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

Olufunke Anne Alabi, Funmilayo Aribidesi Ajayi, Chioma Ann Udeh and FChristianah Pelumi Efunniyi
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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

International Journal of Research and Scientific Innovation, 2024, vol. 11, issue 9, 149-158

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.

Date: 2024
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