Transforming Human Resource Practices Through Big Data: Insights from Recruitment, Performance Evaluation, and Managerial Decision-Making

Abstract

Big data analytics has exploded in recent years, which brings new opportunities for Human Resource Management and provides more advanced tools to assist recruitment, improve performance evaluation, long-term workforce planning, etc. While some sectors have embraced data-driven HR, adoption is inconsistent, and its effect on company success more generally remains to be discovered. By examining the role of big data analytics in enhancing recruitment processes, employee engagement, and managerial decision making, this research attempts to unfold how and where HRM practice is taking its strength from. It also discusses the main problems that organisations face in adopting them and explores some suggestions to remedy those challenges. A mixed approach was used to get a more complete view. Quantitative data was collected in a survey of 200 HR managers spanning across industries who have been practising data-driven recruitment, retention, and performance assessment. Interviews with 30 senior managers provided qualitative insights into practical barriers and perceived benefits of big data in HRM. Quantitative findings show that the majority of managers consider themselves more efficient in recruiting and with a higher level of employee involvement when using analytical tools, as analysed by statistical methods. Improved performance management decision-making was also a common observation. Despite positive results, they said, participants cited hindrances such as struggling to amalgamate different pools of information and fears over data privacy, as well as technical skills gaps in HR teams. The research highlights the criticality of overcoming these challenges to achieve the strategic potential offered by big data analytics in contemporary HRM.