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Predictive Analytics in Human Resources: Enhancing Workforce Planning and Customer Experience

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  • Olufunke Anne Alabi

    (Teesside University International Business School, Middlesbrough United Kingdom)

  • Funmilayo Aribidesi Ajayi

    (Department of Corporate Services, Gelose Marine Services Nig. Ltd, Port Harcourt, Rivers State, Nigeria)

  • Chioma Ann Udeh

    (Independent Researcher, Lagos Nigeria)

  • FChristianah Pelumi Efunniyi

    (OneAdvanced, UK)

Abstract

This paper explores the transformative role of predictive analytics in human resources (HR), focusing on how it can enhance workforce planning and improve customer experience. By leveraging data-driven insights, predictive analytics enables HR professionals to forecast workforce needs, optimize resource allocation, and anticipate skills gaps, aligning staffing with fluctuating customer demand. The paper also examines the application of predictive models in understanding customer behavior, facilitating dynamic workforce adjustments, and ensuring a balance between cost efficiency and service quality. Additionally, the study addresses the challenges of implementing predictive analytics in HR, including data quality, integration issues, and resistance to change, while considering the ethical implications, such as privacy concerns and biases in predictive models. The paper concludes with a discussion of future directions, highlighting emerging trends and opportunities for further research and development.

Suggested Citation

  • Olufunke Anne Alabi & Funmilayo Aribidesi Ajayi & Chioma Ann Udeh & FChristianah Pelumi Efunniyi, 2024. "Predictive Analytics in Human Resources: Enhancing Workforce Planning and Customer Experience," International Journal of Research and Scientific Innovation, International Journal of Research and Scientific Innovation (IJRSI), vol. 11(9), pages 149-158, September.
    • Handle: RePEc:bjc:journl:v:11:y:2024:i:9:p:149-158
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