The Impact of Employee Engagement on Organizational Performance: A Machine Learning Approach

Abstract

Employee engagement is a vital component that drives the success of modern organizations. Engaged employees contribute more to organizational objectives, demonstrate higher productivity, and are generally more satisfied. This research investigates the relationship between employee engagement and organizational performance using a machine learning approach, aiming to explore how predictive models can improve engagement strategies and their impacts on organizational performance. By analyzing actual organizational data, this study applies machine learning algorithms to identify the key factors influencing employee engagement and their correlation with key performance indicators (KPIs) such as productivity, profitability, and customer satisfaction. The findings reveal a strong positive correlation between employee engagement and organizational performance, with machine learning models proving to be an effective tool for HR analytics. The paper also discusses potential models, their underlying equations, and visualizes results through graphs. This research underscores the importance of a data-driven approach to human resource management.

DOI - https://doi.org/10.65525/SVUP.9788199651500.2026.7-17