1 School of Management and Labor Relations – Rutgers University, New Brunswick, NJ, USA.
2 School of Business – University of Cape Coast, Ghana.
3 Department of Business Administration – Accra Institute of Technology, Ghana.
4 Department of Accounting and Finance – Kwame Nkrumah University of Science and Technology, Ghana.
Received on 16 June 2026; revised on 06 August 2026; accepted on 08 August 2026
Background: Organizations across critical U.S. industries continue to face workforce challenges, including employee turnover, labor shortages, skills gaps, and workforce disruptions. Data-driven workforce analytics has emerged as a strategic approach for improving employee retention, workforce resilience, and organizational performance. This study aimed to synthesize evidence regarding the effectiveness of workforce analytics in enhancing employee retention and workforce resilience across critical U.S. industries.
Methods: A systematic review was conducted of peer-reviewed studies published between 2021 and 2026. Studies examining workforce analytics, people analytics, predictive HR analytics, artificial intelligence (AI)-enabled workforce management systems, employee retention, workforce resilience, and talent management were included. Following screening and eligibility assessment using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA 2020) guideline, 22 studies met the inclusion criteria and were included in the qualitative synthesis.
Results: The reviewed studies consistently demonstrated positive associations between workforce analytics and workforce outcomes. Workforce analytics improved employee retention through the identification of turnover risks, enhanced talent management, workforce planning, and employee engagement. AI-enabled HR analytics supported recruitment effectiveness, talent optimization, and workforce decision-making, while workforce analytics contributed to workforce resilience by improving organizational adaptability, workforce agility, and preparedness for labor market disruptions. These benefits were observed across healthcare, education, manufacturing, technology, and hospitality sectors.
Conclusion: The findings suggest that workforce analytics represent a valuable strategic tool for improving employee retention, strengthening workforce resilience, and enhancing organizational performance. The increasing adoption of predictive analytics and AI-enabled workforce management systems may contribute to stronger human capital development, workforce sustainability, and long-term economic competitiveness in critical U.S. industries.
Workforce Analytics; Employee Retention; Organizational Performance; Human Capital Development
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Aminat Jumoke Folawewo, Jessica Fosua Agyei, Matthew Oman-Amoako, and Solomon Doe Adjaottor. Data-driven workforce analytics for improving employee retention and workforce resilience in critical U.S. Industries: A systematic review. Magna Scientia Advanced Research and Reviews, 2026, 17(02), 372–385. Article DOI: https://doi.org/10.30574/msarr.2026.17.2.0156