Uncovering the fragility of large-scale engineering project networks

TL;DR

This paper empirically investigates how activity deviations in large-scale engineering project networks propagate, revealing that perturbations can cascade significantly, affecting project delays and performance.

Contribution

It provides the first empirical evidence of activity deviation contagion and links network properties to project delay outcomes, introducing a network-science framework for project management.

Findings

Perturbations can impact up to 4 downstream activities.

Perturbation clustering influences overall project delays.

High reach nodes are critical in poorly performing projects.

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.