Predictive Analytics in HR Management

Objective: - This paper accentuates how predictive analytics can offer HR pioneers assistance with scrutinizing the issues natural to HR procedures. It likewise highlights how some key HR challenges can be tended to utilizing predictive analytics. Analysis: - This study proceeds in the following manner. It starts with a literature review in Predictive analytics for Human Resources that depend on setting up the information-driven measurable relationship between the objectives and activities of the HR function. Then followed by the assessment of the likelihood using the Predictive business intelligence tools 'Data mining' and 'End-User query, reporting, and analysis'. Lastly, implementation of predictive analytic techniques, such as 'Fraud analysis and detection applications', 'Multilayer perceptron (MLP)' and 'K-Nearest neighbour' that studies the similar unit in a different sample will exhibit the specific performance. Findings: - From this study, the key areas are identified from which the predictive analytics can create the values for HR perspective including 1) Employee Profiling, 2) Employee Attrition and Loyalty Analysis, 3) Forecasting of HR Capacity and Recruitment Needs, 4) Appropriate Recruitment Profile Selection, 5) Employee Sentiment Analysis and 6) Employee Fraud Risk Management. Accepting these practices have set up, this paper investigates the distinctions in the way of objectives and accomplishments of ventures that utilized predictive analytics versus those that did not. Novelty: - This study can further extend to the building of service outlines how businesses are performing relative to their peers and pinpoints improvement opportunities--and today, areas where robust workforce analytics can contribute game-changing insights.