Organizing knowledge workforce for specified iterative software development tasks

Organizing knowledge workers for specific tasks in a software development process is critical for the success of software projects. Assigning workforce in software projects represents a dynamic and complex problem that concerns the utilization of cross-trained knowledge workers who possess different productivities and error tendencies in coding and defect correction. This complexity is further compounded when the development process follows a software release life cycle and involves major releases of alpha, beta, and final versions in the context of iterative software development. We study this knowledge workforce problem from three essential project management perspectives: (1) timeliness - obtaining shortest development time; (2) effectiveness - satisfying budget constraint; and (3) efficiency - achieving high workforce utilization. We explore ideal workforce composites with two strategic focuses on productivity and quality and with different scenarios of workload ratios. An analytical model is formulated and a meta-heuristic approach based on particle swarm optimization is used to derive solutions in a simulation experiment. Our findings suggest that forming an ideal workforce composite is a non-trivial task and task assignments with divergent focuses for software projects under different workload scenarios require different planning strategies. Practical implications are drawn from our findings to provide insight on effectively planning workforce for software projects with specific goals and considerations.