Markov Chain: A Predictive Model for Manpower Planning

The use of Mathematical models for manpower planning has increased in recent times for better manpower planning quantitatively. In respect of organizational management, numerous previous studies have applied Markov chain models in describing title or level promotions, demotions, recruitments, withdrawals, or changes of different career development paths to confirm the actual manpower needs of an organization or predict the future manpower needs. The movements of staff called transitions are usually the consequences of promotions, transfer between segments or wastage and recruitment into the system. The objective of the study is to determine the proportions of staff recruited, promoted and withdrawn from the various grades and to forecast the academic staff structure of the university in the next five years. In this paper, we studied the academic staff structure of university of Uyo, Nigeria using Markov chain models. The results showed that there is a steady increase in the number of Graduate Assistants, Senior Lecturer and Associate professors, while, there is a steady decrease in the number of Assistant Lecturer, Lecturer II, Lecturer I, and Professor in the next five years. The model so developed can only be applied when there is no control on recruitment but the research can be extended to include control on recruitment. The model can also be applied in school enrollment projection.

Keywords
Markov Chain; Transition Probability Matrix; Manpower Planning; Recruitment; Promotion; Wastage