Enhanced Analytical Framework for Work Stress Management and Its Influence on Employee Performance: A Case Study in Chennai’s BPO Sector

Indian business process outsourcing (BPO) companies, particularly those located in metropolitan areas like Chennai, are defined by high-pressure environments, extended work hours, and performance-driven cultures. Many of these factors contribute significant work-related stress, which can directly influence employee performance and organizational output. Unstructured, evidence-based stress management strategies have helped to lower job satisfaction, absenteeism, and turnover. Though this is true, stress is a normal part of high-demand industries like business process outsourcing (BPO). A clear awareness of the effects of stress and a proper evaluation of the efficacy of various stress management techniques determine sustainable human resource development. The approach of this study is a hybrid one that combines survey data collecting with stress prediction from machine learning simulations. Two hundred Chennai-based business process outsourcing (BPO) employees' stress levels, management practices, and performance indicators were evaluated using a standardized questionnaire. A simulation classifying the levels of stress impact on performance using a Decision Tree algorithm was also run using Python-based stress prediction. Review and compare the findings with four currently in use alternative stress management assessment tools. Stress at work significantly affects the results of this study on the efficacy of activities, job satisfaction, and staff retention. With respect to the projection of stress-related performance drop, the proposed method revealed an 89% higher accuracy compared to the statistical or rule-based models currently in use. When implemented proactively, important stress management techniques including mindfulness programs, schedule flexibility, and peer support groups revealed a significant rise in performance metrics.