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International Journal of Modern Engineering and Management | IJMEM
Multidisciplinary
Open Access Journal
ISSN No: 3048-8230
Follows UGC–CARE Guidelines
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Role of Talent Analytics in Improving Recruitment Quality and Workforce Planning

Author(s):

Ritika Chauhan, Naman Jindal, Surbhi Mehta, Aditya Rathore

Affiliation: Department of Management Studies, Blue Ridge College of Management, Kota, Rajasthan, India

Page No: 24-27

Volume issue & Publishing Year: Volume 2 Issue 11 , 2025-11-30

Journal: International Journal of Modern Engineering and Management | IJMEM

ISSN NO: 3048-8230

DOI: https://doi.org/10.5281/zenodo.18088088

Article Indexing:

Abstract:

Talent analytics, also known as HR analytics or people analytics, has become a transformative tool for modern organizations aiming to enhance recruitment quality and optimize workforce planning. This study examines how data-driven HR practices improve hiring accuracy, reduce turnover, and support long-term manpower forecasting. Using survey responses from 160 HR professionals across IT, banking, manufacturing, and service sectors, combined with interviews from 10 senior HR leaders, the research evaluates the impact of analytics-based recruitment tools, predictive hiring models, and employee performance dashboards. Findings reveal that organizations utilizing talent analytics achieve 27–35% higher recruitment accuracy, significantly lower hiring costs, and better alignment between job roles and candidate competencies. Predictive workforce planning models were shown to minimize understaffing and overstaffing issues by improving demand forecasting. The study concludes that integrating analytics into HR decision-making enhances strategic workforce management and strengthens organizational competitiveness. 

Keywords:

Talent Analytics; Recruitment Quality; Workforce Planning; HR Analytics; Predictive Hiring; Data-Driven HR

Reference:

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