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In today's competitive world, attention to the improvement and development of employees has become increasingly important. One of the procedures that organizations can use to improve their employees is implementation of assessment and development centers. But it should be noted that the implementation of improvement programs for each participants in the assessment center is time-consuming and costly. Accordingly, the aim of this study is reducing costs of assessment center implementation by segmenting the participants in assessment center and providing improvement programs for each sector. Sampling method is targeted and based on criteria and the sample consists of 75 employees. In this research, self-organizing maps have been used for segmentation of employees and the data were analyzed by Viscovery Profiler software. According to the findings, four sectors identified in the assessment center and they have been named: Talented, improvable employee (with a focus on competence), improvable employee (with focus on character) and insusceptible experts. Results of this segmentation can be used in five areas, including training, promotion, solve organizational challenges, recruitment and retention policies and rewards. Based on the results, for the areas that identified in the assessment center, suggestions are offered.

Keywords: assessment center, segmentation of employee, artificial neural networks, Self-organizing maps

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