Too Many Meetings? Scheduling Rules for Team Coordination

• 成果类型: Article
• 署名作者: Roels, Guillaume; Corbett, Charles J.
• 署名单位: INSEAD Business School; University of California System; University of California Los Angeles
• 刊物名称: MANAGEMENT SCIENCE
• ISSN/ISSBN: 0025-1909
• DOI: 10.1287/mnsc.2021.03227
• 发表日期: 2025
• 关键词: collaboration and coordination models; game theory; teams and group decisions; new product design and development

摘要

Workers in knowledge-intensive industries often complain of having too many meetings, but organizations still give little thought to deciding when or how often to meet. We investigate the efficiency and robustness of various coordination scheduling rules. We consider workers who are engaged in a common activity (e.g., software programming) that can be divided into largely independent, parallel production tasks, but that necessitates periodic coordination. Coordination enables workers to address issues they have encountered in their independent work but takes time away from production. Using a stylized game-theoretic model, we show that small teams allow a more fluid, that is, worker-driven, approach to scheduling coordination, such as preemptive coordination (or production), under which any worker can impose coordination (or production). In larger teams this becomes inefficient. Several approaches can mitigate this effect. One option is to allocate the decision rights to produce or coordinate to the most productive worker. A more general version is to implement a voting-based scheme, where a minimum number of workers from a predetermined subset choose to coordinate. A third approach is to modify the preemptive coordination and production rules by adding time-based controls, to reserve some minimal amount of productive time or to enforce coordination after some point. Finally, a fixed-interval meeting schedule works well for very large teams. Our research helps formalize the tension between meeting (coordinating) and producing and indicates how to adapt team coordination scheduling rules to the degree of worker heterogeneity and team size.