A Linguistic Fuzzy Approach for Employee Evaluation

Employee being knowledge asset for an organization, employee evaluation is carried out by the organizations for performance appraisal and rewards to be given to the employees. Employee evaluation represents a critically important decision that often involves subjective information. An impartial assessment of this subjective information is difficult. Thus employee evaluation is vague, uncertain and imprecise which may not result into fair decision. The paper proposes a linguistic fuzzy approach for employee evaluation that removes any psychological elements that may have a negative bearing on unbiased evaluation. Fuzzy logic provides a simple way to draw definite conclusions from vague, ambiguous or imprecise information. It resembles human decision making with its ability to work from approximate data and find precise solutions. The paper discusses parameters that effect the performance evaluation and gives design of employee evaluation interface. The evaluations are expressed using fuzzy scales. Weight matrices are designed for each evaluation parameter and final evaluation is computed as weighted average of fuzzy evaluations. Keywords— Evaluation Parameters, Employee Evaluation, Fuzzy Logic, Weight Matrix I. EMPLOYEE EVALUATION Employee evaluation is used to identify industrious employees and encourage meritocracy by promoting a system of compensation that is commensurate with performance [1]. Human resources with knowledge and competencies are the key assets in assisting firms and/or countries to sustain their competitive advantage. Globally competitive organizations will depend on the uniqueness of their human resources and the systems for managing human resources effectively to gain competitive advantages [2]. Generally employee evaluation includes measuring the things that make the most difference. The problem is that many of the things that make the most difference are not easily quantifiable. The sort of parameters that can be considered includes attendance and punctuality, initiative, dependability, attitude, communication, productivity, interpersonal relationships, organisational & time management, knowledge sharing, safety, etc [3]. Employee evaluation should be fair and unbiased, since employee compensation is based on the results of performance appraisal. II. WHY FUZZY LOGIC FOR EMPLOYEE EVALUATION? Employee evaluation represents a critically important decision that often involves subjective information. Models and heuristic techniques that focus on the use of different types of information are available; however, with few exceptions, the models are not robust enough to be applied in a practical, managerially useful manner. Fuzzy logic models provide a reasonable solution to this common decision situation [4]. It is common to use discreet scales with sharp real values in the evaluation process. The theory of fuzzy sets allows for the use of such linguistic fuzzy scales, where the various scale values are expressed linguistically and modeled by fuzzy numbers. The purpose of using the instruments of linguistic fuzzy modelling is, on the one hand, an exact mathematic data processing that excludes unwanted subjective influence, and, on the other hand, the natural expression of the expertly defined vague evaluations using natural language [5]. III. EXISTING FUZZY LOGIC SOLUTIONS FOR EMPLOYEE EVALUATION C.C. Yee and Y.Y. Chen proposed a performance appraisal system using multi-factorial evaluation model in dealing with appraisal grades which are often expressed vaguely in linguistic terms [6]. The project was carried out in collaboration with one of the Information and Communication Technology Company in Malaysia with reference to its performance appraisal process. Ming-Shin Kuo and Gin-Shuh Liang presented a performance evaluation method for tackling fuzzy multi-criteria decision-making (MCDM) problems based on combining VIKOR and interval-valued fuzzy sets [7]. To illustrate the effectiveness of the method, a case study for evaluating the performances of three major intercity bus companies from an intercity public transport system is conducted. G Meenakshi proposed a Multi source feedback or 360-degree feedback based performance appraisal system using Fuzzy logic and implemented it in academics especially engineering colleges [8]. The 360 degree appraisal system includes self-appraisal, superior’s appraisal, subordinate’s appraisal student’s appraisal and peer’s appraisal. Adam Golec and Esra Kahya presented a comprehensive hierarchical structure for selecting and evaluating a right employee [9]. The process of matching an employee with a certain job is performed through a competency-based fuzzy model. Nisha et al., International Journal of Advanced Research in Computer Science and Software Engineering 4(1), January 2014, pp. 975-980 © 2014, IJARCSSE All Rights Reserved Page | 976 IV. THE EVALUATION METHODOLOGY The evaluation methodology is based on multiple evaluation parameters. The evaluation parameters can be objective or subjective. After reviewing evaluation criteria of various multinational companies and performance appraisal reports of different organizations evaluation parameters shown in Table 1 have been considered: TABLE I: EMPLOYEE EVALUATION PARAMETERS Personality Communication skills Attendance Cooperative Punctuality Qualifications Initiative Work Experience Self control Job Knowledge Responsibility Leadership Quality of Interpersonal Relationships Innovativeness Quality of work Accomplishments Attitude Effectiveness Commitment Result-Oriented Each evaluation parameter is expressed using linguistic fuzzy scales. The evaluator gets an opportunity to consider evaluation parameters in form of intervals. In this case objectiveness can be associated with fuzzy scales of evaluation parameters by defining weights for each evaluation parameter [10]. Moreover, the evaluation methodology considers different organizational levels i.e. Strategic, Tactical and Operational. It is obvious that not all the parameters are equally important for the employees at different organizational levels hence weight matrix is defined for each evaluation parameter against the management level in the organization. Weight Matrix indicates the significance of particular parameter for an employee at a particular organizational level. A. Weight Matrices for evaluation parameters Personality Very Good Good Quite Good Not Good Management Level Strategic √ √ Tactical √ √