An Empirical Study on Employee Engagement & Turnover Intention Among IT Professionals for Predictive Analytics

Abstract

Employee engagement and turnover intention, especially in high technology industries such as Information Technology (IT), where there is intense competition as to who gets a skilled workforce, and the turnover is high. This paper will discuss how predictive analytics, in this case, various analyses used to control employee turnover and improve employee engagement strategies. The quantitative methodology was used, and a cross-sectional survey based on Likert scale was utilized to gather data on employee engagement, job satisfaction, workplace environment, and turnover intention. Regression, correlation, exploratory data analysis (EDA) and factor analysis were used to analyze the relationships between organizational factors and turnover intentions. The regression analysis showed the value of R² of 0.738; this means that there was a strong correlation between predictive analytics and turnover intentions but the p-value of 0.0620 meant that the null hypothesis (H0) that predictive analytics does not strongly influence turnover management could not be rejected. The analysis of correlation revealed that the turnover intention is negatively correlated with job satisfaction (-0.60), conducive working environment (-0.55), pay and benefits (-0.65), career growth prospects (-0.50) and work-life balance (-0.60). Exploratory Data Analysis (EDA) revealed that the employee engagement (29.3%) and job satisfaction (40.7) had the greatest influence on turnover intentions. Factor analysis also showed that predictive analytics is a moderately influencing factor in HR decision-making, as 250 of them strongly agreed that predictive analytics is a factor in more effective management approaches. The results suggest that while predictive analytics shows strong potential for enhancing HR decision-making, the relationship did not reach the standard threshold for statistical significance (p = 0.0620). Consequently, the research acknowledges that organizational factors currently play a more primary role in turnover intentions than predictive models alone. On this understanding, the research adopted the alternative hypotheses (H1) that organizational factors and predictive analytics play an important role in turnover intentions and HR outcomes, which will help to develop more efficient employee retention measures.