A transit authority awards a multi-package contract - twin tunnels, elevated track, and three stations - on a fixed completion date. Every activity in that schedule is executed by a skilled crew, and crews are scarce: tunnelling gangs, track-laying teams, and signalling specialists are all competing against other megaprojects for the same labour pool. The question that decides the delivery date is not which activities are technically hardest, but which labour-driven activities most reliably move the finish when their crews run short. Tamara, Vose Software's project schedule and cost risk tool, runs the whole network as a Monte-Carlo simulation and plots exactly that.
The criticality-vs-cruciality scatter is the headline. Each activity is placed by how often it sits on the critical path (horizontal) against how strongly its duration correlates with the project finish (vertical). The top-right corner is where to spend labour-securing money. Tunnel boring & excavation dominates - on the critical path in 100% of the 60,000 simulated builds with a cruciality of 0.56, the single strongest driver of the delivery date. Systems & signalling fit-out (100%, 0.43) and track installation (100%, 0.42) follow, then tunnel lining & fit (0.35) and testing & commissioning (0.33). By contrast mobilisation & site setup, though always critical, has a cruciality of just 0.15 - its crew supply barely moves the outcome. Securing tunnelling and track gangs first is worth more than treating every critical activity alike.
Each activity duration is modelled with a Beta-PERT distribution, and six discrete workforce risk events - crew shortages, strikes, turnover, seasonal scarcity - add delay to specific trades. The deterministic plan - every crew at full productivity, no labour event firing - finishes 800 days from the 6 April 2026 start, yet across the simulation that plan holds only 4% of the time. The P50 lands 132 days later and the realistic schedule needs a P80 contingency of 204 days (6.7 months) beyond the published plan.
The stochastic Gantt shows where that uncertainty accumulates. Each bar runs to its activity's P50 finish, with red whiskers spanning P10 to P90. Tunnel boring, track installation, and the systems fit-out carry the widest bands - the same labour-intensive trades the scatter flagged, where crew availability swings the duration most.
The tornado restates the scatter's vertical axis as a ranked bar chart. Tunnel boring & excavation (0.56), systems & signalling fit-out (0.43), and track installation (0.42) top the list - the activities where a swing in crew productivity most reliably moves the delivery date, and where pre-committed crews buy the most certainty.
Schedule risk is cost risk: every day beyond the plan carries extended overhead. Before mitigation the project costs a mean of $162M with a P90 of $175M and a 27% chance of breaching the $168M budget. A labour-securing package - regional skilled-crew recruitment, an automated track-laying machine, pre-committed station crews - shifts the distribution left to a mean of $159M, a P90 of $170M, and cuts the overrun probability to 15%.
The Pareto chart isolates the six workforce risk events and ranks them by expected schedule impact - probability times average delay, in weeks. Tunnelling crew shortage (4.1 weeks) leads, followed by the station crew competition draw (3.0 weeks) and seasonal trades scarcity (3.0 weeks); the top five events carry roughly 80% of the total discrete-risk delay exposure. That ranking is the authority's labour-mitigation priority list.
The combined picture - a single chart that names the crews that set the schedule, a 4% chance of hitting the plan, and a 6.7-month P80 contingency - lets the authority pre-commit critical crews and size labour contingency before the first tunnel-boring machine is launched, rather than discovering the shortage mid-drive.
This article is part of our Tamara case study series. Contact us to discuss how Tamara can quantify schedule and cost risk on your projects.