Leveraging Advanced Analytics to Enhance Employee Retention and Engagement

Abstract: The increasing complexity of workforce dynamics poses challenges for organizations striving to retain skilled employees. High turnover rates lead to operational inefficiencies and financial burdens. Advanced analytics provides a proactive approach by leveraging machine learning, artificial intelligence (AI), and statistical modelling to predict attrition risks and improve engagement strategies. This study explores the effectiveness of predictive analytics, sentiment analysis, and personalized engagement methods in fostering employee retention. Findings indicate that flexible work arrangements, leadership quality, and career development opportunities significantly influence employee loyalty and satisfaction. Organizations that integrate data-driven retention strategies experience reduced turnover and enhanced workforce stability. This study underscores the transformative impact of analytics in shaping a resilient and engaged workforce. Keywords: Employee Retention, Workforce Engagement, Advanced Analytics, Predictive Modelling, AI in HR JEL Classification Number: M12, M54