A Hierarchical Inference System to Evaluate the Organizational Readiness for Talent Management Implementation

Document Type : Sterategic Management

Authors

1 Industrial Management Department, Faculty of Social Science , Imam Khomeini International University, Qazvin, Iran

2 Executive Management Department, Industrial Management Institute, Tehran, Iran

Abstract

Organizational readiness assessment to implement improvement projects with maximum acceptance within the organizations have always been a concern for managers. To this end, several methods have been developed for different types of projects such as knowledge management, integrated systems implementation, electronic learning systems and etc. In this paper a new model is developed to evaluate the organizational readiness for talent management system implementation. Firstly, influencing parameters on the organizational readiness are collected through literature review and experts knowledge acquisition. Then the parameters are categorized and a hierarchical structure of parameters is built. Constructed structure consists of four levels in which organizational readiness to implement talent management is placed in the first level. Organizational readiness degree is assessed based on values of four parameters positioned in second level. In the same way, the values of parameters in the second level are calculated using parameters in level three and finally parameters in level four are employed to evaluate third level parameters. Subject to the qualitative nature of the problem and lack of explicit functions to formulate the relations between the level of organizational readiness and the influencing parameters, the fuzzy rule base is employed. Fuzzy rules are made by using industrial and academic experts’ knowledge and the resulted system is implemented in a food distribution company as a case study. Readiness degree of this company is calculated as 0.463, which shows medium readiness of this organization for talent management.

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References

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  • Receive Date: 21 July 2017
  • Revise Date: 17 September 2017
  • Accept Date: 01 September 2017

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