The increasing utilization of data-driven technology in human resource management has transformed organizational strategies for people management, workforce optimization, and strategic decision-making. Human resources analytics has transformed into a robust instrument that enables firms to examine employee data, forecast employee behavior, and enhance overall organizational performance. In industrial enterprises, where employee productivity, engagement, and well-being profoundly influence operational efficiency, the utilization of HR analytics has become paramount. The purpose of this study is to investigate the impact that HR analytics has on the well-being, engagement, and productivity of worker populations across various industrial firms. The purpose of this study is to investigate the relationships that exist between data-driven human resource activities and worker satisfaction, organizational commitment, stress reduction, employee engagement, and overall productivity. The researchers used standardized questionnaires to collect information from workers at industrial companies as part of this study, which followed a quantitative research methodology. The examination of the association between HR analytics and employee outcomes was performed utilizing descriptive statistics, correlation analysis, and regression analysis. HR analytics markedly enhances employee well-being through the optimization of task management, employee support systems, and workforce planning. Research findings indicate that HR analytics markedly enhances employee engagement via performance assessments, career development initiatives, and personalized employee experiences. Moreover, HR analytics enhances efficiency by accelerating fact-based decision-making and optimizing workforce allocation. Research findings indicate that industrial organizations implementing HR analytics solutions exhibited elevated employee happiness, reduced turnover intentions, and enhanced labor efficiency. The findings of this study contribute important new information to the current body of literature on human resource analytics, employee well-being, and organizational success. Moreover, it has pragmatic consequences for industrial enterprises striving to cultivate data-driven, employee-centric environments.