Employee Satisfaction Analytics: An Ai and Power Bi-based Approach for Strategic HR Decision-making

Abstract

Employee satisfaction is a critical factor in organizational success, directly influencing productivity, retention, and workplace harmony. This study explores how HR practices contribute to employee satisfaction by combining real-life observations with analytical tools. A total of 65 employee responses were collected through Google Forms, and the data were analyzed using Power BI, employing visualizations such as pie charts, cards, and clustered column charts to highlight key trends and insights. To further enrich the analysis, Artificial Intelligence (AI) techniques, including sentiment analysis, are proposed to categorize employee feedback and uncover underlying concerns beyond numeric data. The findings reveal the most influential factors affecting employee satisfaction, including recognition programs, training opportunities, and work-life balance, and demonstrate how integrating AI with Power BI dashboards enables HR to implement targeted, data-driven strategies. By bridging practical HR interventions with modern analytical tools, this research provides a comprehensive roadmap for organizations seeking to enhance workforce engagement, optimize employee performance, and foster a positive workplace environment.