Digitalization of human resource management: A machine learning based decision support system

Technological developments such as social and mobile platforms, artificial intelligence, big data analytics and cloud computing have had a significant impact on the function, design and processes of human resource management. Technological advances have enabled more effective decision making in human resource management, transforming HR managers into partners who provide strategic support to organisations. With the automation of HR processes, digital technologies are used to perform many HR functions such as recruitment, payroll and performance management, labour turnover and workforce planning. High employee turnover is a common concern for organisations in terms of cost reduction, business performance, strategic growth and corporate image. The ability to predict employee turnover will be an important tool for any organisation that wants to retain employees and predict their future behaviour. For this purpose, a decision support system has been developed for predicting turnover and making optimum staff-department matching. In the first stage of the study, machine learning techniques are used to predict how soon employees will leave their current organisation. In the second phase, an assignment model is developed to maximise the total working time in staff-department assignments. In the case studies conducted with the proposed decision support system, it has been observed that there is a significant increase in the estimated working time in the proposed staff-department assignments compared to the current situation.