Staff Assignment to Multiple Projects Based on DEA Efficiency

Abstract

An adequate staff assignment plan is recognized as one of the most important factor for fulfilling the foreseeable delivery of multiple projects with restrictions on available budget, time and quality. This problem is very complex and becomes more complicated as the number of projects, tasks and staff members increases. Decision makers need to find a single unique performance measure as the primary criterion for making a balanced and efficient staff assignment plan. The efficiency of an assignment plan depends on different input and output criteria related to staff member performances which can be economic, qualitative or quantitative by nature. Therefore, the main question is how to make the most efficient assignment plan in multi-project, multi-task environment if several staff members can carry out different tasks at the different level of performance. This paper proposes an integration of all input-output criteria, regardless of their type through a DEA-based mixed-integer programming model. It evaluates the efficiency of staff members as a unique criterion, based on their past performances, together with making an assignment plan. Practical examples with different restrictions empirically demonstrate the possibilities of the decision model. The results show that the fulfilling of maximum efficiency criteria of all staff members in implementing the required tasks provides balanced efficiency in the implementation of all on-going projects, which makes this model a useful tool for decision makers.