Markovian approaches in modeling workforce systems

Manpower planning is a fundamental aspect of Human Resource Management which is to a great extent based on statistical techniques and focused on quantitative models for workforce systems. Aggregated Markov models are defined by transition probabilities between homogeneous subgroups of personnel of the workforce system. The analytical Markovian approach in manpower planning allows identifying interesting characteristics of the workforce system, allows predicting the evolution of the workforce and controlling it by setting the organization's human resource policies (e.g. recruitment, promotion, training). There is a rich variety of publications on Markov manpower models, in which properties of workforce systems are investigated under very specific assumptions. This paper offers a review of the different types of Markov manpower models. Hereby attention has been paid to the successive stages of the Markov manpower planning methodology in real-world applications, from model building and selection, parameter estimation, model validation to prediction and control. The paper covers the latest advances in the field.