Data-Driven Strategies in Human Resource Management: The Role of Information Science in Workforce Resilience – A Systematic Review

ABSTRACT :

In a time characterized by swift technological advancements and increased workforce vulnerabilities, incorporating data-driven strategies into Human Resource Management (HRM) has become essential for bolstering organizational resilience. This systematic review investigates how information science influences HRM practices through data-driven strategies designed to address workforce resilience. workforce resilience is a central concept in organizational sustainability in the context of accelerating change, digital disruption, and global crises. The review used PRISMA, a thorough search of the Scopus, Web of Science, and Google Scholar databases identified 47 peer-reviewed studies published from 2012 to 2024 that met the inclusion standards. These studies were examined to assess the use of data driven strategies in HRM such as predictive analytics, AI-driven workforce analytics, and real-time monitoring systems in HRM. The review revealed five central themes, the strategic imperative of data-driven HRM, enhancing workforce resilience through predictive analytics, information systems supporting workforce decision-making, the role of artificial intelligence in HRM, and challenges and considerations in implementing data-driven HRM. The analysis highlights that data-driven HRM is both a technological enhancement and a strategic necessity. In addition, organizations that integrate data analytics into HR processes are better positioned to anticipate workforce disruptions, optimize talent acquisition, and support employee well-being.