Social Security Journal

Social Security Journal

Identifying the factors Influencing the success of human resource analytics in the Social Security Organization and its Subsidiary Companies

Document Type : Original Article

Authors
1 1. Ph.D. Department of Industrial Management, Faculty of Management and Economics, Science and Research Branch, Islamic Azad University, Tehran, Iran
2 Master of Human Resource Development , Department of Management, Farabi Campus, University of Tehran, Qom, Iran.
3 Ph.D, Department of Industrial Management, Faculty of Economics, Management and Accounting, Yazd University, Yazd, Iran.
10.22034/qjo.2025.483965.1387
Abstract
Purpose: The use of digital technologies in human resource management through human resource analytics to improve employee performance has garnered significant attention. However, its implementation in organizations often fails due to the complexity of the process and the organization's lack of readiness to adopt it. Given the insufficient focus of researchers on this area and the gaps in the literature, this study aims to identify the success factors of human resource analytics in Iranian organizations and enrich the research literature.
Method: The current research is a qualitative that was conducted using the Delphi method.
Findings: After data analysis, 28 factors influencing the success of human resource analytics in the Social Security Organization and its affiliated companies were identified, categorized into five dimensions: "data management," "managerial factors," "technological factors," "organizational factors," and "personnel factors."
Conclusion: The results showed that the success of human resource analytics in an organization is not dependent on a single factor but requires a comprehensive view and a systematic approach. The organization needs to implement changes across various dimensions. The key to success in this process lies in the correct combination of interactive strategies and technological tools.
Keywords

  • Receive Date 29 March 2024
  • Revise Date 21 May 2024
  • Accept Date 09 July 2024