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Intelligent decision system for self‐assessment
Author(s) -
Xu DongLing,
Yang JianBo
Publication year - 2003
Publication title -
journal of multi‐criteria decision analysis
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.462
H-Index - 47
eISSN - 1099-1360
pISSN - 1057-9214
DOI - 10.1002/mcda.343
Subject(s) - excellence , strengths and weaknesses , computer science , decision support system , knowledge management , multiple criteria decision analysis , action (physics) , operational excellence , diversity (politics) , process management , operations research , engineering management , artificial intelligence , engineering , psychology , social psychology , physics , quantum mechanics , political science , law , sociology , anthropology
Many small and medium enterprises (SMEs) in the UK use the beta (Business Excellence Through Action) approach to the EFQM Excellence Model to conduct business excellence self‐assessment, which is in essence a multiple criteria decision analysis (MCDA) problem. This paper introduces a decision support software package called Intelligent Decision System (IDS) to implement the beta approach. It is demonstrated in the paper that the IDS‐beta package can provide not only average scores but also the following numerical results and graphical displays on: Distributed assessment results to demonstrate the diversity of company performances The performance range to cater for incomplete assessment information Comparisons between current performances and past performances, among different companies among different action plans.Strengths and weaknesses The IDS‐beta package also provides a structured knowledge base to help assessors to make judgements more objectively. The knowledge base contains guidelines provided by the developers of the beta approach, best practices gathered from research on award winning organizations, evidence collected from companies being assessed and comments provided by assessors to record the reasons why a specific criterion is assessed to a certain grade for a company. Four small UK companies, the industry partners of the research project, have carried out the preliminary self‐assessment using the package. The results and experience of the application are discussed at the end of the paper. Copyright © 2004 John Wiley & Sons, Ltd.