Journal of Management Information and Decision Sciences (Print ISSN: 1524-7252; Online ISSN: 1532-5806)

Abstract

Predictive Analytics in Employee Churn: A Systematic Literature Review

Author(s): Ardhianiswari D. Ekawati

The increase of capacity in the collection, storing, and analyzing the massive volume of data due to the rapid advancement of information technology has changed how the decision-makers in organizations approach their work. Human Resource Information Systems provide a lot of data on the employees, but there are still a few best practices on how to make use the abundant data for better decision making in Human Resources area. This limited implementation is mostly due to the decision making process in Human Resources is highly depended on the intuition, the use of advanced data analytics is still in the very early stage of implementation which is left behind in comparison to the use of advanced analytics in other areas such as Marketing, Sales or Finance. This article answers the question on how is the current implementation of predictive analytics in employee churn or employee turnover which is one of the most discussed topics in Human Resources Management, and which method of predictive analytics are better to use in predicting the employee churn. The answers of these questions are obtained from the result of a systematic literature review on the scholarly articles related to the topic published from 2000 to 2018 in major databases such as IEEE, ACM, Science Direct, Emerald and Willey Online.