Machine Learning Algorithms for Optimizing Performance Management in Human Resources

Performance management, which is a critical component of any organisation and a major concern to employers, has always been a subject of discussion, in terms of how best to go about it, in order to achieve the best organisational result. Performance management processes have shifted from a mere traditional approach to a more modern approach with many organisations trying to leverage AI for best results. This work examines the application of machine learning (ML) in enhancing performance management (PM) in human resource management (HRM). For this study, we used a semi-systematic literature review, critically examining 30 publications using a comparative framework highlighting similar, exceptional, novel, and differing perspectives. This paper finding indicates that ML models such as CatBoost, backpropagation, and CRISP-DM significantly improve appraisal accuracy, fairness, and decision-making efficiency. However, there are ethical, technological, and Organisational barriers, which continue to affect adoption.

Keywords: Algorithms, Machine Learning, Performance Management, Human Resources.