Exploring the Antecedents, Analytical Tools, and Challenges in Implementation of Adoption of HR Analytics: A Study in the Indian Context - Mansi Saxena; Teena Bagga; Sangeeta Gupta; Rudra Rameshwar (SAGE Open)
This study aims to explore how and why human resource analytics, which involves using data analysis for HR-related decisions, is being adopted by Indian IT companies. It also seeks to understand the challenges faced in implementing these analytics and which analytical tools are commonly used. To achieve these goals, researchers collected and analyzed 478 responses from individuals working in the Indian IT industry. They used a software called AMOS version 21.0 to test their ideas. This software helps researchers understand relationships and patterns in data. The study found that certain factors, called “antecedents,” influence the adoption of HR analytics in IT organizations in India. It also revealed that problems with data, such as not having enough data or having data of low quality, were significant challenges in using HR analytics. Additionally, the research showed that many professionals in the Indian IT industry prefer using analytical tools like R and Power BI for HR analytics. The results of this study have important implications for businesses and HR professionals. By understanding the factors that influence the adoption of HR analytics, companies can make better decisions about how to implement these practices. Recognizing the challenges related to data quality and quantity can help organizations address these issues. Knowing which analytical tools are popular can guide companies in selecting the right tools for their HR analytics needs. Overall, this research provides valuable insights that can facilitate the adoption of HR analytics in various industries, not just in India. It’s important to note some limitations of this study. The research focused specifically on the Indian IT industry, so the findings may not apply equally to other sectors or regions. Additionally, the study used a specific software (AMOS version 21.0) and analyzed a specific number of responses (478), which could limit the generalizability of the results. Further research in different contexts and with larger samples may be needed to confirm these findings more broadly.