APPLYING FUZZY LOGIC THEORY TO PERFORMANCE MANAGEMENT

Year 2017, , 153 - 162, 30.06.2017

Cemal Ardil

https://doi.org/10.17261/Pressacademia.2017.584

Abstract

Organizations usually apply classical methods of employee performance
evaluation. In this classical system, employee performance depends on work
results, and it is evaluated only as success or failure in job behaviors. The
non-classical performance evaluation methods such as fuzzy logic may mainly be
used to many forms of decision-making including artificial intelligence
systems. This research proposes a new employee performance evaluation method
based on fuzzy logic systems. The process of performance measurement for
evaluating the effectiveness, efficiency, and productivity of employees
encompasses data collection, data design, and data analysis stages and it
involves a level of uncertainty associated with performance measures. In
evaluating employee performance, it usually involves granting numerical values
or linguistic labels to employee performance in the organization. The scores
accorded by the appraisers are only approximations, which are
then, used to represent each employee’s achievement by reasoning incorporated
in the computational methods. In this paper, the fuzzy logic theory approach is
used to represent the uncertainty caused by performance measures during its
design, use and analysis stages. This research seeks to describe and execute
the fuzzy logic theory approach for decision making in the employee performance
appraisal process. Finally, reasoning based on fuzzy logic theory provides an
alternative way in dealing with imprecise data, which is often reflected in the
way humans think and make judgments in real life.

 

Keywords

Performance management, performance appraisal, performance tracking, evaluation parameters, performance measurement

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