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Modelling heterogeneity in manpower planning: dividing the personnel system into more homogeneous subgroups

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  • Tim De Feyter

Abstract

Manpower planning is very useful for human resource management in large organizations. Most manpower models are concerned with the prediction of the future behaviour of the staff: they might leave the organization, get promoted or acquire more and new skills. This behaviour can vary a lot among different employees, what makes prediction difficult. It is common to tackle this problem by dividing the whole heterogeneous personnel system in several more homogeneous subgroups. This approach is often used to develop manpower planning models for prediction, control or optimization. Although the division in homogeneous subcategories is a fundamental and important step in the application of the models, up till now literature neglects to discuss a procedure to deal with this in practice. This paper suggests a general framework to find the distinguished homogeneous subcategories by determining and considering observable sources of personnel heterogeneity. Copyright © 2006 John Wiley & Sons, Ltd.

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  • Tim De Feyter, 2006. "Modelling heterogeneity in manpower planning: dividing the personnel system into more homogeneous subgroups," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 22(4), pages 321-334, July.
    • Handle: RePEc:wly:apsmbi:v:22:y:2006:i:4:p:321-334
    DOI: 10.1002/asmb.619
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    Cited by:

    1. Tim De Feyter & Marie-Anne Guerry & Komarudin, 2017. "Optimizing cost-effectiveness in a stochastic Markov manpower planning system under control by recruitment," Annals of Operations Research, Springer, vol. 253(1), pages 117-131, June.
    2. Guerry, Marie-Anne, 2011. "Hidden heterogeneity in manpower systems: A Markov-switching model approach," European Journal of Operational Research, Elsevier, vol. 210(1), pages 106-113, April.
    3. Philippe Carette & Marie-Anne Guerry, 2022. "Markov models for duration-dependent transitions: selecting the states using duration values or duration intervals?," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 31(5), pages 1203-1223, December.

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