Predictive Analytics as a Strategic Tool in Workforce Planning

Authors

  • Betty Damayantie Universitas Teknologi Yogyakarta Author
  • Sujoko Sujoko Universitas Teknologi Yogyakarta Author

DOI:

https://doi.org/10.62872/rr6ccb12

Keywords:

Analitik Prediktif, Perencanaan Tenaga Kerja, Sumber Daya Manusia Strategis

Abstract

Changes in the business environment, characterized by technological disruption, labor market dynamics, and increasing organizational complexity, demand a more adaptive and evidence-based approach to workforce planning. Conventional approaches that rely on historical data and managerial intuition are increasingly inadequate for anticipating long-term workforce needs. This study aims to examine the role of predictive analytics as a strategic tool in workforce planning and its implications for organizational performance and sustainability. The study employed a qualitative approach with a literature review method through a systematic review of relevant scientific publications in the fields of strategic human resource management and predictive analytics. The study results indicate that predictive analytics can transform workforce planning from a reactive to a proactive approach by improving the accuracy of workforce need projections and alignment with business strategy. The use of predictive analytics contributes to increased operational efficiency, workforce risk mitigation, and strengthening the strategic role of the human resources function. However, its implementation faces challenges such as data quality, algorithmic bias, limited analytical competency, and ethical and privacy issues. This study emphasizes the importance of a critical approach and responsible governance for predictive analytics to provide sustainable strategic value in workforce planning

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References

Bassi, L., Carpenter, R., & McMurrer, D. (2012). HR analytics handbook. McBassi & Company.

Becker, B. E., & Huselid, M. A. (1998). High performance work systems and firm performance: The mediating role of employee skills and motivation. Academy of Management Journal, 41(1), 8–29.

Boudreau, J. W., & Ramstad, P. M. (2007). Beyond HR: The new science of human capital. Harvard Business School Press.

Brynjolfsson, E., Hitt, L. M., & Kim, H. H. (2011). Strength in numbers: How does data-driven decision making affect firm performance?. Management Science, 57(2), 321–339.

Davenport, T. H., Harris, J. G., & Shapiro, J. (2010). Competing on talent analytics. Harvard Business Review, 88(10), 52–58.

Davenport, T. H., & Harris, J. G. (2017). Competing on analytics: The new science of winning (Updated ed.). Harvard Business Review Press.

Fitz-enz, J., & Mattox, J. R. (2014). Predictive analytics for human resources. Wiley.

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.

Minbaeva, D. (2018). Building credible human capital analytics for organizational competitive advantage. Human Resource Management, 57(3), 701–713.

Ployhart, R. E., Nyberg, A. J., Reilly, G., & Maltarich, M. A. (2014). Human capital is dead; long live human capital resources!. Journal of Management, 40(2), 371–398.

Rasmussen, T., & Ulrich, D. (2015). Learning from practice: How HR analytics avoids being a management fad. Organizational Dynamics, 44(3), 236–242.

Stone, D. L., Deadrick, D. L., Lukaszewski, K. M., & Johnson, R. (2015). The influence of technology on the future of human resource management. Human Resource Management Review, 25(2), 216–231.

Van den Heuvel, S., & Bondarouk, T. (2017). The rise of HR analytics: A new approach to HRM?. The International Journal of Human Resource Management, 28(3), 381–404.

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Published

2026-02-07

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Section

Articles

How to Cite

Predictive Analytics as a Strategic Tool in Workforce Planning. (2026). Maneggio, 3(1), 28-35. https://doi.org/10.62872/rr6ccb12

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