Analysis of Workforce Characteristics in the IT Industry for Improved Performance: A Multifaceted Data Analytical Approach

Abstract

This study provides a comprehensive examination of the demographic and professional attributes of a sample group consisting of 189 individuals working in the Information Technology Enabled Services (ITeS) sector. The dataset exhibits a nearly equivalent gender distribution, with males accounting for 50.3% and females accounting for 49.7%. The majority of individuals in the group are under 30 years old (31.7%). Regression analysis indicates that age and work experience are significant predictors of managerial positions, while education does not have a significant impact. Model 1 demonstrated a negative correlation between age and managerial positions, accounting for 8.6% of the variation in positions. According to Model 2, there is an inverse relationship between work experience and management positions, with work experience accounting for 27.1% of the variation. The analysis of correlation and exploratory data has uncovered significant connections between variables. Elderly employees demonstrate lower utilization of HR analytics despite possessing higher levels of education. Enhanced performance scores contribute to the utilization of HR analytics, while a higher level of education is associated with holding management positions. Factor analysis is associated with variables such as age, the utilization of HR analytics, education level, performance scores, and the number of years an individual has been with the company. This thorough examination provides a fundamental comprehension of the demographics and professional environment of the ITeS industry, allowing HR analytics to enhance employee performance. Different employee segments have diverse demands and levels of engagement, which are used to determine the methods for improving performance and engaging in HR analytics.

Keywords: