Teams are building blocks of organizations and essential inputs of organizational success. This article studies a data-driven analytical approach that exploits the rich data accumulated in organizations in the digital era to design teams, including prescribing team composition and formation decisions. We propose to evaluate a team regarding its performance and temporal stability, referred to as (SE). Our approach estimates the team's performance and stability using models. It then optimizes an integrated objective of the team's performance and stability through mixed-integer programming models formulated according to predictive models. Consequently, this approach mines meaningful team compositions from historical data and guides strategic team formation accordingly. We conduct empirical studies using authentic data from our partner company in the real estate brokerage industry. The findings reveal that teams that adhere to our model's recommendations achieve an average percentage improvement of 153.1% to 156.5% higher than the benchmark teams, particularly when recruiting one or two members in their actual SE during the post-formation period. We further disclose the mechanism underlying this improvement from the perspective of changes in team compositions. Our study provides a decision support tool for team design and ensuing team dynamic management.

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可持续有效性的战略团队设计：数据驱动的分析视角及其影响

团队是组织的基石，也是组织成功的重要投入。本文研究了一种数据驱动的分析方法，该方法利用数字时代组织中积累的丰富数据来设计团队，包括规定团队组成和组建决策。我们建议评估团队的绩效和时间稳定性，称为（SE）。我们的方法使用模型来评估团队的绩效和稳定性。然后，它通过根据预测模型制定的混合整数规划模型来优化团队绩效和稳定性的综合目标。因此，这种方法从历史数据中挖掘有意义的团队组成，并相应地指导战略团队的形成。我们使用房地产经纪行业合作伙伴公司的真实数据进行实证研究。研究结果表明，遵循我们模型建议的团队比基准团队的平均进步百分比高出 153.1% 至 156.5%，特别是在组建后期间在实际 SE 中招募一到两名成员时。我们从团队构成变化的角度进一步揭示了这种改进背后的机制。我们的研究为团队设计和随后的团队动态管理提供了决策支持工具。