3.1 Participants perceptions regarding barriers to CM implementation

Mann-Whitney-U and Kruskal Wallis tests are used out to analyze participant

perceptions based on their gender differences, CM experience, academic education, and

types of organization on three groups of CM barriers. These tests (Mann-Whitney-U and

Kruskal Wallis) are non-parametric which gives reliable results if the data is not

normally distributed (Pallant, 2010) or the received data is discreet or ranked (Motulsky,

1995). Since the data is discreet or ranked and also not normally distributed [since the

sig. value is zero for all three groups (table 6-7)] hence Mann-Whitney-U and Kruskal


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Wallis tests are used for inferential statistics. Detailed analysis on the subject is given in

the following four sections.

6.3.3.1.1 Effects of academic qualification on participants perceptions while

identifying barriers to CM implementation

Kruskal Wallis test is used to determine any significant difference in the perception of

participants based on their academic qualification. The results obtained by using SPSS

are presented in table 6-8 shows that Asymp. Sig. for each of the three groups and its

group-average is more than 0.05, meaning that there is no significant differences in

perception of CM practitioners based of their academic qualification hence we reject the

hypothesis as outlined in section 6.1 for academic qualification.

Group G-1 G-2 G-3 Groups-Avg

Asymp. Sig. 0.106 0.704 0.683 0.558

Table 6-8: Significance of barriers to CM implementation with academic qualification

The outputs in table 6-8 could be further explained with the help of their mean rank

values (table 6-9) generated by the same test. In the case of significance, the difference

between the mean rank values is greater and the parameter having greater mean rank

value shows its importance over other parameters. Since there is no significant

difference in the perception of CM professionals on the basis of their academic

qualification, the mean rank values of the four groups (having PhD degrees, master

degrees, bachelor degrees, and HND/HNC) as shown in table 6-9 are quite close to each

other hence justify the previous result highlighted above.


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Academic Qualification N Mean Rank

Groups-Avg

HND / HNC 25 71.26

Bachelor degree 79 76.23

Master degree 50 85.53

Doctorate degree 2 82.75

Table 6-9: Mean Rank for academic qualification

6.3.3.1.2 Effects of gender differences on participants perceptions while


We know that significant difference in the perception of CM professional on the basis of

their gender differences will present if the significance value obtained from Mann-

Whitney-U test is less than 0.05. The significance values for all the three groups and

their group-average is shown in table 6-10 which are greater than 0.05, meaning that

there is no significant difference in the perception of CM professionals based on their

gender differences in identifying and rating the barriers to CM implementation. Based

on these results we reject the hypothesis as outlined in section 6.1.


Asymp. Sig. 0.508 0.971 0.757 0.990

Table 6-10: Significance of barriers to CM implementation with gender differences

The outputs in table 6-10 can be further explained with the help of mean rank values

generated by the same test and are shown in table 6-11. The mean rank values for both

male (93.97) and female (94.08) are quite close to each other which justify the results as

presented in table 6-10 and hence we reject the hypothesis as outlined in section 6.1 for

gender differences.


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Gender N Mean Rank

Groups-Avg

Male 134 93.97

Female 53 94.08

Table 6-11: Mean Rank for gender differences

6.3.3.1.3 Effects of CM experience on participants perceptions while identify

barriers to CM implementation

Kruskal-Wallis Test is applied to find the significance of CM experience on the

participant’s perception while identifying barriers to CM implementation. The output of

Kruskal-Wallis test is presented in table 6-12 which shows that the significance value for

all the three groups and groups-average are greater than 0.05 hence we can say that there

is a no statistical significant difference in the perception of CM professions to identify

and rank barriers to CM implementation on their previous experience in CM. On the

basis of these results we reject the hypothesis outlined in section 6.1 for experience in

CM.


Asymp. Sig. 0.105 0.794 0.118 0.911

Table 6-12: Significance of barriers to CM implementation with CM experience

For more explanation, the mean ranks for the groups-average is presented in table 6-13.

As we know that when the significance values are more than 0.05, the difference

between the mean ranks within sub-groups will not be significantly different and is

proved by the results as shown in table 6-13.


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CM Experience N Mean

Rank

Groups-Avg




15 Years or Above 71 91.75

Table 6-13: Mean Rank for CM experience

6.3.3.1.4 Effects of typology of organization on participants perceptions while


The significance of organizations types on participant’s perception is found with the

help of significance values by using Kruskal-Wallis test. The results of Kruskal-Wallis

test is shown in table 6-14 where the significance values for all three groups and its

groups-average is less than 0.05 which represent a statistical significant difference in the

perception of practitioner’s views on barriers to CM implementation. On the basis of

these results i accept the hypothesis outlined in section 6.1 for the types of organizations

which means that CM professionals in different organizations view these barriers

differently from each other.


Asymp. Sig. 0.002 0.043 0.004 0.003

Table 6-14: Significance of barriers to CM implementation with organizational types

This is further explained with the help of mean rank values generated by the same test

which are shown in table 6-15. Since the significance values in table 6-14 are less than

0.05 hence a significant difference can be seen in the mean rank values between defence


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and aerospace sectors for all the three groups and its group average. The mean rank

values for aerospace industries are more than those of defence industries which means

that aerospace sectors are facing more problems in the implementation of CM

applications than those of defence industries. This looks true since CM is religiously

practiced in defence industries whereas CM is not only initiated from defence sectors but

also most of the standards in the fields are also initiated from defence sectors.

Organizational types N Mean Rank

G-1

Aerospace 106 106.32

Defence 78 76.79

G-2


Defence 78 84.64

G-3


Defence 78 77.36

Groups-Avg Aerospace 106 105.92

Defence 78 77.34

Table 6-15: Mean Rank for organizational types

6.3.4 Interpretation of CM barriers groups

It is important to discuss the effects of highlighted nineteen barriers in the preview of

literature and semi-structured interviews conducted with CM professionals. The

discussion is presented in the following three sections.

6.3.4.1 Group 1: Managerial and organizational barriers

Managerial and organizational barriers includes seven barriers i.e. lack of top

management support, lack of centralized body for the governance of CM, lack of CM


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training across organizations, lack of authority to implement CM principles / policies,

implementation costs outweigh CM benefits, lack of recognition and underestimating the

importance of CM at every level of the organization, and lack of career progression for

CM professionals.

B1: It is believed that management doesn’t understand the role, significance and

criticality of the CM process and hence do not fully support it. This looks true after its

repeated evidence as barrier in this research and is also considered a root cause for many

other barriers. On one side, it is believed that management support could play an

essential role in establishing CM as a core business process (Guess, 2006) but on the

other hand lack of management support is considered a major concern towards CM

application (Gonzalez and Zaalouk, 1997; Burgess et al., 2005). Lack of management

support is one of the major issues for any business process management (Da-Silva,

2012).

B2: It is believed that decentralization has badly affected the implementation of CM

across different industries. There are few organisations having a senior manager with

CM specific responsibility but in majority CM is often considered a secondary role

(Burgess et al., 2003). It is also observed that project teams often have different

approaches towards CM application which is the main reason for inconsistent process

across the organisation. Since projects are often multi-disciplinary activities which cross

many boundaries, specific projects develop their own project related CM strategies and

procedures (PMI, 2007). This approach has split the CM practices across the

organization and instead of one common practice we can often observe a diluted view of

the process. The notion of Project Based CM has become increasingly popular in the

past where, in fact, PMI have been quite open in their definition of project versus

domain specific CM (PMI, 2007). This has created difficulty for those project managers

who are trying to maintain a high level of control over the ‘Configuration Items’ within

his / her project. In such situations, it is tough to combine all related policies and ensure

harmonization of the CM process across the project. It is believed that in organizations

like aerospace and defence, centralized CM setup is more suitable which ensure the


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implementation of single guidelines and minimizes the dilution of the CM practices

across projects.

B3: Lack of training is one of the core issues to any business process management

(Da-Silva, 2012) and is considered a serious concern for the effective implementation

CM process (Burgess et al., 2005; Fowler, 1996). It has been highlighted in the first part

of this research presented in Chapter 4 that professional having CM certification and

training understand the limitations of the CM process and play a vital part in its overall

implementation. It is believed that CM should be part of the organizational training

programme to ensure that individuals have a high level of understanding of the use and

advantages of the CM process. It is always remained an issue in most of the allied fields

which could play an important role for organizational development and success.

B4: It is believed that project managers can undermine CM principles by not

following the process and believe that they can control their projects without CM

assistance (PMI, 2007). It has been observed that often PM manages change through a

project change board but not a domain specific CM change control board which is one of

the reasons which allow project managers a room to implement their own concepts of

the process. In theory CM managers are the sole owners the CM process but in reality

they are just custodians and have no authority in the decision making process. It is a

major issue since lack of authority to implement CM specific tasks creates risk to poor

quality processes which are responsible for poor quality deliverables.

B5: One of the weak areas in the limited CM literature is the lack of research on cost

versus benefit analysis which can answer the highly cited problem identified as

‘implementation cost outweighs CM benefits’. It is a major concern since CM is often

not realistically followed and ignored in companies because of the overall cost related to

the specialized CM process (Burgess et al., 2003) just like Quality Management was

ignored in the past (Bhat and Rajashekhar, 2009). There might be many reasons behind

this problem but the most obvious is the lack of CM training and education where CM is

not only neglected by academia but also by organizations which have limited the


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knowledge on CM benefits across organization and its role in reducing product

development time, reducing cost and increasing the overall quality of products.

B6: Ownership of the CM process and commitment to its implementation are major

concerns in organizations (Fowler, 1996). It is understandably true to observe lack of

recognition and underestimating the importance of CM within organizations in the

presence of lack of centralized body for the governance of CM, lack of management

support and lack of authority to implement CM. It is highlighted by interview

participants that CM is just tolerated but not embraced since top management doesn’t

understand its role while some managers believe that they can control their products

without CM applications. CM is only seen a necessary evil and has no importance within

facilities until something really goes wrong.

B7: Lack of career progression is considered a major failing for developing CM as a

process (Burgess et al., 2005) is directly linked with poor recognition of the CM process

and instigated by lack of education and training across organizations. It is believed that

retaining talented human resource which is an essential requirement for the effective

implementation of any process is really difficult in fields with no career progression.

6.3.4.2 Group 2: Planning and process barriers

The planning and process barriers group consist of six barriers i.e. poorly defined CM

requirements and process, lack of maintaining consistency in CM practices across

projects, lack of flexibility in CM process, outdated CM process, lack of current CM

plans, and lack of CM process across the lifecycle.

B8: It is highlighted that CM guidelines are not fully understood by functional

stakeholders and hence not implemented at different levels of organization. It is

observed that the available standards lack some important explanation and are quite

complex and hence needs special attention to improve such standards and make it more

user friendly. It is difficult to implement a successful CM process if the boundaries are


220

unclear, having a vague role, and its benefits are not accepted across organization. In

these conditions it is right to observe multiple issues e.g. considerable mistakes in data

interpretation, inadequate workflow design and cumbersome and voluminous change

implementation methodologies.

B9: It is believed that lack of communication, lack of proper CM planning, lack of

centralized body for the governance of CM, and lack of authority to implement the CM

process are the main causes behind maintaining consistency in CM application across

projects. It has been pointed by interview participants that organizations have little or no

legislative requirements for CM and instead of having one common CM process,

projects tends to adopt project specific CM practices which often resulting in a diluted

view of the process. It is harmonization of the CM process which highlights maintaining

consistency in CM practices across organization (PMI, 2007) and is a major concern

across aerospace and defence industries.

B10: It is believed that since CM policies are quite rigid and inflexible and irritates

users hence not effectively followed in industries. According to research participants of

this research, lack of flexibility is a major risk for overall CM effectiveness. It is

believed that CM policies needs to have balance of this concept because when the

process is too flexible and then made tighter, it becomes very difficult to implement due

to different project requirements. It is already highlighted in the first part of this research

presented in Chapter 4 that requirements of complex projects (e.g. space shuttle) cannot

be matched with small and simple products (e.g. ball point pens), hence CM process

should not be rigid and users may offer a room of flexibility to adopt CM requirements

according to the nature of the products.

B11: It is highlighted that CM standards have remained unchanged for many years and

possibly never aligned with other processes which are updated with time to deal with

technological advancements. Since many of these standards are either not clear or lack

explanation and hence needs amendments to inline them with new ideas and concepts. It


221

is also quoted by research participants that some of the standards give references to

specific templates which are never used.

B12: CM planning builds on the foundation established by an enterprise for similar

products (EIA-649, 2011) and is termed as the backbone of the CM process (Lyon,

2008). It has major contribution in productivity and effectiveness of projects and plays

an important role in the overall success of projects (Sachs, 2009). It is believed that CM

plans are often unavailable / not effectively generated / not updated across different

phases of the projects and hence create difficulty in the implementation of CM activities.

The implementation of CM planning is quite weak in industries and the level of

motivation of companies towards CM planning can be found from the fact that out of 72

% of the companies having CM plans; only 41 % of the companies refer to those plans

(Burgess et al., 2003).

B13: The late involvement of CM in the project or product lifecycle is also considered

a major cause for not fully implementing the CM process across projects. It is pointed

out by the research participants that CM practices are missing most of the time in

concept, allocation, and maintenance or modification phases of the projects which might

be the result of multiple uncertainties in the project life cycle. Since most of the

standards have no detailed CM guidelines related to maintenance / modification phase

which might be a reason for its ignorance.

6.3.4.3 Group 3: Implementation barriers

The third group of CM barriers is formed with the combination of six factors i.e. lack of

CM awareness in customer world, lack of effective communication, lack of effective

CM tools, lack of resources, lack of support from stakeholders, and extreme project

pressures.

B14: CM facilitates customers by ensuring their requirements throughout product-life-

cycle and assures quality of their products. Even with increase of knowledge and


222

peoples understanding of managing their product requirements, there is still a lack of

CM awareness in the customers. It is pointed out by many research participants that

many customers are unaware of the importance of CM which could ensure the

development and production of quality products against their requirements.

B15: It is very difficult to deny the significance of communication in every filed

across the projects or industries. Lack of communication is a major concern in dealing

with engineering changes (Huang and Mak, 1999) because it is believed that 40 % of

time in the implementation of configuration changes could be reduced through effective

communication (Tavcar and Duhovnik, 2005; Wasmer et al., 2011) whereas two thirds

of the changes could be avoided through improved communication strategies because

failure in this area could result number of changes through decisions on obsolete data

(Jarratt et al., 2011).

B16: Availability of suitable software tools which has got much attention over the last

few years is one of the important subjects for industries. These tools have improved

individual capabilities in work and helped organizations with enhanced data and

information (Cantamessa et al., 2012) but the most of them are not user friendly (Guess,

2006). It is believed that lack of CM knowledge involved in the design and development

of these tools and lack of standardization of the CM practices are the main reasons for

the uncertain behaviours of these tools in different environments. It is essential to have a

standardized body of knowledge to establish an agreed CM boundary and come-up with

uniform practices at lowest levels of the process.

B17: Lack of sufficient resource is a major issue in the implementation of CM

(Gonzalez and Zaalouk, 1997) and is also reflected a major concern in other allied fields

(e.g. Anthony and Desai, 2009; Bhat and Rajashekhar, 2009; Sebastianelli and Tamimi,

2003; Riege, 2005). The most apparent obstacle in terms of resources for CM

implementation is the lack of human resources which is often connected with lack of

funds. It is pointed out by research participants that CM is always under resourced in

comparison with other design and development activities.


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B18: Support from stakeholders plays a vital part in the implementation of CM which

is obvious from its established role pointed out by Watts (2008) and Watts (2010) as

‘CM is the communication bridge between design engineering and the rest of world’.

Lack of commitment badly influence the communication process among stakeholders

and has a huge effect on the implementation of CM process. It is also referred as a major

barrier by Huang and Mak (1999) that change management- an important part of the CM

process - has not received the due importance and support from stakeholders.

B19: It is highlighted by research participants that many project managers don’t stick

to centralized CM guidelines and either bypasses them or follow project specific variants

of them to achieve their shot-term goals. It is believed that ‘extreme project pressures’

which is termed as a barrier is not supposed to be a barrier in the presence of a well

defined and flexible CM process. It is a barrier only because the significance of this

process is not understood which often causes failure to the process.


6.4.1 Summary

The main objective of this research is to identify the barriers associated with managing

CM application, prioritize them with the help of differential statistics, categorize them

into more manageable groups of factors through factor analysis, and analyse the effects

of multiple factors e.g. academic education, gender differences, CM experience and

types of organization on the perception of CM professionals in the process of

identification and rating these factors through inferential statistics.

This part of the research is based on survey research strategy. A questionnaire survey

was conducted to validate the findings and verify the established hypothesis. The

questionnaire was divided in two parts. The first part was related to general information

whereas the second part was related to barriers to CM implementation where

respondent’s opinions were asked on a series of statements. Respondents of the


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questionnaire survey were asked to mark trueness of each statement based on their

organization by using a five-point scale (1 = not at all true, 2 = slightly true, 3 =

somewhat true, 4 = mostly true, 5 = completely true). A web based questionnaire was

designed and the link was sent by email to all respondents. To maintain high degree of

legitimacy of received data, judgemental sampling is used where only identified CM

professionals were contacted to provide their views on the issue.

On the basis of descriptive statistics all nineteen barriers were retained as barriers to CM

implementation on the basis of their mean rank values (table 6-1). Factor analysis is used

to group the nineteen barriers into small sets of factors based on their inherent

relationship followed by varimax rotation. Three groups (managerial and organizational

barriers, implementation barriers, and planning and process barriers) are extracted with

the help of factor analysis. Inferential statistics is applied to determine the effects of

different parameters (academic education, gender difference, CM experience, and

typology of organization) on barriers to CM implementation. Nonparametric tests

(Mann-Whitney-U and Kruskal Wallis Tests) are used to find the significance of these

four parameters on barriers to CM implementation. The results shows (since the

significance values are less than 0.05) that professional’s from different organizations

perceive the barriers differently in their setups hence we accept the hypothesis for types

of organization. Since the significance value for other parameters i.e. academic

education, gender differences, and CM experience is greater than 0.05, meaning that no

differences exist in the perceptions of CM professionals on CM barriers based on these

parameters hence we reject the hypothesis for all these parameters as highlighted in

section 6.1.

6.4.2 Conclusions

This study was conducted to finalize and prioritize barriers to effective implementation

of Configuration Management process in both aerospace and defence industries. All

nineteen barriers identified through the first part questionnaire and second part

interviews are retained and further extracted through factor analysis into three groups


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(managerial and organizational barriers, planning and process barriers, and

implementation barriers) based on their inherent relationship to facilitate professionals in

targeting specific areas for improvements. Emphasis is made to reveal any significant

differences in the perceptions of CM practitioners on the basis of their gender, academic

qualification, CM experience, or types of organization. Since configuration managers

believe the existence of these barriers in both aerospace and defence industries, in

general, the responses highlight that these barriers are more obvious in the aerospace

industry as compared to defence. This is further validated through the use of inferential

statistics where significant difference is found in the perception of CM professionals on

the basis of their organizations.

The research results are quite significant since it highlights barriers related to areas such

as governance, management support, principles and policies, training, authority to

implement, planning, communication, stakeholders support and resource requirements

which are not only considered the most significant factors for the successful

implementation of Configuration Management highlighted in the first part of the

research presented in Chapter 4 but also for other allied fields such as Project

Management (e.g. Fortune and White, 2006; Belassi and Tukel, 1996), and Knowledge

Management (e.g. Wong, 2005).

It is believed that these barriers have affected the organizational image of the process

and effected the overall implementation of the process over the years. These barriers

require special attention since it is evident that some of the barriers which are believed to

be the root cause for many other obstacles may considerably affect the implementation

of the CM. It is believed that effective training programmes across the organization will

not only facilitate to achieve the required support from top management but may also

help to reduce the lack of recognition and perceived importance of the CM process

across the organization. It is also obvious that effective CM planning may take control

on other aspects like lack of maintaining consistency in CM practices across the projects

and lack of flexibility in CM practices which needs special emphasis. Most importantly,

organizations should to give special consideration to these obstacles and target their


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areas of weakness and set-up their action based strategy to provide focussed and value

added solutions.

There is a growing body of knowledge evolving in CM in the form of new or revised

standards. This programme will surely be slowed down if organisations fail to identify

barriers to their process prior to their attempt to meet the requirements of such

documents. It is important to take note of the factors identified in Chapter 4 which

provides baseline guidelines on the CM process improvements methodologies in the

form of activity model specific to CM which if properly understood and followed could

help in the elimination of such barriers.

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CHAPTER 7

CONFIGURATION MANAGEMENT MATURITY MODEL

7.0 Introduction

This chapter highlights fundamental aspects of a Configuration Management Maturity

Model (CMMM) which is developed through continuous interaction with Configuration

Management professionals from December 2012 to November 2013. The importance of

maturity as a concept could be seen through extensive literature in multiple fields such

as Software Engineering (e.g. Bate et al, 1995; Paulk et al., 1993; Team, 2006), Project

Management (e.g. Crawford, 2006; Jugdev and Thomas, 2002; Kwak and Ibbs, 2002),

Risk Management (e.g. Hillson, 1997; Yeo and Ren, 2008), Requirements Engineering

(e.g. Beecham et al., 2005b), safety (e.g. Filho et. al., 2010), Knowledge Management

(e.g. Kulkarni and Freeze, 2004; Paulzen and Perc, 2002) IT (Gottschalk and Solli-

Sæther, 2006) and Configuration Management for medical device industries (McCaffery

and Coleman, 2007) etc. Configuration Management is a major process area in the

Capability Maturity Model for Software (Paulk et. al., 1993), Systems Engineering

Capability Model (Bate et al, 1995), and Capability Maturing Model Integration (Team,

2006). The other such model is that of McCaffery and Coleman, (2007) which is specific

to medical device industries and is adopted from the concept of maturity model

integration (i.e. Team, 2006). It is important to note that these studies are similar in

nature, lack important information, and are based on what to implement instead of how

to implement (Jugdev and Thomas, 2002; Niazi et al., 2005).

Recent studies on maturity models have changed the traditional concept of developing

such models. Andersen and Jessen, (2003) developed a model for projects maturity in

organization based on attitude, knowledge, and actions parameters while describing

organizational maturity into three layers i.e. Project, Programe, and Portfolio

Management. Niazi et al. (2005) emphasised on the identification of critical success

Chapter 7: Configuration Management Maturity Model

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factors and critical barriers while generating maturity model for software process

improvements and Yeo and Ren (2008) emphasised on process capabilities which are

based on the critical success factors and barrier to process implementation. The study of

Beecham and Rainer, (2005b) introduced Requirements Process Improvements Model

based on previous literature and problems highlited by professionals through forty-five

focused groups in the software development process. These studies have given a new

dimension to further research in the field.

The objective of this research is to integrate CM Critical Success Factors and Barriers to

develop a maturity model for the improvement of CM practices in aerospace and

defence organizations. It is important to note that an incremental approach has been

followed to mature the CM process through this maturity model. Each level represents a

set of capabilities which would help in proceeding to the next higher level of maturity.

Through a survey based research strategy, views of CM professionals were obtained

through semi-structured interviews and organized questionnaire to capture the different

aspects of maturity concept.

Note: It is important to mention that some materials presented in this Chapter are also

published in my following publication.

• Ali, U., Kidd, C. (2013). Configuration Management Process Capabilities. Procedia

CIRP, 11, 169-172.

7.1 Research Objective

The objective was to develop Configuration Management Maturity Model to ensure

effective implementation and continuous development of Configuration Management

process within aerospace and defence industries. The CMMM is based on critical

success factors, barriers to Configuration Management implementation, and expert

opinion of Configuration Management professionals obtained through unstructured

interviews. It was essential to see the implementation of Configuration Management


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process both in aerospace and defence industries and investigate the following

hypothesis.

Hypothesis: There is a significant difference in the maturity levels between


7.2 Research Methodology

The pre-existing body of knowledge plays a vital role in research by providing important

information and forms the foundation for further research. Some research studies are

non-empirical in nature and are based on reviewing and analysing existing literature

(Guo and Sheffield, 2008; Veal, 2006) while others are empirical which involves the

collection and analysis of new data - quantitative or qualitative (Veal, 2006) and is

mostly based on observation or experience (Hussey, 1997). This research is based on

semi-structured interviews and questionnaire surveys which are part of the qualitative

and quantitative research methodology respectively (Ghauri & Gronhaug, 2005) and

critical analysis of the available literature especially the studies on critical success

factors and barriers in the field.

Thorough review of the literature in other allied fields on Critical Success Factors,

barriers, and maturity models in general while the critical success factors highlighted in

Chapter 4, barriers to CM implementation presented in Chapters 5 and 6, and studies of

Niazi et al. (2005) and Yeo and Ren (2008) in particular helped to identify Configuration

Management process capabilities and framing the Configuration Management Maturity

Model. Through semi-structured interviews with six Configuration Management

professionals working in four different aerospace and defence industries helped us to

finalize ten Configuration Management process capabilities explained with the help of

thirty-five processes, structuring of the Configuration Management Maturity Model, and

finalization of the measuring mechanism for the maturity of Configuration Management

practices by using the newly developed Configuration Management Maturity Model. It

is essential to note that each interview was recorded for later analysis.


230

Because of the limited number of interviews and the problems with arranging further

interviews, it was decided to validate the developed Configuration Management

Maturity Model through a questionnaire survey and get the views of CM professionals

on the validity of the developed model. A questionnaire (Appendix E) was developed in

three sections to validate the multiple aspects of the developed model. The first section

having six questions was related to background information whereas the second section

constitutes explanation of the maturity model under four different heading. The third and

last section includes seventeen statements which are required to be measured through a

Likert-type scale running from 1 (strongly disagree) to 5 (strongly agree) to validate the

Configuration Management Maturity Model. It is important to note that the target

population was Configuration Management professionals working in different aerospace

and defence industries. A total of 50 responses were received which are used for the

final analysis.

It was necessary to test the maturity concept and the application of thirty-five practices

(constructs) which build the maturity questionnaire since the maturity of Configuration

Management process will be measured through these thirty-five practices on the same

four point scale. With the addition of six questions at the start to collect general

information for the analysis of data to discuss the designed hypothesis, the second

questionnaire on Configuration Management process maturity (Appendix F) was

circulated to Configuration Management professionals primarily to test the maturity

questionnaire and the concept of maturation. A total of 52 responses were received

which are used for the final analysis.

7.3 Configuration Management Maturity Model

The Configuration Management Maturity Model is based on key process capabilities

necessary for the effective implementation and continuous development of

Configuration Management activities. The finalized ten process capabilities are grouped

in four groups which forms the four levels of Configuration Management Maturity

Model. The level of maturity from one level to the next higher level correlates to


231

specific goals at the higher levels. The accomplishment of each goal depends on the

effective adaptation of key process capabilities which can be measured through thirty-

five key practices (constructs) on a four point scale. These steps are fully elaborated in

the following sections which provide the necessary foundation for understanding the

Configuration Management Maturity Model.

7.3.1 Identification of key process capabilities

It is important to highlight the study of Yeo and Ren (2008) which emphasizes the

identification of key process capabilities extracted from critical success factors and

barriers while developing a maturity model specific to risk management. The process

capabilities ensure to avoid the possible risks and helps in achieving the desired

objectives. The key capabilities for Configuration Management are finalized by critically

analysing the data obtained from the study on critical success factors highlighted in

Chapter 4 and barriers to CM implementation presented in Chapters 5 and 6 and semi

structured interviews with Configuration Management professionals from aerospace and

defence industries. The comprehensive coverage of Configuration Management

requirements in the form of key process capabilities is highlighted by almost all research

participants.

The completeness of the factors could be seen from the statement as ‘Most of the key

elements, I think, that you have got links to all the effective requirements; behind all

those, I would like to see in the execution policies, I assume that there would be

standards like government standards, EIA standards’ [sic] It is important to note that

some of the process capabilities are the composition of many other factors (critical

success factors or barriers) which are grouped based on their inherent relationships. The

list of ten key capabilities for the implementation and continuous development of

Configuration Management practices are show in figure 7-1.


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Figure 7-1: Configuration Management process capabilities


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7.3.2 Establishing goals

There are two dimensions of this issue; the general goals related to the development of

Configuration Management Maturity Model and specific goals associated with each

maturity level. The general goals are:

• To provide a systematic path of sophistication for assessing the current practices of

Configuration Management within aerospace and defence sectors.

• To provide a roadmap on how to evolve the Configuration Management capabilities

to achieve the overall objectives.

• To provide common grounds of communication for Configuration Management

practitioners with functional stakeholders.

• To provide a platform to adopt the critical success factors and avoid barriers to

Configuration Management applications.

It is essential to get answers on ‘how’ to achieve these general goals. This needs specific

gaols related to each maturity level and have limited scope based on particular

capabilities. Specific goals help in achieving the general goals and hence results in

achieving the overall objectives. The specific goals are:

• The CM practices are formalized which fulfil project specific requirements

• The CM practices are standardized having favourable implementation environment

• The CM practices are fully implemented, reviewed, and continuously improved

7.3.3 Composition of CMMM

The CMMM has four levels (figure 7-2) with lowest maturity at level 1 corresponds to

‘static’ while highest maturity at level 4 corresponds to ‘dynamic’. These levels play an

important role in assessing maturity since it is based on key capabilities and expert

opinions from CM professionals. The model has all key characteristics necessary for the

implementation and continuous improvement of a process highlighted by recent research


234

studies on the issue (e.g. Team, 2006; Niazi et al., 2005; Strutt et al., 2006; and Yeo and

Ren, 2008). This is an action based model having the concept of both single and double

loop learning (Argirys and Schön, 1978) whereas in single loop learning errors are

detected and corrected while double loop learning is the name of continuous

improvements methodologies where errors are detected and corrected with modifications

in organization's policies to eradicate the root cause.

Figure 7-2: Configuration Management Maturity Model

The first level of CMMM is based on execution policies which are not actively

practiced. Since there is a lack of management support and knowledge of the process

across organizations, the process does not receive the due importance and is not actively


235

supported by stakeholders. The process is more formalized and is backed by experienced

professionals and staff with required resources at level 2 but is more confined and has

limited interaction with functional stakeholders across organization. The process is

reactive due to lack of communication and acceptance by the stakeholders. The process

is more proactive but still open loop at level 3 where stakeholders are involved in the

implementation process through continuous education programmes. The process is more

dynamic at level 4 through double loop learning where continuous improvements

strategies are in place to upgrade the process according to the changing demands of the

environment. Detailed description of each maturity level is given in the following

sections.

Level 1: Static. This level is characterized by little or no maturity where CM is not

properly understand and practiced. There is no organized and systematic approach to

implement the process due to absence of any organized body for the governance of CM

and limited support from senior management. The lack of recognition and importance of

the process is evident across organization mainly due to limited understanding of the

process which is mainly caused by inadequate training programmes throughout the

organization. The process exists not because of proven practices but because of the

competence and heroics of individuals.

Level 2: Reactive. This stage emphasises on team building and improving its

organizational strength. The process is organized through defined CM standards and is

formally implemented by dedicated group of CM professionals. Since training and

education is limited to CM professionals, there is a lack of recognition and importance

of the process across the organization. This lack of awareness effect organizational

support and intensify unfavourable environment which limit the outcomes in terms of

implementation. The Configuration Management plans are available and are forced to

implement but is largely opposed or ignored by functional stakeholders because they

still don’t own the process. The process is well implemented in some projects but its

holistic implementation across the projects or organization is limited.


236

Level 3: Proactive. The proactive maturity level exercise both resources and supportive

environment to plan and execute the CM process for maximum outputs. The

standardized CM process fulfils the requirements of all projects and is part of the

documented organizational policies. The CM process does receive recognition and

support from functional stakeholders through management backing and effective

training programmes across the organization. Through effective communication and

focused teamwork, everyone contributes to the process irrespective of political and

cultural barriers. The process is managed at vendor’s premises and ensures involvement

of customers in the development process to validate their requirements before producing

final product. Even in the presence of all these positives, the process is still running on

open-loop learning mechanism where emphasis is made on problem solving instead to

investigate and eliminate the root cause of the problems and hence have issues like

consistency, flexibility, and cost effectiveness of the CM methodologies.

Level 4: Dynamic. This level is dedicated to continuous improvement of CM practices

with the help of supportive environment. Process improvement methodologies are

established, monitored, and revised to satisfy the technological advancement and remove

inadequacies arising with time. The CM process conforms to the latest standards on CM

and is holistically implemented across organization. Through strong coordination with

functional stakeholders and inducing the required consistencies and flexibilities in

policies, project pressures are absorbed and the process is sustained and implemented

through all phases of the project life cycle. Performance of the process is monitored

though CM system audits conducted round the year on multiple projects and suggested

improvements are implemented. With the help of the double-loop learning mechanism,

problems are not only resolved but are fully investigated to eradicate the root cause,

resulting in change of the respective polices where required.

These four maturity levels have sufficient depth to mature the CM process resulting

from its robust structure supported by key process capabilities. On the other side, the

bulk of literature on the subject have five maturity levels initially introduced by Crosby

(1997) and followed by SEI (e.g. Bate et al., 1995; Paulk et. al., 1993; Team, 2006) with


237

many other research studies afterward (e.g. Crawford, 2006; Filho et. al., 2010; Kwak

and Ibbs, 2002; Kulkarni and Freeze, 2004; Paulzen and Perc, 2002; Yeo and Ren,

2008). There are still many maturity models which have introduced varied stages in their

maturity models e.g. Andersen and Jessen, (2003) introduced a three staged (project

management, programme managment, and portpolio management) projects maturity

model, Gottschalk and Solli-Sæther (2006) developed a three stage (cost stage, resource

stage, and partnership stage) IT outsourcing relationships maturity model, Niazi et al.

(2005) launched a four stage (initial, aware, defined, and optimizing) software process

improvement model, Hillson (1997) introduced a four levels (naive, novice, normalized,

natural) risk maturity model, and Sommerville et al. (1997) proposed a three staged

(initial, repeatable, and defined) RE process maturity model.

It is essential to highlight the responses of interview participants on the maturity model

which are given below.

‘Looking at the CM process capabilities, I think that the four level capability is set of the

correct number of levels. I don’t think that three would be enough simply because no

organization can work on three capability levels; it would be four as a minimum.

Secondly I like the way it is actually set out at each of the four different levels and the

criteria that meet those. I certainly think that five levels would be a level too far, and

how a distinction between four levels and five levels which would be supported by what

we trying to do would be very difficult. So I certainly think that four levels would be

acceptable.’ [sic]

‘What are the qualities of an organization you would expect to see? So if you went into a

company that would be static, what would it be like? you wouldn’t expect to see CM

training plans for people, you wouldn’t see necessity to introduce a CM manager, you

would expect people to know what you are talking Configuration Management is

perhaps or may be the odd one or two peoples, perhaps that could be up the scale------

for a reactive organization you would be looking for a CM system that is much more like

a fire fighting so when problem arise they hold hassle around, than they make that fire


238

out, so there is no consistency of process no standardization of process and is very much

adhoc they doing it-----all proactive companies start thinking about the next life cycle

phase, they may even have policies to describe across the enterprise about the whole life

of describe CM at various levels, they have people into start having training, they may

have few people accredited with various bodies, they may send people on training

courses----dynamic company, what would you like them to see to do, than you probably

saying, yes they have all the things of top level policies but they actually have CM

empowered down through the organization.’ [sic]

7.3.4 Key focus areas of CMMM

The CMMM presented above is self explanatory and easy to implement in any aerospace

and defence sectors. The set of thirty five practices (constructs) has provided sufficient

depth and explanation which makes its implementation even simpler. The CMMM can

help organizations to effectively implement and develop their existing process if they

understand the key focus areas of the model and target them at the right time. There are

some important areas to emphasize at each level of model. The first and most important

area to target is the Configuration Management practices outlined through companywide

policies. These policies needs to be simple, easy to understand, fully elaborated, and

fulfils the requirements of any latest international standard.

The next important area to work on is to have an independent and centralized body for

the governance of Configuration Management within organization. In the presence of

any centralized body for the organization of this process ensures that process

requirements (e.g. budgetary, human resources, and training) are met to execute their

responsibilities and have the authority to implement the process according to

organizational policies. To start with, they need to target specific projects, fully

implement their CM process in those project(s), learn from their mistakes, and make

those projects as a role model for the implementation of Configuration Management

practices across all projects irrespective of their size and complexity. Implementation of

the process across all projects is a hard job and needs that functional stakeholders


239

understand the importance and criticality of the process within their projects. This can be

ensured through continuous training programmes across the organization and realizing

the importance of the process to senior management to ensure their support. The

application of CM should not be limited within organization but its functioning needs to

be ensured at vendor’s premises responsible for the provision of parts to the

organization.

The most significant area to target is the cost effective implementation of the process

both in complex and simple or small and large projects. This is again correlated with

issues like consistency and flexibility of the process. It is known that Project Managers

needs flexibility in various practices which on the other hand influence the consistency

of the process across the organization. It is important to note that there is a need to

balance the two issues which needs tight control of the CM plans throughout project

lifecycle, communication of information with functional stakeholders at right time and

expertise of the CM applications. Such issues could be balanced through CM system

audits in different projects throughout the year which are not only necessary for

continuous improvements of the process but also to note the deviations of individual

process in projects from companywide CM policies adopted for the sake of required

flexibilities.

7.3.5 Measuring the level of maturity

There are two dimensions to measure the level of maturity, first to establish key

practices or sub-processes from process capabilities and second is to develop a scale to

measure the defined practices. The two concepts are explained in the following sections.

7.3.5.1 Key Practices on Constructs

A list of thirty-five practices (constructs) were finalized after semi-structured interviews

with six Configuration Management professionals where they were asked to highlight


240

the important aspects while measuring the strength of each parameter in a facility. The

responses from interview participants on various parameters are presented below.

‘Execution policies, I would be looking for a standard they were active, either a military

standard or EIA standard or whatever else, I will also be looking for any local

standards.’ [sic]

‘For the CM governance I will be expecting that there will be governance policies in

place, a CM organization that shows governance lays on it, so who is in-charge, who

report to whom and who is at which levels. I will also be looking at the governance

documentation which would be the actual CM Plan and any follow-up documents that

support the CM plan such as if you are in a contract with a contractor than I would like

to see the contractor CM plan so that you actually show to our customers that we have a

plan and we are also controlling the way our suppliers by providing the same kind of

information.’ [sic]

‘I would be expecting to see an organizational chart for the actual people working in the

area of execution, I would be expecting to see a process flow of how that work is

executed and I would be expecting to see audit documentation that shows the process

has been audited and it has been applied on work as it has been written.’ [sic]

‘Effective CM tool, that’s difficult because who is to say what’s an effective CM tool, I

would like to see things like why that tool set was chosen, what were the requirements of

that tool set, how that tool set fixing with the organization and how it fix across the

organization because it needs to fix not just the requirements and planning elements but

needs to look at the design and development and it looks at the manufacturing

environment and it needs to look at the assembly and whatever else environment so

that’s quite a bit complicated issue really.’ [sic]

‘Professional development, all we have to look to see professional development plans for

each leg of the organization, people don’t want to be static in their environment to be up


241

to develop people one to do the job properly but two to developing that job so they can

either move up the ladder or train up their people which is essential to a good

organization.’ [sic]

‘Management support again all develops and comes from the actual organizational

chart making sure that you know who you need to go to support you and you know who

you need to go when you got problems.’ [sic]

‘If the CM process has the infrastructure and resources allocated in the budget for it,

it’s all often a good indicator that management will understand the importance of CM

and invest in doing it.------ if they invested in enhancing the capability, they recognized

the process and invest in people; you getting a level of commitment.’ [sic]

‘Career opportunities, is exactly what we talked about professional development, we

need to be able to know that what we got position in certain slot what people’s

awareness opt to be and what people’s career development prospects should be to be

able to look at their development plans and see how they actually reach that level of

maturity.’ [sic]

‘Internal politics should be sorted out within the high end of the organization and all we

should be worrying about when it comes to the actual process flows and data flows and

information sets is or we passing over the right information at the right time, so all the

organizational politics should be sorted out by the higher end of the organization and

should be not reflected in the main day-to-day running of what we doing’ [sic]

‘Communication is got to be very effective----------be at the right level and the right

point in time----- from top to bottom and bottom to top to make sure that everybody is

liaising at the right way’ [sic]

,We need to work very clearly with our external customer as at the end of the day its

them, they are taking the end product and so therefore, one they need to be satisfied and


242

be able to be satisfied that the way we developed and created that product and tested it,

meets their requirements. So we need to be liaise with them and make sure that they are

aware that main of their milestone in the developmental and manufactured of that

product that we have achieved everything they need to achieve and that need to be

integrated within the team to support till that, and two, that we are discussing with them

any issues that we may find in relation to the requirements and so on and so for that as

you know as it goes through the whole process that when we start and we finish, one, we

finish on time, we hit our milestone and that we are actually achieving the customer

satisfaction. So it’s really important that we discuss with the customer, we liaise with the

customer and get the customer involved on what we do on the daily basis.’ [sic]

‘Process control at vendor’s sites is very very important because we got to be able to

assure ourselves under customers that what we are putting in our product is one,

acceptable to the requirements of the product so it’s got to meet the standard and two

that in twelve months time if I order the same product again, I am going to get the same

product.’ [sic]

‘Consistency of a process, whatever the process is, highly important; you need a

manageable and repeatable process all the way through’ [sic]

‘Flexibility and consistency are not hand to hand partners so it’s got to be controlled in

the right manner and that’s the key to do in that.’ [sic]

‘Its understanding what variables you have got? Understanding what measuring criteria

you have got? and are they a proper measuring criteria? Not I work at least a hundred

and fifty drawings by the end of the next month irrespective of what those drawings are;

that’s absolutely rubbish. You need to have clear and precise measurement milestone

and be able to understand what they mean to you.’ [sic]

‘Its (continuous improvement) common sense, look at what you doing? Is it the right way

to do it within the restriction you have got? And can we make it better? And its


243

continuous improvement always looking it trying to improve and making the process

more flexibly within the rigidity that you got to have.’ [sic]

‘If we have targets and deadlines, than again it comes to the effective communication, if

we communicate which form measurement criteria and we hitting all the milestone

properly than effective handling of the project pressure is easy somewhat.’ [sic]

It is hard to present the full discussion on the topic but is summarized in the form of

thirty five practices (constructs) presented below which will be used to find the strength

of Configuration Management process capabilities and helps in measuring the capability

of Configuration Management process within aerospace and defence industries. It is

important to highlight the complexity in defining the execution policies explained

through eleven practices or constructs (P1 to P11) and measuring them will need

extensive knowledge, experience of Configuration Management, and help from any

latest standard on Configuration Management at the same time to further explore those

practices. The highlighted practices do cover the core areas of Configuration

Management but do not highlight details of each practice which could be obtained from

any international standard and should be part of the organizational procedures which is

further covered in practice twelve (P12). Details of all thirty five practices (constructs)

under ten process capabilities are presented below. It is important to note that the

practices P1 to P35 could be represented with C1 to C35.

7.3.5.1.1 Execution strategies

P1: The CM process is available in the form of documented procedures

describing the organizational policies, activities, and conventions related to CM

planning, configuration identification, configuration control, configuration status

accounting, and configuration auditing.

P2: CM practices are implemented in all projects irrespective of the value or

complexity of that project.


244

P3: Product configurations (hardware system and software) and their related

configuration documentation have a strong correlation and unique identification.

P4: Configuration documentation is released through a formal release process

which includes the review and approval of all functional stakeholders.

P5: The CM process specifies the rules and procedures to identify and control

Configuration Items across all projects.

P6: The CM process specifies requirements of managing baselines from concept

to disposal of the product or system, which are implemented across projects

through the application of company-wide procedures.

P7: The configuration change management process is implemented through a

closed loop cycle where configuration changes are identified, documented,

evaluated, and implemented with appropriate approval.

P8: Engineering changes are classified in two high-level categories i.e.

permanent changes (dealt through ECOs or ECPs) and temporary changes (dealt

through waivers and deviations) which are properly identified and recorded

across all projects.

P9: The Change Control Board (CCB) is the sole authority to accept or reject

both permanent and temporary changes.

P10: Configuration status accounting is in place to capture and maintain product

configuration information throughout the product life cycle.


245

P11: The physical and functional configuration audits are conducted to provide

assurance of the physical and functional configuration verifications before

release of the products to customers.

P12: The documented CM process fulfils detailed requirements of any latest

international standard(s) on CM [e.g. EIA-649 (Rev B)] which covers the sub-

elements of all areas highlighted from P3 to P11.

7.3.5.1.2 Governance

P13: The Configuration Management process is governed through a defined

organization with dedicated staff having documented responsibility and

authority.

P14: Configuration Management planning is the fundamental activity during

project specific CM activities which are managed through updated CM plans

throughout the product life cycle.

7.3.5.1.3 Process Executers

P15: The CM process is managed and governed by a dedicated individual having

in-depth knowledge of CM and leadership qualities.

P16: The CM process is backed by CM expert(s) having previous experience with

a team of competent, committed, and focused practitioners (according to

requirements) to carry out CM activities according to defined CM principles and

practices.

7.3.5.1.4 Resources Allocation


246

P17: The CM process has the required infrastructure (buildings, equipment etc.)

and resources (human and financial) to effectively execute the process within

projects.

P18: The CM process is supported by a software tool which is easy to use and

fulfils the organizational requirements to effectively implement and support CM

principles and practices.

P19: Professional development is part of the organizational training programme

to create awareness, importance, and help in the implementation of CM

methodologies and related fields in the organization where required.

7.3.5.1.5 Organizational support

P20: Management understands the importance of CM practices and are

committed to establish CM as a core business area.

P21: CM is recognized as a key process area where both management and

stakeholders understand the importance and criticality of the process.

P22: The growing awareness and importance of CM practices has resulted in

career progression opportunities for CM professionals similar to those in the

fields of project management, quality engineering, and design etc.

P23: CM managers have the authority through strong backing of senior

management to implement the process against established guidelines.

P24: Stakeholders understand the importance of CM, provide the required

resources, ensure effective coordination, and show commitment to effectively

implement the process.


247

7.3.5.1.6 Effective communication

P25: The communication with both internal and external customers is open,

timely, and free flowing both from top to bottom and bottom to top.

7.3.5.1.7 Customer’s awareness

P26: It is our company policy to maintain close liaison with external customers to

make them aware of the completion of their major milestone and ensures their

active participation in product design reviews to validate their requirements

before finalization of product specifications.

7.3.5.1.8 Effective environment

P27: Organizational culture does support the effective implementation and

continuous development of the CM process.

P28: The working environment is politics free where decisions are made on merit

to ensure holistic implementation of the process for quality products.

P29: CM professionals work as a team while establishing, implementing, and

continuously improving CM practices.

7.3.5.1.9 Process control at vendor premises

P30: CM is planned against international standards at a vendor’s premises which

fulfils your organizational CM requirements and is assured through periodic

audits to ensure production of acceptable and consistent products.

7.3.5.1.10 Process transformation


248

P31: CM practices are consistent throughout the organization irrespective of the

size and complexity of projects and across the projects or products life cycle

phases whether it is concept, development, production, and maintenance or

modification.

P32: CM practices are flexible and may vary to accommodate project specific

requirements based on the complexity, criticality, and project / product life cycle

phases while ensuring compliance with company-wide CM principles and

practices.

P33: CM system audits are planned and conducted periodically to identify areas

of weakness, plan remedial actions, and address needs to enhance performance of

the process in terms of identified and measurable criteria.

P34: The CM process is continuously improved through small incremental

changes to accommodate technological advances, reduce limitations of the

process, and induce more flexibility within the rigidity you have.

P35: CM activities are planned, effectively communicated, and properly executed

by keeping in mind the criticality of tasks with respect to project scheduling to

effectively handle project pressures.

7.3.5.2 Measuring Scale

Each of the practice (P1 to P35) will be measured with the help of four-point-scale i.e.

Static, Reactive, Proactive, and Dynamic. The four point scale is fully explained below.

1. Static: The practice is not properly practiced / implemented / supported.


249

2. Reactive: The practice is limited to specific projects and has lack of holistic

implementation across projects and product life cycle. There is a visible lack of

support from all functional stakeholders.

3. Proactive: The practice has good implementation or provides the necessary

support required across projects. The CM process is uniformly implemented

across projects irrespective of their size and complexity because of the lack of

flexibilities in CM policies which most of the time diminish its importance in

small projects because of cost versus benefit analysis. The environment is not

supportive to accommodate new changes which lacks in performance monitoring

and continuous development of the process.

4. Dynamic: The practice has best implementation or provides the desired support

in the effective implementation of the process to accommodate project specific

requirements. Through established improvements methodologies and supportive

environment, inadequacies arising with time are removed and policies are revised

where applicable to assure effective implementation and continuous development

of the process.

7.4 Validation of CMMM

The term validation means to ensure that newly developed model fulfils the

requirements for which it has been designed (Carson, 1986). The important aspect of this

validation process was to check that the model is generic in nature, rightly designed and

fulfil the generic requirements for establishing and continuously developing the

Configuration Management process. The validation process does not directly assess the

usability, quality, and utility of the model but verify that the components have a

satisfactory accuracy which is consistent with the intended application of the model

(Beecham et al., 2005a).


250

The limited number of interviews and problems in arranging further interviews forced us

to validate the model through a questionnaire survey. The model was validated with the

help of Configuration Management professionals by asking them to mark different

statements covering multiple aspects of the model. A total of seventeen statements (S1 to

S17) provided in the questionnaire to validate the Configuration Management Maturity

Model are shown in table 7-2. Efforts have been made to generalize the concept and

cover different aspects of the model while designing each of the statement. The limited

number of responses is always an issue but there are studies (e.g. Beecham et al., 2005a)

where models are validated with limited number of research participants. It is essential

to note that this study follow some previous studies (e.g. Beecham et al., 2005a; Dyba,

2000; El Emam and Birk, 2000) where questionnaires were generated to validate their

model with the help of professionals on the subject. The important aspect of this

validation process is that most of the research participants are not only experts in their

field but have extensive previous experience in CM applications as shown in figure 7-3.

The five point Likert scale used for measuring each statement is presented in three

groups (table 7-1) to explain the behaviour of data as presented in table 7-2. Analysis of

the data presented in table 7-2 shows high supportive responses which highlight

completeness and comprehensiveness of the Configuration Management Maturity Model

presented above.

Critical response Neutral response Supportive response

Extremely disagree Disagree Neutral Extremely agree agree

Table 7-1: Five point scale in three groups


251

Figure 7-3: Experience of research participants under different categories


252

Statements Neutral

Responses

Critical responses Supportive responses

No of responses % No of responses %

S1: Effective implementation and continuous

development of Configuration Management practices

can be largely facilitated through workable

Configuration Management Maturity Model.

1

1 +

1 =

2

Disagree= 2

Strongly disagree= 2

Total= 4

28 +

19 =

47

Agree=56

Strongly agree=38

Total=94

S2: The Configuration Management Maturity Model

based on key process capabilities extracted from critical

success factors and barriers to Configuration

Management implementation is the most effective way

to establish such models.

7

1 +

0 =

1

Disagree= 2


Total= 2

21 +

21 =

42

Agree=42

Strongly agree=42

Total=84

S3: The four levels of maturity of the Configuration

Management Maturity Model provide the necessary

depth for the implementation and continuous

development of Configuration Management process.

7

1 +

0 =

2

Disagree= 2


Total= 2

31 +

11 =

42

Agree=62

Strongly agree=22

Total=84

S4: The key process capabilities dedicated to each

maturity level shows its correct representation. 7

1 +

0 =

1

Disagree= 1


Total= 1

30 +

12 =

42

Agree=60

Strongly agree=24

Total=84

Table 7-2: Expert opinion on different aspects of Configuration Management Maturity Model


253

Table 7-2: Expert opinion on different aspects of Configuration Management Maturity Model (Contd)

S5: The Configuration Management Maturity Model has

covered the core elements of Configuration Management

process which are the requirements of any international

configuration management standards.

1

1 +

0 =

1

Disagree= 0


Total= 0

21 +

27 =

48

Agree=42

Strongly agree=54

Total=96


covers all support areas necessary for the implementation

and continuous development of Configuration

Management practices.

4

2 +

1 =

3

Disagree= 4


Total= 6

23 +

20 =

43

Agree=46

Strongly agree=40

Total=86

S7: All thirty-five practices explaining the Configuration

Management process capabilities are easy to understand

and are rightly explained to achieve the desired goals.

2

2 +

0 =

2

Disagree= 4


Total= 4

35 +

13 =

48

Agree=70

Strongly agree=26

Total=96

S8: All thirty-five practices are general in nature and will

equally apply to most industries. 3

1 +

0 =

1

Disagree= 2


Total= 2

29 +

17 =

46

Agree=58

Strongly agree=34

Total=92

S9: All thirty-five practices cover the required parameters

necessary for the implementation and continuous

development of Configuration Management practices.

2

2 +

0 =

1

Disagree= 4


Total= 4

36 +

10 =

46

Agree=72

Strongly agree=20

Total=92


254

S10: The four point scale is well defined and will provide

the desired results while measuring the strength of each

practice and maturity of an overall Configuration

Management process.

6

0 +

1 =

1

Disagree=0


Total= 2

30 +

13 =

43

Agree=60

Strongly agree=26

Total=86

S11: Implementation of process capabilities in small

groups at different levels of maturity will help

practitioners to better implement the Configuration

Management process.

7

2 +

0 =

2

Disagree= 4


Total= 4

26 +

15 =

41

Agree=52

Strongly agree=30

Total=82

S12: Implementation of Configuration Management

Maturity Model does not need much experience of the

maturity process but demands understanding of the

Configuration Management process.

3

4 +

0 =

4

Disagree= 8


Total= 8

26 +

17 =

43

Agree=52

Strongly agree=34

Total=86

S13: It is more realistic for industries to implement and

progressively improve their Configuration Management

process by adopting this model.

6

1 +

0 =

1

Disagree= 2


Total= 2

34 +

9 =

43

Agree=68

Strongly agree=18

Total=86



255

S14: It is easier to implement and improve Configuration

Management practices by adopting this maturity concept

instead of any other haphazard methodology.

4

0 +

0 =

0

Disagree= 0


Total= 0

35 +

11 =

46

Agree=70

Strongly agree=22

Total=92


will help organizations to identify areas of weakness and

prioritise actions to streamline their Configuration

Management practices.

1

0 +

0 =

0

Disagree= 0


Total= 0

23 +

26 =

49

Agree=46

Strongly agree=52

Total=98

S16: Questions asked in this questionnaire have provided

the necessary depth to assess strengths and weaknesses

of the Configuration Management Maturity Model.

7

4 +

1 =

5

Disagree= 8


Total= 10

26 +

12 =

38

Agree=52

Strongly agree=24

Total=76

S17: Any further research on the topic would be useful

and help industries in finding useful ways to transform

their Configuration Management process.

4

0 +

0 =

0

Disagree= 0


Total= 0

22 +

24 =

46

Agree=44

Strongly agree=48

Total=92



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7.5 CM process maturity

This section investigates the data obtained through process maturity questionnaire to

investigate the maturity level of Configuration Management practices both in aerospace

and defence industries. Descriptive and inferential statistics are used to analyse and draw

conclusion on data. The results are explained in the following sections.

7.5.1 Level of maturity of Configuration Management practices

The maturity of Configuration Management process was calculated by using descriptive

statistics on the data obtained by measuring thirty-five practices with the help of a four

point scale explained in section 7.3.4.2. The level of maturity in the form of mean values

is presented in table 7-3 for aerospace, defence and both these two sectors together. The

level of maturity is presented for each of the twelve process capability, four capability

levels and overall Configuration Management process. The mean values populated in the

table are between 2 and 3 for all process capabilities, maturity levels and overall

Configuration Management process, meaning that these sectors have achieved reactive

level and on the verge of attaining proactive capability. This shows that both aerospace

and defence industries have capabilities to manage their Configuration Management

process on independent projects but needs their attention to the overall implementation

of the process across organization.

According to the findings presented in Chapter 6 that Configuration Management

practices are well understood and implemented in defence sectors as compared to

aerospace could be seen here as well since the mean values are slightly high in defence

sectors in comparison to aerospace both in level 1 and 4 which mainly deals with

Configuration Management practices. The recognition of the support processes covered

in level 2 and 3 are almost similar in both sectors. The overall maturity levels calculated

for both aerospace and defence sectors is 2.7484, meaning that these organizations

approaching to achieve proactive level and have largely established their process on

organizational level but still needs enough hard-work to take their practices to dynamic

capability.


257

Capability Level

(CL) Process capabilities (PC)

Defence Sectors Aerospace Sectors Both Aerospace and Defence

Mean Values Mean Values Mean Values

PC CL overall PC CL overall PC CL overall

Level 1 Execution policies 3.0534 3.0534

2.7516

2.9808 2.9808

2.7385

3.0353 3.0353

2.7484

Level 2

Governance 3.1538

2.8242

2.8846

2.8462

3.0865

2.8297 Process executers 2.7436 3.1538 2.8462

Resources allocations 2.6581 2.6154 2.6474

Level 3

Organizational support 2.2821

2.4522

2.3846

2.4965

2.3077

2.4633

Communication 2.5385 2.4615 2.5192

Customer awareness 2.8718 2.9231 2.8846

Effective environment 2.5128 2.4872 2.5064

Process control at vendor’s

premises 2.6154 2.6923 2.6346

Level 4 Process transformation 2.5846 2.5846 2.5385 2.5385 2.5731 2.5731

Table 7-3: Mean values of defence sectors


258

7.5.2 Hypothesis validation

An independent-sample t-test, a type of parametric tests, is used to analyse the

hypothesis presented in section 7.1. An independent-sample t-test is used when

comparing the mean scores of two different groups of people or conditions and give

reliable results if the data is normally distributed (Pallant, 2010). The normality of the

data can be determined on the basis of Sig. value calculated by using Kolmogorov-

Smirnov or Shapiro-Wilk Tests. The data is called normally distributed if the Sig. value

is greater than 0.05 (Pallant, 2010). Since the Sig. value is greater than .05 presented in

table 7-4 hence the data is normally distributed and an independent-sample t-test is used

for inferential statistics.

Tests of Normality



CM practices .093 52 .200 .973 52 .289


An independent-samples t-test was conducted to observe any significant difference in

the mean values for both aerospace and defence industries. The results of the test are

presented in table 7-5 and table 7-6. There is no significant difference in the scores of

aerospace sectors (M=2.7385, SD=.82642) and defence sectors (M=2.7516,

SD=.48417). Since the Levene’s test for equality of variances is less than 0.05, meaning

that the variances for the two groups (aerospace and defence sectors) are not the same

and hence we are using the data in the last row of table 7-6 i.e. ‘equal variances not

assumed’. Since the Sig. (2-tailed) value is .957 which is greater than .05, meaning that

there is no significant difference in the maturity of Configuration Management process

both in aerospace and defence sectors and we reject the hypothesis as highlighted in

section 7.1.


259

It is important to note that non-parametric tests are recommended by some researchers if the data obtained is ordinal i.e. ranked

(Motulsky, 1995), but since similar results are obtained from both tests and also most of the researchers have only mentioned the

assumption of normality for selecting any of the two tests hence we have presented the data obtained by using parametric test.

Types of organization N Mean Std. Deviation Std. Error Mean

Aerospace 13 2.7385 .82642 .22921

Defence 39 2.7516 .48417 .07753

Table 7-5: Group statistics

Levene's Test for

Equality of Variances t-test for Equality of Means

Sig. t df Sig. (2-tailed) Mean

Difference

Std. Error

Difference

95% Confidence Interval

of the Difference

Lower Upper

Equal variances

assumed .006 -.070 50 .944 -.01319 .18731 -.38941 .36303

Equal variances

not assumed -.054 14.842 .957 -.01319 .24197 -.52940 .50303

Table 7-6: Independent samples test


260


7.6.1 Summary

The objective of this research was to develop Configuration Management Maturity

Model for the effective implementation and continuous development of Configuration

Management practices. By keeping in view the recent studies in other allied field, the

Configuration Management Maturity Model is based on process capabilities extracted

from CM critical success factors and barriers to CM implementation. It was essential to

see the level of implementation of Configuration Management practices in both

aerospace and defence sectors and analyse any significant difference, if exist, between

the maturity of both aerospace and defence industries.

This research is based on critical analysis of the existing literature on critical success

factors, barriers to CM implementation and maturity models in other allied fields

followed by semi-structured interviews and questionnaire surveys which are part of the

qualitative and quantitative research methodologies respectively. Review of the existing

literature followed by interviews helped us to finalize the Configuration Management

process capabilities, structure of Configuration Management Maturity Model, and

measuring mechanism for the maturity of Configuration Management practices. By

keeping in view the limited number of interviews conducted for this research and

problems with arranging further interviews; it was decided to validate the developed

Configuration Management Maturity Model through a questionnaire survey. It was also

necessary to test the maturity concept and the application of thirty-five practices through

another questionnaire survey.

The CMMM is based on ten process capabilities which are the outcome of twenty-one

critical success factors (chapter 4) and nineteen barriers to Configuration Management

implementation (chapters 5 and 6). These process capabilities cover every aspect of the

process which is necessary for the effective implementation and continuous

development of the configuration management practices. The process capabilities are


261

further elaborated with the help of controlling parameters in the shape of thirty five

process detailed practice definition where a list of thirty five practices are presented

which could help CM professionals to better understand and target the required areas for

improvement. It is always hard to define the key parameters which are used to judge the

effectiveness of process capability and is accomplished through detailed discussion with

CM professionals. The highlighted practices do cover the core areas but do not highlight

the insight of detailed practices which could be obtained from any international standard

and should be part of the organizational procedures.

A four level (Static, Reactive, Proactive, and Dynamic) Configuration Management

Maturity Model was developed which was then validated through a questionnaire

surveys as explained in section 7.4. The maturity of Configuration Management

practices in both aerospace and defence sectors was calculated and presented in section

7.5.1 which shows that both these sectors are on the verge to achieve the requirements of

proactive level and will need more efforts to fulfil the needs of dynamic capabilities. It is

also validated through inferential statistic that there is no significant difference in the

maturity of both aerospace and defence industries as presented in section 7.5.2.

7.6.2 Conclusions

This study investigates the maturity concepts, provides the necessary foundation, and

establishes a Configuration Management Maturity Model to evolve the capabilities of

the CM process along with an anticipated and logical maturation path to achieve the

desired objectives. The CMMM is based on detailed discussion with CM professionals

and the outcomes of two independent studies which have contributed greatly to the

understanding of CM as a value added process in an organization. To the best of our

knowledge, this is the only study on the subject which is based on CM specific process

capabilities to help organizations in establishing and improving their CM practices since

it is not only based on the success and failure factor specific to CM implementation but

on detailed practices summarizing expert opinions of CM professionals necessary for the

effective implantation and continuously development of the process. It is essential to


262

note that detailed aspects of the CMMM were highly recommended by CM experts both

in aerospace and defence organizations through an independent validation process.

This research also investigates the maturity of the CM process in aerospace and defence

organizations which have provided some interesting results. As previously highlighted

(in Chapter 6) that CM applications are largely undermined in aerospace as compared to

defence sectors; it was believed that there will be a significant difference between the

maturity levels of both aerospace and defence industries. This assumption is not justified

by our results here which suggest that mean values for both these sectors are close to

each other and there is no significant difference in the maturity level of CM practices in

aerospace and defence industries. This needs further investigation with a large sample

size having same representation from both aerospace and defence sectors.

263

CHAPTER 8

SUMMARY, CONCLUSIONS AND RECOMMENDATIONS

8.0 Introduction

This chapter is comprised of research summary and conclusion based on the data

obtained through interviews and questionnaire survey conducted in all three parts to

identify, finalize, and rank CM CSFs and barriers to CM implementation and develop a

Configuration Management Maturity Model for the effective implementation and

continuous development of Configuration Management practices within aerospace and

defence organizations. The interviews in the second part of this research consist of

discussion on the governance aspects of the Configuration Management process which

provides important information on strengthening the implementation aspects of the

process. It is important to note that first two parts (i.e. identification of critical success

factors and barriers to Configuration Management implementation) are conducted to

provide necessary data essential for the third and final part of this research (i.e.

development of Configuration Management Maturity Model).

8.1 Summary of the research

The prime objective of this research was to establish a mechanism for the effective

implementation and continuous development of the Configuration Management process

within aerospace and defence organizations. The literature suggests that one of the most

disciplined instruments for the maturity of a process is defining maturity model which

define path of maturation for the development and continuous improvement of a process.

The current literature on the subject suggests that these models could be more effective

if based on critical success factors and barriers. To develop a Configuration

Management Maturity Model, this research was divided into three parts i.e.

identification of critical success factors for the effective implementation of

Chapter 8: Summary, conclusions and recommendations

264

Configuration Management, identification of barriers to Configuration Management

implementation and analysing the governance aspects of the process, and developing

Configuration Management Maturity Model. It was imperative to have a thorough

review of the existing literature (covered in chapter 2) which provides necessary

foundation for further research. The topics covered in all three parts with adopted

research methods is summarized in table 8-1.

Part 1 Part 2 Part 3 In

tervie

ws

Qu

estion

naire

Interv

iew

s

Qu

estion

naire

Interv

iew

s

Qu

estion

naires

CSFs for CM implementation √√√√ √√√√ √√√√

Barriers to CM implementation √√√√ √√√√ √√√√

governance of CM process √√√√ √√√√

CM maturity model √√√√ √√√√

Table 8-1: Research focus in different research parts

The summary in Table 8-1 highlight that research in all three parts is triangulated to

ensure validity throughout this research. The first two parts of this research are not

dependent on each other but provides the necessary information to the third and final

part which means that the third part is dependent on the data obtained from the first two

parts. The summary of each study is discussed below.

In the first part twenty-one CSFs for the effective implementation of Configuration

Management were identified with the help of CM professionals working in the leading

aerospace and defence industries through mixed method research with in-depth

interviews followed by a questionnaire survey. It is important to note that the success

factors identified with the help of in-depth interviews with CM subject matter experts,


265

email conversation with Configuration Management expert, and the available literature

were retained in the shape of critical success factors after the questionnaire survey

resulted high mean values for all factors (4≤ Mean Values ≤ 5) obtained through

descriptive statistics which highlight the importance of these factors in the

implementation of the CM process. The twenty-one CSFs have been organized into

seven categories by establishing a relationship between the human activity model

(Checkland, 1981), the formal system model (Fortune and White, 2006), and the

requirements of the CM activity model. Factor Analysis on the other hand is not

considered since the data failed to meet basic assumptions essential where it is necessary

to have a strong correlation among the factors that can be checked with correlation

coefficients which should be above 0.3. Since, less than 35 percent of the values are

above 0.3 in the correlation matrix attained from factor analysis, factor analysis was not

considered appropriate. The parallel analysis suggested the same result which proposes

comparison of the first eigenvalue obtained from SPSS with the corresponding first

value generated by parallel analysis and maintains the component where the actual

eigenvalue is larger than the criterion value from parallel analysis; if it is less, then it is

rejected (Pallant, 2010).

In the second part nineteen barriers to Configuration Management implementation were

identified with the help of CM professionals working in leading aerospace and defence

industries through in-depth interviews followed by a questionnaire survey. The

questionnaire survey in the first part of this research is also used where an open question

was posted by asking research participants to address their concerns which they think are

the more obvious problems in the implementation of Configuration Management. The

replies received through this survey were grouped into multiple factors for further

analysis and combined with the data received from the seven semi-structured interviews

with CM experts of four different industries. A group of nineteen barriers were finalized

after careful analysis of the data received from the two forms of studies where efforts

were made to avoid possibilities of ignoring or repeating factor. In the final phase, all the

barriers were accepted as barriers to Configuration Management implementation (2≤

Mean Values ≤ 4) through a questionnaire survey by asking questions through a series of


266

statements explaining the existence of each barriers with the help a five-point scale.

Through factor analysis, the set of nineteen barriers were grouped into three groups

namely ‘managerial and organizational barriers’, ‘planning and process barriers’, and

‘implementation barriers’. In the first place factor analysis was deemed the right option

because inspection of the Pearson Product-Moment Correlation Coefficient Matrix

revealed the presence of many coefficients of 0.3 and above. Secondly, the Bartlett’s

Test of Sphericity which is used to detect whether variables are uncorrelated is

significant (significance value should be less than 0.05 which is 0.000 in this study).

Thirdly, the Kaiser-Meyer-Olkin (KMO) value is 0.893 which exceeds the

recommended value of 0.6 meaning that factor analysis is highly recommended for the

sample data. It is important to note that results of inferential statistics which highlight

professional’s from aerospace and defence organizations perceive the barriers differently

in their setups.

The second part also included discussion on Configuration Management where multiple

issues (e.g. the organization of Configuration Management, the roles / appointments of

the working staff, the rules and regulations of the process, and the control of

Configuration Management practices at vendor’s premises) were discussed. It is

important to highlight that variations were observed on the issues highlighted above

within research participants. It is highlighted that the issues discussed above varies from

one organization to other which are mainly dependent on the size and number of projects

handled at any particular location. The research participants were mainly in favour of

functional and hybrid types of organizations to have dedicated staff for the execution of

Configuration Management principals and maintaining consistency within projects. The

second outcome of the discussion was that Configuration Management staff should be

more technical whereas the Configuration Management officers / engineers should have

engineering background to understand and implement the process according to its merit.

It is also highlighted that Configuration Management practices at vendor’s premises

should be handled by Configuration Management officers of specific projects as they are

the right persons to discuss and resolve the issues with vendors.


267

The third and final part is related to the development of a Configuration Management

Maturity Model. This part is based on semi-structured interviews, questionnaire surveys,

and critical analysis of the available literature on maturity frameworks and the studies on

critical success factors and barriers to Configuration Management implementation. The

critical analysis of available literature on maturity models and the two studies on critical

success factors and barriers to Configuration Management implementation helped us to

establish Configuration Management Maturity Model which is further refined on the

inputs of semi-structured interviews with six Configuration Management professionals

from four aerospace and defence organizations. On the basis of ten process capabilities

extracted from critical success factors and barriers to Configuration Management

implementation, a four level (static, reactive, proactive, and dynamic) Configuration

Management Maturity Model has been developed. To measure the level of maturity of

Configuration Management implementation, thirty-five practices extracted from the ten

process capabilities were defined which would be measured on a four point scale

(1=static, 2=reactive, 3=proactive, and 4=dynamic). The limited number of interviews

and the problems with arranging any further interviews forced us to validate the

developed Configuration Management Maturity Model through a questionnaire survey.

The questionnaire survey was developed to validate the model with the help of

seventeen statements measured on Likert-type scale running from 1 (strongly disagree)

to 5 (strongly agree) after explaining the model at the beginning of questionnaire. To test

the overall maturity concept and the developed measuring criteria, it was felt necessary

to run a second questionnaire which is based on established thirty-five practices on a

four point scale. The same questionnaire having thirty-five practices with the same scale

will be used by organizations to measure their Configuration Management practices.

8.2 Conclusions

Based on the analysis of data acquired from this research and the literature review on the

subject and other allied fields, the research is concluded under the following four

headings.


268

8.2.1 CSFs for the effective implementation of Configuration Management

Following conclusions have been drawn on the basis of literature and the final analysis

of this research.

• There is no single study found on critical success factors in the field of

Configuration Management in the literature, however, limited literature in the form

of case studies and research theories are available on the success and failures of

Configuration Management implementation. On the other hand, some researchers

believe that in the presence of extensive literature in other allied fields like PM and

QM, it is useless to do further research on the subject in the field of Configuration

Management. It is logical that being a technical management discipline some of the

areas will be critical for CM, and PM e.g. management support, resource

requirements etc., but many factors identified through PM research have limited

direct correlation on the overall performance of CM implementation e.g. market

intelligence, technical uncertainty innovation, accurate initial cost estimates, strong

business case.

• A list of twenty-one critical success factors were identified and prioritized for the

effective implementation of Configuration Management in aerospace and defence

industries through literature review followed by interviews, email conversation,

discussions, and questionnaire survey to collect the required data from Configuration

Management professionals.

• All twenty-one CSFs have been organized into seven categories (i.e. execution

strategies, decision taker (s), performance monitoring, sufficient resources, effective

environment, communication, and defined boundary) by establishing a relationship

between the human activity model (Checkland, 1981), the formal system model

(Fortune and White, 2006), and the requirements of the CM activity model. The

groups of factors are populated in the form of an activity model to emphasize the

importance of these factors in the implementation of a process.


269

• There is a significant difference in the CM practitioner’s perception on the basis of

their experience in Configuration Management and Configuration Management

certification / training on the ranking of CSFs which presents the importance of these

areas in the implementation of the CM process.

• There is no significant difference in the CM practitioner’s perception on the basis of

their academic qualification and experience in stakeholders departments on the

ranking of CSFs.

8.2.2 Barriers to Configuration Management implementation

Following conclusions have been drawn on the basis of literature and the final analysis

of this research.

• The research on barriers to Configuration Management implementation contributes

to existing knowledge by identifying barriers to CM application since the literature

suggest that research based study on the topic is extremely limited in comparison

with other allied fields such as Knowledge Management and Quality Management.

There are some studies which could be considered most influential in the field but

have specific limitations on their own because they have targeted specific elements

of Configuration Management and do not present holistic view of the process.

• Through mixed method research, nineteen barriers to Configuration Management

implementation are identified with the help of Configuration Management

professionals working in aerospace and defence industries. The list of nineteen

barriers is further extracted into three groups (managerial and organizational barriers,

planning and process barriers, and implementation barriers) with the help of factor

analysis based on their inherent relationship to facilitate professionals in targeting

specific areas for improvements.


270

• The outcome of this research is quite significant since it highlights obstacles related

to areas such as management support, governance, principles and policies, training,

authority to implement, planning, communication, stakeholders support, and

resource requirements which are not only considered the most influential factors for

the successful implementation of Configuration Management but also for other allied

fields such as Knowledge Management and Project Management.

• The responses suggest that while configuration managers perceive the existence of

these barriers in both aerospace and defence sectors, in general, these barriers are

more evident in the commercial aerospace sector. This is validated by the results of

inferential statistics where significant difference is observed in the perception of

Configuration Management professionals on the basis of the organization in which

they work. These results are quite significant since Configuration Management is

well understood in the defence industries and is contractually mandated through

meeting of the required defence standards evoked by the customers.

• The results of inferential statistic indicate that identification and ranking of barriers

to Configuration Management acceptance and application, from the perspective of a

CM practitioner, will not be influenced by their academic education, gender

difference, and CM experience.

• It is believed that some of the factors which are the root cause for many other

barriers may substantially affect the effective implementation of the CM function.

For example effective training programmes will not only help to get the required

support from top management but may also help to alleviate the lack of recognition

and perceived importance of the CM process across the organization while

Configuration Management planning, on the other hand, may take control on other

aspects like lack of maintaining consistency and lack of flexibility in CM practices.

• There is a growing body of knowledge evolving in the form of Configuration

Management which undoubtedly will be slowed down if organisations fail to identify


271

critical barriers and meet the requirements of such documents. It is equally important

to have an idea of such barriers along with understanding and documenting

requirements based CM methodologies defined in the latest international standard(s).

8.2.3 Governance of the Configuration Management process

The following conclusion can be made on the basis of research conducted in the second

part of this research.

• Issues of governance vary from one organization to another which is mainly

dependent on the size and number of projects handled at any particular location.

• The functional and matrix organizational structure which demands dedicated staff

for the execution of a process are the most favourable mechanism(s) for the

execution of Configuration Management process.

• It is important to understand technical aspects of the process by recruiting technical

staff whereas emphasis should be made on Configuration Management officers to

have engineering background to understand and implement the process according to

its merit.

• The Configuration Management practices at vendor’s premises needs to be

controlled with the help of Configuration Management professionals since they are

the only right individuals to deal this issue.

8.2.4 Configuration Management Maturity Model

Following conclusions are drawn on the basis of literature and final analysis of 3rd

part

of this research.


272

• This research is designed to build maturity framework for the effective

implementation and continuous development of Configuration Management

practices based on critical success factors and barriers to Configuration Management

implementation finalized with the help of Configuration Management professionals

from aerospace and defence sectors. The literature suggest that other studies in the

field are similar in nature, lack important information, and are based on what to

implement instead of how to implement that prompted us to build Configuration

Management Maturity Model with new concept supported by latest studies on the

concept in other allied field.

• Ten process capabilities were extracted from critical success factors (presented in

Chapter 4) and barriers to Configuration Management implementation (presented in

Chapters 5 and 6) which would ensure to avoid the possible risks and help in

achieving the desired objectives. On the basis of these ten Configuration

Management process capabilities, a four levels (static, reactive, proactive, and

dynamic) Configuration Management Maturity Model was developed. The model

has all key characteristics essential for the effective implementation and continuous

development of the Configuration Management process highlighted by recent

research studies on the issue. This is an action based model having both the concept

of single and double loop learning.

• To measure the level of maturity of Configuration Management practices in any

facility, the process capabilities were explained with the help of thirty-five practices

which should be measured on a four point scale (1=static, 2=reactive, 3=proactive,

4=dynamic) to calculate the overall maturity of Configuration Management

practices.

• On the basis of inferential statistics it is concluded that there is no significant

difference in the maturity of Configuration Management process in aerospace and

defence sectors and hence we reject the third hypothesis presented in Chapter 1.


273

8.3 Limitations of the study

There are some limitations with this study which should be acknowledged for further

research. As previously highlighted that Critical Success Factors, Barriers to CM

implementation, and Process Capabilities were identified through limited number of

interviews followed by questionnaire surveys. On the other hand, literature on similar

topics in other allied fields suggest the importance of focus groups for similar research

which could better explore multiple aspects as the discussion evolves and hence provide

comprehensive aspects of the issue which is sometimes difficult to explore through

limited interviews.

The limited number of interviews in all three phases could be considered a possible

limitation to the study but since the sample was highly relevant, experienced and every

effort was made to present related information in its actual and truest form, there are less

chances to ignore areas of importance. Further, the data obtained from interviews were

also triangulated through questionnaire surveys to ensure reliability and validity of the

data. Since the high number of questionnaires in all three studies validate the data

obtained through interviews, the outcomes could be easily generalized across aerospace

and defence industries across the world.

It is always essential to explore hypothesis with large simple size having same

representation of the simple size from different categories. The third hypothesis have

been explored with a relatively small sample size (n=52) with an uneven representation

from both defence (n=39) and aerospace (n=13) sectors. Further research is therefore

recommended to investigate this vary issue with the help of a large sample size have

same representation from both aerospace and defence sectors.

8.4 Contribution of this research

This research has some significant academic and practical implications in the area of

process maturity in general and Configuration Management as a process in particular. It


274

is important to note that the objective behind this research is to highlight and evaluate

practitioners’ perception on critical success factors and barriers to Configuration

Management implementation to develop a roadmap for achieving excellence in the

implementation and continuous development of Configuration Management process in


8.4.1 Academic perspective

The importance of Configuration Management could be seen after its reflection in many

standard as a compliance requirements and the extensive literature issued by different

sectors, mostly from defence; however, being ignored by academia in the past (Burgess

et al., 2005; Huang and Mak, 1998), the academic literature is extremely limited as

compared to other allied fields e.g. Quality Management, Project Management, and

Knowledge Management etc. This research has targeted three areas of Configuration

Management which provide the necessary foundation for the fourth and final study. This

research attempted to link the theoretical and industrial perspective to investigate the

maturity concept of the Configuration Management process since the limited literature

on the subject lack important aspects in comparison with latest literature on the topic in

other allied fields. The contribution of this research to current literature is as follow:

The study on Critical Success Factors is the first formal study on the subject where a list

of factors are identified which helped in the formation of Configuration Management

activity model to better implement the CM activities. Some researchers believe that in

the presence of extensive literature on the subject in the field of Project Management,

Quality Management, and Knowledge Management, it is unproductive to further explore

the subject within CM but in reality no single study could be used as a baseline for the

development of Configuration Management Maturity Model. It is also pertinent to

mention that being a technical management discipline it is logical that some of the areas

will be critical for both CM and PM but other PM factors identified through literature

have limited or no direct correlation with the overall performance of CM operation e.g.

market intelligence, technical uncertainty innovation, etc. This highlight the importance


275

of this study which provided the necessary foundation for the implementation and

continuous development of Configuration Management practices.

The literature on Configuration Management does not reflect one singular study

dedicated to CM implementation barriers. By keeping in view the importance of the

study in the continuous development of a process, this study was conducted which

highlight many barriers that are not reflected before in the literature on CM, for example

lack of flexibility in CM process, extreme project pressures, lack of authority to

implement CM principles / policies, poorly defined CM requirements and process, lack

of CM awareness in customer worlds, and outdated CM process which highlights a

major gap in the literature. This highlights the importance of this study which could be

used as a baseline for the development of Configuration Management Maturity Model.

The importance of this research is evident from the fact that Configuration Management

Maturity Model is developed for the first time with the help of Configuration

Management professionals on the basis of critical success factors and barriers to CM

implementation. The process could be measured for the first time with the help of thirty-

five practices derived from Configuration Management process capabilities and can be

improved with little experience in less time and will help to target the weak areas to

improve the overall process performance.

The other important aspect to mention is that Configuration Management is still not well

understood and practiced against the requirements of international standards which are

pointed by previous researchers. On the other hand it is believed that Configuration

Management is ignored by academia which has greatly affected the growth of this field.

The growing requirements of Configuration Management and adaptation of standardized

methodologies, it is important for academic institutes to provide graduates to industries

having the necessary knowledge of Configuration Management before joining their role.

There is a great deal of research available which could help organization to better

implement Configuration Management practices which is highlighted in section 8.5.


276

8.4.2 Industrial perspective

This research highlights important aspects for the successful implementation and

continuous development of Configuration Management and has therefore significant

implications for industry.

The research study highlight the CM activity model which is a logical representation of

the identified twenty-one critical success factors organized in seven groups necessary for

establishing, maintaining, and continuously improving the Configuration Management

process. This activity model combines the core concepts of formal system model

development and the human activity model to help Configuration Management

professionals in the identification of actual or potential weaknesses in their

Configuration Management process. It is important for industries to give special

attention to the seven groups where decision taker(s) manage Configuration

Management strategies through effective communication channels and dedicated

boundary. Decision taker(s) ensure(s) that sufficient resources are available for the

execution of strategies and controlling of Configuration Management practices. The

important aspect in the execution and monitoring of a process is effective

communication which is effected by environment. The environment has a total control

on all activities of the process and has major role in the execution of the CM process.

Organizations need to pay special attention to the seven areas which would enable them

with effective Configuration Management process to fulfil customer requirements and

produce quality products.

The study also emphasize on the identification of nineteen barriers categorized in three

groups which would facilitate professionals in targeting specific areas for improvements.

The research outcome is significant since it highlights barriers related to specific areas

which are not only considered influential for the successful implementation of

Configuration Management but also for other allied fields such as Project Management

and Knowledge Management. It is believed that some of the obstacles need special

attention which are considered the root cause for many other barriers and have


277

substantially affected the implementation of the Configuration Management process. It

is advised that effective training and educational programmes should be in place which

could help in getting the required support from top management and alleviate the lack of

recognition and perceived importance of the Configuration Management process across

the organization. Organizations need to have special emphasis on these obstacles since it

is believed that several of these barriers have not only affected the organizational image

of the process but have also influenced the implementation of the process over the years.

This research presents Configuration Management Maturity Model which defines a path

of maturation to achieve excellence in Configuration Management practices. This study

provides baseline guidelines on Configuration Management process maturity to help

organizations in continuous improvement of their Configuration Management practices.

The organizations needs to emphasize on specific process capabilities extracted from

critical success factors and barriers which define the four levels of Configuration

Management Maturity Model. The Configuration Management professional can measure

the maturity of their Configuration Management practices through thirty-five practices

outlined for process capability on a four point scale. The study could help Configuration

Management professional to identify the potential areas of weakness in the process and

propose any remedial action(s).

8.5 Research application

This research is designed to help practitioners in the effective implementation and

continuous development of their CM practices working in both aerospace and defence

industries. Literature in other allied fields suggest that organization should target process

specific critical success factors which helps practitioners to work on areas responsible

for the success of the process, provide opportunities to avoid barriers, helps in

establishing directions to achieve their goals, and offer means of measuring the

effectiveness of their processes. Similarly the identification of barriers helps

organizations in establishing plans to avoid the possible factors which could be the real

reasons of failure or poor performance of their process. Targeting the highlighted critical


278

success factors, barriers, and governance aspects of the process and following the

maturity concept highlighted in the form of CMMM, organization can measure the level

of maturity of their process and target areas of improvements. This research is mainly

based on aerospace and defence industries, other commercial industries can also use the

outputs of this research to enhance their CM practices because of its generalisability.

It is important to mention that since the objective of this research is to enhance the

applications of CM, the first three studies (critical success factor, barriers, and CM

governance) can be used independently and areas of weakness can be targeted to

improve the CM practices. Since the critical success factors and barriers to CM

implementation are extracted in the form of process capabilities which are further

explained with the help of thirty five constructs (practices), organizations needs to

emphasis on these constructs. To start with, it is essential to measure the CM

applications with the help CM professionals working on multiple projects with the help

of maturity questionnaire (Appendix F). This will provide data in the form of mean

values through which not only maturity of the overall process is calculated but will also

provide data regarding different maturity levels. On the basis of this data, areas of

weakness can be easily highlighted and remedial action could be planned accordingly.

Further details of this issue is well elaborated in Chapter 7.

8.6 Recommendations and further research

It was not possible to explore all the emerging dimensions of this research because of the

time limitation. There are some areas which are not addressed in this research while

other requires further research to generalize the concept. Following are the areas which

needs further investigations:

This research is mainly focused on aerospace and defence industries to identify and

frame the critical success factors and barriers to Configuration Management

implementation and develop the CM maturity model. The focus on these industries

raises an associated question of what is the current situation of this practice in


279

commercial sectors. It is believed that commercial sectors have either limited

understanding of CM, or fragment it through several business processes. Research could

be done in these sectors to investigate the implementation status of Configuration

Management practices, cost versus benefit analysis, barriers to the process that have

limited its implementation, and areas that can contribute in the effective implementation

of the CM process in these sectors.

It is important to target some issues on priority e.g., the issue of cost versus benefit

analysis – one of the weak areas in the limited CM literature- which may answer many

concerns highlighted as barriers to Configuration Management implementation. This has

been observed a major concern since CM is often not realistically followed because of

its overall cost overhead related to the specialized CM process just like Quality

Management was ignored in the past. It is important to work on multiple issues e.g. how

standard bodies are linked through companies and take care of the specific companies

requirements in the standardization process, the extent of flexibilities which could be

allowed between two extremely different projects (e.g. small vs. large or complex vs.

simple), and how to deal with the environment in extreme project pressures?

The model has been tested with the help of Configuration Management professionals

working in aerospace and defence industries but it would be more effective to test in

three facilities at-least to come-up with the pros and cons of this model during

application. It was initially part of this research but because of the time limitation and

some other constraints it was not possible to further investigate the issue. It is important

to investigate the different aspects of this model and improve the concept to ensure the

applicability of this model during implementation.

280

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296

APPENDIX A

CRITICAL SUCCESS FACTORS FOR THE IMPLEMENTATION OF WORLD-

CLASS CONFIGURATION MANAGEMENT PROCESS

This questionnaire is part of a research in The University of Manchester. We are looking

to identify the Critical Success Factors which could directly affect the implementation of

World-Class configuration management process in organizations. These critical success

factors would help us in developing a model for the continuous maturity of configuration

management process within organizations.

This questionnaire will take approximately 15 minutes to complete. This data are

gathered in confidence and shall not be communicated in any form to identify

participants without prior permission. Please give your opinion by providing text, numbers

and ( �� ) mark where applicable.

1. GENERAL INFORMATION

S. NO Questions Responses

a. Name?

b. Gender? 1. Male:

2. Female:

c. Contact details? Email: ___________________

Phone: ___________________

Appendix A

297

d. What is your academic

qualification(s)? 1. Bachelor Degree:

2. Master Degree:

3. Doctorate Degree:

4. HND / HNC:

5. Other: _________________

e. Do you have any form of

Configuration Management

qualification / training?

Provider: __________________

Duration: __________________

f. For how long you have worked in a

Configuration Management role? 1. Less than 5 Years:

2. Between 5 to 10 Years:

3. Between 10 to 15 Years:

4. 15 years and above:

g. Have you worked previously in

stakeholder departments e.g. quality,

design, and manufacturing etc?

Department: ____________________

Experience in Years: ______________

h. In which tier does your organization

belong? Have you previously worked

in another tier?

1. Tier one ( Experience in Years): __

2. Tier two ( Experience in Years): __

3. Tier three ( Experience in Years): _

i. What type of Configuration

Management organization do you

have in your company?

1. Centralized:

2. Decentralized:

3. Matrix:

Appendix A

298

j. How many people are working in

Configuration Management role

within your organization?

Number of Peoples: __________

k. In which sector of the defence

industries does your company exist

in?

1. Aerospace:

2. Military Hardware:

3. Naval:

4. Software / Systems:

5. Munitions:

6. Others: _________________

2. CRITICAL SUCCESS FACTORS

S. No Critical Success Factors What is your Opinion?

a. Management Support

Management support is very important

for the implementation of world-class

configuration management Process.

b. Configuration Management

Organization

Without proper configuration

management organization, it is hard to

implement an effective configuration

management process.

Appendix A

299

c. Effective Leadership

Experienced and Dedicated head of the

Configuration Management Process is

very important to take the current

process to a world class status.

d. Clear Vision, Mission, and Policies for

Configuration Management Process

Organizations should have clear vision,

mission, and policies for the

implementation of best configuration

management process.

e. Configuration Management Planning

Configuration management planning

plays a vital role in achieving best

configuration management process.

f. Competent Configuration

Management Practitioners

Competent configuration management

Practitioners are very important for the

implementation of an efficient


g. Professional Development

Professional Development of all

personnel involved directly or indirectly

in the configuration management

activities can play a leading role in the

implementation of world class


Appendix A

300

h. Effective Support from the

Stakeholder Departments

Effective support from the Stakeholder

departments (Quality, Manufacturing,

and Design etc.) is very important for

the implementation of the best


i. Adequate Resources Allocation

Lack of resources (HR, financial, etc)

can affect the level of implementation of

configuration management.

j. Organizational Culture

Organizations must have a supportive

culture where configuration

management is every bodies job to

achieve excellence in configuration

management practice.

k. User friendly Software (tool) for

Configuration Management

Organizations can achieve a world-class

status of configuration management if

the selected Software (tool) for

Configuration Management is user

friendly and meets the requirements of


l. Effective Control of Configuration

Management Process at Vendor

Premises

Configuration management process at

Appendix A

301

vendor premises should be checked at

regular interval as it will directly effect

the quality of the products and effect the

overall image of the configuration

management process within

organization.

m. Effective Communication of

Configuration Management with

Stakeholder Departments

Effective and prompt communication

between configuration management and

Stakeholder departments is necessary to

have an excellent configuration

management process.

n. Previous Configuration Management

Experience

At least one of the key configuration

management team members should have

previous experience of configuration

management execution to achieve world

class status for configuration

management process.

o. Continuous improvement in

configuration management practices

Continuous improvement in

configuration management practices is

vital to achieve and maintain world-class


p. Committed and focused configuration

management practitioner

Hardworking and focused configuration

Appendix A

302

management staff is the backbone of

world-class configuration management

process.

q. Team work

Team work during configuration

management practices plays an

important role to enhance the


r. Politics free projects environment

Politics within projects have negative

effects on the overall performance of


s. Flexibility in Configuration

Management Practices

Best configuration management

processes should have flexibility in their

execution where the level of

implementation could be different

depending on the complexity and size of

the products.

t. Recognition of Configuration

Management Employees Efforts

Recognition of efforts of configuration

management staff by the top

management is very important for

continuous improvement of

configuration management practices.

Appendix A

303

u. Equal Career Progression

Opportunities for Configuration

Management Staff

Equal career progression opportunities

for configuration management staff

enhance the configuration management

practices within organization.

3. Based on your own experience, can you list below any additional factors which are not

listed above and are most critical for the successful implementation of Configuration

Management process?

a.

b.

c.

d.

e.

f.

g.

4. As a result of your experience with the Configuration Management Process, can you list

below the problems, which in your opinion are the main barriers in the continuous

improvement of configuration management process?

Appendix A

304

a

b

c

d

e

f

g

THANK YOU VERY MUCH FOR TAKING THE TIME TO COMPLETE THIS

QUESTIONNAIRE

Once you have completed this questionnaire, post it to Mr. Callum Kidd, Room E2, Pariser

Building Sackville Street, School of Mechanical, Aerospace and Civil Engineering, The

University of Manchester, Manchester, M13 9PL.

305

APPENDIX B

INTERVIEW GUIDE

PURPOSE

The purpose behind this interview is twofold, first to explore the barriers which CM

practitioners faces in the effective implementation of CM process and second to define

mechanisms for the efficient governance of this process

CONFIDENTIALITY AGREEMENT

It is important that all participants know that the information given in this interview is

confidential to The University of Manchester. The University of Manchester is fully

aware of the importance of maintaining secrecy of the individual participant. No

research participant will be referenced, identified, or comments attributed to them by

name without the formal written permission of the individual participants.

GENERAL INFORMATION

S. NO QUESTIONS RESPONSES

a. Name

b. What is your Academic Qualification(s)?

c. Do you have any Configuration Management

Qualification / Training?

d. For how long you have worked in a Configuration

Management role?

Appendix B

306

BARRIERS IN THE IMPLEMENTATION OF CM PROCESS

Question 1: During your career as a CM practitioner, what execution based problems

did you observe / face in the effective implementation of the configuration management

process?

Question 2: Do you think that following typical factors act as barriers in the

implementation of Configuration Management? If yes than how we can overcome these

barriers?

a. Lack of top management support

b. Lack of CM awareness and importance at top management level

c. Lack of support from Project Managers

d. Lack of Authority to Implement CM Principles

e. Incompetent CM Leadership

f. Lack of centralized corporate body (Lack of Core CM team)

g. Lack of CM Training

h. Lack of career progression for CM professionals

j. Lack of Simplified and Updated CM Standards

k. Lack of effective CM procedures

l. Lack of an adequate or current CM Plan

m. Lack of CM Process Across Life-Cycle

n. Outdated CM Process

o. Lack of early involvement within projects

p. Lack of clear road map for continuous process improvement

q. Lack of CM awareness in customer world

r. Lack of understanding the role / importance of CM by employees

s. Lack of support from stakeholders

t. Recruitment of non-technical staff

u. Lack of effective CM tools

v. Lack of Resources

Appendix B

307

CM GOVERNANCE

Question 1: Can you explain the CM structure in your organization? Is it the most

appropriate, if no, what would be the most appropriate structure [centralized

(functional), decentralized (divisional), hybrid, and matrix)? Who should be both

accountable and responsible for the CM process?

Question 2: What are the specific CM roles within your organization (e.g. CM analyst,

CM Engineer, CM Manager)? Are they always engineers?

Question 3: What qualification, academic and professional, would they typically have

level by level (e.g. degree, CM certification)?

Question 4: In your opinion, who should define CM rules and regulations within

organizations? From where should these rules be reviewed and approved?

Question 5: Who should deal with CM related issues with vendors within an

organization? What are the current practices?

308

APPENDIX C

BARRIERS IN THE IMPLEMENTATION OF CONFIGURATION

MANAGEMENT (CM) PROCESS

This questionnaire is part of a research work in The University of Manchester. We are

looking to identify and finalize the barriers in the implementation of the configuration

management process. This data will help us in developing a model for maturating

configuration management as a process.

This questionnaire will take approximately 10 minutes to complete. This data is gathered

in confidence and shall not be communicated in any form to identify participants without

prior permission. Please give your opinion by providing text, numbers and / or dot mark

where applicable.

The questionnaire is in two parts i.e. general information and barriers in the

implementation of configuration management with a total of 31 questions.

1. General Information

S No QUESTIONS RESPONSES

1. What is your name?

2. What is your gender? Male:

Female:

3. What is your academic

qualification(s)?

HND / HNC:

Bachelor degree:

Master degree :

Doctorate degree :

Other (please specify):

Appendix C

309

4. Do you have any configuration

management qualification /

training?

Provider:

Method of delivery:

5. For how long have you worked

in a configuration management

role?

Less than 5 years:

Between 5 to 10 years:


15 years and above:

6. Have you worked previously in

stakeholder departments e.g.

quality, design, and

manufacturing etc?

Design:

Manufacturing:

Quality:

Project Management:

Other (please specify):

7. For how long have you worked

in the stakeholder departments

as highlighted in the previous

question?

Less than 5 years:



15 years and above:

8. How many projects have you

worked-on as a configuration

management practitioner?

Less than 10 projects:

Between 10 to 30 projects:

More than 30 projects:

9. How would you define the size

of your organization in terms

of employees?

Less than 500 employees:

Between 500 to 3000 employees:

More than 3000 employees:

10. How many people are working

in a configuration management

role within your organization?

Number of People:

11. In which sector do you

currently work in?

Aerospace:

Defence:

Appendix C

310

Naval:

IT:

Munitions:

Others (please specify):

2. Barriers in the implementation of configuration management (CM)

S. No Barriers in CM Implementation rank the statement by

checking one option

1.

Lack of top management support

Top management doesn’t understand the role,

importance, and criticality of CM process within

projects and hence ignore it.

1 not at all true

2 slightly true

3 somewhat true

4 mostly true

5 completely true

2. Lack of centralized body for the

governance of CM

Existence of centralized CM body for managing

CM activities is either missing or not effective,

resulting in lack of cross fertilisation of skills

and losing control on maintaining consistency

across projects.

1 not at all true

2 slightly true

3 somewhat true

4 mostly true

5 completely true

3. Lack of CM training across organizations

Lack of CM knowledge across organizations is

evident since management and even

stakeholders are unaware of the role and

importance of CM.

1 not at all true

2 slightly true

3 somewhat true

4 mostly true

5 completely true

Appendix C

311

4. Lack of authority to implement CM

principles / policies

Authorities of CM personnel to implement CM

activities are not effective because of their

dependencies on staff to whom they are

responsible being unfamiliar with the

importance of CM.

1 not at all true

2 slightly true

3 somewhat true

4 mostly true

5 completely true

5. Implementation costs outweigh CM

benefits

CM has been viewed as an overhead on projects

in terms of cost. Cases may arise where CM

implementation cost looks high and not feasible

within overall cost of some projects.

1 not at all true

2 slightly true

3 somewhat true

4 mostly true

5 completely true

6. Lack of recognition and underestimating

the importance of CM at every level of the

organization

CM process is not getting the due importance

and recognition from the top and is

underestimated at every level of the

organization.

1 not at all true

2 slightly true

3 somewhat true

4 mostly true

5 completely true

7. Lack of career progression for CM

professionals

People don’t join or continue their career in CM

because of lack of career progression for CM

professionals in organizations.

1 not at all true

2 slightly true

3 somewhat true

4 mostly true

5 completely true

Appendix C

312

8. Poorly defined CM requirements and

process

CM is not very well defined within

organizations. CM standards address general

requirements that require extensive

implementation procedures, which could be

interpreted in different ways by a CM

manager.

1 not at all true

2 slightly true

3 somewhat true

4 mostly true

5 completely true

9. Lack of maintaining consistency in CM

practices across projects

Organizations face a lack of consistency in the

CM activities from projects to projects.

1 not at all true

2 slightly true

3 somewhat true

4 mostly true

5 completely true

10. Lack of flexibility in CM process

CM process is inflexible in terms of

requirements for both complex and simple

projects hence doesn’t facilitate project

managers and as a result CM concepts can be

used inappropriately.

1 not at all true

2 slightly true

3 somewhat true

4 mostly true

5 completely true

11. Outdated CM process

CM process (standards & policies) has remain

unchanged and never been in-line with other

processes which have been optimized over the

years to cope with technological advancements.

1 not at all true

2 slightly true

3 somewhat true

4 mostly true

5 completely true

Appendix C

313

12. Lack of current CM plans

CM plans are unavailable / not effectively

generated / not updated through life cycle of

projects; hence create difficulty in the

implementation of CM activities within

products.

1 not at all true

2 slightly true

3 somewhat true

4 mostly true

5 completely true

13. Lack of CM process across the lifecycle

CM process has never received the due credence

across the lifecycle of projects especially in the

early phase and the maintenance / modification

phase of projects.

1 not at all true

2 slightly true

3 somewhat true

4 mostly true

5 completely true

14. Lack of CM awareness in customer world

There is a lack of awareness on the need and

benefits of CM in the customer world which

could facilitate them to ensure the availability of

quality products and maintain it through the

lifecycle.

1 not at all true

2 slightly true

3 somewhat true

4 mostly true

5 completely true

15. Lack of effective Communication

Lack of communication with stakeholders and

among CM groups create delays in the

completion of tasks and create disparity in CM

policies from project to project.

1 not at all true

2 slightly true

3 somewhat true

4 mostly true

5 completely true

Appendix C

314

16. Lack of effective CM tools

Organizations still face difficulty to get the right

CM tool to suit their process in terms of

fulfilling the company CM specific requirements

and satisfaction in ease of use.

1 not at all true

2 slightly true

3 somewhat true

4 mostly true

5 completely true

17. Lack of resources

Organizations have never had enough resources

for CM in terms of personnel, equipment, and

funding etc. for the effective implementation of

CM process.

1 not at all true

2 slightly true

3 somewhat true

4 mostly true

5 completely true

18. Lack of support from stakeholders

Stakeholders (project management, quality,

design etc.) don’t support CM implementation in

terms of requirements (HR, work processing

requirements, timely completion, etc) and hence

create delays in CM practices.

1 not at all true

2 slightly true

3 somewhat true

4 mostly true

5 completely true

19. Extreme project pressures

CM policies are disregarded and not practiced

by projects mainly due to extreme project

pressures to meet demands in urgency.

1 not at all true

2 slightly true

3 somewhat true

4 mostly true

5 completely true


QUESTIONNAIRE

315

APPENDIX D

INTERVIEW GUIDE

PURPOSE

The purpose behind this interview is to discuss ways and establish consensus on an

agreed maturity model that would help us in the effective implementation and

continuous development of a CM process.

CONFIDENTIALITY AGREEMENT

It is important that all participants know that the information given in this interview is

confidential to The University of Manchester. The University of Manchester is fully

aware of the importance of maintaining secrecy of the individual participant. No

research participant will be referenced, identified, or comments attributed to them by

name without the formal written permission of the individual participants.

GENERAL INFORMATION

Names of participant:

Academic qualification:

CM training:

CM experience:

Appendix D

316

CONFIGURATION MANAGEMENT MATURITY MODEL

Finalization of key capability areas

1. Are there any missing parameters in the attached list which you think would be

influential for the effective implementation and continuous development of a CM

process?

Measuring the strength of each parameter

2. What are the most important aspects to enquire when measuring the strength of each

parameter in a facility? What is your opinion about these highlighted practices?

3. What scales would you advise to measure the strength of these parameters (through

questions highlighted above) to evaluate its presence within an organization?

Defining the maturity levels and its key characteristics

4. How many maturity levels would you suggest when developing a maturity model on

the basis of the key parameters finalized above and why? What is your opinion about

this (presented proposed model) highlighted model?

5. How would you populate the key parameters finalized above in the maturity levels

finalized through question 4? Give your opinion on the proposed model and

populated parameters at each level.

Testing

6. How can we test the applicability and usability of this maturity model?

Appendix D

317

Applications

7. Do you believe that this model is only limited to aerospace and defence sectors or

could be used an effective tool for maturating the CM process in any other sector?

318

APPENDIX E

VALIDATION OF THE CONFIGURATION MANAGEMENT

MATURITY MODEL

This questionnaire is part of a research work in The University of Manchester. The objective of

this questionnaire is to validate the configuration management maturity model which is

developed as part of our research work through continuous interaction with configuration

management professionals working in different aerospace and defence sectors.

The questionnaire is divided in three sections i.e. general information having 5 questions,

structure of configuration management model (detail information on the model structure), and 17

questions on “model validation” at the end.

It is important to note that data is gathered in confidence and shall not be communicated in any

form to identify participants without prior permission. Please give your opinion by providing

text, numbers or selecting an option(s) from multiple choices.



e. What is your gender? Male:

Female:

f. What is your Academic

Qualification(s)?

Bachelor Degree:

Master Degree :

Doctorate Degree :

HND / HNC:

Other:

g. For how long you have worked in a

Configuration Management role?

Less than 5 Years:

Between 5 to 10 Years:


Appendix E

319

15 years and above:

h. In which sector do you currently

work in?

Aerospace:

Defence:

Others:

i. In which country do you work?

j. If you are interested in the results of

this survey, please add your name

and email below.

name:

email:

2. Structure of configuration management maturity model

The configuration management maturity model is a four staged (static, reactive, proactive, and

dynamic) maturity model and is based on configuration management process capabilities. The

process capabilities for configuration management are finalized by analysing the data obtained

from the studies on critical success factors, barriers to configuration management

implementation, and semi structured interviews with configuration management professionals.

The configuration management process capabilities will be measured with the help of thirty-five

practices on a four point scale. The four point scale (static, reactive, proactive, and dynamic) will

be used to determine the overall maturity of the process in organization.

2.1. Configuration Management Maturity Model

Note: Figure 7.2 was provided in this place.

2.2. Configuration Management Process Capabilities

Note: Figure 7.1 was provided in this place.

2.3. Practices

Note: All thirty five practices (P1 to P35) highlighted in chapter 7 were provided in this place.

2.4. Scale to measure the maturity of CM process

All 35 practices will be measured on a four-point-scale i.e. Static, Reactive, Proactive, and

Dynamic. The criteria for marking each practice are given below.

Appendix E

320

Note: same text for scale discussed in appendix F and highlighted in chapter 7 was provided in

this place.

3. Validation of Configuration Management Maturity Model

In this section there are seventeen statements to measure the effectiveness of the CM maturity

model explained in section 2 on five point scale. Please rank each statement by keeping in view

the CM maturity model explained in section 2.

Statement strongly

disagree disagree Neutral agree

strongly

agree

Effective implementation and

continuous development of


can be largely facilitated through

workable configuration management

maturity model.

1 2 3 4 5

The configuration management

maturity model based on key process

capabilities extracted from critical

success factors and barriers to

configuration management

implementation is the most effective

way to establish such models.

1 2 3 4 5

The four levels of maturity of the

configuration management maturity

model provide the necessary depth for

the implementation and continuous

development of configuration

management process.

1 2 3 4 5

The key process capabilities dedicated

to each maturity level shows its correct

representation.

1 2 3 4 5

Appendix E

321


maturity model has covered the core

elements of configuration management

process which are the requirements of

any international configuration

management standards.

1 2 3 4 5


maturity model covers all support

areas necessary for the implementation

and continuous development of


1 2 3 4 5

All thirty-five practices explaining the

configuration management process

capabilities are easy to understand and

are rightly explained to achieve the

desired goals.

1 2 3 4 5

All thirty-five practices are general in

nature and will equally apply to most

industries.

1 2 3 4 5

All thirty-five practices cover the

required parameters necessary for the

implementation and continuous

development of configuration

management practices.

1 2 3 4 5

The four point scale is well defined

and will provide the desired results

while measuring the strength of each

practice and maturity of an overall


1 2 3 4 5

Appendix E

322

Implementation of process capabilities

in small groups at different levels of

maturity will help practitioners to

better implement the configuration

management process.

1 2 3 4 5

Implementation of configuration

management maturity model does not

need much experience of the maturity

process but demands understanding of

the configuration management process.

1 2 3 4 5

It is more realistic for industries to

implement and progressively improve

their configuration management

process by adopting this model.

1 2 3 4 5

It is easier to implement and improve


by adopting this maturity concept

instead of any other haphazard

methodology.

1 2 3 4 5


maturity model will help organizations

to identify areas of weakness and

prioritise actions to streamline their


1 2 3 4 5

Questions asked in this questionnaire

have provided the necessary depth to

assess strengths and weaknesses of the

configuration management maturity

model.

1 2 3 4 5

Appendix E

323

Any further research on the topic

would be useful and help industries in

finding useful ways to transform their


1 2 3 4 5

You can add your suggestions / remarks here on the maturity model or validation process

which you think could help us in developing this concept.

S No Your Comments

1.

2.

3.

4.

5.


QUESTIONNAIRE

324

APPENDIX F

CONFIGURATION MANAGEMENT PROCESS MATURITY

This questionnaire is part of a research work in The University of Manchester. The objective of

this questionnaire is to know the maturity of configuration management process within

aerospace and defence sectors and establish the designed hypothesis.

This questionnaire will take approximately 20 minutes to complete. This data is gathered in

confidence and shall not be communicated in any form to identify participants without prior

permission. Please give your opinion by providing text, numbers and / or check the appropriate

statement.

The questionnaire is in two parts i.e. general information having 6 questions and “fundamental

practices for configuration management process maturity” which has 35 questions.



k. What is your gender? Male:

Female:

l. What is your Academic

Qualification(s)?

Bachelor Degree:

Master Degree :

Doctorate Degree :

HND / HNC:

Other:

m. For how long you have worked in a

Configuration Management role?

Less than 5 Years:



Appendix F

325

15 years and above:

n. In which sector do you currently work

in?

Aerospace:

Defence:

Others:

o. In which country do you work?

p. If you are interested in the results of this

survey, please add your name and email

below.

name:

email:

3. Configuration Management Process Maturity

� Important note on the scale

Please mark the following 35 statements on a four-point-scale i.e. Static, Reactive, Proactive,

and Dynamic by keeping in view the implementation of each statement within your facility.

Explanation on the scale is given below.

1. Static (not properly implemented)

The practice is not properly practiced or supported.

2. Reactive (limited implementation)

The practice is limited to specific projects and has lack of holistic implementation across

projects and product life cycle. There is a visible lack of support from all functional

stakeholders.

3. Proactive (good implementation across projects)

The practice is fully implemented or provides the necessary support in the implementation of

CM practices across projects. The CM process is uniformly implemented across projects

irrespective of their size and complexity because of the lack of necessary flexibilities in CM

Appendix F

326

policies which most of the time diminish its importance in small projects because of its cost

versus benefit analysis. The environment is not supportive to accommodate new changes which

lacks in performance monitoring and continuous development of the process.

4. Dynamic (best implementation across projects)

The practice is effectively implemented or provides the desired support in the effective

implementation of the process to accommodate project specific requirements. Through

established improvements methodologies and supportive environment, inadequacies arising with

time are removed to assure effective implementation and continuous development of the process.

Please mark single option for each statement below

Statement Static Reactive Proactiv

e Dynamic

P1: The CM process is available in the form

of documented procedures describing the

organizational policies, activities, and

conventions related to CM planning,

configuration identification, configuration

control, configuration status accounting, and

configuration auditing.

1 2 3 4

P2: CM practices are implemented in all

projects irrespective of the value or

complexity of that project.

1 2 3 4

P3: Product configurations (hardware system

and software) and their related configuration

documentation have a strong correlation and

unique identification.

1 2 3 4

P4: Configuration documentation is released

through a formal release process which 1 2 3 4

Appendix F

327

includes the review and approval of all

functional stakeholders.

P5: The CM process specifies the rules and

procedures to identify and control

configuration items across all projects.

1 2 3 4

P6: The CM process specifies requirements

of managing baselines from concept to

disposal of the product or system, which are

implemented across projects through the

application of company-wide procedures.

1 2 3 4

P7: The configuration change management

process is implemented through a closed loop

cycle where configuration changes are

identified, documented, evaluated, and

implemented with appropriate approval.

1 2 3 4

P8: Engineering changes are classified in two

high-level categories i.e. permanent changes

(dealt through ECOs or ECPs) and temporary

changes (dealt through waivers and

deviations) which are properly identified and

recorded across all projects.

1 2 3 4

P9: The Change Control Board (CCB) is the

sole authority to accept or reject both 1 2 3 4

Appendix F

328

permanent and temporary changes.

P10: Configuration status accounting is in

place to capture and maintain product

configuration information throughout the

product life cycle.

1 2 3 4

P11: The physical and functional

configuration audits are conducted to provide

assurance of the physical and functional

configuration verifications before release of

the products to customers.

1 2 3 4

P12: The documented CM process fulfils

detailed requirements of any latest

international standard(s) on CM [e.g. EIA-

649 (Rev B)] which covers the sub-elements

of all areas highlighted from P3 to P11.

1 2 3 4

P13: The configuration management process

is governed through a defined organization

with dedicated staff having documented

responsibility and authority.

1 2 3 4

P14: Configuration management planning is

the fundamental activity during project

specific CM activities which are managed

through updated CM plans throughout the

1 2 3 4

Appendix F

329

product life cycle.

P15: The CM process is managed and

governed by a dedicated individual having

in-depth knowledge of CM and leadership

qualities.

1 2 3 4

P16: The CM process is backed by CM

expert(s) having previous experience with a

team of competent, committed, and focused

practitioners (according to requirements) to

carry out CM activities according to defined

CM principles and practices.

1 2 3 4

P17: The CM process has the required

infrastructure (buildings, equipment etc.) and

resources (human and financial) to

effectively execute the process within

projects.

1 2 3 4

P18: The CM process is supported by a

software tool which is easy to use and fulfils

the organizational requirements to effectively

implement and support CM principles and

practices.

1 2 3 4

P19: Professional development is part of the

organizational training programme to create 1 2 3 4

Appendix F

330

awareness, importance, and help in the

implementation of CM methodologies and

related fields in the organization where

required.

P20: Management understands the importance

of CM practices and are committed to

establish CM as a core business area.

1 2 3 4

P21: CM is recognized as a key process area

where both management and stakeholders

understand the importance and criticality of

the process.

1 2 3 4

P22: The growing awareness and importance

of CM practices has resulted in career

progression opportunities for CM

professionals similar to those in the fields of

project management, quality engineering, and

design etc.

1 2 3 4

P23: CM managers have the authority through

strong backing of senior management to

implement the process against established

guidelines.

1 2 3 4

P24: Stakeholders understand the importance

of CM, provide the required resources, 1 2 3 4

Appendix F

331

ensure effective coordination, and show

commitment to effectively implement the

process.

P25: The communication with both internal

and external customers is open, timely, and

free flowing both from top to bottom and

bottom to top.

1 2 3 4

P26: It is our company policy to maintain

close liaison with external customers to make

them aware of the completion of their major

milestone and ensures their active

participation in product design reviews to

validate their requirements before finalization

of product specifications.

1 2 3 4

P27: Organizational culture does support the

effective implementation and continuous

development of the CM process.

1 2 3 4

P28: The working environment is politics free

where decisions are made on merit to ensure

holistic implementation of the process for

quality products.

1 2 3 4

P29: CM professionals work as a team while

establishing, implementing, and continuously 1 2 3 4

Appendix F

332

improving CM practices.

P30: CM is planned against international

standards at a vendor’s premises which fulfils

your organizational CM requirements and is

assured through periodic audits to ensure

production of acceptable and consistent

products.

1 2 3 4

P31: CM practices are consistent throughout

the organization irrespective of the size and

complexity of projects and across the projects

or products life cycle phases whether it is

concept, development, production, and

maintenance or modification.

1 2 3 4

P32: CM practices are flexible and may vary

to accommodate project specific

requirements based on the complexity,

criticality, and project / product life cycle

phases while ensuring compliance with

company-wide CM principles and practices.

1 2 3 4

P33: CM system audits are planned and

conducted periodically to identify areas of

weakness, plan remedial actions, and address

needs to enhance performance of the process

1 2 3 4

Appendix F

333

in terms of identified and measurable criteria.

P34: The CM process is continuously

improved through small incremental changes

to accommodate technological advances,

reduce limitations of the process, and induce

more flexibility within the rigidity you have.

1 2 3 4

P35: CM activities are planned, effectively

communicated, and properly executed by

keeping in mind the criticality of tasks with

respect to project scheduling to effectively

handle project pressures.

1 2 3 4

S No Your Comments (if any)

6.

7.

8.

9.


QUESTIONNAIRE