LEVERAGING HR ANALYSIS FOR WORKFORCE COST OPTIMIZATION AND DATA-DRIVEN DECISION MAKING: EVIDENCE FROM JASAN TOOLCRAFTS & EQUIPMENTS, SALEM

Abstract

This study aimed to explore the role of HR analytics for workforce cost optimization and for data-driven HR decisions at Jasan Toolcrafts & Equipments, a manufacturing company based in India. Within the framework of a descriptive survey, a stratified random sample of 130 employees was analyzed by using Two-Way ANOVA, Multiple Linear Regression as well as Factor Analysis (PCA). The main results reveal that the frequency of reviewing employee performance data significantly affects workforce planning (p = 0.000). Furthermore, Gender has a significant effect on statistical use (p = 0.001).The second regression model revealed that management’s evaluation of employee’s utilization strongly predicts skill optimization (Beta = 0.475; p = 0.000; R² = 0.284). The third regression model revealed that the workforce data used for performance evaluation significantly controls workforce related expenses (p = 0.001). Factor analysis of the variables work experience, trend analysis as well as performance data led to the identification of one dimension of HR analytics which explained 49.74% of total variance (KMO = 0.628). In summary, this study highlights the importance of well-structured HR analytics for optimized workforce costs and for strategic HR management at manufacturing companies. Therefore, sufficient investment in corresponding tools as well as in HR staff’s analytics capabilities and in a data-oriented HR culture is required.