Abstract
M.Phil. (Engineering Management)
Proper manpower planning is a key factor in the demand and supply of workforce in every organization. It probes the skills and capability sets, the right quantity, location, timing, and quality of the needed manpower. It is evident according to empirical studies that undivided attention has been given to manpower planning in the last decade. Different bodies involved include government parastatals, academic and industrial organizations and institutions performing some form of manpower planning research and activities to maintain stability and retention in the system. Whether these inputs are reflected in the manpower policies and make a significant contribution in this regard is yet to be seen.
Several analytics and methods of modelling manpower planning exist, however, Markov chain has been used widely and accepted in various facets and domains.
In this research, Markov Chain is used as a tool to analyse the manpower data from an academic institution as a case study with the aim to unearthing the hidden details regarding existing manpower policies and hence, its fairness and robustness towards staff training, promotion, and ultimately retention.
A 9-year stage of manpower data split into states is used and matrix operations employed in analysing the manpower data obtained. Bayesian probability is also used for establishing the transition probability matrix (TPrM), and these matrix transformations are carried out repeatedly to achieve stability.
The results of the analysis show that manpower policy in the participating organization towards overall staff retention is rigid and stern. The results clearly satisfy the purpose of the study which is to predict the trend in the manpower practice, the potential cause of manpower loss and subsequently, the flow and fairness of the existing manpower policy.