Overall performance measurement in a supply chain: towards a supplier-prime manufacturer based model
- 533 Downloads
This study deals with the supply chain (SC) overall performance expression. The developed idea concerns more particularly the performance of the manufactured products. Indeed, two companies or more contribute to the manufacturing of products that are generally assembled by the prime manufacturer company. Moreover, in the industrial practice, performance scorecards are defined with regard to each process; and the overall performance is neither expressed for each company, nor for the whole SC. We propose here to identify the SC overall performance to the combination of the performances of the different involved companies in the SC. Thus, in order to obtain a definition of such performance, we choose to focus first on the performance of the prime manufacturer. In this sense, the approach is based on the SCOR model for the handling of the main processes around the considered product manufacturing. The prime manufacturer performance is then defined as the aggregation of its involved processes’ performances. While the prime manufacturer performance is strongly dependent on the suppliers’ performance, we suggest the integration of the impacting supplier performance into the prime manufacturer scorecards. From an operational point of view, the MACBETH methodology is used to coherently express both processes and overall performances. More precisely, the Choquet aggregation integral operator is applied in order to model mutual interactions between processes. Finally, the expression of a bearing’s manufacturer performance illustrates the proposition.
KeywordsMulti-criteria performance evaluation Supply chain management SCOR model MACBETH aggregation methodology Choquet integral operator
Unable to display preview. Download preview PDF.
- Ayers, J. B. (2000). Handbook of supply chain management, 400 p APICS series on resource management. Alexandria, Virginia, USAGoogle Scholar
- Bana e Costa C., De Corte J. M., Vansnick J. C. (2004) On the mathematical foundations of MACBETH, 409–442. In: Figueira J., Greco S., Ehrgott M. (eds) MCDA multiple criteria decision analysis. Kluwer, Boston/Dordrecht/London, p 1040Google Scholar
- Clivillé, V., & Berrah, L., (2006). Overall performance measurement in a supply chain. In Proceedings of 12th IFAC symposium on information control problems in manufacturing (INCOM 2006). CD-ROM, Saint-Etienne, France, May 2006, 6 p.Google Scholar
- Hausman, W. & (2004) In H. T. P. Harrison, H. L. Lee, J.J. Neale (Eds.). The practice of supply chain management: Where theory and application converge. New York, NY: Springer Science & Business MediaGoogle Scholar
- ISO. (2001). Qualité et systèmes de management ISO 9000, AFNOR, 581 p.Google Scholar
- Kranz, D. H., Luce, R. D., Suppes, P., & Tversky, A. (1971). Foundations of measurement: Additive and polynomial representations. Academic Press, 1971, new edition by Dover edition, 2006 (624 p).Google Scholar
- Saaty, T. (2004). The analytic hierarchy and the analytic network processes for the measurement of intangible criteria and for decision making, 345–407. In J. Figueira, S., Greco, & M. Ehrgott (Eds.), MCDA: Multiple criteria decision analysis: State of the art surveys (p. 1040). Boston/Dordrecht/London: Kluwer.Google Scholar
- SCOR 80 (2007). SCOR 80 overview booklet, supply chain council editions. 2000 organisation avalaible on http://www.supply-chain.org/cs/root/home.