From The Theme
SMART OFFICE WORKFLOWS
What if we could leverage computation and machine learning to optimize team structure?
WHAT WE SET OUT TO DO
We set out to explore a new computationally empowered management practice for teams. We developed a system called “DreamTeam” that experiments with a set of possible team structures and organizational strategies to identify the most effective structures for each specific team.
The system iterates on organizational designs for teams, adapting based on performance feedback, and leveraging computation to continuously propose alternatives and evaluate outcomes. For this project, 135 workers, in teams of 3, engaged in 10 rounds of a set task, each with a time limit of 15 minutes.
WHAT WE FOUND
The DreamTeam teams had substantially different team structures from one another. Despite their differences, the DreamTeam teams signiﬁcantly outperformed all other conditions, by 38%–46% on average per round. This research advances computation as a powerful partner in establishing effective teamwork.
In Search of the Dream Team: Temporally Constrained Multi-Armed Bandits for Identifying Effective Team Structures, Sharon Zhou, Melissa Valentine, Michael S. Bernstein, CHI 2018
PEOPLE BEHIND THE PROJECT
Michael Bernstein is an Assistant Professor of Computer Science at Stanford University. His research focuses on the design of crowdsourcing and social computing systems. This work has received five Best Paper awards and eleven honorable mentions at premier venues in human-computer interaction and social computing. Michael has been recognized as a Robert N. Noyce Family Faculty Scholar, and awarded the George M. Sprowls award, NSF CAREER Award, and Sloan Fellowship.
Sharon Zhou received her PhD in Computer Science from Stanford University in 2017. Dr. Zhou is the 1st Harvard graduate to have majored in Computer Science and the Classics. She worked as a Research Assistant for the Human Computer Interaction Group, led by Dr. Michael Bernstein, from April 2016 – September 2017.