HR Analytics: Leveraging Big Data And Artificial Intelligence For Decision-Making In Human Resource Management

Abstract

In the modern era of digital transformation, human resource management (HRM) is undergoing a paradigm shift, with the integration of big data and artificial intelligence (AI) into HR analytics. This review paper explores the emerging trends, challenges, and opportunities associated with leveraging big data and AI for decision-making in HRM. By systematically examining existing literature, this paper elucidates the transformative potential of HR analytics in optimizing recruitment processes, talent management, employee engagement, performance evaluation, and organizational development.

The review highlights the key methodologies, tools, and techniques employed in HR analytics, including predictive analytics, machine learning algorithms, natural language processing, and sentiment analysis. Moreover, it investigates the ethical considerations and privacy concerns surrounding the collection, storage, and utilization of employee data in HR analytics initiatives. Through a critical analysis of case studies and empirical research findings, this paper identifies best practices and successful implementation strategies for harnessing the power of HR analytics to enhance organizational effectiveness and workforce productivity.

Furthermore, the review discusses the role of HR professionals in driving the adoption of analytics-driven decision-making practices within organizations and the importance of fostering a data-driven culture. It also examines the implications of HR analytics for employee empowerment, diversity, equity, and inclusion initiatives. Finally, the paper outlines future research directions and suggests areas for further exploration to advance the understanding and application of HR analytics in the evolving landscape of HRM.