Uncovering the fragility of large-scale engineering project networks

Abstract

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 the first empirical evidence of the infectious nature of activity deviations, where perturbations in the delivery of a single activity can impact 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.

arXiv comment13 pages, 3 figures, 7 supplementary figures

References in corpus (7)

• Power-law distributions in empirical data
• Error and attack tolerance of complex networks
• Epidemic spreading in scale-free networks
• Epidemic processes in complex networks
• What You Should Know About Megaprojects, and Why: An Overview
• Cost Overruns and Demand Shortfalls in Urban Rail and Other Infrastructure
• Modelling indirect interactions during failure spreading in a project activity network

Cited by in corpus (2)

• Activity delay patterns in project networks
• Emerge of scaling in project schedules