Process Optimization in Human Resource Management

The efficiency of Human Resource Management (HRM) practices is responsible for enhancing organizational productivity, streamlining workplace operations, engaging employees to the benefit of the organization, and aligning Human Resource strategies with business goals. Machine learning techniques have emerged as valuable tools in HRM, offering data-driven, scalable, and reliable methodologies. AI-driven tools using machine learning techniques primarily optimize HR practices. This study focuses on how application of ML is redefining HRM practices. The wide range of HR functions carried out by AI tools/platforms are explored. A number of ML techniques are discussed along with their efficacy. A case study of predicting employee attrition with the help of support vector machine (SVM) on IBM data is presented. The empirical study yielded 87.75% accuracy. The commonly encountered challenges while transforming manual HR practices to optimized one using machine learning are stated.