Leveraging Big Data for Enhanced Human Resources Management
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Background. In today’s rapidly evolving business environment, leveraging big data has become a crucial component for enhancing human resource management (HRM). Big data enables organizations to collect, analyze, and interpret vast amounts of employee information, providing insights that can optimize recruitment, performance evaluation, retention, and overall workforce management. However, many companies struggle to fully integrate data-driven strategies in HR, often due to a lack of expertise or understanding of big data analytics in this context.
Purpose. This study aims to explore the impact of big data on HRM practices, focusing on how data analytics can improve decision-making, workforce productivity, and employee satisfaction.
Method. A mixed-method research approach was employed, combining quantitative data analysis from HR metrics with qualitative insights from HR professionals. Data from various HR functions, including recruitment, employee engagement, and performance, were analyzed using machine learning algorithms to identify trends and inform decision-making processes.
Results. Interviews with HR managers provided additional context on the practical challenges and benefits of implementing big data in HRM. Findings reveal that big data analytics significantly enhances HR processes, leading to a 30% increase in recruitment efficiency and a 25% improvement in employee retention rates.
Conclusion. The study concludes that integrating big data analytics into HRM offers substantial benefits, enabling more precise, evidence-based decisions that enhance workforce management. However, successful implementation requires ongoing investment in technology and training to ensure data accuracy and relevance. This research emphasizes the value of a data-driven approach in HRM and provides a foundation for organizations seeking to maximize their human capital potential.
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