| Vose Software

Industry: Construction and Infrastructure
Product: Tamara
Application: Construction schedule risk analysis


The Plan Promised Handover in July 2028. The Simulation Gives That Date a 1% Chance

An 18-storey commercial tower was scheduled with a rolled-up critical path of 865 working days — a clean July 2028 handover the developer took to its anchor tenant and its lender. The schedule was built the orthodox way: most-likely durations for each of eleven activities, chained through the network, read off the end date. The number was not wrong on its own terms. It was simply the answer to a question nobody should ask of a project schedule — what happens if every activity lands exactly on its most-likely duration and nothing goes wrong?

Rebuild the same network in Tamara, Vose Software's Monte Carlo project risk tool, with each activity carrying a Beta-PERT duration and six discrete risk events layered on top, and the deterministic date dissolves into a distribution: P50 December 2028, P90 April 2029, and a probability of finishing by the published July 2028 plan of just 1%. The S-curve below is the whole argument — the deterministic plan sits at the very foot of the curve, in the regime a project commits to only if it intends to re-forecast every quarter.

Stochastic S-curve of project completion date versus the deterministic plan

The gap between the July 2028 plan and the P80 finish is 232 days — roughly 7.6 months. That gap is not pessimism; it is the project's true schedule contingency, and it was invisible to the deterministic roll-up.

Why a single critical-path date fails

A bar-chart critical path adds most-likely durations along one assumed-longest chain. Two things break it. First, durations are right-skewed — an activity can finish a little early but can overrun a lot, so the mean finish sits later than the most-likely roll-up and the mean simulated finish is 1,029 days against the 865-day plan. Second, with parallel chains (envelope, MEP rough-in and core all run off the structural frame), whichever chain happens to be longest in a given iteration drives the finish — so the project inherits the worst of several paths, not the average of one. The deterministic method sees neither effect.

Where the duration risk actually lives

Tamara reports each activity twice: its criticality index (how often it lands on the critical path) and its cruciality (the rank-correlation between its duration and the project finish — i.e. how much its variability actually moves the end date).

Schedule tornado ranking activities by correlation with the finish date

Interior fit-out dominates (cruciality 0.56), followed by the structural frame (0.51) and permits & mobilisation (0.38). This is the action list: the finishing chain (interior fit-out → MEP commissioning → inspections → handover) is on the critical path in essentially 100% of iterations, so the highest-leverage week of risk reduction is buying duration certainty on fit-out and the frame — not on whichever task the team happens to find easiest to compress.

The same simulation places every activity in time as a band, not a bar:

Stochastic Gantt showing each activity P50 bar with P10 to P90 finish spread

The whiskers widen downstream because uncertainty compounds along the chain: each activity inherits the spread of everything it waits on, so handover carries the accumulated variability of all ten activities before it.

The discrete risks that drive the tail

Beyond continuous duration uncertainty, six discrete events were modelled as Bernoulli risks — each may or may not occur, but if it does it adds delay (and cost). Ranking them by expected schedule impact (probability × delay) gives a clean Pareto:

Pareto of discrete risk events by expected schedule impact

Five of the six events carry ~80% of the expected discrete-event delay — severe-weather lost days (3.4 weeks expected), skilled-labour shortage (2.9), permit delay (2.6), structural-steel supply delay (2.5) and a major design change (2.2). Once the ranking is visible, the risk-response budget writes itself.

Schedule risk is cost risk

Every day beyond the deterministic plan carries extended general-conditions and escalation overhead, so the schedule distribution drives the cost distribution. Tamara let the team price two mitigations together — weather protection plus an early structural-steel supply contract, and a fit-out labour pre-commitment — and compare before/after on the same axis:

Project cost distribution before and after mitigation against the budget

Without mitigation the cost distribution runs to a mean of $99M and a P90 of $108M, with a 20% probability of breaching the $105M budget. The $2M mitigation package cuts the P80 finish by 66 days (1,097 → 1,031 days), and because schedule drives cost, the overrun probability falls from 20% to 7% — the mitigation pays for itself several times over in avoided overhead, not in the line items it touches directly.

What Tamara changed

  • The external commitment moved from the deterministic July 2028 date to a risk-informed P80, ending the rolling-promise cycle with the tenant and lender before it started.
  • A 7.6-month schedule contingency was quantified and funded, rather than discovered one slipped milestone at a time.
  • Risk-reduction effort was redirected to fit-out and the structural frame — the two highest-cruciality activities — instead of being spread evenly across the bar chart.
  • A $2M mitigation package was approved on its tail-clipping effect, cutting budget-overrun probability from 20% to 7%.

Tamara Functionality Used

  • Monte Carlo schedule simulation over the full activity network, with Beta-PERT durations and parallel-path logic.
  • Discrete risk-event modelling (Bernoulli occurrence × Triangular impact) layered onto task durations and costs.
  • Criticality and cruciality analysis distinguishing how often a task is critical from how much its variability moves the finish date.
  • Stochastic Gantt and cumulative S-curve for communicating schedule uncertainty to non-technical stakeholders.
  • Integrated cost–schedule modelling linking finish-date overruns to extended-overhead cost, so mitigations are priced on their joint effect.
  • Scenario comparison quantifying a mitigation package's before/after impact on both the P80 finish and the budget-overrun probability.

A construction schedule is not a date; it is a distribution with a body the team can plan against and a tail it cannot afford to ignore. Tamara is what turns "when will it finish?" into a probability the developer, the tenant and the lender can all sign.