a framework to analyse collaborative performance

www.elsevier.com/locate/compind

Computers in Industry 58 (2007) 687–697

A framework to analyse collaborative performance

France-Anne Gruat La Forme a,*, Valerie Botta Genoulaz b, Jean-Pierre Campagne b

a Laboratoire LIESP, INSA-LYON, F-69621 Villeurbanne, Batiment Blaise Pascal, 7 Avenue Jean Capelle, Franceb Laboratoire LIESP, INSA-LYON, F-69621 Villeurbanne, Batiment Jules Verne, 19 Avenue Jean Capelle, France

Available online 8 June 2007

Abstract

When competitiveness, responsiveness and customer satisfaction are keywords of a successful management in a business area, companies

cannot work in an autonomous way anymore. They have to get closer to their supply chain partners and to optimize their relations, to interface and

to integrate their information systems and decision-making in order to synchronize product flows and activities. In this context, the general

framework proposed in this paper characterizes the performance of the collaboration in supply chains and it is based on two models: a collaboration

characterization model and a collaboration-oriented performance model, both based on main supply chain business processes. The framework

proposed has been instanced and validated on an industrial case study.

# 2007 Elsevier B.V. All rights reserved.

Keywords: Supply chain; Business process; Collaboration; Performance indicators; Industrial case study

1. Introduction

When competitiveness, responsiveness and customer satis-

faction are keywords of a successful management in a business

area, companies cannot work in an autonomous way anymore,

but they have to get closer to their supply chain partners. A supply

chain is the whole system thanks to which, companies bring their

products and services up to their customers [1]. Indeed, the

industrial performance of a company depends more and more

strongly on its ability to optimize its relations with its partners,

suppliers or providers, to interface and to integrate its

information system and decision-makings, to synchronize its

products flows and activities. Owing to this problem, a company

has to rethink its organization, introduce new types of relation

with its partners, and increase the collaboration, the coordination

and the synchronization across the supply chain. This partnership

requires the establishment of processes of coordination,

collaboration or cooperation. One begins to speak about

collaborative supply chain [2] and the goal is to gain competitive

advantage, by improving overall performance with a holistic

perspective of the supply chain. An efficient collaboration across

* Corresponding author. Tel.: +33 4 72 43 62 34; fax: +33 4 72 43 85 38.

E-mail addresses: [email protected]

(F.-A. Gruat La Forme), [email protected] (V.B. Genoulaz),

[email protected] (J.-P. Campagne).

0166-3615/$ – see front matter # 2007 Elsevier B.V. All rights reserved.

doi:10.1016/j.compind.2007.05.007

the entire system is driven not only by the coordination of the

physical flows but also by the flow of different kinds of

information such as demand, capacity, inventory, scheduling,

through the supply chain. According to Barut et al. [3], the inter-

company integration and coordination via information sharing

has become a key success factor to improve the supply chain

performance. Nevertheless, little attention has been given to the

issue of measuring the effectiveness of information sharing and

collaboration across the supply chain.

Facing this problem, the consortium ‘‘COPILOTES’’

(Collaboration et Partage d’Information dans les chaınes

LogistiquES - Collaboration and information sharing in supply

chains), supported by the Region Rhone-Alpes (France) works

on the improvement of supply chain performance via collabora-

tion and information sharing. More precisely, the project aims at

bringing together companies, frameworks and tools allowing

them to qualify and to estimate the performance of their supply

chain, focusing on the different ways to collaborate with partners,

without forgetting related stakes and risks. This paper aims at

introducing one COPILOTES study about a general framework

characterizing the performance of the collaboration in supply

chains, by focusing on the exchanged information between

partners as well as on the exploitation of this sharing. Two models

compose this framework: one is focused on the collaboration

relationship characterisation and the other is a collaboration-

oriented performance model.

mailto:[email protected]



http://dx.doi.org/10.1016/j.compind.2007.05.007

F.-A. Gruat La Forme et al. / Computers in Industry 58 (2007) 687–697688

The following section surveys the related literature and

further isolates our contributions. Sections 3 and 4 describe the

collaboration characterisation model (cc model) and the

collaboration-oriented performance model (CoP model).

Section 5 presents the performance analysis that one can

realize from these two models and details a part of the results

obtained from the instantiation of the general framework on an

industrial case study.

2. Literature review

A supply chain is a network of organisations that are

involved, through upstream and downstream linkages, in

different processes and activities that produce value in the

form of products and services in the hand of the (ultimate)

customer [4]. The literature dealing with supply chain is rich

and has grown fast during the last few years. Among the works

realized on this subject, numerous terms emerge and some of

them need to be defined and explained before presenting the

core of this paper. In this literature review we present some

performance frameworks or supply chain models already

established and we specify notions like supply chain

processes, collaboration and performance indicators. Based

on this review, we elaborate two models, which compose a

general framework characterizing the performance of the

collaboration in supply chains.

2.1. Performance reference models

The collaborative performance within supply chains is still a

quite recent research subject. We identified five main process

reference models already established to analyse or evaluate a

supply chain: the strategic audit framework to improve supply

chain performance of Gilmour [5], the supply chain model of

Cooper et al. [6], the Supply Chain Council’s SCOR-model [7],

the logistics audit guides of the ASLOG association [8] and

finally the EVALOG frame of Ref. [9]. Even if these models are

not collaboration oriented, they consider different supply chain

processes and supply chain performance measures.

2.1.1. Gilmour’s model

The strategic model proposed by Gilmour [5] describes both

a framework, which can be used to evaluate supply chain

processes and a group of benchmark measures, which can be

applied to supply chain processes.

The integrated supply chain model is used to examine the

logistics operations of the respondent companies. It comprises

six functional process capabilities, which are supported by

enabling capabilities in organisation characteristics and

information technology. An organisation with an integrative

approach to managing logistics will tend to have the majority of

these capabilities in place.

The measures are based on a set of capabilities, which

incorporate the extent of integration, and the use of technology

in the logistics processes of an organisation. The degree to

which logistics is used as a key element of overall strategy

formulation and implementation.

2.1.2. Cooper’s model

Copper et al. [6] propose a conceptualization of supply chain

management, which includes three elements: the business

processes, the management components, and the structure of

the chain. The processes cut across the functions within a firm

and across other firms within the supply chain. Each firm in the

supply chain has its own set of functional silos that must be

related to each key supply chain process.

2.1.3. SCOR model

The Supply Chain Council’s SCOR-model [7] is an

international standard for process description and reorganiza-

tion and considers five main supply chain processes: planning,

sourcing, production, delivering, and return activities. Through

a common set of definitions, performance indicators and best

practices, the SCOR-model is a framework for a common

language between supply chain partners concerning its five

management processes. Thanks to three levels of details, the

SCOR-model allows a company to analyze and configure its

supply chain according to its production type (make to stock,

make to order, etc.) and to its specific needs and requirements

(process mapping, operational process description, etc.).

Companies that use the SCOR-model describe their actual

processes (‘‘as is’’) in order to compare them to the ‘‘standard

processes’’ described by the SCOR-model and use the

performance indicators and best practices, they consider as

pertinent, to attain optimized processes (‘‘to be’’).

2.1.4. ASLOG audit

The logistics audit guide of the ASLOG association [8] is a

European standard looking to attain logistics excellence with

the help of ten supply chain processes: management, strategies

and planning, product conception and projects, sourcing,

production, moving, stock, sales, return and maintenance,

management of indicators, and permanent progress. Thanks to

an audit questionnaire concerning these processes and their

assessment, the logistics audit guide of the ASLOG association

allows a company to describe its actual processes (‘‘as is’’) and

to evaluate its logistics performance. Specifically trained,

ASLOG auditors analyse the situation of a company in order to

propose recommendations for continuous process improvement

(‘‘to be’’).

2.1.5. EVALOG guide

The logistics guide of the EVALOG organization [9] is a

worldwide evaluation frame of reference focused on the

automobile industry. Its approach is based on six topics: strategy

and improvement, organization, production plan and availability,

customer relationship, product and process control, supplier

relationship. Many questions are associated to each topic and

constitute a set of good practices for the automobile sector. The

referee company has to respond with a binary answer: Yes or No.

Each question is weighted with a priority criterion.

2.1.6. Synthesis

The EVALOG guide and the SCOR model are focused on

the internal processes of a company whereas the ASLOG audit

F.-A. Gruat La Forme et al. / Computers in Industry 58 (2007) 687–697 689

and the performance framework of Gilmour are more focused on

cross-processes along the supply chain. More precisely, the best

practices proposed by the ASLOG audit put emphasis on the

collaborative relationships between the actors and on the

activities integration across the supply chain. Two of the five

models quoted above distinguish various performance degrees to

attain. For the ASLOG audit, the nature of levels depends on the

topic: for example, for the risk aspect, degrees of maturity reflect

the risks control (0: risks are neither evaluated nor considered; 1:

risks are evaluated; 2: risks are restrained; 3: risks are under

control). For Gilmour’s model, the four levels proposed for each

practice represent a continuum of sophistication for each

capability component (strategy and organization, planning,

product flow, performance measurement and processes). Con-

trary to others performance models, Gilmour states that the

highest level is not necessarily appropriate for all companies or

industries. The cost of achieving it may not be justified.

To conclude, we can notice that most of these models are

structural frameworks (i.e. they specify a topology for the

performance management in supply chains), which are based on

a business process approach. A second kind of framework is

proposed in other works, based on procedural models, which

develop from the strategy a performance management. Never-

theless, the rate of development of structural frameworks is

outpacing procedural ones, that may explain the difficult

qualitative nature of the problem of formulating basic

performance procedure between companies in supply chain,

according to Folan and Browne [10]. That is why these authors

propose an extended enterprise performance measurement

framework that combines both of the structural and the

procedural natures. The first one is an extended enterprise

balanced scorecard offering a four perspective framework that

provide a generic structure for the management of performance

measures in extended enterprises. The procedural framework

provides a step-by-step generic process toward the selection and

implementation of measures.

2.2. Business processes in supply chain modelling

The five reference models that we have identified and

presented in Section 2.1 describe elements related to supply

Table 1

Overview of processes in supply chain reference models

Gilmour’s model [5] Cooper’s model [6]

Downstream part Supplier partnering Procurement

Internal part Lean manufacturing Manufacturing flow mana

Upstream part Customer driven supply chain Customer relationship ma

Demand driven sales planning Customer service manage

Efficient logistics Demand management

Order fulfilment

Cross-supply chain Integrated SCM Product development and

commercialization

Returns

chain functioning. Some of them are dedicated to supply chain

modelling, others to supply chain audit. All of them are based on

a process approach describing both upstream and downstream

activities of the supply chain. Based on these five main reference

models putting in perspective the question of integration between

different activities of a supply chain, we identified main supply

chain processes and we recognized similar processes named

differently in various reference models as presented in Table 1.

2.3. Collaboration and information sharing across the

supply chain

Collaboration is defined as a way by which all companies in a

supply chain are actively working together toward common

objectives, and is characterised by sharing information, knowl-

edge, risks and profits. Concerning the collaboration relationship

across a supply chain, two main aspects are commonly

considered in numerous studies. On one hand, some works deal

with the intensity of the relation between the partners, from

simple information sharing to real partnership including the

sharing of the experiments until the sharing of risks and profits.

More precisely and gradually, the communication is firstly

‘‘unidirectional’’, then ‘‘bidirectional’’, when the relation is

formalized we used to talk about ‘‘industrial agreement’’, and

finally, the integrated communication is linked to the partnership

relation [11]. On the other hand, others studies deal with the

extent (or perimeter) of the collaboration, along the supply chain.

More precisely, Thierry [2] presents a progressive approach from

an internal exchange relation allowing the integration of internal

functions of procurement, production and distribution of a

company, to an integrated vision implying the relations spread to

all partners of the supply chain. Collaboration is also

characterised by information sharing between supply chain

stakeholders and main information exchanged across a

collaborative supply chain are classified in Table 2 [12–16].

2.4. Key performance indicators in collaborative supply

chain

Supply chain performance is traditionally focussed on

operational logistics activities. For example, in a warehouse,

SCOR model [7] ASLOG audit [8] EVAOLG guide [9]

Source Procurement Supplier relationship

management

Storage

gement Make Production Lean manufacturing

nagement Deliver Distribution Customer relationship

management

ment Sell

Return Design Product development

Plan Return

Table 2

Overview of main information shared across collaborative supply chains

Downstream part SC Internal part SC Upstream part SC Cross-supply chain

Replenishment order forecast Production order Sales forecast Product management profile

Inventory Master production plan Sales order/actual usage Product design

Goods receipt Capacity plan Order delivery notes Market demand

Supply lead-time Bill of material Delivery forecast Global performance measure

Inventory position Production plan Critical product availability Traceability

Backlog Technical information Quality parameters

Operating cost

Capacity

Mean of demand

Critical product availability

Quality parameters

Technical information (reorder point, security factor. . .)


pallets per hour is a typical performance measure for receiving

and despatch. More recently many companies are becoming

more customer-oriented as shown with actual performance

assets. Many performance models propose both customer

facing measures ‘‘KSF’’ (Key Success Factor) and company

facing measures ‘‘KPF’’ (Key Performance Factor) [7,17]. KSF

have a decisive impact on the sector competitiveness and they

represent success stakes among customers. Generally, they are

external performance criteria (customers oriented) and they are

elements on which is based the competitive fight. For example,

a KSF can be the delivery lead-time for the upstream part of the

supply chain, or the on-time replenishment for the downstream

part of the supply chain. KPF result from the KSF, on the

company process point of view. They reflect internal

performance stakes and more often, they are not perceptible

to customers. A KPF is necessarily associated to a KSF as

illustrated in Fig. 1. For example, the KPF associated to the

delay facet (KSF) is related to the production flow aspect and

can be indicators such as the set-up time or the time to product

for example.

A company needs to have indicators to evaluate its

flexibility, reactivity, reliability and profitability. Benefits of

collaboration generally noticed are the flexibility improvement,

reactivity improvement, better resources utilization, shorter and

controlled delays, quality improvement and competencies

development [18]. Thus, many performance models and studies

Fig. 1. Set of performance indicators: customer facing measures and company

facing measures.

related to the performance in supply chains propose some

typologies of key performance indicators: reactivity, flexibility,

reliability, quality, cost [7,10,18,19], precision, innovation and

environment [10]. At the strategic level, indicators are most of

the time financial measures (ex: profit margin) [20], but on the

tactical and operational level, indicators are more diversified:

for example, customer service level, customer response time, or

customer order fulfilment lead time are typical measures for the

supply chain upstream part performance. Concerning the

downstream part of the supply chain, a collaboration relation-

ship has often an impact on the on time supplier performance or

on inventory accuracy criteria (etc.). A detailed framework

about the performance indicators impacted by the collaboration

is proposed in Section 4 and is based on a substantial literature

review [3,15,19–24].

2.5. Concluding remarks

The main necessary notions to develop a framework to

analyze the collaborative performance of a company have

emerged from this literature review: information exchanged

between partners and exploitation of this sharing, integration of

activities, maturity degrees of collaboration, performance

indicators associated to good collaborative practices.

Two models compose the general framework proposed in

this paper. The first one is a collaboration characterization

model (cc model) and it is based on ten generic processes,

which emerged of the literature review (Section 2.2) and on the

main information exchanged across the supply chain (Section

2.3). The second one is related to the collaboration-oriented

performance model (CoP model) and it has been developed

based on the indicators highlighted in Section 2.4.

3. A collaboration characterization model (CC model)

The framework characterizing collaboration in supply

chains focuses on information exchanged between partners

as well as on the exploitation of this sharing. Thus, this first

model is based on many facets such as the characterization of

the perimeter of the exchanges along the supply chain, the use

of this collaboration, its intensity and its regularity.

Fig. 2. Processes of the collaboration characterization model.


3.1. Structure of the collaboration characterization model

We propose a three-dimensional model as proposed in

Fig. 2. The first axis lists the ten relevant processes of the

supply chain management, presented in Fig. 2. They result

from the literature review presented in Section 2.2. The

second axis allows studying these processes on various

dimensions such as strategy and organization, planning and

product flows. For each process and each dimension, two

intentions are distinguished: reactive and proactive colla-

Fig. 3. Structure of the collaboration c

borative practices are defined. For each collaborative

practice, the third axis distinguishes four levels of intensity

and extent in the relation between the entities concerned by

the shared information as detailed in Fig. 3. Definition of the

two axes ‘processes’ and ‘dimensions’ are given in Tables 3

and 4, respectively.

3.1.1. Proactive and reactive collaboration relationship

A reactive collaborative practice is engaged when the

company activates a collaborative relationship after a stimulus

of its partner, in order to improve the local and global

performance. This stimulus can be information, a data or a

request and is considered as an input for the collaborative

action.

A pro-active collaboration is engaged when the company

activates spontaneously the collaborative relationship without

any external stimulus. The pro-active collaboration is closely

related to the company sense of anticipation. The information

communicated from the company to its partners is considered

as the input of the collaborative action.

We make a distinction between two types of collaboration in

order to underline firstly the trigger factor (internal or external

initiative) of the collaboration relationship and secondly to

highlight the risk generated by the information sharing. In [25],

the authors underline: ‘For some information, retailers

acknowledged that providing additional information to

manufacturers would offer some saving to the manufacturers,

but many retailers were sceptical about the benefits for their

firms in sharing information with manufacturers’. Thus, the

haracterization model (CC model).

Table 3

Definition of the 10 processes of the CC model

Processes

‘‘Customer Driven Supply Chain’’ means the importance given by the company to its customers in its organization and mode of functioning

The name of Gilmour’s process [5] has been adopted but this process integrates ‘‘customer relationship management’’ of [6,9], ‘‘customer service

management’’ and ‘‘order fulfilment’’ of [6], and ‘‘sell’’ of [8]

‘‘Demand Driven Sales Planning’’ means the knowledge that the company have, about the customers’ demand and the real impact of this information in

its organization and mode of functioning

The name of Gilmour’s [5] process has been adopted but this process integrates ‘‘Demand management’’ of [6]

‘‘Transport and Distribution’’ means the activities bound to the traffic and to the storing of finished products, from the company to the customer, and

the associated management rules

This process integrates ‘‘Efficient logistics’’ of Gilmour’s [5], ‘‘Deliver’’ of [7] and ‘‘Distribution’’ of [8]

‘‘Lean Manufacturing’’ concerns all the operations proposed to improve and to optimize the efficiency of the production of the focus company,

including the work-in-progress

The name of Gilmour’s (99) process and Evalog process has been adopted but this process integrates ‘‘manufacturing flow management’’ of [6],

‘‘make’’ of [7], ‘‘production’’ of [8]

‘‘Supplier Collaboration’’ concerns the level of collaboration and integration of the suppliers in the purchasing process of components or raw materials

of the company

This process integrates ‘‘supplier partnering’’ of Gilmour [5], ‘‘Source’’ of [7], ‘‘Supplier relationship management’’ of [9]

‘‘Supply Logistics’’ concerns the activities bound to the traffic and to the storing of components or raw materials, from the supplier to the stocks of the focus

company, and the associated management rules

This process integrates ‘‘procurement’’ of [6,8], ‘‘Source’’ of the [7], ‘‘storage’’ of the [8]

‘‘Integrated Supply Chain Management’’ concerns the integration of activities and characteristics of suppliers and customers in the organization

and the mode of functioning of the focus company [5]

‘‘Reverse Logistics’’ concerns the activities bound to the reverse logistics, from customers to the company and from the company to its suppliers

This process integrates ‘‘return’’ of [6–8]

‘‘Product Design’’ concerns the activities from the phase of design to the phase of commercialization of new products

‘‘Product Development and Product Evolution’’ concerns the activities of modification and evolution until their commercialization of the

existing products

This process integrates ‘‘product development and commercialization’’ of [6], and ‘‘product development of [9]


collaboration effort is different when the company integrates

information from its partners to collaborate with them

(reactive collaboration) and when it provides its partners

with information about its plans, strategy ( pro-active

collaboration). The risk is more important for the focal

company than for its partners, and the benefits are not

necessarily equal for the two concerned entities. To sum up,

according to us, pro-active collaborative practices are more

difficult to implement because of an asymmetry of the profits,

because these practices are susceptible to compromise some

more important stakes.

3.1.2. Maturity levels in a collaboration relationship

To each collaborative practice, four levels practices have

been established in order to characterize and measure the

intensity and the extent of the relation between partners. The

Table 4

Definition of the three dimensions of the CC model

Dimension

‘‘Strategy and organization’’ declines the elements of strategy and organizatio

strategy and the organization of the company

‘‘Planning’’ declines for each attribute, all principles, methods and activities th

term and prepare their execution

‘‘Product Flow’’ declines all elements of management and tracking of product

short term

generic axis characterizing the four levels is proposed in

Fig. 3.

3.1.3. Illustration of collaborative practices

As an example of those collaborative relationships, the

proactive and reactive collaboration practices for the process –

Supply logistic – are allocated among the three dimensions

strategy and organization, planning and product flow. The

generic maturity axis has been instanced in Fig. 4. A company

shows reactive collaboration behaviour when:

� O

n

at

s f

n the strategic level, the company considers its suppliers’

strategy and constraints to elaborate its supply and

inventories strategy.

� O
n the tactical level, the company includes its suppliers’
constraints in his replenishment planning.

for each attribute of the supply chain, defining for the long term, the

a company use to organize and to schedule its activities for the middle

rom the operational steps to the final step of its realization, mainly on

Fig. 4. Illustration of the maturity levels for the supply logistics process.


� O
n the operational level, the company is able to provide
information about its product flow at its suppliers’ request.

A company shows pro-active collaboration behaviour when:

� O
n the strategic level, the company announces information
related to its sourcing strategy, goals or stakes to its suppliers,

in order to improve the supply performance.

� O
n the tactical level, the company shares its projected supply
planning with its suppliers in order to validate it with them.

� O
n the operational level, the company systematically shares
information on its inventories with its suppliers in order to

synchronize and optimize the supply flow.

As an example of the collaboration maturity associated to

each collaborative practice, the four levels for the process –

Supply logistic – are allocated among the dimension – strategy

– and the pro-active intention as follows:

� L
evel 1: The company does not announce information related
to its sourcing strategy, goals or stakes to its suppliers.

� L
evel 2: Punctually and for some key suppliers, the company
announces information related to its sourcing strategy, goals

or stakes, in order to improve the supply performance.

� L
evel 3: Regularly and for some key suppliers, the company
announces information related to its sourcing strategy, goals

or stakes, in order to improve the supply performance.

� L
evel 4: Regularly and for the whole of its key suppliers, the
company announces information related to its sourcing

strategy, goals or stakes, in order to improve the supply

performance.

3.2. Collaborative profile

Filling the CC model allows the manufacturer to rank among

one of the four levels for each process each dimension (strategy

and organization, planning, product flow) and each intention

(proactive and reactive). He realizes a real ‘‘picture’’ of his

company, of his internal and external collaborative practices.

This picture is in fact the collaborative profile of the company.

Several analyses are possible from the collaborative profile of a

company and they will be detailed in Section 5.

4. A Collaboration-oriented performance model (CoP

model)

Collaborative actions across organization and throughout

the supply chain can significantly enhance individual and

global performance. Various indicators, which illustrate the

impact of potential collaborative practice benefits, allow the

measure of the performance. These performance indicators

can be classified in order to propose a structured set of

indicators.

4.1. A set of performance indicators

The main benefits that one can obtain from collaborative

practices with partners are improvement of flexibility, reactivity

and quality, better resources utilization, shorter and controlled

delays. The set of performance indicators associated to the CC

model described in Section 3 has to reflect this performance

classification. From a literature review, we have selected the

main performance indicators impacted by collaboration

relationships throughout the supply chain. They have been

classified and they depend on the supply chain perimeter

(downstream, internal, upstream part of the supply chain (SC)

and cross-supply chain) (see Section 2). We keep a well-known

classification adopted by many models: reactivity–reliability–

flexibility–quality and cost assessment. The set of performance

measures makes the distinction between customer facing

indicators and company oriented indicators as explained in

Section 2 (KSF and KPF). Table 5 represents the whole of

selected indicators on which the CoP model is based.

4.2. Perceived collaboration-oriented performance profile

From the CoP model, we aim at obtaining the perceived

collaboration-oriented performance profile of a company. To

compare it with the collaboration profile resulting from the CC

model, and to exploit it for a relevant analysis, the maturity axis

used to define the four maturity levels of the CC model is reused

for the CoP model. For example, for the – on-time delivery –

indicator, the four levels are defined as follows:

� L
evel 1: The company is not satisfied with the reached
performance level related to the reliability of its delivery

activity.

� L
evel 2: Punctually and for some distributors, the company is
satisfied with the reached performance level related to the

reliability of its delivery.

� L
evel 3: Regularly and for some distributors, the company is
satisfied with the reached performance level related to the

reliability of its delivery.

� L
evel 4: Regularly and for the whole of its main distributors,
the company is satisfied with the reached performance level

related to the reliability of its delivery relation between

collaborative practices and performance indicators.

The general framework analysing the collaboration perfor-

mance of a company is based on both CC model and CoP

Table 5

Classification of performance indicators influenced by collaboration relationships (CoP model)

Upstream part of the SC Internal part of SC Downstream part of SC Cross-SC

Customers facing indicators: KPF

Reliability Order fill rate

Quality Product quality

Reactivity Order fulfilment lead time

Customer query time

Flexibility Flexibility of service system to

meet customer need

Financial Sale price

Profit margin

Company facing indicators: KSP

Reliability On-time delivery On time production On-time supplier performance Reverse plan adherence

Forecast accuracy Production plan adherence Inventory accuracy

Delivery plan adherence Stock out probability

Sourcing plan adherence

Quality Production quality Supplier quality performance

Reactivity Delivery lead time Production cycle time Source cycle time Design cycle time

Supplier response time Reverse cycle time

Development cycle time

Total SC cycle time

Flexibility Upside delivery flexibility Production flexibility Downside capacity flexibility Mix product flexibility

Volume flexibility

Financial Delivery cost Production cost Purchasing cost Total supply cost

Inventory cost Resources utilization rate Replenishment cost Total cash flow time

Inventory cost Inventory cost Reverse logistic cost

Design product cost


model. This framework is illustrated on the entity relationship

diagram in Fig. 4.

5. Performance analysis

In Sections 3 and 4, two models have been described. The

first one characterizes the collaborative situation of a company

and leads to the construction of its collaborative profile. The

second one characterizes the perceived collaboration-oriented

performance of this company and leads to the construction of its

perceived collaboration-oriented performance profile. From the

CC model only or from both of CC model and CoP model,

various industrial uses and kinds of analysis is possible.

5.1. Performance analysis from the CC model

Firstly, the use of the CC model ensures a manager a better

understanding about the notions related to collaborative

practices between partners. Indeed, different collaborative

practices are described for each process, each managerial

dimension and each dimension. This point is essential for the

manufacturers, according to Akintoyee et al. [26] for whom one

of the main reasons of failures of collaboration within the

supply chain takes its source in the misunderstanding of the

manager about the concepts of the supply chain management.

Secondly, the CC model allows for checking of the coherence

of company actions. First, filling the model allows the manager to

position himself on one of the four levels for each process, each

managerial dimension and each intention. Therefore, he

structures his discussion on the functioning of the company.

The goal is not to discover forces and weaknesses because the

purpose is not to reach level ‘‘4’’ every time. It depends on the

context (MTO, MTS. . .), the strategy, etc. . . The objective is to

confront for each process, the three dimensions to verify the

coherence of actions. The model allows showing the gaps

between the strategy of a company and the tactical and

operational collaborative practices, which are connected with it

. . . Do they really support the strategy? Are collaborative

practices aligned from the strategic level through the tactical and

the operational level? It is possible to check if the strategy that the

manager believes to set up is really supported by tactical and

operational collaborative practices, and on the other hand, it is

possible to see if the actions led correspond to a wished strategy.

In other words, the CC model allows verifying if the company

puts its actions, its resources, and its money in front of the

appropriated problems. If some gaps are detected, the model

helps to redefine and to prioritize actions to lead or to underline

the process to put under control. Furthermore instancing the

model 1 year later could follow the evolution of the company. Is

the situation more coherent? Has it improved? The CC model

could become a communication tool or a global reporting tool for

a top management team since it synthesizes collaborative actions

of the downstream and upstream processes.

5.2. Performance analysis from the general framework

Juxtaposing the profiles given by the collaborative character-

isation model and the collaboration-oriented performance model

Fig. 5. Entity relationship diagram of the framework analyzing the collabora-

tion performance.


is a way to check the coherence between collaborative efforts and

the perceived performance, from radar diagrams. Each indicator

identified in Table 5 is associated to one or several collaborative

practice(s) as described in Fig. 4. For each collaborative practice

and each indicator, the manager has established its position on

one of the four proposed levels as described in Section 4.

Therefore, he has built his collaborative profile from the CC

model and his perceived performance profile from the CoP

model.

As an example, in Fig. 5, indicator ‘‘A’’ is impacted by six

collaborative practices (CP1! CP6). The performance level

concerning indicator ‘‘A’’ and the six practices are noticed on

the radar diagram radar. For each indicator three kinds of

situations may be observed as illustrated in Fig. 6:

� S
cenario 1: The perceived performance related to the
indicator A is consistent with the levels reached for most

of associated collaborative practices. A way to improve the

performance of the indicator A could go through an increase

at the collaborative practices level.

� S
indicator A is below the levels reached for most of associated

collaborative practices. In others words, collaborative efforts

seem to not bear fruit. For example, the reason for this

ineffectiveness could be explained by the context or the

information system, which does not support efficiently the

collaborative actions across the supply chain. . .

Fig. 6. Typologies of diagram radars for

� S

col


indicator A is superior to the levels reached for most of

associated collaborative practices.

5.3. Application of the two frameworks on the industrial

case study

Our case study is based on a company, which belongs to the

textile industry. It is an area in which, the increasing number of

customized and adjustable products induces high diversity,

important mix model and small batch orders. Awell-established

way of overcoming competitors is to introduce new trends.

Innovation in design activities is a key success factor for this

company, which has the ambition to stay among the leaders of

its sector. To fulfil customers’ requirements and needs, the

company production strategy is a combination of MTO (Make

To Order) and ETO (Engineer To Order) policy. The goal of this

study is to investigate which collaboration relationships the

company keeps up across entities of its supply chain and to

observe the impacts of its collaborative practice on its

performance. The framework proposed in this paper has been

instanced on this company by the way of interviews with the

plant manager. An illustration of the potential analyses from the

application of the framework is proposed in this section and

some results are shown in Figs. 7 and 8.

The collaborative profile given in Fig. 7 underlines that the

company reinforces its collaborative efforts on the upstream

part rather than on the downstream part of the supply chain.

Most of the points are positioned on level 3 for the upstream

side and on level 2 for the downstream side. This first remark

can be explained by the context of the company. The second

significant point concerns the two processes ‘‘product design’’

and ‘‘Product Development/Evolution’’ for which the company

is much more collaborative than for the others processes (level

3 or 4), for the reactive intention as well as for the proactive one.

Integrating systematically all of the main partners who have a

main role in the innovation and design steps is the guiding

principle that the company has set itself. Its competitively

aspect is closely related to a very high quality of product, and a

long-term collaboration relationship is a way by which the

company hopes to succeed.

In a general way, the company does not have a real proactive

attitude neither for the strategic level nor for the tactical or

laborative performance evaluation.

Fig. 7. Collaborative profile of the industrial case study.


operational levels. In other words, the company is not used to

communicate in advance information to its supply chain

partners. Faced with this assessment, a first discussion has been

engaged with the company and it turns out that this poorly

proactive collaborative situation is not linked to a willingness of

the company to protect some data. On the other hand, this

situation could be explained by a lack of suitable technology for

each of the three managerial levels. More precisely, its actual

information system is not efficient enough to simulate some

scenarios, to forecast the customers’ demand or to foresee some

strategic trends that may be communicated to its partners. The

planning system is not integrated enough to forecast the

replenishment or distribution activities and so the company is

not able to convey these plans to its supply chain partners.

Finally, on the operational point of view, the information

system of the company is not reactive enough to give some

relevant information about the product flow, its risks or hazards

to its partners in real time.

Concerning the results obtained from the CoP model, we

notice that the company evaluates most of the reliability

indicators on level 2. Furthermore, we observe in Fig. 7, that the

company evaluates itself on level 2 for most of proactive

collaborative practices related to the planning dimension. In

Fig. 8. A part of the perceived performance profile of the case study.

other words, this situation means that it communicates its

purchasing planning, its distribution planning, its replenish-

ment planning. . . punctually and only to a part of its partners.

This could explained the bad result noticed for the reliability

indicator ‘‘order fill rate’’ for example, since all of these

proactive practices related to the planning dimension have an

impact on this indicator as described in Fig. 8.

Actually, two main projects are under development on the

strategic and tactical level in the company and they may

promote the diffusion of information across the supply chain.

This anticipation and this proactive information sharing could

have a significant and positive impact on the performance of the

reliability of the company if one believes the relationship

between collaborative practices and performance indicators

given in the framework.

6. Conclusion

The general framework presented in this paper characterizes

the performance of the collaboration throughout the supply

chain. It is composed by a collaboration characterization model

(CC model) and by a collaboration-oriented performance

model (CoP model). A collaboration profile and a perceived

collaboration-oriented performance profile result from these

two models. These two models are mainly structural and the

methodological analysis associated to the general framework

introduces a procedural dimension. Folan and Browne [10]

have already coupled these two aspects to obtain a complete

supply chain performance measurement system.

The application of this general framework on an industrial

case study allowed his validation. Furthermore, it allowed the

estimation of the coherence and the efficiency of collaborative

actions practiced by the company.

The research perspectives of this work are the design of a

context model to evaluate the pertinence of action regarding the

environment of a company. A technology and information

system point of view could also be helpful. The general


framework could become a real decision-making tool to drive a

company towards its choices of strategies, actions and

information system to develop.

Acknowledgement

This work was supported by the Regional Council of Rhone-

Alpes, France. This support is gratefully acknowledged.

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France-Anne Gruat La Forme received her engi-

neering degree and her postgraduate certificate in

2004 from the INSA of Lyon, France. She is cur-

rently PhD student at the same Grande Ecole of

Engineering. She is a member of PRISMa laboratory.

Her main research interests include performance

measurement, collaboration and information sharing

in supply chains, and scheduling problem with par-

allel human resources.

Valerie Botta-Genoulaz is Professor in the Indus-

trial Engineering Department of the National Insti-

tute of Applied Sciences (INSA) of Lyon, France,

and member of PRISMa laboratory. Her main

courses deal with production management and enter-

prise information systems. Five years experience in

industry, PhD in Computer Sciences, application

consultant ‘Production Planning’ for SAP R/3, her

research interests are oriented on planning and man-

agement of supply chains (SCM), ERP and SCM

project management, enterprise and business process modelling.

Jean-Pierre Campagne is an electronics engineer of

INSA Lyon. He has a PHD degree in Computer

Science and he is Professor and Head of the Indus-

trial Engineering Department in INSA Lyon. He is a

member of PRISMa laboratory. His main research

interests are production management and logistic

systems. He was the coordinator of Copilotes project.

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http://www.aslog.org/

http://www.galia.com/

a framework to analyse collaborative performance

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