Data-Driven Insights: HR Analytics for Tracking Employee Performance

Abstract: In the current day competitive business scenario, organizations have started perceiving that data driven decision making in human resource management plays an important role in the business landscape. In this research, every implementation and effectiveness of artificial intelligence and machine learning techniques in the HR analytics areas of HR analytics to improve employee performance management, retention rates and organizational productivity is set as research area. A study that develops and evaluates an AI based HR analytics system that uses different machines learning algorithms (including Decision Tree, Logistic Regression, and Random Forest) to analyze the HR metrics like employee satisfaction, performance score, attendance record, attrition indicator. An interactive dashboard is incorporated to the system which is used to visualize the critical HR indicators and the predictive results. Results show that the implemented AI models are highly accurate in predicting employee attrition and performance path, which will help HR managers to come up with targeted strategies to retain the employees and improve their performance. The results are that the AI driven analytics hold the power to enable proactive evidence-based HR practices that can make a huge difference in organization success in increasingly data centric business climate.