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.

中文翻译：

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EFQM模糊多层评估方法


尽管欧洲质量管理基金会 (EFQM) 是最著名的卓越商业框架之一，但其固有的自我评估方法存在一些局限性。对自我评估模型的严格审查表明，大多数模型都是模糊的并且仅限于精确的数据。此外，专家知识对评分的影响过于主观，大多数方法都假设变量之间的关系是线性的。本文提出了一种新的模糊多层评估方法，该方法依靠模糊推理系统来适应不精确的数据和不同的评估者经验，以克服 EFQM 模型中的不确定性和复杂性。该方法已在某地区电力公司的实际情况下实施、测试和验证。该案例由公司内部专家和来自 EFQM 卓越业务组织的外部评估员进行评估，并使用 MATLAB 软件实施该模型。在将经典模型与新模型进行比较时，评估人员和专家更青睐新模型的输出。