Validating a Tool for Predicting Problem-Specific Optimized Team Characteristics

The performance of a team is highly dependent on how the team is structured, how individuals in the team communicate with one another, and the properties exhibited by the problem being solved. It is generally assumed that teams are a superior approach in problem-solving and design. However, this work shows that for a configuration design problem of moderate size, the optimal approach for a homogenous team is in fact for members of the team to work independently, with the best solution from the individuals chosen at the end. Moreover, this work demonstrates that this surprising strategy can be predicted from knowledge of the problem’s properties through a computationally-derived set of response surfaces. First, a novel design problem is defined that requires solvers to create a system of internet-connected products to maintain the temperature within a home. Next, the characteristics of this new design problem are measured, and a computationally-derived response surface yields the untraditional prediction that teams should not interact while solving the problem. Finally, this prediction is tested and shown correct through a cognitive study. This work makes two contributions to the state of the art. First, it provides verification of a methodology that allows optimal team characteristics to be predicted based on knowledge of a design problem. Second, it demonstrates an additional problem instance for which interacting teams are inferior to nominal teams (adding to a growing literature to that effect).