  Resolving major societal challenges, such as stagnated economic growth or
wasted resources, heavily relies on successful project delivery. However,
projects are notoriously hard to deliver successfully, partly due to their
interconnected nature which makes them prone to cascading failures. We deploy a
model of cascading failure to temporal network data obtained from an
engineering project, where tasks constituting the entire project and
inter-dependencies between tasks correspond to time-stamped nodes and edges,
respectively. We numerically evaluate the performance of six strategies to
mitigate cascading failures. It is assumed that increased time between a pair
of inter-connected tasks acts as a buffer, preventing a failure to propagate
from one task to another. We show that, in a majority of cases that we
explored, temporal properties of the activities (i.e., start and end date of
each task in the project) are more relevant than their structural properties
(i.e., out-degree and the size of the out-component of the task) to preventing
large-scale cascading failures. Our results suggest potential importance of
changing timings of tasks, apart from the static structure of the same network
of tasks, for containing project failure.
