A Study on Machine Learning Application in Human Resource Operations to Predict Improper Employee Exit

Mr. DEV KUMAR, Student, II MBA, Department of MBA, Annamacharya Institute of 517501 Technology &Sciences: Tirupati- (Autonomous).
Prof. C. NADHAMUNI REDDY, MTech, Ph.D., FIE., MISTIE., MORSI., PRINCIPAL, Annamacharya Institute ofTechnology &Sciences: Tirupati (Autonomous)

Abstract:Machine Learning has emerged as a powerful tool for improving decision-making across business functions, includingHuman Resource Management. Modern organizations collect large volumes of employee data, which can be analysedusing machine learning algorithms to identify patterns related to employee behaviour and workforce dynamics. Thepurpose of this study is to explore how machine learning techniques can be integrated into HR operations to predictemployees who are likely to leave the organization without following the prescribed exit procedures. Early predictionallows HR departments to take proactive actions such as counselling, engagement programs, and retention strategies. Thestudy utilizes employee demographic details, employment records, performance data, and engagement indicators to buildpredictive insights. The results demonstrate that machine learning models can significantly improve HR decision-makingby identifying risk factors associated with employee attrition and enabling better workforce planning.