Candidate Performance Prediction—A Detailed Analysis Using Predictive Analytics Workbench

Predictive Analytics involves anticipating future outcomes by leveraging both historical and current data. Descriptive analytics plays a crucial role in this process, providing a comprehensive understanding of the current problem scenario and insights from past data. Predictive analytics employs various tools such as statistics, modeling techniques, and data mining, and utilizes models like decision trees, correlation, and regression. The sequential application of techniques encompasses Deep Learning, Artificial Intelligence (AI), and Machine Learning (ML). This predictive approach finds applications across diverse domains such as Finance, Human Resources (HR), Marketing, and Operations. This research specifically focuses on predicting employee performance before the hiring process based on interview scores, utilizing the Predictive Workbench. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.