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These studies suggest that HR analytics in public service can enhance workforce planning, recruitment, HR development, performance management, employee engagement, organizational performance, talent management, and strategic contributions by reducing subjectivity bias and enabling predictive decision-making.
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Human Resources (HR) analytics, also known as people analytics, leverages data technology, including machine learning and artificial intelligence, to enhance HR-related decision-making. While its application in the private sector is well-documented, its integration into public service remains underexplored. This synthesis examines the current research on HR analytics within public service, focusing on its implementation, benefits, and challenges.
Implementation Process and Challenges:
Impact on Employee Engagement and Performance:
Performance Appraisal and Subjectivity Bias:
Talent Management and Predictive Decision-Making:
Strategic Contributions and Analytical Skills:
HR analytics holds significant potential for enhancing HR practices in public service. Key benefits include improved workforce planning, recruitment, HR development, and performance management. However, successful implementation requires addressing challenges related to data management, staff capabilities, and privacy concerns. By leveraging HR analytics, public sector organizations can make more informed, data-driven decisions, ultimately leading to better employee engagement and organizational performance.
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