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Predictive Analytics of Manpower Estimation using Markov Chain Model: A Real time Case on a Manufacturing Plant in Odisha


Affiliations
1 Professor & HoD, NIST Institute of Science and Technology (Autonomous), Berhampur, Odisha. 761008, India
2 Associate Professor, NSB Academy, Bangalore-560099, India
 

Manpower management is one of the core functional area of any business operations. In practice, right deployment of manpower at right positions in right time is very crucial. People usually join their corporate life in multiple times in a calendar year at various positions. They also move across various levels due to usual corporate HR interventions at different times in a year as well. So, optimization and successful prediction of work-force movement in the verticals by aligning its way to reduce surplus and shortage is key to survival in business. Right prediction of work-force position movements at right time is crucial to every organization success. This article focusses on insight of the optimization of human resources for key success of the organization. Results obtained from this study indicated the model validation when compared to actual data. The study took the data of a large steel making company in the state of Odisha and found this model useful for practice. The results indicated towards some suggestions for the company in employee hiring plans in future. Out of the available models available this ‘Markov Chain’ model application actually intends to show a positive direction towards decision making in managing and controlling the employee base.

Keywords

Predictive Analytics, Manpower Estimation, Markov Chain Model, Manufacturing Plant.
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  • (n.d.). doi:doi:10.1214/12-Udom, A. U. 2014. Optimal controllability of manpower system with linear quadratic 10.1214/12-
  • A.C.Georgiou. (2022). Modelling recruitment training in mathematical human resource planning. Wiley Online Library, 18(1), 53-34.
  • A.M.Kshirsagar, C. R. (1978). A Semi-Markovian Model for Predator-Prey Indicators. Biometric, 34(4), 611-619. doi:https://doi.org/10.2307/2530380 Abaza, K. A. (2015). Simplified staged-homogenous Markov model for flexible pavement. Road Materials and Pavement Design.
  • Babu, P. K. (2017). A study on manpower models with continuous truncated distributions. International Journal of Advance Research in Computer Science and Management Studies, 5(7), 16-29.
  • Belhaj, R. &. (2013). Forecasting the demand for construction skills in Hong Kong. Construction Innovation , Construction Innovation , 3-19.
  • E.C. Amanamba, C. C. (2021). A Markovian Study of Manpower Planning in the Soft-Drink Industry in Nigeria. Nigerian Journal of Technology, 4(4), 558-563. Retrieved from 10.4314/njt.v40i4.1
  • Guerry, D. F. (2010). Markov models in Manpower planning: A review , In : Varela J and Acuna S (Eds). Handbook of optimization theory: Decision Analysis and Applications., 67-88.
  • Herbert G. Heneman, I. a. (1997). Markov Analysis in Human Resource Administration: Applications and Limitations. Academy of Management Review, Vol. 2(No. 4). doi: https://doi.org/10.5465/amr.1977.4406722
  • https://www.economicsdiscussion.net/human-resource-management/manpowerplanning/ 32257. (n.d.).
  • Huang. (2004). Pavement ananlysis and design. Upper Saddle Review.
  • Hugh Courtney, J. K. (1997). Strategy Under Uncertainty. Harvard Business Review. Retrieved from https://hbr.org/1997/11/strategy-under-uncertainty
  • JAROSLAW OCZKI. (2014). Forecasting Internal Labour Supply with a Use of Markov. International Journal of Knowledge, Innovation and Entrepreneurship, 2(2), 39-49.
  • Maurer, B. D. (1 Apr 1988). Conceptualizing and Measuring The Economic Effectiveness of Human Resource Activities. Academy of Management Review, VOL. 13, NO. 2. Retrieved from https://doi.org/10.5465/amr.1988.4306887
  • Maurer, B. D. (1998). Conceptualizing and Measuring The Economic Effectiveness of Human Resource Activities. Academy of Management Review, 271-286. doi:https://doi.org/10.5465/amr.1988.4306887
  • McClean, S. E. (1997). Non homogeneous continuous time Markov and semi- Markov manpower models. Applied Stochastic Models and Data Analysis, 3(4), 191-198. doi:10.1002/(SICI)1099-0747(199709/12)13:3/4191::AIDASM3123.3. CO;2-K
  • P.Coleman, B. (1970). An integrated system for manpower planning. Business Horizons, 13(5), 89-95. doi:https://doi.org/10.1016/0007-6813(70)90118-7
  • Peter J.H.Sharpe, G. L. (1977). Distribution model of organism development times. Journal of Theoretical Biology, 66(1), 21-38. doi:https://doi.org/10.1016/0022- 5193(77)90309-5
  • Predictive Analytics of Manpower Estimation using Markov Chain ..... 82 Parikalpana - KIIT Journal of Management [Vol. 19.2, December-2023]
  • Rao & Kshirsagar, 1. (1978). A Semi-Markovian Model for Predator-Prey Indicators. Biometrics, 34, 611-619.
  • The Functional Response of Invertebrate Predators to Prey Density. (1977). Cambridge Core.
  • uan Varela and Sergio. (2011). Mathematics Research Developments. Handbook of Optimization Theory: Decision Analysis and Applications.
  • Udom, A. U. (2014.). Optimal controllability of manpower systam with linear quadractic performance index. . Brazilian Journal of Probability and Statistics, 28(2), 155-166. doi:10.1214/12-
  • Vandan Trivedi, I. M. (1987). A Semi-Markov Model for Primary Health Care Manpower Supply Prediction. 33(2), 150-160. doi:https://doi.org/10.1287/ mnsc.33.2.149
  • W, L. C. (2009). Markov Chain Analysi. International Encylopedia of Human Geography, 455-460.
  • William G.Snow, M. C. (2008). WAIS-R Test-retest reliability in a normal elderly sample. Journal of Clinical and Experimental Neuropsychology, 11(4

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  • Predictive Analytics of Manpower Estimation using Markov Chain Model: A Real time Case on a Manufacturing Plant in Odisha

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Authors

Ratnakar Mishra
Professor & HoD, NIST Institute of Science and Technology (Autonomous), Berhampur, Odisha. 761008, India
S. Dhanabagiyam
Associate Professor, NSB Academy, Bangalore-560099, India

Abstract


Manpower management is one of the core functional area of any business operations. In practice, right deployment of manpower at right positions in right time is very crucial. People usually join their corporate life in multiple times in a calendar year at various positions. They also move across various levels due to usual corporate HR interventions at different times in a year as well. So, optimization and successful prediction of work-force movement in the verticals by aligning its way to reduce surplus and shortage is key to survival in business. Right prediction of work-force position movements at right time is crucial to every organization success. This article focusses on insight of the optimization of human resources for key success of the organization. Results obtained from this study indicated the model validation when compared to actual data. The study took the data of a large steel making company in the state of Odisha and found this model useful for practice. The results indicated towards some suggestions for the company in employee hiring plans in future. Out of the available models available this ‘Markov Chain’ model application actually intends to show a positive direction towards decision making in managing and controlling the employee base.

Keywords


Predictive Analytics, Manpower Estimation, Markov Chain Model, Manufacturing Plant.

References





DOI: https://doi.org/10.23862/kiit-parikalpana%2F2023%2Fv19%2Fi2%2F223469