A Generalized Framework for Algorithm Based Team Formation

Teams must be formed for all kinds of projects and purposes. Team formation is a key activity for innovation, entrepreneurship, class projects, and industry initiatives. Our experience with entrepreneurship and innovation has shown that a project's results are highly dependent on the quality of team formation. In real life situations, team building is also time consuming. In this work we are developing a method and approach to form teams using algorithms. To do this, we develop a taxonomy for how teams are formed. We consider the key factors for team formation, identify measures for team effectiveness, as well as synthesize the framework with natural team formation processes. More importantly, we are proposing a generalized framework for algorithm based team formation. We provide sample algorithms with this framework to demonstrate its use in practical situations. The work of this paper also informs future characterization of the models developed here, which includes trade-offs for factors including optimality of team effectiveness, computation time, and policy considerations.