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Supporting collaboration in the development andmanagement of lean supply networksE. D. Adamides a; N. Karacapilidis a; H. Pylarinou a; D. Koumanakos aa Department of Mechanical Engineering and Aeronautics, University of Patras,Greece

Online Publication Date: 01 January 2008To cite this Article: Adamides, E. D., Karacapilidis, N., Pylarinou, H. andKoumanakos, D. (2008) 'Supporting collaboration in the development andmanagement of lean supply networks', Production Planning & Control, 19:1, 35 - 52To link to this article: DOI: 10.1080/09537280701773955

URL: http://dx.doi.org/10.1080/09537280701773955

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Production Planning & ControlVol. 19, No. 1, January 2008, 35–52

Supporting collaboration in the development and management of lean supply networks

E.D. Adamides*, N. Karacapilidis, H. Pylarinou and D. Koumanakos

Department of Mechanical Engineering and Aeronautics, University of Patras, Greece

(Received 9 August 2006; final version received 15 October 2007)

The purpose of this paper is to demonstrate how the appropriate information and communication technology canact as a catalyst in the development and operations management of lean supply networks; not by automatingtasks and procedures, but by providing the enabling infrastructure required for structuring difficult problems andissues arising at inter-organisational boundaries and for taming the social complexity of their resolutionprocesses. Towards this end, we present the design rationale and the functionalities of Co-LEAN, which is anintegrated suite of software tools developed by the authors for the design and management of lean supplynetworks. In addition to providing full operational support in the planning and execution of the lean supplynetwork, Co-LEAN supports internet-based collaboration in the specification of value, the identification andoptimisation of value-streams, the alignment of supply-chain strategy with the overall operations strategy, andthe supply-chain improvement tasks. The paper discusses the knowledge and information managementrequirements of lean supply networks, and presents the main components and functionalities of Co-LEAN in thecontext of a use case in a supply network formed around a stainless steel tanks’ manufacturer.

Keywords: lean management; supply chain management; collaboration; knowledge and informationmanagement

1. Introduction

The notion of the lean supply network (Hines 1994)has been a natural extension of the concept of leanmanufacturing. Since the mid-1990s, the philosophyand the toolset of the lean approach were extended tocover the full spectrum of activities from the produc-tion of raw materials to the end customers’ transac-tions (Hines and Rich 1997, Rother and Shook 1998,Womack and Jones 2003, Hines et al. 2004). Clearly,the holistic nature of lean ideas require an equallyholistic approach to the supply which extends beyondrestrictions of time, place and scope, such as (opti-mised) supplier selection, supply chain sourcing,supplier development, and logistics (Jones et al. 1997,Davis and Spekman 2004). Instead, a defining char-acteristic of lean supply chains and networks is thatthey are formed and maintained by proactive, system-wide collaborative relationships among all-tier suppli-ers and customers. This means that they are practicallyvery close to the ‘external integration’ (Stevens 1989)and ‘market-in’ (Merli 1991) stages in the evolution ofsupply chains with respect to their organisationalstructure (Rich and Hines 2000). As a result, theassociated problem-solving and decision-makinginvolves issues that can be found throughout the

entire product lifecycle, across both functional and

organisational boundaries, aiming at achieving ‘co-

makeship’ (Merli 1991). It involves designing, planning

and executing across multiple partners to deliver

products of the right design and features, in the right

quantity, in the right place, at the right time (Lamming

1993).In operational terms, a lean supply network, in

addition to lean manufacturing principles, such as 5S,

visual factory, takt time (i.e. the production rate that

equals the rate of sales), pull, flow, etc. (Womack and

Jones 2003), uses rate based planning and execution

(RBPE), a way to smooth production and deliveries

along the network through capacity planning driven by

the end-products’ bills of materials (Reeve 2002).

In employing these lean techniques throughout the

network, the objective is to decrease redundancy in

materials, processing and transportation activities,

as well as in information and knowledge supply by

providing them dynamically where and when they are

required. Towards achieving this objective, a number

of obstacles, which include the difficulty to see and

manage cause–effect relationships established across

company boundaries, and are responsible for waste,

the requirement to break walls between normally

insulated parties, and the need to practice collaborative

decision making by developing a win/win philosophy*Corresponding author. Email: adamides@mech.upatras.gr

ISSN 0953–7287 print/ISSN 1366–5871 online

� 2008 Taylor & Francis

DOI: 10.1080/09537280701773955

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of thinking supported by agreements and trust betweenpartners should be overcome (Sako 1992, Muckstadtet al. 2001, Cox 2004, Hines et al. 2004, Evans andWolf 2005). In the problem-solving context, theseobstacles are expressed as the ‘forces of fragmentation’(Conklin 2005) which act against collective decisionsand actions, and are intensified by geographic distance,different roles, involvement in different industries, etc.The employment of interfaced manufacturing planningand execution systems is suitable only for inter-firmcollaboration in issues characterised by clearness andlow social complexity. Otherwise, their contribution ismarginal, if not negative by intensifying the effects offragmentation and unsystemic thinking (Davis andSpekman 2004). As the lines between innovation/product development, manufacturing, sourcing anddistribution are blurring, lean supply managementneeds to move away from arm’s length contractualrelationships towards obligational contractual rela-tions (Sako 1992, Kerrin 2002). These require thedevelopment of shared understanding and sharedcommitment, as an antidote to fragmented perspectivesin product and process development, in common visionand shared goals, and in supply network design,planning, execution and improvement.

As a result of the above, lean supply chain/networkimplementations are rare, and collaboration in thisdomain is still at an embryonic stage, mainly beingconcentrated on efforts directed towards informationexchange among participants at the purely operationallevel. Also in the form of collaborative planning,forecasting and replenishment (CPFR), vendormanaged replenishment (VMR) and synchronisedsupply, employing technologies such as advancedplanning systems (APS) and extended decision man-agement (XDM) (Barratt 2004, Chung and Leung2005, Holweg et al. 2005). This arises from the fact thatorganisations can integrate their processes at theoperational level without great difficulty becausethe issues are well-structured, and integration isaccomplished through codified information exchanges.However, collaborative strategic processes, such asvalue specification, innovation, strategy developmentand improvement, which are crucial for the implemen-tation of the lean supply network, are messy, involvesocial complexity, and require the development ofshared understanding through capturing andcommunicating knowledge, as well as the managementof complex interactions and behaviours among theagents that hold it. Collaboration in such issuesrequires either face-to-face interaction or the employ-ment of advanced information and communicationtechnology to ‘virtualise’ social interaction and supportrich knowledge exchanges. The holding of

physical-presence meetings for exchanging knowledgeand information in a structured manner is quitedifficult, and distributed decision processes are unpro-ductive if the dialogues and debates are not structuredproperly (Muckstadt et al. 2001). This is true not onlyin very fast changing industries with world-wide supplychains (Shi and Gregory 2005), but also in moremature and geographically restricted business activities(Azumah et al. 2005). Advanced information andcommunication technologies (ICT) operating over theInternet can overcome these obstacles and act ascatalysts not only for information exchange, but alsofor supporting more advanced collaboration modes(Samaddar et al. 2005). Therefore, the employment ofadvanced ICT in the broader meaning of the term,including use capabilities and procedures, is necessaryfor supporting the development and execution of leansupply, both vertically (from raw materials to the endcustomers) and horizontally (from value specificationto supply chain execution).

Towards this end, in this paper we present thecharacteristics and the organisational embedment of anintegrated suite of internet-based software tools thatcan effectively support the design and the operationsmanagement of a lean supply network. The rationalebehind the suite is based on the idea that the holismof lean requires an equally holistic and consistentapproach in making the transformation process and itsimplementation more productive and more effective.As a result, two recent technologies, namely computer-supported argumentation and automatic planco-ordination, are employed to support collaborationamong partners in a supply network at three levels ofcapability development and deployment (Collis 1994).A knowledge management system (KMS) supportscollaborative knowledge-intensive strategic processes,such as value specification, value stream mapping, andsupply-network strategy development, in a consistentway. A similar system, employing the same logic indialoguing and decision-making, supports collabora-tive supply-network improvements, where a modulebuilt around a database using AI techniques addressesin a more automatic fashion previously structuredissues and facilitates robust rate-based planning andexecution (operational level). At every level, theengagement of Co-LEAN is not for automating tasksand procedures, but to provide the enabling knowledgeand social infrastructure for the implementation oflean supply in a network of organisations. Following,in Section 2, we review the activities involved in leansupply network management and identify the ICTchallenges that must be met for actively supportingthem. In Section 3, we present our suite of toolsexplaining each one’s functionalities in the framework

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of the operational environment of the suite’s pilot

application. Finally, in Section 4, we draw ourconclusions.

2. Operational requirements and technological

challenges of lean supply networks

As has already been mentioned, collaboration andprocess integration are the two principal constituentparts of lean supply network management. Merli(1991) has argued that the strategic integration of

companies involved in a supply chain/network isa function of the level of ‘trust’ created between thestrategists of the organisations and the level of

integration of information systems. Sharing informa-tion and creating common knowledge in argumenta-tive discourses contributes to shared understandingand trust development, and, in turn, enhances

collaborative behaviour (Chesnevar et al. 2000,Hardy et al. 2005). In addition structured argumenta-tion facilitates learning as it increases the coherence of

organisational mental models by assuring theirrationality, logical consistency, and by eliminatingany internal contradictions (Rescher 1970), thuscontributing to increased overall supply chain/net-

work performance (Hult et al. 2004). Moreover, byproviding structured procedures, it encourages indivi-duals and organisations to enter the cyclic learning

process which involves a combination of experience,reflection, concept formation and experimentation(Bessant 2004), and facilitates knowledge manage-ment (Raccah 1990) and decision-making (Macoubrie

2003). Similarly, as it creates trust and powerrelations (Bachmann 2001), argumentation has beenproved to be an efficient co-ordination mechanism

(Malone and Crowston 1990). Therefore, in additionto responding to the requirement for intelligentplanning (Vollmann et al. 1997) for addressingpurely operational requirements, the employment of

ICT that supports argumentation-based knowledgemanagement (argumentation as explanation (vanEemeren et al. 1996)) can provide a consistent

platform that integrates strategic and improvementprocesses across the lean supply network.

Lean operations management concentrates on fiveareas which are associated to different but interrelateddesign and operational tasks. First, the management of

the value stream starts with the specification of valuefrom the customer point of view. In the context ofsupply network management, value is defined notonly by the end (external) customers but also by the

internal ones, and is related to product and servicecharacteristics, as well as to the information that

accompanies them. The collaboration of partners of

supply networks for accomplishing incremental and

radical innovations through learning is a highly sought

activity (Bessant 2004, Chapman and Corso 2005).

Undoubtedly, value of long-term significance is created

when innovative offerings are developed to best meet

the needs of customers. In operational terms, however,

innovation is a process where knowledgeable and

creative people and organisations frame problems,

and select, integrate, and augment information to

create understandings and answers (Teece 2001). In

this process, the role of information technology is not

only to organise data into useful information, but also

to enable the transformation of personal information

into newly-created organisational knowledge by struc-

turing the problem space and by coordinating activities

and actors to tame the social complexity of the

problem resolution process (the process of knowing).

These are the main tasks of computer-based knowledge

management systems (CKMS), which can be defined as

systems intended to provide a corporate memory, i.e.

an explicit, disembodied persistent representation of

the knowledge and information (a sort of knowledge

base) in an organisation or a network or related

organisation and mechanisms that improve the sharing

and dissemination of knowledge by facilitating inter-

action and collaboration (Taylor 2004).Once value has been specified in the form of

product (or/and service) and market characteristics, on

the way towards lean operations the supply-network’s

structure and behaviour necessary for seizing this value

has to be determined. This is the subject of supply-

chain/network strategy formulation, whose content has

been addressed both as a separate entity (Fisher 1997,

Childerhouse and Towill 2000), as well as within the

framework of manufacturing/operations strategy (e.g.

Slack and Lewis 2002, Appelqvist 2003). In the

framework of the first approach, Fisher (1997) used a

configurational approach to derive normative condi-

tions for the objectives and the behaviour of supply

chains suitable for functional (stable demand, low

margins, long life cycles) and innovative (changing

demand, high margins, short life cycles) products. He

suggested that the former should be supported by

efficient (low cost) supply chains, whereas the latter by

responsive ones (no inventories and stock-outs in sharp

demand fluctuations). In a similar logic, Childerhouse

and Towill (2000) proposed efficient supply chains for

functional products and the employment of the

concept of ‘leagility’ for innovative ones. The leagile

(lean and agile) supply chain has an efficient (lean) and

a responsive (agile) part separated by a decoupling

(strategic) inventory.

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In the second approach, scholars and practitionersof operations/manufacturing strategy that distancethemselves from ‘best-practice’/configurationalapproaches (‘recipes can easily be imitated, thus theyare not strategic’) (Hayes et al. 1996, Hill 2000, Slackand Lewis 2002), view supply network strategy undertheir own subject’s broad umbrella as a set of supply-related decisions that must be taken for achievinggeneric, previously prioritised operational objectivessuch as cost, flexibility, dependability, speed, quality,innovativeness, service, etc. In practice, the objective isto develop and leverage the appropriate supply-net-work resources and capabilities which are in long-termcorrespondence with the environment-induced, butmanagement-prioritised, objectives (Gagnon 1999).Clearly, this is an iterative group decision processinvolving participants from different functions anddifferent organisations (Riis et al. 2006). Informationtechnology with the characteristics of the aforemen-tioned computerised knowledge management systemscan assist and leverage this collaborative effort notonly by helping strategists to reach an agreed actionplan effectively, but also by augmenting (inter)organi-sational learning in the strategy process per se (Lane1994, Karacapilidis et al. 2006).

The definition of value and the alignment ofoperational resources and capabilities with operationalobjectives act as inputs to the process of defining thevalue stream which extends along the entire supplynetwork. Mapping, even better modelling and simulat-ing, the value stream facilitates the development ofshared understanding and the identification of initia-tives for its improvement, e.g. for reducing oreliminating waste (Rother and Shook 1998, Mertinsand Jochem 2001, Duggan 2002). In multiple partici-pant/stakeholder settings, collaborative modelling andsimulation technology (Miller et al. 2001, Taylor 2001,Umeda and Zhang 2006) enhances the design and/orredesign tasks (including the implementation of ‘flow’and ‘pull’ objectives) by acting as the transitionalobject (Papert 1980) for improvement ideas, mindframes and argumentations, thus fully supportingactions towards the ‘continuous search for perfection’imperative of lean management (Lamming 1994,Middel et al. 2005).

Finally, although the ‘single-piece flow’ and ‘pullby the customer’ objectives are associated with thedesign phase of supply networks (the definition ofstructural and operational characteristics of thesystem), they also entail purely operational challengeswhich are addressed at the information rather than theknowledge layer. So, in addition to the value streamdefinition task that takes place at design time, theoperational model underlying the planning and

execution mechanism for specific value streams and

for specific time frames and demand patterns, shouldguarantee that flow and pull of waste-free activities areexecuted in an efficient manner. For this task, internet

technology (XDM and APS) has been proposed as abetter alternative to attempts of legacy system (ERP)integration (Kehoe and Boughton 2001). Nevertheless,since lean is contingent to stable demand and operating

conditions, at this level, it is necessary to implementintelligent technologies for assisting in the efficientinstantiations/reconfigurations when the assumed con-

ditions in supply network are not present, and whendemand or internal operating conditions changesignificantly (Vollmann et al. 1997). This can be doneby exploiting, automatically or semi-automatically, the

relations that exist among the activities and resourcesin the value stream maps within the same companyand/or across different companies in the network,

as well as those that exist in individual order fulfilmentplans.

Overall, the ICT requirements for supporting leansupply network management can be summarised in thesupport for synergy (to tame social complexity), as well

as in the consistent integration of knowledge andinformation across activities in the entire product(s)life-cycle. The Co-LEAN software suite describedbelow is a coherent response to these requirements.

3. The Co-LEAN suite

The Co-LEAN suite consists of five interconnectedtools that operate over the internet to enable thedevelopment and implementation of a lean supply

network. As already mentioned, they support knowl-edge, social, and decision-making processes at threelevels: strategic, improvement and operational. At thestrategic level, Co-INNOV supports the collaborative

innovation and product development processes (valuespecification) while Co-NET assists in the collabora-tive development of transparent supply strategies at the

individual node and network levels, whereas Co-SISCis used for collaborative simulation-based supplychain/network design. At the supply-network improve-ment level, Co-SOLVE, in connection with Co-SISC,

supports collaborative problem-solving and improve-ment teams. Finally, at the operational level, Co-LEAN-PE, which is the binding core of the suite,

provides algorithms for rate-based planning andexecution of the supply chains of individual products,groups of product offerings (value streams), andcustomer orders by exploiting the multi-level relations

that exist between operations in different value streamsand different order fulfilment paths. Table 1 shows the

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correspondence of Co-LEAN modules with the lean

management objectives and drivers. Co-LEAN has

been developed over the last four years, initially as

separate components that were later integrated

through Co-LEAN-PE. Figure 1 shows the overall

functional structure of Co-LEAN whose operation and

individual module details are described below. A use

case of a stainless-steel tank manufacturer that

accompanies the description demonstrates the features

of the suite in an applications context.For the implementation of Co-LEAN, technologies

supported by the Microsoft’s.NET platform, such as

ADO.NET, XML Web Services, and Visual J#.NET,

have been exploited. The Delphi Rapid Applications

Development environment was also used. Access to the

tools of the Co-LEAN suite is provided through a

dedicated Web server. To use the complete range of

services provided, users at the focal company, custo-

mers and suppliers, require only a Web browser (i.e.

there is no need to download any specific applicationat the client side). Depending on the tool used eachtime, users may exploit some built-in templates andcustomise their working environment according totheir profile and collaboration requirements. Theinteroperability of the suite’s tools is achieved throughthe exchange of the appropriate XML messages. Thecommunication of the suite’s tools with its proprietarydatabase, model base and knowledge base, as well aswith remote databases is regulated through a dedicatedSQL server. Connections with remote databases areachieved through the OLEDbControls of .NETplatform.

3.1. Developing the lean supply network:Co-INNOV, Co-NET and Co-SISC

Co-INNOV and Co-SOLVE are based onKnowledge Breeder, a web based computer-supported

Table 1. The lean imperatives and the response of the Co-LEAN suite.

The lean supply chain agendaCorresponding tools ofthe Co-LEAN suite

Specify value Co-INNOVDevelop supply chain strategy Co-NETMap the supply chain, eliminate waste,construct ‘pull’ loops, make value flow

Co-SOLVE, Co-SISC

Collaborative rate-based planning Co-SOLVE, Co-LEAN-PECollaborative rate-based execution(coordination of plans)

Co-LEAN-PE (Relations Manager)

Supply chain improvement Co-SOLVE

Co-LEAN-PE planning

Co-LEAN-PE order

management

Relationsmanager

Schedules(production anddelivery rates)

Forecasteddemand

Actual orders

Customers and

suppliers databases

Supply network(current state)

Collaborationdatabase

Co-INNOV

Co-NET

Co -SISC

Co-SOLVE

Co-LEAN-PE

Figure 1. The functional structure of Co-LEAN.

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argumentation system that implements the G-MoBSA

(group model building by selection and argumenta-

tion) participative problem solving methodology

(Adamides and Karacapilidis 2005, Adamides and

Karacapilidis 2006). Knowledge Breeder uses a

systemic problem-knowledge representation scheme

and an evolutionary problem-resolution methodology

which enables the ‘breeding’ of the knowledge

necessary for the resolution of a specific organisa-

tional issue. Co-SOLVE is a stand-alone environment

used as a platform for argumentation-based resolu-

tion of specific lean supply chain improvement issues,

also enabling evolutionary decision making.

Co-INNOV, on the other hand, implements a more

refined and domain-specific version of Co-SOLVE by

supporting the value specification, innovation and

product development process in its entirety, enabling

the gradual ‘breeding’ of innovation concepts.

In Co-INNOV, the value specification and/or the

innovation process is/are viewed as a sequence (not

necessarily being executed in linear fashion) of issue/

problem resolutions/solutions (Leonard and Sensiper

2003), in which cause-effect-like models are used to

represent individual and organisational cognitive

schemata of related issues and their possible resolu-

tion(s). If the value specification task involves an

already existing product, Co-INNOV allows for the

‘deconstruction’ of the final offering to identify the

principal sources of value for the customers.

The models proposed have a generic structure of the

following form:

Through Co-INNOV, all the participants involvedin the value specification process are able to providetheir own complete interpretations and proposals ofthe issues concerned in the form of the logic-basedcause-effect models given above. Clearly, models arethe result of individual perceptions of the internal and

external organisation, market and supply network

environment. All models are opportunistic representa-

tions of the problem and solution spaces and are

subject to discussion, argumentation, and eventually,

modification by the same or other actors as more

information is crystallised in the form of organisational

knowledge. In this way, Co-INNOV, as well as the rest

of Co-LEAN’s modules, fully supports the empirically

observed opportunity-driven design and problem-

solving process (Guindon 1990).In the argumentation process, conflict resolution is

through formal argumentation (logic) rules. The

defensibility of each model (the assessment of its

coherence as a collectively-owned knowledge item) is

determined as an indication of its validity, which acts

as suggestion for its eventual collective selection or

rejection. On the basis of their perception of the issue,

participants can construct and propose models of the

problem and their solutions using the problem-solution

modelling formalism. As they have access to the whole

set of models proposed, they may then adjust their own

models and/or contribute to the construction of other

models accordingly. Both a model per se (complete-

ness) and/or its defensibility (fact-supported argumen-

tation) can change a participant’s perception of the

issue. As a result, mental models (beliefs) are conver-

ging around specific models which attract more

attention concentrating the argumentation on them.

Normally, the model that is best supported by facts

and attracts the majority of favourable views of the

group is selected.

The argumentation system of Co-INNOV, as wellas those of the other collaboration supporting modulesof Co-LEAN, relies on the system (set of rules forargument placement and conflict resolution) of logicalpropedeutic of the Erlangen school (van Eemeren et al.1996). Complete arguments are represented by means

because symptoms S1,S2,S3 . . . are observed Symptoms of the issue

�observations supported by arguments AS1,1,AS1,2,. . .AS2,1,AS2,2 . . . ,

problem � is what characterises the issue, Problem identification

�caused by R1,R2,R3,. . . , Roots of the problem

�causes are supported by arguments AR1,1,AR1,2,. . .AR2,1,AR2,2 . . . ,

solution � is the most appropriate Proposed solution

�because actions A1,A2,A3,. . . which are implied in the solution

eliminate R1,R2,R3,. . . , Justification of solution

and � is feasible and effective solution

�because actions result in ðobservable effectsÞ E1,E2,E3,. . .

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of simple statements related by logical connectives(operators). The logical connectives used are confinedto: AND (conjunction), OR (disjunction),IF . . .THEN (implication) and NOT (negation). Theargumentation schema provides the rules for conduct-ing the dialogue among participants and for resolvingconflicts, i.e. it indicates which argument or clauseholds and which is defeated.

Structurally, the kernel of Co-INNOV consists ofits knowledge base that stores models under considera-tion, as well as models of already closed discussions.Any form of electronic information (text, spreadsheets,hypertext, drawings, photographs, etc.), as well asdirect links to individual tools (e.g. to tools supportingthe engineering design phase of product development)can be attached to the model(s) and transmitted toother participants. Models are stored and selectedhierarchically using a meta-model of the issuesaddressed (context definition). Users can upload thecurrent issues under consideration in which they wishto be involved, see the current state of the dialogue andcontribute accordingly. They can then move into otherissues through the navigating meta-model. By takinginto account the structure of the model, the argumentsplaced and the argumentation rules, the inferenceengine of the computer-assisted argumentation moduledetermines the defensibility of each model-proposal ofproblem-solution. The interface of Co-INNOV (as wellas those of Co-SOLVE and Co-NET) is in hyper-textual form with menus associated to the featuresprovided, and diverse functionalities related to visua-lisation (folding/unfolding of model components, view/hide of inputs, creators, dates, etc.).

Use case 1. A proposal for new value definition in theindustrial equipment sector

Stainless Steel Tanks (SST) SA is based in Greece andis one of the largest manufacturers of stainless steelindustrial equipment in south eastern Europe. (As thecase description inevitably contains information ofstrategic nature, the real name of the company andother identifying details are protected.) The companyspecialises in the production of stainless steel tank-likeequipment for the food (oil, dairy) and alcoholicbeverages (wine, beer) industries, i.e. fermenters,stabilisers, vinificators, oil and milk vats, etc. Inaddition to a standard product range, which consistsof about 50 products, the company undertakes thedevelopment and production of customised productsand turn-key projects for the above industries, as wellas for other more demanding ones, including pharma-ceuticals. The main suppliers of SST are a steel mill,various suppliers of motors and electro-mechanical

components such as valves, shakers, sensors, etc., aswell as suppliers of materials for the construction ofheating and cooling jackets. The custom products andturn-key projects (mainly breweries and micro-brew-eries) are built to order and their components areforwarded and installed under SST’s own responsi-bility. At the time of the study, the core productionfacility of SST was located at a distance of about300 km from Athens, and the company’s downstreamsupply network included a distribution centre/ware-house for supporting sales in the Athens metropolitanregion, four regional distributors, as well as retailers allover Greece, and agents/resellers in five other nearbycountries.

In the process of adoption of a lean operationsmanagement style, SST agreed to host the pilotapplication of the Co-LEAN suite. The software wasinstalled at the company’s headquarters and, aftera short training and familiarisation period, access wasgranted to its main suppliers and customers (distribu-tors and retailers). Although Co-INNOV was not thefirst module of which actual use was made, for thecontinuity of the presentation Figure 2 shows ascreenshot of the use of this module for collaborativelyidentifying with customers new sources of value. In theinstance of the argumentative dialogue shown, whichas it can be clearly observed adheres to the syntaxoutlined above, the market of used equipment as a newsource of value is discussed. A complete model wassubmitted by a manager of a SST customer company(George). In the instance shown there is only a counterargument on the complete position raised by a SSTmanager (Thanos) which concerns the need forconsulting activities if his company enters the usedequipment market. In reality, the debate on enteringthis market lasted for a couple of months and attractedall the major suppliers and customers that were givenaccess to the software. The final decision taken was toenter this market whose organisation proved to be asignificant source of value for both the company(intermediary), as well as for large and smallercustomers, acting as sellers and buyers, respectively,within a lean supply network operation (see below).

Co-NET is a customised version of Co-MASSwhich is a computerised knowledge managementsystem for assisting operations managers in theformulation of manufacturing and operations strategy(Karacapilidis et al. 2003). It supports the social andknowledge processes of collaborative manufacturingstrategy development by integrating a domain-specificmodelling formalism based on the resource-basedtheory of competitive advantage (Wernerfelt 1984,Gagnon 1999), an associated structured dialoguescheme, again an argumentation-enabling mechanism,

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and an efficient algorithm for the evaluation ofalternatives. Co-NET helps in deciding on the supplychain related resources and capabilities, which areessential for achieving the prioritised objectives derivedfrom value definition. For example, in the typicaloperations logic, if it becomes clear that customersvalue ‘variety’ highly in a product range, oncethis source of value has been identified, the innovationand product development function comes up witha ‘modular design’ strategy and the operationsfunction puts ‘flexibility’ as the primary objective ofproduction and supply chain initiatives. That is, theresources and capabilities system of production andsupply chain should be considered under the objectiveof flexibility.

As a technological artefact, Co-NET can beconsidered as a web-based application-specific knowl-edge management system. Compared with otherinformation systems proposed for the collaborativedevelopment of strategy, Co-NET takes a moreevolutionary perspective based on the aforementionedG-MoBSA methodology. That is, it relies on theassumption that strategy development is a process thatbegins with the exploration of as many alternatives aspossible, followed by the gradual exploitation of themost appropriate of them. Empirical evidence has

shown that in team-based strategy development there

is interplay between social and knowledge processes

(Schwarz 2003). Groups-within-groups of managers

with similar views can emerge at any instance as a

result of knowledge exchange and (re)construction.

The group with the most persuasive idea, or solution,

attracts a critical mass of supporters who argue in its

favour. Other groups/views attract less support and

more opinions against their proposals for action.

As social processes result in the formation of groups,

knowledge is clustered around specific ideas, solutions

or views.

Use case (revisited) 2. Developing supply network

strategy

One issue of strategic importance related to the

supply network of SST was the assessment of the

effect of the used industrial equipment market on

the overall operations strategy of the company, as

well as the determination of the necessary capabil-

ities for this market. Argumentative discussion

among supply network participants (managers from

different functions, as well as from supplier and

customer organisations) included both the determi-

nation/prioritisation of strategic objectives and the

Figure 2. A sample dialogue for value specification.

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assessment of the capabilities that are required for

achieving them. In particular, the discussion was

centred on the importance of quality and depend-

ability as strategic directions. Optimistic (quality will

contribute to the enlargement of markets) and

pessimistic (quality will increase the reliability and

life span of products, and will eventually saturate

markets) views were expressed according to the

position of the proponent organisations in the

topology of the supply network. Suppliers were

sceptical about increased quality (and prices) in

connection with the development of the used

equipment market. Distributors and retailers, on

the other hand, were optimistic that the increased

quality and the used-equipment market will stimu-

late demand as a brand name synonymous with

quality will be established and more new customers

will be approached. The latter views proved more

logically sound in the debate as they were supported

by stronger arguments and were eventually adopted.

Nonetheless, the open argumentative debate of the

issue and the logic of the arguments placed built

more trust among stakeholders as, in addition to

specific positions, ways of thinking were exposed

and discussed.In the fringe between strategy and operations, the

‘leaning’ process of a supply network is facilitated by

value stream mapping (Rother and Shook 1998).

Towards this end, Co-SISC implements a language

and dialoguing structure specific to simulation-

modelling-based supply chain design (Karacapilidis

et al. 2004). Co-SISC is used for mapping the value

stream and for collaboratively identifying sources of

waste. It deploys a generic systems-oriented language

(activities, resources, decisions and their structural

and operational parameters), thus enabling different

commercial simulation environments to be easily

incorporated with. Again, argumentation on model

items and their attributes is supported by the system,

as is storage and retrieval of discussions/argumenta-

tions and simulation models. The construction,

validation and verification of simulation models are

accomplished by a simulation specialist (technical

facilitator) (probably the only external consultant

engaged when using Co-LEAN), whilst the rest of

decision makers/participants can only see its structure

and simulation results, as well as experiment with

different parameters. So, in addition to value stream

mapping and waste identification, collaborative mod-

elling using Co-SISC augments shared understanding,

transparency of individual decisions and trust build-

ing along the supply network through the execution

of the modelling and simulation process per se.

Use case (revisited) 3. ‘Leaning’ operations in the

supply network (elimination of waste, small batchflow and pulling by the customer)

At this stage the actual ‘leaning’ of SST’s supply

network was accomplished. The process started witha one-day modelling/mapping workshop, on whichmembers of different organisations that participated inSST’s network were exposed to the features andfunctionalities of Co-SISC in the context of value-stream mapping. This was carried out by modelling theexisting (non-lean) supply network which did not

include the collection and selling of used equipment.With the help of an external consultant, the

Operations Management division of SST used themodel developed in the workshop to determineinitiatives towards a leaner supply network. The‘leaning’ of the network downstream was considerednecessary due to the bulkiness of the end products thatwere difficult and costly to handle at every processing,transportation and storage node. It should be noted

that before considering its supply network, an attemptto lean the internal operations by defining productfamilies (mainly around market segmentation: wine-making, brewery, dairy, etc) and developing theassociated value stream maps were attempted.However, in view of the new operations to be under-taken, it was thought that only the lean operation of

the whole network could provide significant results. Asa consequence, SST’s Operations Management func-tion launched an initiative for ‘leaning’ the supplynetwork by forming the project team mentionedbefore.

Using Co-SOLVE and Co-SISC, the team identi-fied three supply chains spanning the network, eachhaving different strategic objectives and correspondingto three value streams: the supply chain of standard

products, the supply chain of custom built-to-orderproducts, and that of used equipment. Standardproducts had periodic but constant demand, henceefficiency was considered as the principal operationalrequirement. On the other hand, the demand for thesecond-hand and custom equipment (and projects) wasunstable and, therefore, dependability through respon-

sive supply chains was the main requirement. Co-SISCwas used for the design of the whole network (all threesupply chains). The existing simulation model wasmodified collaboratively to investigate the effect of twoproposed changes towards leaner supply and distribu-tion: the elimination of the Athens warehouse and theintroduction of mixed-mode production through level

schedules (heijunka) for the standard products(Figure 3). Both issues were debated extensively usingthe argumentation-supporting functionalities of

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Co-SOLVE. Based on different (stochastic) end-customer demand patterns, different production rates(capacity bounds) were obtained and assessed, both intechnical and economic terms. The interoperability ofthe three supply chains and the essential (minimum)resource requirements for the whole network were alsoinvestigated through simulation modelling.

The resulting operational structure of SST’s supplynetwork is described in the following section where theuse of Co-LEAN-PE is presented.

3.2. Managing the lean supply chain. Rate basedplanning and execution using Co-LEAN-PE

The Co-LEAN-supported operations management ofthe lean supply network relies on the appropriatedesign and development accomplished throughCo-INNOV, Co-NET, Co-SISC and Co-SOLVE.The design provides the structure and the fundamentalmodus operandi on which specific medium- to short-term operations plans are based on. At the pureoperational level, Co-LEAN-PE is the suite’s coremodule responsible for the rate-based planning andexecution of the lean supply chain. It uses forecastedand actual demand data, as well as information from acontinuously updated supply database concerning

products, suppliers and supplier relations to accom-

plish a production and/or delivery schedule (rates)

based on the end-customer demand. The principal task

of this module is to develop operational plans

(schedules) for the different value streams at-large

and then to co-ordinate them at the macro (demand

smoothing – planning) and micro (order fulfilment –

plan execution) levels, respectively. To achieve this, it

executes a nested top-down process that starts with the

co-ordination of the plans for the different types of

offerings (e.g. standardised and custom products),

moves down to the coordination of different product

value streams, and ends at the execution of individual

orders.The whole process of schedule determination and

coordination takes place in two phases. At the initial

phase (planning), past orders from end customer

selling points, after being ‘translated’ into production

and delivery rates/capacities, are aggregated, averaged

and used in connection with the products’ bills-of-

material to broadcast capacity bounds (production and

delivery rates) to the nodes (companies) of the supply

network. Based on these values, by using takt times,

the levelled schedule of the focal company and its basic

production sequence within an interval are obtained.

In this way, the operational model assumed in the

Figure 3. Modelling dialogue and simulation model in Co-SISC.

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design of the software treats the focal company as the

‘pacemaker’ process which is linked to the other

network nodes through supermarket-operated

Kanban loops. After their determination, the rate-

based plans are co-ordinated by using the Relations

Manager (see below).At a second phase (execution), the actual end-

customer orders are treated individually and their

fulfilment plans are co-ordinated so that, within the

calculated bounds, the best possible use of resources is

made. In other words, the Kanban loops are optimised

through the co-ordination of individual order execu-

tion streams/plans. This co-ordination is also accom-

plished by the Relations Manager, which is a module

that uses conventional (Coloured Timed Petri Nets)

and artificial intelligence techniques to represent and

manage the relations that exist among the activities

and resources in the plans. Using due dates and lead

times, the orders are expanded as timed plans which,

starting from the outmost-tier supplier activities down-

stream (e.g. delivery from distributor to retailer), are

compared to extract possible relations among them

with respect to resource usage. A virtual actor is

assigned to each order and takes the responsibility for

its most effective fulfilment by extracting at each stage

of the plan the previously mentioned relations

(Adamides 1996). Once relations are extracted, plan

modification operators are employed. The relations

defined and used for the co-ordination are both

‘positive’ and ‘negative’ (von Martial 1992, Adamides

1996). Positive relations are the ‘equality’ (an activity is

included in the plan of a different (virtual) actor too)

and the ‘favour’ relation (a task can be undertaken by

a different activity or active resource producing the

same outcome). On the other hand, the most common

negative relation is ‘conflict’, usually associated with

the requirement of two or more activities for the same

resource, at the same time. The identification of

relations involves the transformation of activity

execution times on an absolute time scale for compar-

ison (von Martial 1992). Appropriate parameterised

operators are used to handle relations (‘move-time-

forward’, ‘move-time-back’, and ‘prioritise’ for con-

flict, ‘do-favour’ for favour and ‘do-equal’ for

equality).The employment of the Relations Manager is of

particular importance when the execution plans of the

actual orders (execution phase) divert significantly

from the rates determined in the first phase, either

because of a significant change in demand, or because

suppliers declare inability to accomplish schedules.

Relations that exist among products (order character-

istics) and suppliers (resources) are considered with

respect to the two principal network node/processorcharacteristics: capacity and capability.

‘Capacity’ refers to the ability of a different nodethat has the product in its current schedule (or in itsstocks) to supplement the initially selected supplier(s),processors in general, with additional capacity,whereas ‘capability’ refers to the ability of producingthe product(s) requiring additional capacity (theproduct is not in the current production mix andthere is no stock). The additional cost burdens that theexploitation of positive relations and the resolution ofnegative ones imply are then calculated. However,frequently rescheduling and reconfiguration decisionsrequire additional qualitative information and discus-sion and argumentation using the features of the othermodules of Co-LEAN. Information and agreementsabout available capacities and capabilities are theresult of argumentative discussion using the othermodules of the Co-LEAN suite.

Use case (revisited) 4. The operation of the leansupply network

To demonstrate the operational support mechanismsof Co-LEAN-PE, we consider two of SST’s productsin vitro: the 60m3 rotary vinificator (code name RV60)and the 100m3 milk vat (MV100). A somewhatsimplified bill of materials (BOM) for RV60 wouldcontain the steel for the 60m3 hollow cylinder(supplied by S1), three valves, one thermometer, oneshaker (all supplied by S2), one standard motor, onePLC module (all supplied by S3) and materials for thecorresponding cooling jacket (supplied by S4).Similarly, the BOM for MV100 consists of the steelfor the 100m3 hollow cylinder (supplied by S1), fourvalves, one thermometer, one spray ball (all suppliedby S2), three sensors (supplied by S3) and materials forthe corresponding heating jacket (supplied by S4).

The average monthly demand (excluding theseasonal trend for wine-making equipment) for RV60was determined by Co-LEAN-PE to be 60 units andthat of MV100 90 units (Co-LEAN-PE has threedifferent forecasting methods, which can be selectedaccordingly). On the basis of the calculated levelledschedule, and taking into account the correspondingBOMs, Co-LEAN-PE calculated the daily suppliesrequired for the production of the product range. Thismeans that for producing two units of RV60 and threeunits of MV100, 2*steel(60m3), 3*steel(100m3), 18valves, five thermometers, three shakers, three spray-balls, two motors, four PLC modules, six sensors,2*cooling jacket material (60m3) and 3*heating jacketmaterial (100m3) have to be delivered to the SST’sfacilities daily.

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On average, SST operates 30 shifts per month,which corresponded to small batch daily production oftwo units of RV60 and three units of MV100. For thesake of the simplicity of presentation, we assume herethat SST has only two distributors (D1 and D2), andeach of them supplying two retailers. In the absence ofactual orders placed by the distributors, dispatches todistributors take place every three days, i.e. a bufferinventory (Kanban supermarket) of up to six RV60and nine MV100 that is held at SST is emptied. Then,three RV60 are dispatched to D1, three RV60 to D2,four MV100 to D1, and five MV100 to D2. Thisoperation acts as ‘pitch’ for assessing the levelledschedule with respect to the actual orders and forcarrying out corrective actions accordingly. Obviously,in the logic of rate-based planning, all the abovesupplier and customer delivery, as well as production

rates correspond to resource capacities expressed asreserved time slots.

This smooth rate-based operational plan of thesupply network for the aggregated value chain ofstandard products had to be co-ordinated with thevalue streams of customised and used products. Insidethe factory, co-ordination took place at the product-family value stream level. In Co-LEAN-PE valuestream co-ordination, at various levels, is accomplishedautomatically by the Relations Manager as newinformation representing the state of the supplynetwork is fed to the system’s databases. A case ofco-ordination corresponding to the plan for the twostandard products of SST with that of custom orders isshown in Figure 4 (only the steel supply chain isshown). The numerical values in the custom-productsvalue stream correspond to the average daily demand

PRODUCESTEEL(2×60+3 ×100 m3)by: midday 1

Required capacity: 15 minutes

DELIVERSTEEL(2×60+3×100 m3)by: midday 2

Required capacity: 3 hours

PRODUCETANKS (2×60+3×100 m3)by: end-day 3

Required capacity: 40 minutes

DELIVERTANKS (2×60+ 3×100 m3)to D1, by: midday 6

Required capacity: 3 hours

DELIVERTANKS (2×60+ 3×100 m3)to R1D1, by: end-day 6

Required capacity: 1 hour

Capability and capacity of steel suppliers

Required capacity: 5 minutes

PRODUCESTEEL(~200 m3)by: midday 1

Required capacity: 3 hours

DELIVERSTEEL(~200 m3)by: midday 1

PRODUCETANKS (custom) by: end-day 3

Required capacity: 5 hours

DELIVERTANKS (custom) by: end-day 4

Delivery capability and capacity of steel suppliers

Capability and capacity of SST

Required capacity: 15 minutes

Delivery capability and capacity of SST

Delivery capability and capacity of distributors

Conflictmove-time-forward ->midday2

Favour do favour

Figure 4. Co-ordination using relations in Co-LEAN-PE.

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for such products. As it can be seen, co-ordination atthis level concerns more the supply part of the network(push part) than the demand satisfaction downstreampart controlled by Kanbans (pull part). In this plan, aconflict relation was detected between the activitiesPRODUCE STEEL for the standard and customproducts, respectively because the steel mill waslacking the capacity to accommodate the combineddemand within the required time constraints.After detecting this negative relation, the ‘move-time-forward’ operator was engaged for adding to the starttime of the activity for the custom products at extratime and displacing its due date to ‘mid-day2’ (insteadof ‘mid-date1’). In addition, a positive relation (favour)was detected in the DELIVER STEEL activities which,as long as there was available capacity, could be bothmoved to only one of the two plans (do-favouroperator). Additional, more demanding conflict reso-lution cases involved the sourcing of steel from adifferent supplier that had the required capability andcapacity, and the use of a different supplier’s trans-portation medium (e.g. that of S2) to deliver on theinitially assigned time. In both cases, these possiblefavour relations are the result of suppliers’ databaseconsultation (suppliers’ capacities and capabilities).

In a similar manner, at the execution phase,Co-LEAN-PE co-ordinated the individual (actual)orders placed by retailers. Here, the co-ordinatedplans for the average demand (the pitch) played a

passive role, but they were the medium through whichthe order fulfilment plans were co-ordinated. Activitiesbelonging to these plans were undertaken or modifiedby the order fulfilment plans according to latter’sneeds. The co-ordination at this phase primarilyconcerned the Kanban loops from the SST’s Kanbansupermarket downstream to the retailers’ deliveries,and the co-ordinated plans for the production anddelivery rates played the role of capacity and capabilitysuppliers and distributors for the efficient orderexecution. The equality relation was detected whenthe delivery rates (capacity) sufficed for the fulfilmentof real orders, the resolution of the conflict relationwas through order prioritisation and delaying, whereasthe favour relation was exploited for optimised use ofresources. For example, instead of returning empty,trucks delivering new equipment were scheduled tocollect used tanks.

Overall, for SST, as well as for its suppliers andcustomers, the adoption and use of Co-LEAN did notprove a particularly difficult task to accomplish.However, as was expected, most of the burden forthe adoption – especially the initial population ofdatabases – was undertaken by SST. With theexception of the population of databases, customersand suppliers were very willing to co-operate. Themanual input of data proved somehow problematicand in full-scale implementations of Co-LEAN thisactivity certainly requires the use of the appropriate

Figure 5. Co-LEAN-PE: the main screen for constructing the supplier database.

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‘data-translation’ technology. In total, the usability ofCo-LEAN would have been improved should theappropriate interoperability technology existed toconnect suppliers’ and customers’ own informationsystems to the modules of the suite.

On the contrary, customers and suppliers were verywilling to discuss issues using the Co-LEAN modules:initially driven by curiosity and willingness forexperimentation with the new medium, later as ameans to put proposals and arguments forward andsupport them. We sensed that users formed theimpression that the argumentation scheme of thesuite acted as an independent trusted arbitrator. Thiswas probably the reason for being accustomed to thesyntax of Co-INNOV, Co-NET, etc. fairly fast, and forinitially using these modules only for issues whereconsensus was not apparent. Gradually, however, theuse of the suite, with the exception of Co-SISC, becamealmost a routine. The technical complexity of Co-SISCrepelled busy executives and it became apparent thatonly well-planned fully-facilitated workshops couldhave a significant impact on the definition and analysisof the supply network value streams using the featuresof this module.

A testimonial for the significance of Co-LEAN wasgiven by a SST manager who said that the softwarehelped him better understand the wine-making market.For the first time he actually listened to his customers.Previously, even when he was visiting customers(distributors) to try and find solutions on leaning thesupply chain to cut-off SST’s and distributors’inventories and reduce costs, the emphasis was in justimposing a solution devised in the office, not askingany questions and opinions. The distributors wereunprepared to suggest different things, the discussionwas just for the sake of discussion, ‘short-termism’ anda shallow approach were prevailing. The installation ofthe software per se resulted in distributors andsuppliers feeling more important and part of anetwork/team. They realised that SST wanted toreally understand them and co-operate for theirmutual benefit.

In addition, the software was a driver for persuad-ing suppliers and customers to be engaged in leaninitiatives. Otherwise, they were reluctant to partici-pate in what they called ‘intangible’ programmes andinitiatives that frequently proved to be just fads. Theinterconnectivity and collaboration were experiencedbefore starting to think in terms of value streams,heijunka, etc. A SST executive that was proficient inlean management tools and techniques provided afirst-class learning experience through informal discus-sion sessions of particular issues. Moreover, theautomation of routine tasks in Co-LEAN-PE removed

any inconsistencies in the methods used in the differentnodes of the network and made this activity far moreefficient and consistent.

Summarising our experiences from this pilot study,we stress three issues of concern for the adoption ofthis sort of technology for lean supply chain/networkmanagement:

(1) The need for technological integration andconsistency with the rest of the ICT infrastruc-ture of customers and suppliers.

(2) The necessity of a pre-existing positiveapproach looking towards a co-operativeenvironment – technology itself cannot createthis, it can just enhance it.

(3) The leading role of the focal company inmaking clear to its suppliers and customersthat the software tool is just an instrument forfacilitating the lean management process. Itdoes not guarantee lean performance, and it isreally up to the organisations involved to devisethe appropriate means and processes forachieving it.

4. Discussion and conclusions

Although the successful implementation of leanmanufacturing is marginally dependent on informa-tion and communication technology (ICT), thegeographic and mental distances involved in (lean)supply chains/networks necessitate the use of ICT.Many vendors have identified this need and devel-oped integrated software systems for supporting leansupply chain management. These systems, in additionto providing operational support for lean logistics,concentrate on the management of data required toidentify non- or low-value adding activities and toreduce costs. Undoubtedly, these are valuable fea-tures but the essence of lean supply networkmanagement lies in the systemic coherence of thenetwork which is enabled by collaborative behaviour.In other words, to gain competitive advantagethrough a lean supply network, prior to leveragingthe intellectual capital across the network, a firmneeds to build social capital in it (Nahapiet andGhosal 1998). As a determining attribute of leanmanagement, collaboration depends on the manage-ment of human interactions encountered amongmanagers and employees of participating companies.

The efficient management of these interactions issynonymous with the elimination of the boundariesthat exist between the companies in the supplynetwork. Conventional ICT technology for leansupply network management tries to get control of

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the supply network dynamics through standardisa-tion of the interfaces between participating firms.Standardised interfacing facilitates data and informa-tion exchange but, in effect, fragments knowledge,the processes of knowing and their creative interplayrequired for achieving shared understanding andcollaboration. Inter-company and functional bound-aries continue to exist, and do not only inhibitcommunication, but most importantly prevent indi-viduals from altering their knowledge in response toevents and attitudes occurring in the network, orfrom acting towards altering the knowledge of othermembers of the network. Boundary spanners (indi-viduals assigned the specific role of facilitating themeaningful communication between organisationsand/or organisational entities) and boundary objects(artefacts like models used to create shared contextamong different organisations) can overcome theproblems of knowledge boundaries and facilitatedistributed co-ordination (Carlile 2002). Since bound-ary spanners are almost impossible to operate ingeographically dispersed supply chains, boundaryobjects seem to be the most appropriate means forcoordinating the lean supply chain.

In effect, this is where the value of the Co-LEANsuite rests. It is an integrated set of boundary objectsthat can be employed on-demand according to thespecific task or initiative of lean management. Thetechnological homogeneity and integration of the toolsand the interoperability of the models used allow theintegration of the knowledge produced and used in thedifferent tasks of lean supply chain management.Knowledge integration and creation can take place attwo different levels: at the specific task level (e.g. valuespecification) where different knowledge sources fromdifferent participating companies are engaged, andlongitudinally across different tasks as knowledgedeveloped in dealing with them can be used in newlyarising situations. For instance, the definition of therelations used at the operational level by theCo-LEAN-PE module may be the result of priordiscussions, argumentations, and eventually knowl-edge integration that take place when dealing withissues in the milieus of value specification, supplynetwork strategy, or even in the framework ofcollaborative improvement programmes.

Summarising, the initial application of Co-LEANpresented in the paper revealed the necessity ofcollaboration at the strategic level and co-ordinationat the operational level of lean supply networkmanagement. In addition, it showed that informationand communication technology has a significant roleto play in lean transformation and operation ofsupply networks, principally not by automating tasks

and procedures, but by providing the enablingknowledge and social infrastructure required tocollaboratively structure the issues involved and tomanage the social complexity of their resolution.

Notes on contributors

Emmanuel D. Adamides is a tenuredAssistant Professor of Operations andTechnology Management in theSection of Management of theDepartment of MechanicalEngineering and Aeronautics of theUniversity of Patras, in Greece.Professor Adamides is a graduate ofDemocritus University of Thrace(Greece), the University of

Manchester, and the University of Sussex (UK). Beforejoining the University of Patras he held academic andprofessional positions in Switzerland and Greece. He haspublished extensively in the areas of systems engineering,operations strategy, strategy and knowledge management,and innovation and technology management. His currentresearch interests are in the areas of manufacturing strategy,and innovation and technology management with a specialinterest in sustainable production technologies. He isparticularly interested in the development and use of systemsmethodologies and tools to support managerial activities inthe above areas.

Nikos Karacapilidis holds the positionof Professor in ManagementInformation Systems at the IndustrialManagement and InformationSystems Laboratory, Department ofMechanical Engineering andAeronautics, University of Patras,Greece. His research interests lie inthe areas of Intelligent web-basedinformation systems, technology-enhanced learning, e-collaboration,

knowledge management systems, group decision supportsystems, computer-supported argumentation, enterpriseinformation systems and semantic web. He has publishedin several business and information systems related journals.More detailed information about his publications list,research projects involved and professional activities can befound at http://www.mech.upatras.gr/�nikos/

Dimitrios P. Koumanakos is a PhDcandidate in the IndustrialManagement and InformationSystems Laboratory of theDepartment of MechanicalEngineering and Aeronautics of theUniversity of Patras, Greece. Hisresearch interests are related to leansupply chain management, inventorymanagement, as well as product

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design and concurrent engineering. His professional experi-ence in the field includes the position of Venue LogisticsManager in the city of Patras during the Olympics Games ofAthens 2004.

Charalambia Pylarinou has graduatedfrom the University of Hull (UK) withthe degree of Masters of Engineering(Mechanical Engineering) in July2004. In November 2004 she startedher PhD in the IndustrialManagement and InformationSystems Laboratory of theDepartment of MechanicalEngineering and Aeronautics of the

University of Patras. Her research interests are related to theco-ordination of lean supply chain, simulation modelling,and generally production planning and management, as wellas knowledge management in decision making.

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