Human Resource Analytics And Strategic Decision-Making In Human Resource Management: A Systematic Literature Review
DOI:
https://doi.org/10.65254/ijese.v2i5.69Keywords:
Human Resource Analytics, Strategic HRM, Decision-Making, Systematic Literature ReviewAbstract
Purpose:This study aims to systematically review the role of Human Resource Analytics (HRA) in supporting strategic decision-making in Human Resource Management.
Design/methodology/approach: A systematic literature review was conducted using peer-reviewed articles indexed in Scopus and SINTA, following PRISMA guidelines with defined inclusion and exclusion criteria.
Findings:The results show that Human Resource Analytics enhances strategic HR decision-making in areas such as workforce planning, performance management, talent acquisition, and employee retention. Key dimensions frequently discussed include data quality, analytical capability, technological infrastructure, and managerial support.
Research limitations/implications: This review is limited to selected databases and time periods. Future studies should apply longitudinal designs and examine mediating and moderating variables across different organizational contexts.
Practical implications:Managers and HR practitioners can use Human Resource Analytics to improve evidence-based strategic HR decisions by strengthening analytical skills and data governance.
Originality/value:This study provides an integrated overview of Human Resource Analytics and identifies key themes and directions for future research.
Paper type:Literature review
Downloads
References
Angrave, D., Charlwood, A., Kirkpatrick, I., Lawrence, M., & Stuart, M. (2016). HR and analytics: Why HR is set to fail the big data challenge. Human Resource Management Journal, 26(1), 1–11. https://doi.org/10.1111/1748-8583.12090
Appelbaum, E., Bailey, T., Berg, P., & Kalleberg, A. (2000). Manufacturing advantage: Why high-performance work systems pay off. Cornell University Press.
Bassi, L., & McMurrer, D. (2016). Four lessons learned in how to use analytics to improve the value of HR. People & Strategy, 39(3), 28–35.
Becker, B. E., & Huselid, M. A. (1998). High performance work systems and firm performance: A synthesis of research and managerial implications. Academy of Management Journal, 41(1), 8–29. https://doi.org/10.2307/256712.
Delery, J. E., & Doty, D. H. (1996). Modes of theorizing in strategic human resource management: Tests of universalistic, contingency, and configurational performance predictions. Academy of Management Journal, 39(4), 802–835. https://doi.org/10.2307/256713.
Fitz-enz, J., & Mattox, J. R. (2014). Predictive analytics for human resources. Wiley.
Guest, D. E. (1997). Human resource management and performance: A review and research agenda. The International Journal of Human Resource Management, 8(3), 263–276. https://doi.org/10.1080/095851997341630.
Guest, D. E. (2011). Human resource management and performance: Still searching for some answers. Human Resource Management Journal, 21(1), 3–13. https://doi.org/10.1111/j.1748-8583.2010.00164.x
Huselid, M. A. (1995). The impact of human resource management practices on turnover, productivity, and corporate financial performance. Academy of Management Journal, 38(3), 635–672. https://doi.org/10.2307/256741.
Jiang, K., Lepak, D. P., Hu, J., & Baer, J. C. (2012). How does human resource management influence organizational outcomes? A meta-analytic investigation of mediating mechanisms. Academy of Management Journal, 55(6), 1264–1294. https://doi.org/10.5465/amj.2011.0088
Manik, S. (2025). The role of big data analytics in strategic human resource planning: A framework for organizational decision-making. Journal of Digital Informatics, 1(1), 1–12.
Marler, J. H., & Boudreau, J. W. (2017). An evidence-based review of HR analytics. The International Journal of Human Resource Management, 28(1), 3–26. https://doi.org/10.1080/09585192.2016.1244699
Minbaeva, D. (2018). Building credible human capital analytics for organizational competitive advantage. Human Resource Management, 57(3), 701–713. https://doi.org/10.1002/hrm.21848
Pfeffer, J. (1998). The human equation: Building profits by putting people first. Harvard Business School Press.
Rasmussen, T., & Ulrich, D. (2015). Learning from practice: How HR analytics avoids being a management fad. Organizational Dynamics, 44(3), 236–242. https://doi.org/10.1016/j.orgdyn.2015.05.008
Ravesangar, K., & Narayanan, S. (2024). Adoption of HR analytics to enhance employee retention in the workplace: A review. Human Resources Management and Services, 6(3), 3481. https://doi.org/10.18282/hrms.v6i3.3481
Sakib, M. N., Chowdhury, S. R., Kabir, M. R., & Hossain, M. I. (2024). How HR analytics evolved over time: A bibliometric analysis on Scopus database. Future Business Journal, 10(1), 87. https://doi.org/10.1186/s43093-024-00375-9
Siagian, M. V. S. E. (2024). Digital transformation in HR: The impact of HR analytics on talent management and strategic decision making. YUME: Journal of Management, 7(2), 215–229.
Solihin, A. (2024). The role of HR analytics in strategic decision-making: A systematic literature review. Management Studies and Business Journal (Productivity), 1(7), 1038–1044. https://doi.org/10.62207/zhqjy759
Trisanti, A., Sitanggang, L. P., & Simbolon, O. J. (2023). The impact of implementing human resource analytics on human resource management decision making. Jasmien: Journal of Accounting, Management and Economics, 5(2), 1221. https://doi.org/10.54209/jasmien.v5i02.1221
Usman, F., Ndubuisi, N. L., Ibeh, C. V., & Daraojimba, E. R. (2024). Data-driven decision making in HR: A review of analytics and its strategic importance. Malaysian Journal of Human Resources Management, 1(2), 98–104. https://doi.org/10.26480/mjhrm.02.2024.98.104
Van den Heuvel, S., & Bondarouk, T. (2017). The rise of HR analytics. Journal of Organizational Effectiveness: People and Performance, 4(2), 157–178. https://doi.org/10.1108/JOEPP-02-2017-0018
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2025 Drajat Sunaryadi
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
