Portraying an employee performance management system based on multi-criteria decision analysis and visual techniques

RIS ID

109458

Publication Details

Ishizaka, A. & Pereira, V. Edward. 2016, 'Portraying an employee performance management system based on multi-criteria decision analysis and visual techniques', International Journal of Manpower, vol. 37, no. 4, pp. 628-659.

Abstract

Purpose - Performance appraisal is one of the most critical and indispensable human resource practices for organisations. However, it generates dissatisfaction among employees as it is often viewed as complex and ineffective. The purpose of this paper is to present a new performance management system that integrates multi-criteria decision analysis (MCDA) methods - the analytic network process (ANP) and PROMETHEE - with the visual techniques of the GAIA plane and the stacked bar chart. MCDA methods allow a structured and consistent evaluation integrating qualitative and quantitative criteria. Design/methodology/approach - The authors developed a structured and transparent performance management system. It is based on the MCDA methods PROMETHEE and ANP. It also incorporates the visual techniques: GAIA and stacked bar chart. Feedback for trainings and developments can precisely be formulated. Findings - Visual techniques permit clear identification and quantification, for each employee, of the areas that need improvement through training and development, which contributes to the resource-based view of organisations. A real case study has been portrayed to show the added value of the MCDA methods and the visual techniques in employee performance management. Originality/value - The paper describes a new employee performance system adopted in an organisation. The multi-criteria analysis transparently combines qualitative and quantitative decision criteria into a holistic and transparent evaluation. The visual techniques permit us to gain a deep insight into the employees' skills profile and capture fine details where individuals perform or underperform.

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Link to publisher version (DOI)

http://dx.doi.org/10.1108/IJM-07-2014-0149