Leveraging HR Analytics for Predictive Talent Management and Employee Retention

Data-driven insights have changed talent management and staff retention in HR analytics spaces. Today business competition for talent makes it essential for companies to identify future potentials to minimize labour turnover while enhancing worker's performance. The paper discusses foresight HR Analysis, which was used for talent tracking and retaining top employees within the organization. In this study, future talent risks forecasting models aimed at estimating probabilities of employees leaving their jobs as well as revealing types of future top talents that require significant investments in development shall be delineated. The method comprises examining a data set containing worker's performance measures, demographic profile as well as details bout his period g employment and whether he has left or not called churning in business language. Techniques like logistic regression have been used in addition too machine learning algorithms such as random forests which can help flood lights on people who are most likely to leave soon. According to results obtained from this research work; it could be concluded that Human Resource Predictive Analytics is able to accurately predict employee's departure rates and find reasons for keeping them satisfied at their workplace by offering room for promotion or other rewards system like job satisfaction anymore stops them from leaving(Performance measures are improved). Henceforth some firms can build personized plans designed only for managing highly talented workers who bring about low exits cost after introducing various retention options with these features