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All Journal Ambidextrous : Journal of Innovation, Efficiency and Technology in Organization
Han Wuen, Chin
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Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Economics, Econometrics & Finance Electrical & Electronics Engineering

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The Application of People Analytics to Enhance Decision-Making in Human Resource Management Han Wuen, Chin
Ambidextrous Journal of Innovation Efficiency and Technology in Organization Vol. 3 No. 01: Human-Centered Innovation and Digital Resilience: Rethinking People, Products, and Pe
Publisher : Takaza Innovatix Labs Ltd.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61536/ambidextrous.v2i02.179

Abstract

This study explores the implementation and impact of people analytics in enhancing decision-making processes within Human Resource Management (HRM). Leveraging a qualitative case study approach, the research examines how organizations adopt people analytics, identifies the challenges faced during implementation, and evaluates the resulting benefits. Key findings reveal that people analytics significantly improves efficiency, effectiveness, and accuracy in HR decision-making, leading to increased employee satisfaction and organizational performance. However, barriers such as technological limitations, data governance issues, and cultural resistance persist, highlighting the need for robust leadership, ethical frameworks, and continuous innovation. The study underscores the strategic value of people analytics in aligning HR practices with organizational objectives and fostering evidence-based management. By providing empirical insights, this research contributes to the growing body of knowledge on analytics in HRM and emphasizes its potential to transform workforce management. Future research should explore the integration of emerging technologies, such as artificial intelligence and machine learning, to enhance predictive capabilities and expand the applicability of people analytics across diverse organizational contexts.
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