TRANSFORMING HR STRATEGIES THROUGH EMPLOYEE EXIT DATA ANALYTICS IN THE PAINT INDUSTRY

Abstract

This study focuses at how HR procedures in the paint industry can be transformed through the use of employee exit data analytics. It focuses on figuring out the primary drivers of employee turnover and assesses how exit data may help make better decisions to increase engagement and retention. The study examines important factors such work-life balance, professional growth prospects, managerial assistance, job satisfaction, and pay. Chi-square testing and descriptive analysis were two statistical techniques used to analyze employee data. The results show that companies can identify the root reasons of attrition and create proactive HR policies by using structured analysis of exit data. The study comes to the conclusion that long-term sustainability, organizational performance, and staff retention are all improved by the efficient use of departure analytics.