Employee Productivity Assessment Using Fuzzy Inference System

Abstract

The success of an organization hinges upon the effective utilization of its human resources, which serves as a crucial developmental factor and competitive advantage, and sets the organization apart from others. Evaluating staff productivity involves considering various dimensions, notably structural, behavioral, and circumferential factors. These factors collectively form a three-pronged model that comprehensively encompasses the facets of an organization. However, assessing the productivity of employees poses challenges, due to the inherent complexity of the humanities domain. Fuzzy logic offers a sound approach to address this issue, employing its rationale and leveraging a fuzzy inference system (FIS) as a sophisticated toolbox for measuring productivity. Fuzzy inference systems enhance the flexibility, speed, and adaptability in soft computation. Likewise, their applications, integration, hybridization, and adaptation are also introduced. They also provide an alternative solution to deal with imprecise data. In this study, we endeavored to identify and measure the productivity of human resources within a case study, by developing an alternative framework known as an FIS. Our findings provided evidence to support the validity of the alternative approach. Thus, the utilized approach for assessing employee productivity may provide managers and businesses with a more realistic asset.