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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:10.55041/IJSREM.GSTCOS077

A STUDY ON IMPACT OF HR ANALYTICS IN TALENT MANAGEMENT AND EMPLOYEE DEVELOPMENT IN IT SECTOR

Stream/Area:

-

Subject:

-

Paper ID:

10.55041/IJSREM.GSTCOS077

Volume:

10 |

7 |

Jul 2026

Pages:

1-6

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
10.55041/ijsrem.GSTCOS077

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

PA

Polsani Akshitha

Student of MBA,

CMR Institute of Technology, Hyderabad, Telangana India.

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Mentors

DBN

Dr. B. Nayeema

,Associate Professor

CMR Institute of Technology, Hyderabad, Telangana India.

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Abstract

The study examines the impact of HR Analytics on talent management and employee development in the IT sector. It focuses on how data-driven HR practices improve recruitment, performance management, training, employee engagement, and retention. Data was collected from IT employees through a structured questionnaire and analyzed using percentage and statistical tools. The findings indicate that HR Analytics positively influences talent acquisition, skill development, workforce planning, and employee productivity. The study concludes that effective use of HR Analytics enhances decision-making, supports employee growth, and contributes to organizational success.

KEYWORDS

talent acquisition skill development workforce planning and employee productivity

Cite This Article

Polsani Akshitha, Dr. B. Nayeema, "A STUDY ON IMPACT OF HR ANALYTICS IN TALENT MANAGEMENT AND EMPLOYEE DEVELOPMENT IN IT SECTOR," International Journal of Scientific Research in Engineering and Management, vol. 10, no. 7, pp. 1-6, Jul 2026. https://doi.org/10.55041/ijsrem.GSTCOS077

Full Article/Conclusion

In addition, this research demonstrates the role of HR analytics on talent management and development in the IT industry. Based on the results from the statistical analysis with the use of Chi-square test and correlation, it is possible to state that the link between HR analytics and certain factors that contribute to employee development is rather strong. Specifically, the analysis revealed that HR analytics helps organizations enhance their talent management strategies, performance improvement initiatives, and other aspects related to development programs. It also makes it possible to make better decisions and increase efficiency and productivity due to the provision of data-driven insights. Overall, the use of HR analytics is crucial to the current practices of the HR department, and it can positively affect employees' development and progress.  

References

1.Vadithe, R., & Kesari, P. (2025). Role of Technology Enablers for Implementation of HR Analytics in the Indian IT Sector: A Mediation Analysis. South Asian Journal of Human Resources Management. 2.Saxena, M., & Jain, V. (2025). HR Analytics in the IT Sector: Linking Performance Appraisal Practices with Employee Engagement. 3.Wirges, F., & Neyer, A. K. (2023). Towards a Process-Oriented Understanding of HR Analytics: Implementation and Application. Review of Managerial Science. 4.khaliq, R., & Saritha, B. (2023). Benefits and Challenges of Adopting HR Analytics: A Comprehensive Review. Journal of Economics, Management and Trade. 5. Agarwal, H., & Raj, V. J. P. (2022). Adoption of Human Resource Analytics in Information Technology and Information Technology Enabled Services Industry in India.   Websites: ·                  https://journals.sagepub.com/doi/10.1177/01672533251314403 ·                  https://link.springer.com/article/10.1007/s11846-022-00574-0 ·                  https://www.sciencedirect.com/science/article/pii/S1475439819000291 ·                  https://www.koganpage.com/product/excellence-in-people-analytics-9781789661182 ·                  https://journals.sagepub.com/doi/10.1177/09716858251364994 ·                  https://www.tandfonline.com/doi/full/10.1080/09585192.2024.2403541  

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Publication Date

7/4/2026

Peer Review Type

Double-Blind Peer Review

Review Rounds: 2

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