What You Get
- Set a seed and the same model gives the same result
- Full history: date, iterations, runtime, author
- Restore, export (workbook / PDF) and share by role
Decisions / Runs and Reproducibility
Run History and Reproducibility
Every run is kept with its iterations, runtime and author. Set a seed and the same model gives the same result. Restore a run to the editor, export it and share it by role. Compare runs to see what changed and why.
Decisions / Runs and Reproducibility
Every Run, on the Record.
Each run is captured with its iterations, runtime and author. Set a seed and the same model gives the same result. Reopen the history, restore any run to the editor, export a workbook or PDF, and share by role. Below is a working preview with sample data.
Run Details
Run 5
Baseline with accelerated long-lead procurement — testing the weather-window sensitivity before board review.
Activities: 28Risks: 15Cost: 1
Run History4 runs
11 Jul, 23:29 · 14 risks · 1,000 iter
RISKS (14)
RSK-0032Supplier / vendor delivery delay
RSK-0033Scope change or late requirement
RSK-0034Design change and rework
RSK-0035Regulatory / permit approval delay
RSK-0036Resource availability shortfall
RSK-0037Third-party dependency slippage
RSK-0038Adverse weather / seasonal disruption
RSK-0039Commodity price escalation
RSK-0040Subcontractor performance shortfall
RSK-0041System integration / interface issue
RSK-0042Quality defect requiring rework
RSK-0043Stakeholder approval delay
RSK-0044Site access constraint
RSK-0045Testing & commissioning overrun
NOTES
Full register — 14 discrete + calendar risks against the accelerated schedule.
20 May, 11:33 · 9 risks · 100,000 iter
20 May, 11:14 · 6 risks · 10,000 iter
19 May, 23:15 · 4 risks · 1,000 iter
Compare
Put Every Run Side by Side.
Overlay each run's S-curve, read the statistics, and see how the drivers shift run-to-run — the same four runs from the history above.
Cumulative distribution
Statistics 4 runs · schedule
| RUN | ITER | DET | MEAN | Σ | P10 | P50 | P80 | P90 | RANGE |
|---|---|---|---|---|---|---|---|---|---|
| Run 1 | 1,000 | 30 Dec 21 | 17 Jan 22 | 8.4d | 5 Jan 22 | 15 Jan 22 | 28 Jan 22 | 5 Feb 22 | 30 Dec 21 – 20 Feb 22 |
| Run 2 | 10,000 | 30 Dec 21 | 23 Jan 22 | 10.6d | 8 Jan 22 | 20 Jan 22 | 5 Feb 22 | 14 Feb 22 | 30 Dec 21 – 5 Mar 22 |
| Run 3 | 100,000 | 30 Dec 21 | 30 Jan 22 | 13.1d | 11 Jan 22 | 26 Jan 22 | 14 Feb 22 | 24 Feb 22 | 30 Dec 21 – 20 Mar 22 |
| Run 4ACTIVE | 1,000 | 30 Dec 21 | 6 Feb 22 | 15.8d | 15 Jan 22 | 2 Feb 22 | 24 Feb 22 | 8 Mar 22 | 30 Dec 21 – 10 Apr 22 |
| Deterministic (CPM) | — | 30 Dec 21 | — | ||||||
See It on Your Own Project.
Start your Demo and run your first Monte Carlo analysis on your own schedule, or talk to sales and we will take you through it on a sample project. No card needed.
Talk to Sales