Analyzing Manpower Data of Higher Learning Institutions: A Markov Chain Approach

Abstract

The approach to manpower policy in most Malaysian universities appears to be guided by the traditional method of putting the right number of people in the right place at the right time or arranging for suitable number of people to be allocated to various jobs usually in a hierarchical structure. The technique has been practiced for years. This traditional method is deficit in the sense that it neither offers computational tools that will enable administrators to determine possible line of action to be taken nor provide tools to generate alternative policies and strategies. The objective of this study was to design a planning model for projecting university faculty employment under alternative policy suggested by the government. The planning model was developed using Markov chain technique. Two scenarios were considered in the study; scenario 1 was based on historical data pattern between year 1999 – 2014 and scenario 2 was based on RMK 9 policies. The results showed the possibility average length of stay by position and probability of loss for both scenarios. The greater impact is expected for average length of stay of senior lecturers compared to other faculty position considering the new policy.