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HR Analytics and Financial Performance: A Quantitative Study of Capability, Integration, and Data-Driven Decision-Making

Author

Listed:
  • Muhammed Zakir Hossain

    (Associate Professor, Department of Business Studies, State University of Bangladesh, Bangladesh)

  • Umma Nusrat Urme

    (Assistant Professor, Southeast Business School, Southeast University, Bangladesh)

  • Md. Ashad Ull Haque Akash

    (Lecturer, Southeast Business School, Southeast University, Bangladesh)

Abstract

The increasing focus on evidence-based decision-making has put HR analytics as a strategic capability that can contribute to organizational performance. However, it is far from clear empirically how HR analytics impact financial performance. This research takes a quantitative approach to investigate the influence of 3 crucial organizational levers—HR Analytics Capability, HR–Finance Integration and Data-Driven HR Decision-Making—on Financial Performance Contribution. Leveraging human capital theory, resource-based view (RBV) and strategic fit literature, we articulate a theory-driven framework that is tested cross-sectionally using HR analytics indicators based on case data from organizations and survey measures. The empirical results indicate that all the three predictors pose statistically significant impact on FPC, whereas HR– Finance Integration has a highest effect, followed by HR analytics capability and data-based decision-making. The findings reveal that the economic value of HR analytics is associated not only with technical competences, but also with its alignment to financial skills and use in making evidence-based decisions. This research contributes to the literature on HR analytics by providing a theoretically-driven and empirically-tested view of how organizational analytical maturity influences financial performance.

Suggested Citation

  • Muhammed Zakir Hossain & Umma Nusrat Urme & Md. Ashad Ull Haque Akash, 2026. "HR Analytics and Financial Performance: A Quantitative Study of Capability, Integration, and Data-Driven Decision-Making," Post-Print hal-05707841, HAL.
    • Handle: RePEc:hal:journl:hal-05707841
    DOI: 10.59324/ejmeb.2026.3(2).06
    as

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