Predictive Analytics in Assessing Employee Retention Rates: An Analysis of Effectiveness and Accuracy of Different Predictive Model

A high rate of employee turnover is a curse to organizations, and therefore it is surprising that the study of employee retention has received so little attention. Employee turnover is a common problem that companies begin to complain about and to show their discomfort. Yet predictors and scientific insights exist, as do solutions. Predictive analytics makes use of several statistical models to provide insights into future events and improve decision-making support. Human resources are beginning to use predictive analytics tools. Predictive analytics works by learning from data and statistics in order to provide insights that help companies make better decisions. This paper studies and evaluates the effectiveness of different predictive models using respondents from a sample of colleges before passing the examination stage. The results provide optimistic support for the usefulness of predictive analytics and also make policy recommendations on how managers can improve employees’ attitudes towards the organization and retain them while working independently before passing the examination stage.