waranpong boonsiritomachai a research framework for the adoption of business intelligence by smes

A Research Framework For The Adoption Of Business Intelligence By SMEs / 2014 Waranpong Boonsiritomachai, SEAANZ 2014

A Research Framework

For The Adoption Of

Business Intelligence By SMEs

Waranpong BoonsiritomachaiPrincipal supervisor : Professor Michael McGrath

Co-supervisor : Assoc. Professor Stephen Burgess

Victoria University, Melbourne

Date : 17 July 2014

A Research Framework For The Adoption Of Business Intelligence By SMEs / 2014 Waranpong Boonsiritomachai, SEAANZ 2014

• The reasons why firms need to adopt BI

• Definition of BI

• Research questions

• The process in developing this

research framework

Overview

A Research Framework For The Adoption Of Business Intelligence By SMEs / 2014 Waranpong Boonsiritomachai, SEAANZ 2014

• Competition

• Product

flexibility

• Demanding

customers

Highly

complex and

dynamic

environments

A Research Framework For The Adoption Of Business Intelligence By SMEs / 2014 Waranpong Boonsiritomachai, SEAANZ 2014

data

overload

challenges

International Data Corporation, 2012

90% Unstructured

Data

48%

Digital Data

A Research Framework For The Adoption Of Business Intelligence By SMEs / 2014 Waranpong Boonsiritomachai, SEAANZ 2014

S’WARE2.9%

ICT3.6%

BI8.7%

What is BI?

A Research Framework For The Adoption Of Business Intelligence By SMEs / 2014 Waranpong Boonsiritomachai, SEAANZ 2014

Business Intelligence (BI)

“ The capability of an enterprise to use its human resources together with a broad category of processes, applications and technologies for accessing, collecting and analysing data in order to generate actionable and competitive information that can support its users to make better decisions.”

A Research Framework For The Adoption Of Business Intelligence By SMEs / 2014 Waranpong Boonsiritomachai, SEAANZ 2014

2,053 CIOs

36 industries

41 countries

“BI is a first priority

in technology

investment”

Gartner Research, 2013

A Research Framework For The Adoption Of Business Intelligence By SMEs / 2014 Waranpong Boonsiritomachai, SEAANZ 2014

A Research Framework For The Adoption Of Business Intelligence By SMEs / 2014 Waranpong Boonsiritomachai, SEAANZ 2014

Small and medium sized

enterprises (SMEs) have

lagged in BI uptake.

Wirtschaft, P, Schieder, C, Kurze, C,

Gluchowski, P & Bohringer, M 2010

‘Benefits and challenges of business intelligence adoption in small and medium-sized enterprises’, paper presented to 18th European Conference on Information Systems, 7-9 June 2010, Pretoria, South Africa.

A Research Framework For The Adoption Of Business Intelligence By SMEs / 2014 Waranpong Boonsiritomachai, SEAANZ 2014

BI in SMEs

Flawed Decisions• instinctive

knowledge • inadequate

access to information

• loss of productivity

• less agility in the market place

Hilgefort, I 2010, Inside SAP BusinessObjects Explorer, SAP Press, Boston.

A Research Framework For The Adoption Of Business Intelligence By SMEs / 2014 Waranpong Boonsiritomachai, SEAANZ 2014

TODAY

BI more diverse, flexible, cheaper

and less complex.

SMEs need BI

LogicXML 2009, BI for small and mid-sized businesses, LogicXML, <http://www.logixml.com/content/02_SMBMarket.pdf>.

A Research Framework For The Adoption Of Business Intelligence By SMEs / 2014 Waranpong Boonsiritomachai, SEAANZ 2014

A Research Framework For The Adoption Of Business Intelligence By SMEs / 2014 Waranpong Boonsiritomachai, SEAANZ 2014

Research questions

1. What is the state of BI

adoption in SMEs?

2. What are the enabling factors

affecting the adoption of BI

in SMEs?

A Research Framework For The Adoption Of Business Intelligence By SMEs / 2014 Waranpong Boonsiritomachai, SEAANZ 2014

Developing the research framework

1. Classify the SMEs to levels of BI

adoption

2. Determine the enabling factors affecting

BI adoption

A Research Framework For The Adoption Of Business Intelligence By SMEs / 2014 Waranpong Boonsiritomachai, SEAANZ 2014

BI Maturity Model

No common classification

of BI level adoption among

researchers.

STEP 1: Classify SMEs to levels of BI adoption

A Research Framework For The Adoption Of Business Intelligence By SMEs / 2014 Waranpong Boonsiritomachai, SEAANZ 2014

BI Maturity Model

BI Maturity Model

Source Concentration AreaFirst level Second level Third level

IEM SAS (2004) Operate Consolidate Integrate

TDWI Eckerson (2007) Infant Child Teenager

BIDM Sacu and Spruit (2010)

Predefined reporting

Department data warehouse

Enterprise-wide data warehouse

EBIMM Chuch (2010) Initial Repeatable Defined

Individual Department Enterprise

Source: Adopted from SAS (2004), Eckerson (2007), Sacu and Spruit (2010) and Chuah (2010)

A Research Framework For The Adoption Of Business Intelligence By SMEs / 2014 Waranpong Boonsiritomachai, SEAANZ 2014

Information Evolution Model (IEM)

Four different dimensions

Human Capital Infrastructure

Knowledge Processes Culture

A Research Framework For The Adoption Of Business Intelligence By SMEs / 2014 Waranpong Boonsiritomachai, SEAANZ 2014

Information Evolution Model (IEM)

five levels of Information

Evolution

Optimize

Integrate

Consolidate

Operate

InnovateHuman Capital Infrastructure

Knowledge Processes Culture

A Research Framework For The Adoption Of Business Intelligence By SMEs / 2014 Waranpong Boonsiritomachai, SEAANZ 2014

STEP 2: Determine the enabling factors affecting BI adoption

1. Diffusion of Innovation theory (DOI) by Rogers

(1983,1995,2003)

2. Technology-Organisation-Environment (TOE)

framework by Tornatzky and Fleischer (1990)

3. IS adoption model for small business by Thong

(1999)

Theoretical frameworks used

A Research Framework For The Adoption Of Business Intelligence By SMEs / 2014 Waranpong Boonsiritomachai, SEAANZ 2014

• Innovativeness• IT background

(knowledge)

• Competitive pressure

• Vendor selection

• Size• Age• Absorptive

capacity• Resource

availability

• Relative advantage

• Complexity• Compatibility• Trialability• Observability

Enabling factors affecting BI adoption

Organisational characteristics

Technological characteristics

Environmental characteristics

Owner-manager

characteristics

A Research Framework For The Adoption Of Business Intelligence By SMEs / 2014 Waranpong Boonsiritomachai, SEAANZ 2014

BI Adoption in SMEs

The Conceptual Framework

Organisational characteristics

Technological characteristics

Environmental characteristics

Owner-manager

characteristics

Optimize

Integrate

Consolidate

Operate

Innovate

BI Adoption in SMEs

A Research Framework For The Adoption Of Business Intelligence By SMEs / 2014 Waranpong Boonsiritomachai, SEAANZ 2014

• The proposed BI adoption framework is based

on literature review, thus it is open and requires

testing to determine its relevancy and validity in

the practical environment.

Conclusion and Future research directions

A Research Framework For The Adoption Of Business Intelligence By SMEs / 2014 Waranpong Boonsiritomachai, SEAANZ 2014

• Prospective outcomes are expected to provide a

clearer understanding of the BI adoption rates

which government agencies and IT providers can

design policies and tailor their products in

accelerating BI diffusion among SMEs.

Conclusion and Future research directions

A Research Framework For The Adoption Of Business Intelligence By SMEs / 2014 Waranpong Boonsiritomachai, SEAANZ 2014

Contact Details

Waranpong Boonsiritomachai

Phone 0430 611 580Email

waranpong.boonsiritomachai@live.vu.edu.au

A Research Framework

For The Adoption Of

Business Intelligence By SMEs

THANK YOU