Industry: Construction and Infrastructure Product: ModelRisk Application: Managing Material Shortages in Large-Scale Infrastructure Projects
On a $600M urban-transit project, the procurement schedule shows every critical material — structural steel, precast segments, rebar, bearings, rail, signalling — arriving exactly on its need date. That schedule is built on median lead times. Run the same lead times as distributions, with the supply-disruption probabilities the last few years have taught every contractor to respect, and the picture inverts: there is a 96% probability that at least one critical material slips more than four weeks, and the resulting schedule-delay cost has a mean of $2.7M and a P90 of $5.0M. The deterministic plan shows zero shortage risk because it was built on the one number — the median — that hides it.
Material-shortage risk is not really about any single material. It is about the fact that a 30-month programme touches seven independent supply chains, each with its own lead-time distribution and disruption probability, and the project only needs one of them to fail at the wrong moment.
Each material is exposed during the quarter it is needed — and the materials are needed in sequence, so the shortage risk migrates across the programme:
Early quarters are dominated by rebar and cement risk; the structural-steel and precast windows peak around quarters 3–4; bearings and rail in the middle; signalling and E&M — the longest-lead, most disruption-prone class — owns the final quarters with a 56% shortage probability at its need date. No single quarter is quiet. A procurement team watching a deterministic Gantt sees none of this, because every bar lands on its planned date by construction.
The deterministic schedule assigns the project a zero-dollar shortage contingency, because at median lead times nothing is late. The simulation prices the real exposure:
The mean shortage-delay cost is $2.7M, the P90 is $5.0M, and there is roughly an 8% chance the delay cost exceeds $6M. None of this is in the base budget. The distinction the chart forces is between "the plan shows no late deliveries" and "the plan has a one-in-eleven chance of a $6M shortage bill" — and only the second is a number a project director can reserve against.
Every critical class carries three uncertainties:
Buffer stock, dual sourcing and pre-arranged expediting are a continuous lever. Sweeping the resilience budget and reading off the probability of avoiding any critical shortage turns the procurement question into an investment decision:
At zero resilience spend, the probability that no class slips more than two weeks is low — seven supply chains make a clean run unlikely. The first ~$3M of spend (buffer stock on the long-lead items plus dual sourcing on the two most disruption-prone classes) moves the probability sharply; beyond that the curve flattens, because the residual risk is irreducible lead-time variability that no buffer fully removes. The 90% target is reachable on the "no slip > 2 weeks" criterion but expensive on the stricter "no slip at all" criterion — which is itself the finding: chasing zero shortage is not worth it; capping shortages at two weeks is.
The P90 cost is dominated by the signalling / E&M lead-time tail and the precast-segment disruption probability — the two longest-lead, highest-consequence classes. Commodity materials (cement, rebar) barely move the answer despite being ordered in the largest quantities. This redirects the procurement team away from the high-volume commodities they instinctively manage and toward the two engineered classes that actually own the tail.
The decision is which sourcing posture to adopt. Comparing single-source JIT against dual-sourcing and a strategic-buffer-plus-dual approach — each with its own up-front premium — on total cost (premium + shortage delay):
Single-source JIT carries no premium but the fattest tail. Dual-sourcing the key items costs ~$1.8M up front and pulls the P95 in materially. The strategic-buffer-plus-dual posture costs ~$3.4M but compresses the tail the most. For a project whose contract carries liquidated damages on the opening date, the right posture is the one whose tail — not whose mean — sits inside the owner's risk appetite, and the CDF crossing is exactly where that trade-off becomes visible.
A material-shortage plan built on median lead times is a prediction that nothing in seven supply chains will go wrong over thirty months. Monte Carlo simulation in ModelRisk replaces that prediction with a distribution — turning "we have no shortage risk" into "we have a 96% chance of at least one slip and a P90 bill of $5M; here is the $1.8M of dual-sourcing that halves the tail."