Employee Retention Prediction In Corporate Organizations Using Machine Learning Methods

Abstract

Employee Retention is the capability of an organization to maintain its employees. The concept is emerging as a key setback to organizations. Payments, organization culture, job satisfaction, remuneration, and flexibility impact the rate of retention for any organization or company. Employee Retention is also an essential function of Human Resource Management. Unless there is a thoughtful and serious effort from the management towards this direction, the competitors within the industry are likely to snatch and attract the talent which another company had nurtured over a period of time. Appropriate approaches for the formulation and implementation of employee retention approaches are a skill and needs to be prioritized by the management. The paper focuses on providing the prospective reasons why employees leave their jobs. The paper also examines the talents which companies want to develop and maintain to predict employee training. Similarly, the paper identifies the immediate productive scrutiny methods and implementations in a practical scenario, and who is eligible to be retained in the company and have a productive career path. Lastly, the paper identifies the essential factors for developing the predictive model. To achieve these, the research employed a survey in collecting primary data. The study surveyed the employees to identify the attributes and factors that are essential in predicting retention rates and improving retention of employees. The research conducted experiments with a machine-learning algorithm on the dataset, which increased the accuracy of the research outcomes. These assisted the research in identifying the employee retention rate. Training count emerged as the top predictor of employee retention. Thus, this research suggests that the company should strive to train more employees since those who have attended more training are retained.