Monte Carlo simulation for project schedule risk
Move from a single target date to a confidence-based view of delivery risk using repeated simulations of uncertain activity durations.
A connected workflow, not another isolated file
Pocket PMO keeps project management techniques close to the rest of the project record so decisions can be based on consistent data.
- Show date confidence ranges instead of one fragile forecast
- Explain schedule risk in terms stakeholders understand
- Use simulation output to guide contingency conversations
How teams use it
- Step 1
Model uncertainty in activity or phase durations.
- Step 2
Run simulations to estimate likely delivery outcomes.
- Step 3
Use the confidence range to set dates and manage risk.
Frequently asked questions
What does Monte Carlo simulation show in project management?
It shows a range of possible project outcomes by repeatedly simulating uncertain inputs, helping teams understand the likelihood of meeting dates or budgets.
Is Monte Carlo only for large projects?
No. It is useful whenever schedule uncertainty is meaningful enough that a single estimate would mislead stakeholders.
How many simulation runs are enough?
Run counts in the thousands give stable percentile results for typical project networks. What matters more is the quality of the duration distributions: calibrated three-point estimates and honest dependencies between activities will move confidence ranges far more than adding another thousand trials.
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See it in Pocket PMO
Pocket PMO keeps project management techniques close to the rest of the project record so decisions can be based on consistent data.