Using Machine Learning to Promote Proactive Human Resources Management: A Case Study

Abstract

Since the Industrial Revolution the function of human resources (HR) has undergone several changes, today it is asked to adopt a long-term and proactive approach which serves to anticipate the needs of the company and the problems likely to impact its productivity and performance in order to implement long-term adaptation actions and be effective in its strategic approach. Otherwise Machine learning has been for some time, a trending technology that has seen massive use in many areas, according to a study conducted by IT decision makers from over 15 different business sectors in the UK, France, Germany and Spain, 87% of the samples have implemented this technology or plan to do so. This technology has allowed companies to improve their processes, increase their competitiveness and help decision-making in several management areas such as finance and marketing.

This present work seeks to highlight the potential of this technology to promote proactive management of human resources by using Machine Learning algorithms in the analysis of turnover and the prediction of employees tending to leave their jobs using a IBM corporate database published as part of a competition for the development of an internal model used to identify employees intending to leave their jobs. The results of this study have shown that this technology can play a crucial role in the proactive management of human resources by providing information that makes it possible to pro-act and anticipate actions related to human resources management.

JEL classification: M12

Paper type: Empirical research