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Predictive Analytics and Workforce Outcomes in Oil Services Firms: Evidence on Turnover Reduction, Employee Engagement, And Productivity in Bayelsa State, Nigeria

Ebimie Melbourne Eleke, Nwachukwu Precious Ikechukwu

Abstract

This study examines the effect of predictive analytics on turnover reduction, employee engagement, and employee productivity in oil services firms in Bayelsa State, Nigeria. Using a cross-sectional survey of 241 employees and managers drawn from six oil services companies, the study employs simple regression analysis to test three null hypotheses. Findings reveal that predictive analytics exerts a significant positive effect on turnover reduction (β = 0.512, R2 = 0.262, p < 0.01), employee engagement (β = 0.467, R2 = 0.218, p < 0.01), and employee productivity (β = 0.443, R2 = 0.196, p < 0.01). These results establish that the systematic application of data-driven workforce intelligence meaningfully improves critical human resource outcomes in the highly volatile oil services sector of Nigeria's Niger Delta. The study contributes original empirical evidence to the emerging literature on people analytics in developing economy contexts and offers practical recommendations for HR professionals, oil firm executives, and Bayelsa State government regulators.

Keywords

predictive analyticspeople analyticsturnover reductionemployee engagementemployee productivityoil services firmsBayelsa StateNigeria

References

Barney, J. (1991). Firm resources and sustained competitive advantage. Journal of Management, 17(1), 99–120. https://doi.org/10.1177/014920639101700108 Becker, G. S. (1964). Human capital: A theoretical and empirical analysis, with special reference to education. University of Chicago Press. Cappelli, P. (2019). Your approach to hiring is all wrong. Harvard Business Review, 97(3), 48– 58. Cascio, W. F. (2006). The economic impact of employee behaviors on organizational performance. California Management Review, 48(4), 41–59. https://doi.org/10.2307/41166356 Creswell, J. W. (2014). Research design: Qualitative, quantitative, and mixed methods approaches (4th ed.). SAGE Publications. Davenport, T. H., & Harris, J. G. (2007). Competing on analytics: The new science of winning. Harvard Business School Press. Hausknecht, J. P., & Trevor, C. O. (2011). Collective turnover at the group, unit, and organizational levels: Evidence, issues, and implications. Journal of Management, 37(1), 352–388. https://doi.org/10.1177/0149206310383910 Marler, J. H., & Boudreau, J. W. (2017). An evidence-based review of HR analytics. International Journal of Human Resource Management, 28(1), 3–26. https://doi.org/10.1080/09585192.2016.1244699 Nunnally, J. C. (1978). Psychometric theory (2nd ed.). McGraw-Hill. Obi, C. (2014). Oil as the 'curse' of conflict in Africa: Peering through the smoke and mirrors. Review of African Political Economy, 37(126), 483–495. https://doi.org/10.1080/03056244.2010.530947 Rasmussen, T., & Ulrich, D. (2015). Learning from practice: How HR analytics avoids being a management fad. Organizational Dynamics, 44(3), 236–242. https://doi.org/10.1016/j.orgdyn.2015.05.008 Schaufeli, W. B., Bakker, A. B., & Salanova, M. (2006). The measurement of work engagement with a short questionnaire: A cross-national study. Educational and Psychological Measurement, 66(4), 701–716. https://doi.org/10.1177/0013164405282471 Tursunbayeva, A., Di Lauro, S., & Pagliari, C. (2018). People analytics: A scoping review of conceptual boundaries and value propositions. International Journal of Information Management, 43, 224–247. https://doi.org/10.1016/j.ijinfomgt.2018.08.002 Yamane, T. (1967). Statistics: An introductory analysis (2nd ed.). Harper & Row.

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