Human Resource Analytics: an Integrative Review of  Data-Driven HR Decision Making

Cokorda Agung Wibowo; Awan Anhara; Bela Bela

Authors

Cokorda Agung Wibowo Departement of Management, Pamulang University, Indonesia
Awan Anhara Departement of Management, Pamulang University, Indonesia
Bela Bela Departement of Management, Pamulang University, Indonesia

Keywords:

Human Resource Analytics, HR Decision-Making, Artificial Intelligence, People Analytics, HR Management

Abstract

The development of digital technology has changed the paradigm of human resource management (HRM), with Human Resource Analytics (HRA) becoming a key approach to data-driven decision-making. This research aims to conduct an integrative review of the roles, benefits, challenges, and current trends in the application of HRA in various organizations. The method used is a systematic literature review, by analyzing 15 academic articles from reputable international journals that discuss the implementation of HRA in workforce management. The results revealed that the implementation of HRA can improve operational efficiency, support employee recruitment and retention processes, and facilitate the development of data-based training strategies. However, key challenges in HRA implementation include the lack of analytics skills among HR professionals, data privacy and security issues, and resistance to change within organizations. The study also identified recent trends, such as the integration of artificial intelligence (AI), the use of people analytics to measure employee engagement, and the adoption of cloud-based HR technologies. Based on the findings, it is recommended that organizations invest in analytics skills training for HR professionals such as drafting a comprehensive data protection policy and gradually adopting HRA technologies to improve the effectiveness of HR management. This research contributes to both academics and practitioners by presenting insights on how HRA can be optimally implemented to support more accurate and evidence-based decision-making in HRM.

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