Empirical Study on Selection of Team Members for Software Projects - Data Mining Approach
This addresses the challenge for project managers in IT industries to allocate personnel effectively to achieve product quality, but it is incremental as it builds on existing qualitative methods.
The paper tackled the problem of selecting team members for software projects by identifying criteria through interviews with project managers and found that consistent use of these criteria significantly correlates with project success, with human factors showing strong correlations to software quality.
One of the essential requisites of any software industry is the development of customer satisfied products. However, accomplishing the aforesaid business objective depends upon the depth of quality of product that is engineered in the organization. Thus, generation of high quality depends upon process, which is in turn depends upon the people. Existing scenario in IT industries demands a requirement for deploying the right personnel for achieving desirable quality in the product through the existing process. The goal of this paper is to identify the criteria which will be used in industrial practice to select members of a software project team, and to look for relationships between these criteria and project success. Using semi-structured interviews and qualitative methods for data analysis and synthesis, a set of team building criteria was identified from project managers in industry. The findings show that the consistent use of the set of criteria correlated significantly with project success, and the criteria related to human factors present strong correlations with software quality and thereby project success. This knowledge enables decision making for project managers in allocation of right personnel to realize desired level.