6.Predictive Analytics for Early Detection of Goal-Progress Driven Shortcut Behaviors in Employee Performance Systems -1Dr.Pradeep Chaurasia, 2Sarla Mishra

Abstract: In recent years, higher education institutions have increasingly adopted Performance Management Systems (PMS) to evaluate and enhance employee effectiveness. However, an overemphasis on measurable targets can inadvertently lead to goal-progress-driven shortcut behaviors—instances where employees manipulate or bypass processes to meet performance criteria. This study investigates the role of predictive analytics in identifying and mitigating such behaviors within the higher education landscape of Jabalpur City. A structured questionnaire was administered to 150 respondents across public and private institutions. The study utilized both descriptive and inferential statistical techniques, including reliability analysis (Cronbach’s Alpha = 0.87) and hypothesis testing, to examine the relationship between performance pressure, the implementation of predictive analytics, and the emergence of shortcut behaviors. Findings suggest that institutions employing predictive tools are more adept at identifying early indicators of manipulative practices. Furthermore, the presence of a robust institutional culture significantly moderates the incidence of unethical responses to performance demands. The study concludes that integrating predictive analytics within employee evaluation frameworks—alongside clear ethical guidelines—can enhance accountability, curb manipulation, and promote long-term academic integrity.