An integrated fuzzy multi-attribute decision-making model for employees' performance appraisal

Abstract

Evaluating and ranking the employees working in organisations are challenging tasks involving several factors. Each employee achieves certain skill levels in various factors and the resulting information can be overwhelming. This article demonstrates how an integrated tool like fuzzy multi-attribute decision making (FMADM), with fuzzy analytic hierarchy process (FAHP), fuzzy quality function deployment (FQFD), is applied as a fair evaluating and sorting tool to support the performance appraisal (PA) system. The fuzzy linguistic approach has the advantage of reducing distortion and losing of information. FMADM focuses on the best practices of employees for the purpose of improving overall performance. Unlike traditional PAs, FMADM searches for the highly skilled employees who will serve as peers. The FMADM process identifies employees who require improvements in certain factor(s), and the magnitude of improvements required. This study supports the ideas that rating formats need re-examination as an alternative to traditional rating methods. Earlier adopted methods have seldom identified and quantified the individual factors for improvement, whereas FMADM could overcome these shortfalls. Based on the results of FMADM, the improvement of employees' performance is possible by way of providing training, talent enhancement and further qualification wherever required.