WORKFORCE BIG DATA ANALYTICS AND PRODUCTION EFFICIENCY: A Manager’s Guide
DOI:
https://doi.org/10.14738/abr.57.3168Keywords:
Big data, capacity utilization, employee productivity, production efficiency, workforce,Abstract
Abstract
The study investigates the use of workforce big data analytics as a tool to guide production managers to boost production efficiency while also ascertaining the level of awareness in the use workforce analytics amongst production managers. The study adopted survey research design and questionnaire were distributed to 20 respondents comprising of all Production Managers of the 20 Manufacturing Companies understudied. Data generated was analyzed using averages and scores. The outcome of the analyses showed that only 30% of the manufacturing companies had established and understood workforce plan while 70% did not have. Again the study showed that only 25% production managers agreed that the use of workforce big data analytics is necessary to boost production efficiency. Further findings showed that 75% of the managers admitted that their production was below average of which 40% of the managers ascribed their dismal performance to excessive manpower downtime which is a by-product of workforce scheduling. Based on the findings, it can be concluded that the use of workforce big data analytics is a more significant and important factor in boosting production efficiency.
References
Banjoko, S. A. (2002). Production and Operations Management. Nigeria: Pumark Nigeria Limited.
Beal, V. (2015). Big-data, http://www.webopedia.com/TERM/B/big_data.html.
Bassi, L. (2011). Raging debates in hr analytics. People and Strategy, 34(2), 14.
Carlson, K. D., & Kavanagh, M. J. (2011). HR metrics and workforce analytics. Human Resource Information Systems: Basics, Applications, and Future Directions, 150.
Chang, C.C., Yang, H.M., & Wen, J.C. (2002). Estimation of total flavonoid content in propolis by two complementary colorimetric methods J. Food Drug Anal., 10 (2), 178–182
Chen, L.H. & Liaw, Y.S (2001) "Using financial factors to investigate productivity: an empirical study in Taiwan. Industrial Management and Data System, 101(7), 378-384.
Craig, C. E. & Harris, C. R. (1973). Total Productivity Measurement at the Firm Level. Sloan Management Review. 14(3).13.
Du Plessis, A. J. (2009). An overview of the influence of globalization and internationalization on domestic Human Resource Management in New Zealand. International Review of Business Research Papers, 5(2), 1-18.
Dumaine, B. (2009). How managers can succeed through speed. Fortune, 13.
Everett, E.R, Eatherley, D. & Slater, S. (1992). Competitiveness Improvements Potentially Available from Resource Efficiency Savings, report for Defra.
Fitz-Enz, J & Mattox, J. (2014). Predictive analytics for human resources. Wiley publishers NY.
Hill, W. (2000). Strategic Management: Formulation, Implementation and Control New York McGraw-Hill.
Lawler, E.E., Levenson, A.R., & Boudreau, J.W. (2005). HR metrics and analytics: Use and impact. Human Resource Planning, 27(4), 27–35.
Lovell, S.J. (2011). The economic contribution of marine angler expenditures in the United States, retrieved from http://www.st.nmfs.noaa.gov/economics/index.
Missildine, C (2013), From HR Metrics to HR Intelligence. HR Examiner, New York, Prentice Hall.
Porter, M. E. (1998). The Competitive Advantage: Creating and Sustaining Superior Performance. NY: Free Press, 1985. (Republished with a new introduction.)
Sumanth, D. J., (1984) Productivity Engineering and Management, McGraw- Hill Book Company, New York.
Taylor, B.W. & Davis, R.K., (1977). Corporate Productivity-Getting It All Together, Industrial Engineering, 9 (3).
Ulrich, K. T. (2013). Product Design and Development. New York: McGraw-Hill.
United Nations Industrial Development Organization (UNIDO) 2015, Lima Declaration adopted at the fifteenth session to promote and accelerate inclusive and sustainable industrial development (ISID) in developing countries and economies in transition.
Walter, M., Sommer, T.D.& Zimmermann, J. (2011) Evaluating volume flexibility instruments by design-of-experiments methods International Journal of Production Research, 49 (6), 1731-1752
Williams, J. S (2012). Introduction to management science, 3rd ed. Burr Ridge, IL. Richard D. Irwin
