Schedule Risk Analysis, screening grade
A Monte Carlo simulation of your Primavera P6 network, in the browser. It answers one question honestly: how much confidence does your deterministic finish date actually deserve, and which activities drive the risk?
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1 · Load & validate
Before simulating, the engine reproduces your deterministic schedule and checks it against the XER’s own dates. A simulation on an engine that can’t match the plan is noise.
2 · Ranges & settings
Review grid, every incomplete activity and the range it will simulate with
A profile is a small JSON file holding your risk assumptions, distribution, iterations and seed, and any per-activity range overrides, but not the schedule itself. Export to save your setup, share it for review, or reproduce the exact same result later (the seed is stored). Import a saved profile to reapply it to this or another schedule. Nothing is uploaded, the file stays on your device.
3 · Results
What am I looking at? (S-curve & P-values)
The S-curve is the cumulative probability of finishing by each date. P80 means an 80% chance of finishing on or before that date. Your deterministic plan date usually lands low (often ~P20–P40) because of merge bias: where two paths join, the later one wins, so parallel risk only ever pushes the date out, never in.
Bar colour key: bars are ranked biggest-driver first. Blue bars are positive, green bars are negative. Criticality is always positive (a % of iterations on the critical path), so those bars are always blue. For sensitivity, a positive (blue) value means the activity drives the finish the expected way — a longer activity pushes the finish later; a negative (green) value correlates the other way — a longer activity nudges the finish slightly earlier, which typically shows up on non-driving parallel paths and is usually statistical noise rather than a real risk driver.
Criticality vs cruciality?
Criticality index = how often an activity sits on the critical path across iterations. Sensitivity/cruciality = how strongly an activity’s sampled duration correlates with the finish date. High criticality + high sensitivity = a true risk driver.