A Fuzzy Multilayer Assessment Method for EFQM

Although the European Foundation for Quality Management (EFQM) is one of the best-known business excellence frameworks, its inherent self-assessment approaches have several limitations. A critical review of self-assessment models reveals that most models are ambiguous and limited to precise data. In...

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Bibliographic Details
Published in:IEEE transactions on fuzzy systems 2019-06, Vol.27 (6), p.1252-1262
Main Authors: Daniel, Jay, Naderpour, Mohsen, Lin, Chin-Teng
Format: Article
Language:English
Subjects:
Business excellence model
Companies
Company structure
Europe
European Foundation for Quality Management (EFQM)
fuzzy inference systems (FISs)
Fuzzy logic
Fuzzy systems
Linguistics
Multilayers
Quality management
Regional analysis
Self evaluation
self-assessment
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Summary:Although the European Foundation for Quality Management (EFQM) is one of the best-known business excellence frameworks, its inherent self-assessment approaches have several limitations. A critical review of self-assessment models reveals that most models are ambiguous and limited to precise data. In addition, the impact of expert knowledge on scoring is overly subjective, and most methodologies assume the relationships between variables are linear. This paper presents a new fuzzy multilayer assessment method that relies on fuzzy inference systems to accommodate imprecise data and varying assessor experiences to overcome uncertainty and complexity in the EFQM model. The method was implemented, tested, and verified under real conditions at a regional electricity company. The case was assessed by internal company experts and external assessors from an EFQM business excellence organization and the model was implemented using MATLAB software. When comparing the classical model with the new model, assessors and experts favored outputs from the new model.
ISSN:1063-6706
1941-0034
DOI:10.1109/TFUZZ.2018.2874019