Prediction of Employee Turnover in Organizations using Machine Learning Algorithms

Abstract

Employee turnover is one of the major issues for the organizations because it causes an adverse effect on the organizational performance, productivity and organizational strategies. With varied solutions for the employee turnover, organizations prefer the machine learning techniques to predict it. The more the prediction is accurate, the better actions organizations may take for the retention of employees in an organization. It also helps in the succession planning of the employees as well as helps the management to decide upon its strategic plans for the organizational growth. Human Resource Information System (HRIS) is one of the area from where the data can be fetched for the prediction of employees’ turnover. One of the major focus of this paper is to avoid the inaccuracy in the prediction so that the prediction can be better validated. The data used in the study is taken from IBM communities’ Watson Analytic Blog.