The Effect of Strategic Human Resource Analytics on Employee Productivity in Nigerian Manufacturing Companies: The Mediating Role of Data-driven Decision-making

Husseini Abalaka Faruna, Esther Onyinyechi Ekwilo, Ayo David Adeyemi, Mary Adanna Nnanna, Oluwadamilola Victoria Balogun and Regina Ochanya Okpanya
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Husseini Abalaka Faruna: Department of Business Administration, Salem University, Lokoja, Nigeria.
Esther Onyinyechi Ekwilo: Department of Economics, Faculty of Social Sciences, University of Lagos, Lagos, Nigeria.
Ayo David Adeyemi: Master of Business Administration (MBA), Faculty of Science, Business and Enterprise, University of Chester, England.
Mary Adanna Nnanna: Department of Management and Business Administration, Faculty of Management and Business Administration, MIVA Open University, Abuja, Nigeria.
Oluwadamilola Victoria Balogun: Department of Industrial Chemistry, Faculty of Physical Sciences, University of Ilorin, Ilorin, Nigeria.
Regina Ochanya Okpanya: Department of Banking and Finance, Faculty of Management Sciences, Joseph Sarwuan Tarka University, Nigeria.

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Abstract: The incorporation of HR analytics into strategic human resource management serves as a means of enhancing organisational performance; however, how HR analytics can be used to enhance employee productivity remains under-researched in developing-economy manufacturing environments. The study investigated the mediating effect of data-driven decision-making on the relationship between strategic human resource analytics and employee productivity among 357 employees and HR practitioners in Nigerian manufacturing firms. Structural equation modelling with bootstrapped mediation analysis was used to test the hypothesised relationships. Strategic human resource analytics significantly and directly influenced employee productivity (β = 0.418, p < 0.001) and significantly predicted data-driven decision-making (β = 0.521, p < 0.001); data-driven decision-making, in turn, significantly predicted employee productivity (β = 0.386, p < 0.001). Data-driven decision-making partially mediated the relationship between strategic human resource analytics and employee productivity (indirect effect: β = 0.201, p < 0.001), accounting for 32.5 per cent of the total effect. The model accounted for 54 per cent of the variance in productivity. The results suggest that HR analytics contributes to productivity partly by enabling more evidence-based HR decisions, providing a practical basis for strengthening HR analytics infrastructure and decision-making capacity.

Date: 2026-09-05
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Published in Journal of Global Economics, Management and Business Research, 2026, 18 (3), pp.339-353

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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-05741963

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