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Incentive Design for Agile Teams

Motivated by the ever-increasing prevalence of agile teams, we study a team incentive design problem where multiple agents are located on a network and work on a joint project. The principal seeks the least costly mechanism to incentivize full eﬀorts, by choosing the work assignment sequence and the rewards to the agents upon success. Whereas the agents’ actions are hidden to the principal, they may be observed among the agents given the internal information that is determined by the network and the sequence. We show that under eﬀort complementarity, the transparency of the agents’ actions can reduce their incentive costs. Moreover, the eﬀectiveness of transparency decreases as an action becomes more transparent. In the optimal sequence, the agents work sequentially in the order of ascending individual importance to the project. The agents who move later eﬀectively monitor their preceding peers and have higher incentive costs. When multiple agile teams collaborate, more important agents also move later in their respective teams, while larger teams are allocated toward both ends of the optimal sequence. Meanwhile, only a small fraction of the agents, as compared to the overall agent group, will serve as monitors. For several typical networks, simple algorithms are oﬀered to explicitly characterize the optimal mechanism.