Collaborative decision-making support system to enhance competencies within enterprise networks

Transcription

1 Collaborative decision-making support system to enhance competencies within enterprise networks X. Boucher Ecole Nationale Supérieure des Mines de Saint-Etienne, 158 cours Fauriel, F Saint-Etienne Cedex, France RÉSUMÉ. Cet article présente un système d aide à la décision destiné à faciliter la gestion collaborative des compétences, dans un contexte de réseau d entreprises. Nous nous intéressons ici au développement de compétences similaires au sein d un réseau d entreprises pérenne sur le long terme. L approche proposée a pour objectif de comparer différentes alternatives de plans d action pour le développement de compétences. Nous décrivons les compétences d entreprises par des sous-ensembles flous, et nous utilisons une méthode d aide à la décision multi-critères. Nous appliquons cette approche à un cas de réseau de PME dans le secteur de l industrie logicielle. ABSTRACT. This paper presents a decision support system to facilitate the collaborative management of enterprise competencies, in the context of company networks. By hypothesis, this research focuses on the development of similar proficiencies within long term stable networks. The decision procedure is based on a comparison among alternative competence development action plans. Enterprise competencies are described using fuzzy subsets and a multi-criteria decision aid method is employed. This approach is applied to a SME network, in the area of the software industry. MOTS-CLÉS : Aide à la décision, Méthode AHP, Gestion des compétences, Réseaux d entreprises. KEYWORDS: Decision support system, AHP method, Competence management, Company networks. Journal of Decision Systems. Volume 18 No. 2/2009

2 320 Journal of Decision Systems. Volume 18 No. 2/ Introduction In a world where technology is ever more accessible to any company, enhancing internal individual and collective competencies increasingly interest company managers, for the competitive advantage they bring. A great deal of scientific work has been produced over the last decade to try and answer this need. In a fairly comprehensive state of the art, (Boucher et al., 2007) studied the impact of competence on efficiency of industrial processes and analyzed several aspects of the causality link between performance and competence. The necessity to better integrate the notion of competence 1 in enterprise information and decision systems was put forth. In the same vein, the current paper proposes a Decision Support System (DSS) to help with the development and fostering of core competencies. The paper focuses on DSS for competence development specifically designed for networked organizations. In the past decade, much research work has underlined that interfirm cooperation are most of the time induced by strategic competence management needs (Sanchez et al., 1996), (Quélin, 1996). For instance, in the domain of agile supply chains, (Yusuf et al., 2004) have shown through statistical analysis, that external competence building through supply chain integration as seamless flows of resource coalitions is essential for enhanced competitive performance. Competence management has also been stressed as a key issue in the field of virtual organizations (Abair, 1995) (Gunasekaran, 1998) often considered as a temporary alliance between a number of core competence based firms/individuals, formed to take advantage of market opportunities (Lackenby and Seddighi, 2002). In this field of networked organizations, competence management appears necessary at distinct phases of the life cycles of organizations (Camarinha Matos et al., 2008a). Some contributions use the notion of competence to deal with the creation phase of virtual organizations. Often, the objective is to use competence-oriented criteria, in the decision process of partner selection for a virtual organization (Pedersen and Vanden Berg, 2001), (Petersen, 2003), (Camarinha Matos et al., 2008b). In the current paper, we examine another phase of the virtual organization life cycle. Several research publications have demonstrated the added-value of establishing Virtual Breeding Environments (VBEs), in the preparation phase prior to the virtual organization start (Camarinha Matos et al., 2008a). VBEs constitute long term collaborative networks whose main objective is to facilitate the creation of highly reactive short term virtual organizations, to quickly respond to opportunities in the market. VBEs provide an organizational environment making possible the time consuming preparation work necessary before launching operational collaborations. In this paper, we consider VBEs as long term networks where a high level of trust among partners is possible. These conditions promote 1 Please note that, in this paper, we are going to use the expression Enterprise proficiencies with the exactly the same meaning that Enterprise competencies.

3 Collaborative DSS ton enhance competencies 321 collective actions for competence transfers and developments. We do suggest that the added-value of virtual breeding environments is not only to accelerate the process of building virtual organizations, but also to offer opportunities for organizational learning among trusting partners. This research examines the issue of proficiency transfer and mutualisation of competence development actions, within long term company networks (VBEs). Our objective is to formalize the notion of competence and then to use it to implement a DSS or cognitive aid, to help managers select suitable collaborative action plans to further develop competence in a networked organization. The feasibility of applying quantitative decision approaches to the notion of competence has already been shown for other types of applications. Here, the model is proposed to represent inter-enterprise collaborative decision processes on competence development scenarios. One of the contributions of the research is to propose quantitative indicators to help with collaborative management decision making, when dealing with competencies. By formalizing the notion of equity and assigning it to organizational learning, a better regulation among individual and shared goals of the companies is possible. Section 2 presents a brief state of the art on the decision approaches applied to competence management for enterprise networks and positions the current contribution. Then, the formalism is explained which is used to manipulate company skill sets, company competence needs and plans of action for competence development (Section 3). The decision procedure for the selection of collaborative scenarios that increase competencies is detailed in section 4. Section 5 illustrates its application in an industrial case study of networked organization. This case study opens some discussions on the operational applicability of the approach (section 6). Finally, a conclusion and several perspectives are suggested. 2. Decision aid for competence management in company networks The focus on core competence as a key concept for performance based decisions was first promoted in the managerial scientific literature with qualitative approaches of proficiency management. However, since then, other scientific fields have integrated this significant notion, and quantitative approaches proposing decision support systems have brought interesting results. An extensive state of the art of the integration of the concept of competence in the field of Industrial Management has been developed in (Boucher et al., 2007). The formalization of competence concepts covers different types of industrial decision processes, for instance: - In the area of production management several decision approaches have been developed: for example, Franchini et al. (2001) use a multi-criteria methodology to manage the assignment of competencies along production processes. Grabot et al. (2000) tackle the issue of production planning optimisation by integrating

4 322 Journal of Decision Systems. Volume 18 No. 2/2009 competence parameters. (Stratman and Roth, 2007) analyze the competence portfolio necessary for successful ERP adoption, and propose a competence measurement scale. - The field of product design management has led to many contributions linked to the cognitive dimension of design activities. Different issues are addressed like project management (Eriksson and Lilliskold, 2005), (Belkadi et al., 2007), team building and competence allocation (Acuna and Juristo, 2004) (Gronau et al., 2007) or collaborative work and coordination processes (Zhu et al., 2002), (Rodriguez and Al-ashaab, 2005). - Other studies concentrate on performance evaluation, by analyzing the impact of competences on process performance. (Zuelch and Becher, 2007) or (Bennour and Crestani, 2007) use a simulation in that objective. Beyond their individual application areas, all these studies led to generic and reusable advances on competence modelling and management. The formalization of competence concepts has acquired an adequate level of maturity, with models supporting the implementation of competence oriented information systems. Some of these models, like the CRAI (Harzallah et al., 2006) got enough maturity to be integrated into enterprise modelling standards such as CEN ENV (Vernadat, 1999). The CRAI model defines the major constructs to integrate competence considerations within a larger enterprise modelling framework. It has been first used as a basis to better take into account competencies within company reengineering projects. The CRAI model has also been further extended to define an ontology supporting competence management (Berio and Harzallah, 2007). Actually, competence models have been the starting point to make a formal link between performance and competence (White, 1996), (Coves, 2000), and to specify Competence Management Systems (Jussopova and Probst, 2007), (Ermilova and Afsarmanesh, 2007). As emphasized in the introduction, this paper will develop decision aids applied to proficiency management for collaborative enterprise networks. We will stress a specific decision process to handle the regulation of competence exchanges. The following sections of the state of the art emphasize quantitative approaches that can be the starting point for a DSS. In the field of business networks, there are scant publications on this problem and what exists does not cover all the requirements. The motivation of the paper is to attempt to fill this void (section 2.3) Competence as a criteria for partner selection in short term networks As previously mentioned, the life-cycle of organization networks offers various contexts and opportunities for competence management. Virtual Breeding Environments (VBEs) are long term collaborative environments, which can be constituted so as to facilitate the creation of short term Virtual Organizations (VO.). Having distinct life spans and diverse objectives, VBEs and VOs do not offer the

5 Collaborative DSS ton enhance competencies 323 same type of competence management opportunities. In section 2.1 we treat competence-oriented decision aids for short-term VOs., before looking at longer term networks (section 2.2). Several scientific papers in the field of VO. try to demonstrate and structure the needs for competence-based Decision Support Systems (DSS) at various stages of virtual organizations management: (1) the creation of the VO. itself, (2) the allocation of adequate project partners to sub-tasks, (3) the redistribution of project earnings or (4) the harmonisation of distributed production processes. Some of these publications only have focused on a specific issue. For instance, (Manthou et al, 2004) emphasise the collaborative decision process leading to agreements between partners to solve the problem of combining their different proficiencies sets. The authors provide a framework based on a role classification and the identification of core company-competencies, in order to structure collaborative relationships. Other work intends to develop a broader vision. Pedersen and Van den Berg (2001) put forth the general need of competence modelling as a basis for various decision aids. And the French project (Grecopme, 2003) goes one step further, by structuring the various needs of decision-making tools to support the coordination and development of competencies within SME networks. The different decision aid requirements are positioned with regards to the life-cycle model of SME s networks. Depending on its position in this life-cycle, any SME network can select a pertinent decision-aid. Among the various challenges faced by virtual organizations, the selection of partners and the configuration of efficient business processes appear to be the driving force for performance improvement (Camarinha-Matos and Afsarmanesh, 1999), (Ermilova and Afsarmanesh, 2007). Indeed, poor partner selection is often a major failure factor. Usually, this results from a gap between the competence required and the actual qualifications among the partners. Multi-Agents Systems (MAS) are often used to build decision support systems for partner selection and they appear very suitable to define competence models. In (Lee and Lau, 1999) the core competencies which characterize companies are used as decision-making criteria to assign tasks to actors. In the multi-agent model, a group of Intelligent Agents using a genetic algorithm scheme identifies firms suitable to handle specific missions, depending on their competence descriptions. In (Neubert et al., 2004), the authors define the partners of a non-hierarchical production network as competence-cells. Their work implements automated negotiation between partners in order to build a productive network able to respond efficiently to customer requests. In relation with the Globemen project and the Virtual Enterprise Reference Architecture and Methodology (VERAM), Petersen (2003) also develops a multiagent architecture to cope with the virtual enterprise formation process (evaluation and selection of partners). In this case, agents are used both to provide models of the potential partners as well as the negotiation processes between partners. A multicriteria utility function is calculated to furnish a ranking of the partners considering some prerequisites. The approach shows a clear added-value for decision-makers, especially when there is a high number of potential combinations.

6 324 Journal of Decision Systems. Volume 18 No. 2/2009 Other types of formalisms have been applied for competence oriented DSS, notably analytical methods. Hammami et al. (2003) suggest a method to allocate customer orders within a network of firms, based on four mains concepts: actor, activity, resource and competence. A Multi-Objective Programming operations research method is used to formulate a mathematical model of the decision problem, with three final criteria observed: Cost, Quality and Delivery time. Using performance and competence criteria, the method generates evaluated patterns for enterprise networks, which match the requirements of an order. Ant Colony Optimisation, used in association with an Analytic Hierarchy Process approach has also been used to solve similar problems (Fisher et al., 2004). Complementary methods can be found in Szegheo and Petersen (2000). They present a computeraided approach for the selection of partners based on competence descriptions, or in Zaidat et al. (2005) who characterize a supply chain by organizational roles, described by the proficiencies or macro-competencies, required to fulfil a specific mission Competence management for stable long-term networks The DSS identified in the previous section deal with short term collaborations, corresponding to the configuration of on-demand networks or supply-chains. However, competence oriented decision systems are also very pertinent in long-term stable networks, often described as Virtual Breeding Environments (VBEs). VBEs provide a long term collaboration background to help in the reactive set up of shorter term on-demand virtual organizations. The stability of such collaborative environments makes them efficient to deploy competence management plans. As such, there is a potential need for decision support systems. Within the scientific literature on competence management for networks, we have distinguished between static approaches which focus on a current state of enterprise competencies, from dynamic approaches which consider the on-going competence evolution or development. Under a mainly static view on competences, several articles show that the management of competencies is a key issue for Virtual Breeding Environments, (Demsar et al., 2007), (Ermilova and Afsarmanesh, 2007), (Hajlaoui et al., 2009). (Ermilova and Afsarmanesh, 2007) provide a good example of a declarative approach of competencies. Their approach gathers primary descriptive information from the members of a VBE for profiling, with competencies as a main element of their profiles. They have provided advances in how to structure the information system required for competence management by using competence ontology. In addition, the authors approach also defines the prerequisites for a Profile and Competence Management System in such enterprise clusters (VBE). However, the notion of decision support remains limited in this Management System. The authors principally implement database based treatments to: identify competence profiles corresponding to given requirements; classify profiles according to several criteria;

7 Collaborative DSS ton enhance competencies 325 identify required company competencies among the VBE members, etc. So, in this management system, there is no particular need to apply decision theory. At the frontier between static and dynamic perspectives on competencies, (Burlat et al., 2003) suggest an interesting model of life-cycle applied to company networks. They take into account the further development of a collective competence as one of the maturity levels of a network on the way to cooperative innovation. Expanding this life cycle, (Burlat and Benali, 2007) proposes a DSS to help identifying coherent opportunities of virtual organization creation emerging from a larger set of potential partners from VBE. Their DSS uses a specific algorithm to generate clusters of partners based on two criteria: similarity of competencies and complementariness of activities. The approach is based on a competence model to provide a declarative (and static) view on available firm proficiency sets. The added value of their work is to identify potential collaborations among firms, consistent with a twofold analysis of competencies and activities. However, it seems that little work really studies the evolution of competencies in long term networks. (Lackenby and Seddighi, 2002) develop a managerial model for the competence developments in the creation of collaborative clusters. Again the approach is based on the concept of core competencies and identifies their progress as the primary strategic objective for a company when integrating into a virtual organization. The advantage of their model is that they have defined five steps in competence development for such clusters. Unfortunately, this approach remains at the managerial level and without formalizing competence dynamics, nor providing any decision support system Positioning and objectives The rest of this paper will focus specifically on the context of long term networks like VBEs. The objective is to contribute to the development of DSS supporting collaborative decision-making for competence management. The analysis of the scientific literature in this field, leads us to some preliminary remarks: - Several publications in enterprise collaboration strategies furnish explicative models which formalize various aspects of collaborative competence dynamics (Orsenigo, 2001), (Zhang et al., 2003), (Soderlund, 2008). These models are very useful to improve collaboration management, however they do not seem to be specifically concerned with the development of operational DSS, perhaps because of the strategic thus overall level of decision considered. - In the field of VBEs, some research suggests to model company competence profiles and formalize decision-aids for competence management. Nevertheless, most of these approaches use a static view on competences and to the best of our knowledge, none formalizes competence dynamics.

8 326 Journal of Decision Systems. Volume 18 No. 2/ Outside of the scope of enterprise networking, one can also mention supplemental papers that have dealt with DSS taking into account competence dynamics. For example, (Hammami et al., 2003) consider a competence learning criteria to select new enterprise business opportunities. (Osterlund, 1997) formalizes competence transfers within R & D structures. And finally, (Pepiot et al., 2005) propose a fuzzy logic approach for the valorisation of competence development. The contribution of this paper consists in developing a DSS focusing on the changes over time for collective competences in stable long-term networks. The evolution of company competencies is formalized by competence development scenarios. In this context, there is a clear need to regulate the collaborative development of competencies for the various partners of a network, by taking into account the equity among them. This equity entails in balancing investment required with the added-value gained by each partner. Our contribution, as detailed in section 4, proposes a way to formalize this collaborative decision-making process: - ability to represent competence development scenarios, based on different types of collaborative actions (e.g. cooperation by transfer of competence or mutualisation by common investment); - definition of decision criteria, to objectively measure the increase of competence for each partner, but also to evaluate their equity in the collaborative competence development process. Section 3 presents below the basic elements of this approach, first with the model used to represent company competence sets and to evaluate company competence needs notion of competence sets, second with the transition from these competence needs to the identification of correlative competence development actions. Then, section 4 will present the full collaborative decision procedure to manage inter-enterprise competence development scenarios, while fulfilling equity requirements. 3. Formalization of competence sets and competence needs This section explains how the characterization of competencies, at the enterprise level, is used as a basis to analyze quantitatively potential competence-based cooperation. The proposed model will provide an evaluation of the needs for competence development in each firm of the network. This will constitute the starting point of the DSS or diagnostic tool developed later on. Boucher and Burlat (2003) developed a qualitative model of company competencies called the s-a-r-c model. This model presents a framework on competencies found in a firm, to be used as a managerial aid and decision-making support. s-a-r-c uses a systemic approach on competence: assigning aggregated proficiencies to the firms, without restricting the idea of competence to simply the skills of individual employees.

9 Collaborative DSS ton enhance competencies 327 In this approach, the competence of a firm depends on three main facets: work methods deployed in the firm (concept of professional situations), individual or collective skills of employees (concept of actors) and technological context (concept of material resources). Thus, with s-a-r-c, business competencies are formalized as the interaction between these 3 basic competence-components: professional situations, actors, and material resources. As a consequence, identification and evaluation of company proficiency sets is based on the identification and characterization of these 3 basic components. Working with company networks, one has to consider the skill sets of each partner or enterprise in the network. Likewise, a proper map of competencies needs to be generated for each firm Competence model and competence sets Each firm of the network is to be described by a set of competencies. From that standpoint, there is a need to systematically identify and characterize such competence sets. A qualitative competence reference grid is used for their identification with a quantitative method to assess competence levels. Competence dictionaries are useful to coherently describe competencies. With them comparative analysis is possible, as required to develop the DSS. In France, a national reference grid ROME (Répertoire Opérationnel des Métiers et de l Emploi) has the advantage of being a national standard and is based on aggregated descriptions of competencies. Some further customized reference grids can also be developed for better adaptation to specific company activity fields. The current research uses competence reference grids previously developed in (Grecopme, 2003). In an industrial context these reference grids can be used to create a competence based audit. Concerning the quantitative approach, the company proficiency sets identified are formalized using the Fuzzy Subset Theory (Zadeh, 1965). Consider that a firm E can be described by an h-rank finite set of competencies C(E) = {C 1, C 2, C h }. Let C i be an element of C(E). Note X the fuzzy subset defined by X = {C 1 X (C 1 ), C 2 X (C 2 ),, C h X (C h )} where X (C i ) is the characteristic membership function of C i in X, X (C i ) takes its values in [0,1]. The characteristic function will be used to assess the competence levels for each company. This Fuzzy Subset Theory formalism as been first used in (Boucher and Burlat, 2003), with application to individual companies.

10 328 Journal of Decision Systems. Volume 18 No. 2/ Competence qualification First, some sort of evaluation for the competence levels is needed. Then, this appraisal will be used for further quantitative analysis of potential cooperation among firms. Competencies can be assessed by different measures of competence levels. Referring to s-a-r-c model, the evaluation of the three competencecomponents {situations-actors-resources} provides a preliminary qualification of competencies or theoretical level of competence. To calculate this level, first, indicators for each competence-component must be taken into account, as explained: S = {S1, S2, Sp} is a finite p-rank subset of situations, characterized with the indicator enterprise expertise level for the professional situation. This indicator can be assessed referring to several basic factors like the degree of rationalization of the professional situation and the occurrence of such situations. A = {A1, A2, Aq} is a finite q-rank subset of actors, characterized by the indicator actor suitableness to the situation, denoting the availability of the actors and cognitive abilities required. Q = {Q1, Q2, Qr} a finite r-rank subset of resources, characterized by the indicator service level, concerning the availability of the technical resources and technological capabilities required for the situation. In industry, information on the basic factors used to assess the three indicators can be gathered through company audits. The indicators provide control parameters for competence development. Depending on the situation, company management can choose to improve one or several of the indicators: expertise level, actor suitableness or service level by taking measures on either situations, actors or resources. This will generate several possible scenarios dealing with of the presence and evolution of the core competencies needed by each company. The 3 indicators also have to be further aggregated so as to assess the so-called theoretical level of competence for each element of a competence set. (Boucher and Burlat, 2003) discussed various ways to aggregate those indicators, referring to the Fuzzy Subset Theory employed. Table 1 presents the notations used for the three indicators as well as the way the theoretical competence level N( is calculated in our current work Targets on competence development Consider that each firm of a collaborative network has its own policy for competence development. This strategy directly depends on the company s top management. In this case, managers are asked to comply with this course of action by designating a set of targets for levels of competence to reach.

11 Collaborative DSS ton enhance competencies 329 The target level for the competence Ci within the company E supplies the value of the characteristic membership function O( (see Table 1). For an entire network, various sets of targets are formalized, each set representing a competence development strategy for one of the partners. Table 1. Basic mathematical characteristics Data Explanation Q( Resource service level in a competence C i for a firm E. A( Actors suitableness level in a competence C i by a firm E. S( Expertise level of the actors in a competence C i by a firm E. N( Theoretical level of competence : = Min( (, (, ( Ci )) N( E) ( S( E) A( E) Q( E) O( Target on competence level by a firm E of the network, on a competence C i With these notations, it is easier to explain the function or goals of the DSS. As illustrated by figure 1, the approach can be split into 3 main phases. Competence mapping gathers all the information required, by creating individual competence maps for each company. These diagrams contain the set of competencies, characterized by the current and targeted levels. A second step (see section 3.4) consists in evaluating the competence development needs in each networked company. Then, a decision support tool is suggested to help negotiate a collaborative plan of action for the improvement of inter-firm proficiencies. The formalization of this decision process will be presented in section 4. E 1 Competence mapping: Identification of competence sets {C 1 X (C 1 ), C 2 X (C 2 ),, C h X (C h )} Assessment of current levels N ( E )( C i ) Assessment of target levels O ( E )( C i ) E 2 E n Assessment of competence needs for each company ( ρ 1 ) Negociation of collaborative plans of action for competence development (Multicriteria Decision Approach) Figure 1. Decision Support Approach

12 330 Journal of Decision Systems. Volume 18 No. 2/ Competence development needs and actions Within the network, each enterprise E is typified by a set of competencies C(E) ={C 1, C 2, C n }, with i taking values from 1 to n. Using a comparison between the target and the theoretical levels of competence one can calculate a pertinence indicator ρ 1, which measures the overall gap between available proficiency and competence strategy for each enterprise. This pertinence indicator can be estimated by the distance between the current competence levels in a company and the corresponding target levels. n 1 = 1 1 N E Ci ( )( ) O( E) ( n i= 1 ρ ρ 1 evaluates the competence development needs within a company. Then, actions of competence development, i.e those aimed at reducing the gap between the current and targeted competence levels can be further deployed. As will be explained in the next section, each company can take advantage of the network to implement cooperative proficiency transfers. To define such action plans, it is necessary to state and formalize actions of competence development. These actions consist in boosting the level of competence within a company. Referring to s-a-r-c model, 3 types of elementary actions to ameliorate competence are considered. Each is applied to the corresponding component either situation, actors or resources. A given action of competence development w j has an impact on the level Q( or A( or S(. As a consequence, the theoretical competence level shifts from a N ( E )( to a new value ( N( ). The action of competence development creates an increment Δ( E i, w j) of the theoretical competence level for a enterprise E i, with ( N( ) N( ) due to the fact that the w j are selected to be actions for improvement. To apply this approach to company networks, the actions of competence development will be based on the collaboration among the partners of the network. Section 4.3 presents two main types of collaboration referring to inter-enterprise competence transfers or shared investment by several companies.

13 Collaborative DSS ton enhance competencies Competence development scenarios: decision criteria and procedure 4.1. Hypothesis and overall structure of the decision process As already stipulated the goal of the Decision Support System is to help in selecting plans to increase companies levels of competencies within long term collaborative networks. This is done in order to reduce the gap between the current and targeted levels of competence for the various partners of the network. Long term networks make it not only possible but mandatory to develop proficiency exchanges among partners. The development of competencies is of major importance for alliance stakeholders. Nevertheless, a restrictive hypothesis was made: the current approach would only deal with the development of the competencies of each of the firms individually. This means that the question of the overall collective competence which could emerge by complementarities among the partners is not addressed here. The actions to increase competence, we have considered, are only based on similarities among the individual needs of each company. In this context of collaboration between among firms, a key issue is the equity or fair play between partners concerning the activities of the network. Typically in our case, the decisional process can support the equitable identification of collaborative actions of competence development. Thus, equity is about gains and losses which can emerge from inter-organizational proficiency development processes. These can be represented by particular decision criteria as explained below. Figure 2 synthesizes the decision process, to select competencies development actions that reduce the gap between the targeted and available levels of competence in the various companies of a network. Having assessed the competence development requirements for each company, an exhaustive set of potential cooperative actions must be identified for competence improvements (transfers of competencies among enterprises, mutual investment, etc.). From this comprehensive set of measures, several possible collaborative action plans or scenarios are extracted. These scenarios must respect technical constraints like monetary budgets. Then, 5 decision criteria are used (see section 4.2) to help in choosing the best scenario cooperatively. The selection of a scenario within a network will obey the following two principles: - Maximize the increase of competencies for each enterprise (with regards to their targeted goal) by actions. - Equitable distribution of the enhancement of proficiencies for each partner. Indeed, as stipulated before, even if the cooperation provides an interesting value-added to inter-organizational learning processes, one can not forget the necessity of equity among the collaborating enterprises to share both gains and losses.

14 332 Journal of Decision Systems. Volume 18 No. 2/2009 Competence development needs needs (Distance (Distance betwen betwen current current and and targeted targeted levels levels on on enterprise enterprise competencies) competencies) Exhaustive sets sets of of potential actions actions Contextual constraints in the company networks Alternative scenarios of of competence development Decision criteria Classification of of the the scenarios Figure 2. Decision Support Procedure 4.2. Decision criteria To adhere to these two principles of scenario selection, a classification of all potential scenarios for collaborative development of competencies can be processed systematically using several criteria including equity measures. Five decision criteria are defined to compare the alternative scenarios. Each scenario (i) is constituted by a set of competence development actions w j, (ii) can affect one or several competencies, and (iii) has an impact on one or several companies. Synthesis indicators are suggested to weigh scenarios along with aggregations concerning the various companies as well as the diverse actions considered. Furthermore, equity on value creation and equity on cost are distinguished because, economically, both constitute two distinct variables Value induced by plans of actions For each action, it is necessary to evaluate the local improvement on the competence components. As discussed in section 3.4, a given action will change the theoretical competence level from N( to a new value N '(. Thus, a set of actions W(R) selected by a Small Firm Network generates a global or overall increment of the theoretical competence level written: n Δ ( E, W( R) ) = ( N ' ( E) ( C i) N ( E) ( Ci ) ) i= 1 This increment Δ( E, W( R) ) measures the increase of competence due to the scenario W(R) for a specific enterprise E. Considering k firms within a network, the indicator I 1 measures the overall competence increase induced by W(R) on all the firms:

15 Collaborative DSS ton enhance competencies 333 (W(R)) = k [1] I Δ (E j, W(R) ) 1 j = Equity on competence increase The fair play for competence increase is the equity between the value transmitted to other partners and acquired from the network by each member company. The homogeneity among all partners is measured by the ratios between the donated and acquired values (one ratio for each partner). As a hypothesis, consider that a transfer of value is an organizational learning action, where a firm E induces a competence increase for its partners in the network, without any competence increase for E. We call acquisition of value the opposite mechanism. Equity should be that an overall increase in competence would be shared fairly among all the cooperating companies. For every action w j and for every enterprise E i, the variable v(e i, w j ) is used to indicate if the action w j is a transfer of value (in that case v(e i, w j )=1) or an acquisition of value (in that case v(e i, w j )=0) for Ei. Considering m actions and k enterprises, the ratio R between the donated and the acquired values for the firm E i is given by: m m R( Ei) = (v(e i, wj) Δ( Ei, w j)) / j= 1 j= 1 ((1-v(E i, wj)) Δ( Ei, w j) ) [2] For a partner when that ratio tends to 1, there is a good balance between the competence provided to the other collaborating enterprises and the proficiency gained from them. Furthermore, an overall indicator is needed, to compare the possible scenarios by taking into account the effect on all the stakeholders. Within the network, the equity indicator I 2 gives an estimation of the dispersion on the ratios R(E i ) by a classic variance measure: I 2 (W(R)) = k 1/( k 1) ( R( Ei ) M R i= 1 ) 2 with M R the mean of the ratios. [3] Overall costs induced by a scenario This function is the sum of the costs stemming from the execution of the actions of competencies development, supported by the k enterprises of the network. I3 costs(ei ) [4] = k i= 1

16 334 Journal of Decision Systems. Volume 18 No. 2/2009 The different costs are determined using grids of reference on costs 2, which provide the calculation parameters necessary for each action Equity on costs The equity of costs incurred from the competence development actions is dealt with here. This measure of fairness is cost dispersion among partners, with regards to the average cost for all of them. This indicator of equity I4 is calculated from the standard deviation of each partner E i costs to the mean: k 2 I4= 1 / k (cos ts (Ei ) Mc ) with Mc = I3/ k [5] 1= Scenario feasibility Each action to ameliorate proficiency can be characterized by its feasibility. Practically, the basic achievability characteristics for each action are evaluated using grids of reference previously determined from competence development experts 1. Then the overall feasibility of a scenario is evaluated by a feasibility mean based on all the actions included in the scenario. I 5 = k j = 1 feasibilit y( wj) k [6] 4.3. Decision support procedure The initial data required for a decision on scenarios is the assessment of competence development needs (see section 3, figure 1). The case study in section 5 will detail the approach used to formalize these needs. However, the current section only focuses on the decision procedure synthesized in figure 2, with the following steps. First step: identification and formalization of potential collaborative actions Every action of competence development w i is formalized by 5 attributes: w i (AT, {C i }, {λ j }, {ρ i }, f i ) - AT: action type (see below) - C i : set of competencies influenced by the action. - λ j : set of costs induced by the action w i for the network. 2 For the results presented in this paper, grids of reference were used, which were previously developed in (Lebureau, 2004) Master Thesis.

17 Collaborative DSS ton enhance competencies ρ i : impacts of w i on C i competence level (distinct for each C i ). - fi: estimation of the action s feasibility. To identify potential actions of competence development suitable for the needs of the companies, two main issues are considered: - First, the actions have a direct impact either on situations, actors or resources. Actions: on resources tend to improve the service levels of material resources, on actors increase employee knowledge or training and on situations improve the methods and techniques available within a firm. - Second, only inter-enterprise collaborative actions are considered here. The objective is to take advantage of the company network to foster multiple increases of competencies, and thus generate an overall benefit for the network. Two main collaboration modes of are considered: cooperative mode puts forth the opportunity of internal inter-firm competence transfers; mutual mode is not a transfer but a shared investment collectively supported by the network, to satisfy needs of assorted member companies. For an action w i, the first attribute AT Action Type specifies if this action concerns situations, actors or resources as well as the cooperation mode used. The value of the three characteristics of the action impact λ j, ρ i, fi, are assessed by referring to generic grids of references 1 concerning respectively costs, local impacts and feasibilities of the actions. From the initial data on the partner s needs and the generic types of action (AT), a full set of competencies development actions is generated. This set, written Ω, gathers a list of potential actions of competence development identified so as to answer the needs of these companies. Second step: generation of scenarios under constraints Actually, the implementation of collaborative actions is bound by budgetary and operational network constraints, that hinder the accomplishment of all the development actions included in Ω{{Ei},{wi}} in a single collaborative actions plan. Therefore, the third stage of the decisional process is the construction of consistent scenarios, which respect such constraints. These scenarios should select a sub-set of Ω. Note W(R) these alternative scenarios, each of which constitutes a possibility of collaborative actions plans for the development of competencies in the SMEs network considered. Third step: evaluation and classification of scenarios This stage classifies scenarios containing the most favourable actions to fulfil the competence development needs. Appropriate scenarios should tend to satisfy the various objectives of the network. To generate the classification, the AHP (Analytic Hierarchical Process) developed by T.L Saaty was employed. The decision-makers

18 336 Journal of Decision Systems. Volume 18 No. 2/2009 retain the possibility to assign different weights to the five indicators previously defined. This method presents the advantage to model the articulation between the individual objectives of each partner and the collective aims of the network. This gives a clear overview of decision-makers preferences, and can easily formulate various scenarios rankings or generate and rank scenarios, according to the weights given to the five indicators. 5. ARTIC case study The case study presented here stems from the collaboration with in a company network called ARTIC. The origins of this network lay in the necessity to collaborate among very small to slightly larger firms in order to ensure, in the long run, their position in a competitive market. ARTIC associates about twenty firms from similar sectors: the SMEs considered in that paper are all working in the design and sale of software. The formal study will focus on three of these companies. The actual information used is altered or masked for confidentiality. In order to facilitate and manage tighter cooperation within the network, ARTIC has launched a systematic identification of competencies maps of the firms and an evaluation of their competencies levels. The identification and evaluation of competencies in use required an internal audit procedure fully defined in collaboration with ARTIC (Boucher and Lebureau, 2005). The objective of the current paper is only to study the resulting decision support system of the approach. This explains why the data on competence levels and competence development needs is considered here as initial data available for the DSS. The reader interested in the way this data was obtained can refer to (Boucher and Lebureau, 2005), (Grecopme, 2003) Software implementation To put into practice the Decision Support System, a computer environment structured in three elements (enterprise modelling system, model database, and decision support module) has been developed (figure 3). Hopefully, in what should be a user friendly manner, the enterprise modelling environment is utilized to gather and structure all information on the companies and the network which are required to build the proposed decision aid. This information is organized within so called enterprise models. For instance, these include competence maps, which gather all data resulting from the internal audit procedure, so as to evaluate the competence levels for each company, and make available a graphical representation of their competence sets. Of course, enterprise models are not limited to only these competence maps, since the manipulation of other contextual information on the companies and network is also needed.

19 Collaborative DSS ton enhance competencies 337 Information structuring Knowledge management Audit, then structuring of the data collected in enterprise models Enterprise modelling environment Decision aid For managers Multi-criteria Analaysis Descriptor Software Enterprise Models Database Sharing of managerial Information and decisions Publications of the results through intranet Figure 3. Software environment for the application The enterprise modelling environment is directly integrated with a centralized data base, which gathers all the data of the enterprise models, and can interact with other external software. These open flexible facilities are utilized initially to process the information available within the enterprise models in order to generate the scenarios of competence development: identify all potential and useful actions for competence development, and then produce reduced scenarios (step 1 then 2 of the procedure explained in 4.3). For the final step of the DSS, DESCRIPTOR software is used, which applies the method AHP as delineated in step 3. All alternative scenarios for competence development are evaluated with the five criteria defined in section 4.2, so as to create an overall classification. The criteria weights can be adapted to represent individual managerial preferences. Thus, in this way, our diagnostic tool furnishes a useful support for collaborative decisions on shared actions for competence development Decision Support System applied The internal competence audit of the 3 companies supplied the initial data synthesized in Table 2. For each competence and every company, Table 2 sets out: - Target competence level, given by the fuzzy values O( and the fuzzy subset O. (E ) i - Current competence level, described by the fuzzy values N( and the fuzzy subset N (E ). As explained in section 3 (and Table 1) aggregation of values obtained i

20 338 Journal of Decision Systems. Volume 18 No. 2/2009 for indicators on situations, actors, and resources: = Min( (, (, ( ). N( E) ( S( E) A( E) Q( E) - Gap e 1 between the target and the current competence levels, calculated by a fuzzy operator of difference between 2 fuzzy subsets : e 1= (O E N ( ) ( E )). i i Table 2. Initial data of the study case ARTIC Competencies C1 C2 C3 Conceive business software Achieve programming Master software adaptability and evolution Enterprise 1 Enterprise 2 Enterprise 3 i) N( Ci O( E ) e 1 )( Ci N( O( E ) e1 )( Ci N ( E ) ( Ci e 1 O( C ) 1 0,5 0,5 0,75 0 0,75 0,5 0,35 0,15 0,5 0,5 0 0,5 0, ,72 0,28 1 0,63 0,37 0,5 0 0,5 0,75 0,4 0,35 C4 Control quality 0,75 0,5 0,25 0,75 0 0,75 0,5 0,38 0,12 C5 C6 C7 C8 C9 Bring under control qualitycosts-lead times Keep in line with quality standards Stage campaigns for quality continuous improvement Achieve marketing Manage customer relationship 1 0,5 0,5 0,75 0 0,75 0,5 0,5 0 0,25 0 0,25 0,5 0 0,5 0,5 0 0,5 0,5 0 0,5 0,5 0 0,5 0,5 0 0, ,25 0 0,25 0,5 0, ,75 0,38 0,37 0,75 0 0,75 C10 Manage sales 1 0,25 0,75 1 0,64 0,36 0,75 0 0,75

21 Collaborative DSS ton enhance competencies 339 Table 3. Potential actions 3 of competencies development for ARTIC case study Actions w 1c [A; C4; E3; E1/ E2] w 2c [A; C8; E3; E1/ E2] w 3c [S; C8; E2; E1] w 4c [A; C1; E1; E2/ E3] w 5c [A; C3; E3; E2] w 6c [S; C4; E1; E2/E3] w 7c [S; C9; E1; E2/E3] w 8c [A; C9/C10; E2; E1/E3] w 1m [S; C1; E1/E2/E3] w 2m [S; C4; E1/E2/E3] w 3m [R; C4; E1/E2/E3] w 4m [A; C9/C10; E1./E2/E3] Actions definition Inter-enterprise competencies transmission for individual actors Inter-enterprise competencies transmission for individual actors Inter-enterprise best practices diffusion Inter-enterprise competencies transmission for individual actors Inter-enterprise competencies transmission for individual actors Inter-enterprise best practices diffusion Inter-enterprise best practices diffusion Inter-enterprise competencies transmission for individual actors Common Investment on methods Common Investment on methods Common Investment on one resource hold by the network Mutual training for the individual actors The resulting set of actions gathers all the possibilities of cooperative competence development, i.e. the exhaustive set called Ω. From Ω, can be generated subsets W(R) which will constitute the tangible action plans to be evaluated. In this case study, a budget constraint was imposed. This limit reduced the selection to only 3 cooperative actions among the twelve identified as possible. Thus in this case, there are 220 possible scenarios consisting of 3 actions (C 3 12 combinations of actions) that have to be evaluated in order to establish which are more in tune with the cooperation objectives of the network 4. Of course, the budgetary constraint may be over-restrictive. Therefore, those cooperative actions that were selected may not respond completely to the all the needs of a company. In that event, a firm can supplement its action-plan with unilateral measures to improve in-house proficiencies. The last step of the decision process consists in classifying the alternative scenarios for competence development. For all the 220 scenarios, the five decision criteria are calculated thanks to the formula (1) to (5), and the analytic hierarchical 3 In Table 3, the notation w1c[a; C4; E3; E1/ E2] indicates that the action w1c has an impact on the actor (A) for the competence C4, with the firms E1 et E2 as beneficiary-firm and E3 as root-firm. 4 In case that a higher number of actions is considered, there would be a risk of combinatorial explosion. This might require the use of other types of approaches for the classification of scenarios. However any optimisation of the classification algorithm is beyond the scope of the paper.