Journal of Knowledge Management Practice, Vol. 7, No. 4, December 2006

Capitalizing On Process Knowledge In Bidding Processes

Rachid Chalal,  Abdessamed Réda Ghomari, National Institute of Computer Science, Algiers


This paper focuses on the key elements of a bidding process including co-operative and strategic decision making. An approach is proposed that shows how to capitalize on the company’s strategic knowledge and how to organize the corporate memory. The proposed approach is aimed at information management in project-oriented organizations, and is based on the MUSIC model (Management and Use of Co-operative Information Systems). The approach is described through the structure of corporate knowledge management and organization of the corporate memory. 

Keywords: Bidding Process, Strategic Decisions, Corporate Memory, Knowledge Capitalization, Cooperative Knowledge

1.         Introduction

This paper focuses on improving the bidding process, which is one of twenty key processes as defined by Davenport (1993) and includes both co-operative and strategic decisions (Alquier & Tignol, 2001). A methodology for knowledge capitalization and corporate memory is proposed that aims to organize knowledge capture, storage and re-use in order to support strategic decisions in the bidding process, through communication and information technology. The approach presented is aimed at information management in project-oriented organizations, and is based on the MUSIC model (Management and Use of Co-operative Information Systems) (Alquier, 1993). MUSIC assumes use of a generic information system model called the Co-operative Information Systems Architecture.

We first describe the structure of a business memory and then introduce the knowledge capitalization process. We show that the corporate knowledge management process organizes knowledge for reuse, sharing and learning from experiences. The paper is organized as follows:

·        Section 2 introduces the bidding process as a key process in a project-oriented organization

·        Section 3 presents the enterprise knowledge management model

·        Section 4 presents the bidding process through the MUSIC model (Management and Use of Co-operative Information Systems)

·        Section 5 presents our approach.

2.         The Bidding Process Resulting From Project-Oriented Organization

2.1.      Innovation Through Project-Oriented Organization

In order to improve their efficiency, companies have been obliged to resort to the principles and methods of project management (Fig. 1). On one hand to be innovative and on the other hand to answer better and more quickly customer needs (Alquier & Tignol, 2001). Van de Ven (1986) defines innovation as the development and the realization of new ideas (product or new service) by individuals who, in time, engage with others in a given institutional context














Figure 1.  Work Organization Extent In The Company.

The new way of distributing the tasks between the actors focuses on the key processes of the company (Fig. 2). This allows identification of the necessary competences which the company implements as required for these processes. The key competence is maturity in the sense of CMM (Capability Maturity Model) (CMM, 1995). This capability can generate other knowledge and favors innovation and competitiveness.














Figure 2.  Process Innovation Starting From The Various Skills.

2.2.      Bidding Process Overview


















Figure 3.The Typical Bidding Process

The typical bidding process (Fig. 3) includes four activities (Friedman, 1996):

1.      On receiving an ITD (Invitation To Tender), a decision to bid or not to bid is taken after a rough analysis of the ITD which provides the formal requirements.  An estimate of the ability of the bidder to respond technically to this tender is a part of this decision making process.  A rough analysis of the likely competitors’ strategy is, in most cases, performed, as well as an analysis of the bidder’s own strategy.  This first activity ends by the decision to bid or not to bid.

2.      Before preparing the bid, a deep analysis of the buyer’s formal requirements is performed in order to design the technical offer to be proposed to the buyer.

3.      Then, the cost of the offer is estimated and a business case is put together which analyses the bid environment (Bidders and expected Competitors’ Strategy, advantages to win the bid, justification of the price asked.)

4.      Finally, the offer (both technical and financial) is submitted to the potential buyer.

The decision situation for the bidding process responds according to the company objectives explained above:

·        Answer to a bidding process only if there is a real possibility to get the contract: go/no-go step. The evaluation step "go/no-go" takes place as soon as the bidding process is done. It consists of quickly mobilizing the information that is necessary to evaluate the interest or the capability to get the contract,

·        Improve the chances to get the contract. For this purpose, one must be able to elaborate a technical offer that satisfies the client needs at an attractive cost, while minimizing the risks incurred on the product or the industrial processes.

In the field of industrial engineering, PDBMS (Product Data Base Management Systems) are in fact supposed to solve this problem. They provide the centralized storage of detailed product (and partly process) descriptions that support the entire product life cycle, and can even be shared with the customer. They are now normalized for certain types of product (for example Continuous Acquisition Life-Cycle Support (CALS) of the DoD, with the MIL-STD-1388-2B norm for weapon systems) (Chevalier, 1993). Storage and integration is an important problem for manufacturers, for example in Computer Integrated Manufacturing (CIM)

The experience of the manufacturers involved in the project contradicts the implicit belief  held by the industrial engineering community that PDBMS are useful. In fact they are far from sufficient, and the assemblage of know-how is not the addition of specific data bases, joined together in a global, centralized and standardized product database. Knowledge and consequently information is specific to skills, people, or functions in the company. It cannot be shared and does not need to be shared. Even objects that could be shared are not likely to communicate easily between specialized skills. Each specialist has a different point of view on the same object or on the project. For example, a piece of sluice gate is not the same object from the point of view of the production manager, of the designer, financial manager, logistics support manager or project manager. Nevertheless, a common technical language generally exists in a company. So this type of data can be modeled, but this “collective language” only represents a minimum. This is in fact the aim of the PDBMS. Specific information exists in far higher proportions, and it needs to remain diverse. There must be coherence with the collective data of the PDBMS and means for knowledge exchange are also necessary. Means are required for suitable assemblage of know-how. This is achieved by integration, co-operation - the way this assemblage has to be made is a research prospective in itself. From the author’s experience this is achieved by defining at least two levels of languages:

·        The first, clearly identified, is the level of the languages of specialist heterogeneous and diverse skills. These languages are considered diverse and heterogeneous, and must remain so, because they cannot or do not need to communicate in their specialized forms,

·        The second, which is called corporate language or know-how, is the means by which integration and co-operation is constructed.

3.         Enterprise Knowledge Management Model

To design intelligent decision support for the bidding process, it is necessary to examine how the current bidding process could be modified in order to take maximal advantage of the possibilities offered by the capture and use of business knowledge together with the use of existing information. Information Technology is the most powerful tool of change in project management when fully exploited as a process innovation enabler for process-oriented organizations (Davenport, 1993). Unfortunately management of information is largely neglected.

3.1.      Justification

The usual approaches using corporate memories are focused on the memorizing of detailed and explicit knowledge: technical facts, operational tasks and procedures of work or documents frequently treated in the company. There needs to be a focus on the problems of cohabitation and interaction between the information system and the system of knowledge. Only two methods focus on modeling the knowledge system in the organization by adopting a systemic sight of the organization. These are MKSM method (Method for Knowledge System Management) (Ermine et al, 1996) and the MUSIC method (Management and Use of Co-operative Information Systems) (Alquiero 1993). Method MKSM is usable in companies with a conventional organization according to Le Moigne (1977). MUSIC is the most readily adapted method for companies with co-operative or project-oriented organizations according to Davenport (1993).

3.2.      MUSIC Model Overview















Figure 4.  Conceptual Structure For The Knowledge Sharing In The Company.

The MUSIC model is aimed at designing global intelligent information systems, integrating all decision support systems, process automation, all types of communication requirements, and their interactions. The MUSIC model proposes an architecture called Co-operative Information System (Fig. 4) which is based on three concepts and related modeling:

(A)       Information profoundness which corresponds to differing degrees of interpretative value and use:

·        Knowledge, linked and leading to the modeling of decisions,

·        Linguistics, semantics, and work organization,

·        Data, and related software design.

(B)       The spatial organization of information, which takes into account knowledge heterogeneity and distribution and the related upper co-operative structure:

·        Centralization, or collective information system i.e. the normalized knowledge, the common language that structures the enterprise as a global unit,

·        Decentralization or departmental and individual systems corresponding to decentralization and project divisions.

·        Co-operation between decentralized and autonomous systems through co-operative systems

(C)       Time, which corresponds to knowledge construction in the organization and the modeling of the temporal evolution of the organization:

·        Knowledge capitalization,

·        Management of organization change,

·        Evolution of information system.

The Co-operative Information System includes four sub-systems, linked by an upper co-operative and inter-operative structure:

·        The Collective Information System or a whole organization collective semantics. The organization's efficiency requires coordination that spans an organization, implying consistency and standardized usage patterns. Collective Information System is the organization skeleton, and is necessary for its survival,

·        The Departmental Information System: Information and processes have specialized semantics, which is collective for a limited number of people (for example, a department),

·        The Individual Information System: Collective or individual information semantics and individual process semantics. Each decider defines the meaning and aggregation for interpretations, analysis of actions, simulations, etc.

·        The Global Information System structure (Fig. 5) is completed by a communication model, defined as the totality of the communications between collective, departmental, and individual Information Systems. It provides exchanges between specialized organizational units to achieve a global finality. It is called Co-operative Information System, defined by cognitive, linguistic and conceptual modeling. The Co-operative Information System is a conceptual structure, which organizes appropriate access to the information needed for strategic decisions from the Information System of the company. It operates in a distributed context, with departments considered as independent areas of excellence, outstanding in their own context and for their local decisions: machines, DSS, skills. The access is organized by co-operation with and between departments throughout transverse knowledge and semantics processes.























Figure 5.  Conceptual Structure For The Knowledge Sharing In The Company.

4.         Bidding Process Through MUSIC Model

The MUSIC model can be applied to differing situations: Decision Support Systems, co-operative work, knowledge capitalization and corporate memory. According to this model, the problem of co-operative work has been characterized in the following way (Fig. 6):



















Figure 6.  Conceptual Structure For The Bidding Structure.

A decision in the bidding process is a cooperative decision where several actors (logisticians, ecologists, and risks specialists) intervene for very precise contributions. In the bidding process, the cooperative decision support is in fact an ODSS (organizational decision support system) (Turban & Aronson, 2001), which is inserted into the information system called intelligent information system (Fig.6).


















Figure 7.  Intelligent IS Architecture For The Bidding Process.

Knowledge is capitalized through an observer at a global level (in a bidding process, sales managers and the bidder). This global level knowledge corresponds to the sales manager’s work mainly involves negotiation with the customer. This level of the Intelligent Information System includes the general requirements with a high level of granularity, the high level piece-parts of the product.

Sales managers can capture and store this specialized knowledge and expertise on products and processes in an aggregated form, which is the Cost Element Structure through the co-operative IS. This specialized knowledge of engineers in charge of quotations of products and processes is at a sub-level (lower level of granularity) and can be found in different Information Systems of the company.

For each proposal, bid managers:

·        Use this Intelligent Information System to describe for example the Cost Breakdown Structure of the product using recurring sub-products (knowledge re-use and updating),

·        Can enter, with the co-operation of the quotation engineers, the description of new components (innovation storage).

5.         Approach For Bidding Process Knowledge Capitalization

The knowledge capitalization approach proposed in this paper is described through the structure of corporate knowledge management and the organization of the corporate memory.

5.1.      Structure Of Cooperative Knowledge

Knowledge manipulated by the specialized organizational units, as a part of the bidding process, is structured around the PBS (Product Breakdown Structure) (Fig. 8). It includes:

·        The product functions: validate implicit and explicit customer requirements based on the functionalities defined in the biding process,

·        PBS and functional analysis: To pass from the functionalities to the components of the future product by engineering approaches. It aims at defining industrial processes and associated resources,

·        CBS (Cost Breakdown Structure): allocate cost estimation tasks to company jobs in order to negotiate an objective cost design. This generic structure has been developed as a part of the ESPRIT project (DECIDE project, ESPRIT °2298, ended in 1998) (Alquier & Soliveres, 1997),

·        LBS (Logistic Breakdown Structure): insert the support elements as well as the associated processes into the product (Chalal & Alquier, 2003),

·        EBS (Environmental Breakdown Structure): analyze the product and the associated industrial processes, from an environmental point of view, to capture the ecological preoccupations (Chalal & Nader, 2006),

·        RBS (Risk Breakdown Structure): manage the risks in relation with the industrial organization of the company in order to negotiate a risk objective design. This generic structure has been developed as a part of PRIMA (Project Risk Management) project, n° IST-1999-10193, ended in 2002 (Alquier & Tignol, 2001).

The corporate knowledge management process organizes:

·        Knowledge reuse and sharing: Bid managers get knowledge they couldn’t acquire in any other way (young employees for example),

·        Learning from experience: The Corporate memory for the bidding process concentrates returns from experience, both from bids themselves and from detailed design corporate memory when it exists.

























Figure 8. A Partial Sight Of Corporate Memory For The Bidding Process.

5.2.      Business Memory Organization

During the bidding process different kinds of information are required to design technical solutions. To support the different kinds of user, i.e. sales managers and engineers, the prototype developed allows one to create new technical solutions by re-using previous bids and the associated information concerning the products, the processes and the resources, or by adding new information that concerns the cost and risks or the technical feasibility.

The corporate memory management is organized into three kinds of items (the temporary items, the to-be examined items, the recurring items) (Fig. 9):


















Figure 9. Memory Organization For Bidding Process.

The temporary items are an extraction of the information system. The user creates completely new technical solutions and products at the moment of the bidding process. The temporary items form completely new technical solutions. From the temporary items, users have the possibility of creating items to be examined, anticipating that these items are those which could probably be reused for another bid. It is worthwhile organizing this anticipation since it occurs in a non-urgent context. From the temporary and to be examined items, recurring items are created. Recurring items are those, which are reused from previous bids and will certainly be reused for future bids. Recurring items could be reused just as they are or brought up to date.

6.         Conclusion

In this paper, the author has proposed an approach to capitalize on a company’s strategic knowledge in the key process of bidding. Intelligent information systems associated with the bidding process must:

·        Constitute a corporate memory for the bidding process,

·        Collect and organize information on the knowledge relating to risks,

·        Manage information to make easier the access to the knowledge about risks,

·        Interact with the corporate memory (Pomian, 1996) to constitute the business memory on risks.

In the bidding process, the result of corporate memory organization is in fact a part of an ODSS associated with this process. This approach needs to be continued by providing other key process memories, for example project management according to PMI (Duncan, 1996). 

7.         Acknowledgements

We are grateful for the computing resources provided by MSI team at LMCS Laboratory at INI Algiers. We thank members of CMEP (Comité Mixte d’Evaluation et de Prospective) Project N°00MDU485 (INI- University Toulouse 1) ended in 2002 especially Professor Anne-Marie Alquier form UT1, France.

8.         References 

Alquier A.M., 1993, MUSIC : Management et Utilisation des Systèmes d’Information Coopératifs, Habilitation à Diriger des Recherches, Université de Toulouse.

Alquier A.M, Tignol M.H., 2001, Project management technique to estimate and manage risk of innovative projects, IPMA International Symposium and NORDNET, Stockholm, Sweden.

Alquier A.M., Soliveres H., 1997, A particular aspect of DECIDE bid decision support system : modeling of life-cycle processes and costs, IEEE Conference on Systems, Man and Cybernetics, Orlando.

Chalal R., Nader F., 2006, Constitution d’une mémoire sur les risques dans les projets et son intégration dans le système d’information de l’entreprise industrielle, MOSIM’06, 6e Conférence Francophone de MOdélisation et SIMulation, Rabat, Maroc.

Chalal R., Alquier A.M., 2003, Une approche hybride pour la constitution d’un référentiel risques, CPI’2003, 3rd International Conference: Integrated Design and Production, Maroc, Mekhnès.

Chevalier P., 1993, CALS et les systèmes d’informations électroniques, Edition Hermès.

Cmm, 1995, System Engineering Capability Maturity Model, Software Engineering Institute.

Davenport T.H., 1993, Process innovation: Reengineering work through information technology, Harvard Business School.

Duncan W.R., 1996, A guide to the Project Management Body of Knowledge (PMBOK), PMI Standards Committee.

Ermine J. L., Chaillot M., Bigeon P., Charenton B., Malavieille D., 1996, MKSM : méthode pour la gestion des connaissances, ISI Vol. 4 No. 4, pp 541-575.

Friedman L., 1996, A Competitive Bidding Strategy, Operation Research, 4; 104-118.

Le Moigne, J.L., 1977, La théorie du système général, théorie de la modélisation, P.U.F., Paris.

Pomian J., 1996, Mémoire d’Entreprise, Techniques et Outils de la Gestion du Savoir, Ed. Sapienta.

Turban E., Aronson J.E., 2001, Decision Support Systems and Intelligent Systems, Prentice-Hall International Inc.

Van de Ven A. H., 1986, Central problems in the management of innovation, Management Science, Vol. 32, No.5; pp. 590- 607; INFORMS, Linthicum, Maryland, USA.

About the Authors:

Rachid Chalal is currently Lecturer – Researcher at LMCS (Systems Design Methodologies Laboratory) at INI (National Institute of Computer Science), Algiers, Algeria. His current research interest includes Risk Management, Information systems and decision support systems.

R. Chalal, LMCS Laboratory, INI, INI, BP 68M Oued Smar, 16270, Algiers, Algeria; Email:

Abdessamed Réda Ghomari is currently Lecturer – Researcher at LMCS (Systems Design Methodologies Laboratory) at INI (National Institute of Computer Science), Algiers, Algeria. His current research interest includes Project Management, Decision support systems.

A. R. Ghomari, LMCS Laboratory, INI, (National Institute of Computer Science), INI, BP 68M Oued Smar, 16270, Algiers, Algeria; Email: