Predicting Employee Performance using Machine Learning

The goal of this research is to create a machine learning model that uses historical employee data to predict future performance in organisational contexts. The goal is to divide people into three distinct categories—high performers, moderate performers, and low performers—and to use data to improve talent management and decision-making. The construction of the model entails addressing issues such as data quality, bias, and interpretability. In comparison to present methods, the expected outcomes include increased accuracy, speed, and versatility. However, ethical concerns, such as fairness and openness, remain central to the initiative. As organisations seek more innovative employee management approaches, this project aims to deliver a forward-thinking and adaptable paradigm that matches with changing organisational dynamics.