Engineering projects are notoriously hard to complete on-time, with project delays often theorised to propagate across interdependent activities. Here, we use a novel dataset consisting of activity networks from 14 diverse, large-scale engineering projects to uncover network properties that impact timely project completion. We provide empirical evidence of perturbation cascades, where perturbations in the delivery of a single activity can impact the delivery of up to 4 activities downstream, leading to large perturbation cascades. We further show that perturbation clustering significantly affects project overall delays. Finally, we find that poorly performing projects have their highest perturbations in high reach nodes, which can lead to largest cascades, while well performing projects have perturbations in low reach nodes, resulting in localised cascades. Altogether, these findings pave the way for a network-science framework that can materially enhance the delivery of large-scale engineering projects.

众所周知，工程项目很难按时完成，项目延误通常会在相互依赖的活动中传播。在这里，我们使用由来自 14 个不同的大型工程项目的活动网络组成的新数据集来揭示影响项目及时完成的​​网络属性。我们提供了扰动级联的经验证据，其中单个活动的交付中的扰动会影响下游多达 4 个活动的交付，从而导致大的扰动级联。我们进一步表明，扰动聚类显着影响项目的整体延迟。最后，我们发现表现不佳的项目在高可达节点有最大的扰动，这可能导致最大的级联，而性能良好的项目在低可达节点有扰动，导致局部级联。总而言之，这些发现为网络科学框架铺平了道路，该框架可以实质性地增强大型工程项目的交付。