WORKFORCE ANALYTICS IN MANUFACTURING: A REVIEW OF MIS TOOLS FOR LABOR PLANNING, ABSENTEEISM MONITORING, AND PRODUCTIVITY OPTIMIZATION

Abstract

This meta-analysis explores the transformative impact of Management Information Systems (MIS) on workforce analytics within the manufacturing sector, focusing specifically on labor planning, absenteeism monitoring, and productivity optimization. By systematically reviewing and synthesizing data from 53 empirical studies published between 2010 and 2024, the research provides a comprehensive evaluation of how MIS tools enhance workforce-related decision-making and operational outcomes. The findings demonstrate that MIS-based workforce analytics significantly improve labor efficiency, with firms reporting an average 22% increase in labor planning accuracy through the integration of scheduling modules and predictive simulation tools. Real-time absenteeism monitoring systems, including biometric and RFID-enabled attendance tracking, resulted in an 18% reduction in unplanned absences, while predictive absence analytics achieved a forecasting accuracy rate of 82%, enabling proactive labor interventions. Furthermore, the use of performance monitoring dashboards led to a 15% rise in output per labor hour, enhancing both individual accountability and team productivity. The study also reveals that MIS platforms facilitate skill-based task allocation, cross-functional coordination, and seamless integration of HR, production, and quality data, contributing to improved workforce agility and long-term cost efficiency. These outcomes are theoretically grounded in Human Capital Theory, Socio-Technical Systems Theory, the Unified Theory of Acceptance and Use of Technology (UTAUT), and the Strategic Alignment Model, all of which support the role of MIS as a strategic enabler of labor optimization and enterprise-wide coherence. The results underscore the importance of embedding data-driven workforce analytics into manufacturing operations to support continuous improvement, reduce operational disruptions, and build a high-performance, future-ready labor management infrastructure. This study provides critical insights for industry leaders, system designers, and policymakers aiming to leverage MIS for sustainable workforce transformation in complex, competitive manufacturing environments.