Efficient Human Resource Allocation in Projects Using Centralized Data Envelopment Analysis

Abstract

Human resource allocation is a critical component of project management, especially for projects that rely on the knowledge and expertise of skilled personnel. Data Envelopment Analysis (DEA) is a suitable method for this allocation since teams working for different tasks of a project can be considered as Decision Making Units (DMUs) that produce valuable outputs using different types and levels of personnel (inputs). We use Centralized DEA models for efficient allocation of human resources of the overall project among several teams. Using the software teams of a project undertaken in a large technological defense company as DMUs, we define appropriate outputs that measure effort, importance of work, and schedule performance. Factors relevant to the importance of work are aggregated using Rank Order Centroid weights according to expert evaluations. We differentiate between the permanent personnel of the company by their expertise level, and also subcontractors as different inputs. We define staffing policies with varying flexibilities that can be applied in different time periods, and suggest the transfer or removal of some personnel. Our results demonstrate that a centralized view on human resource allocation can bring noteworthy savings, especially in the long term when there is higher flexibility in staffing decisions.