Predictive Analytics in Talent Management

Abstract

This research focuses on in predicting the factors influencing Talent and Knowledge management on employee performance. Through reliability testing, data reduction on a sample of 395 respondents using multiple linear regression analysis and exploratory factor analysis (EFA), the factor analysis condenses 19 items into 6 key determinants of talent management and knowledge management. The factor analysis uses principal component analysis algorithm for initial solutions and varimax algorithm for rotation and extracting the final factor. The linear regression algorithm suggests a model that shows how three knowledge management and three talent management determinants affect worker performance. According to the study, staff performance is greatly impacted by knowledge acquisition, organisation, and storage, as well as by talent development, identification, and strategy. Thus, IT companies can improve their knowledge and talent management practices to improve employee performance.