Understanding Monte Carlo Schedule AnalysisProbabilistic project scheduling
What is Monte Carlo?
Monte Carlo Schedule Analysis is a technique that uses random sampling to estimate project completion dates. Instead of single-point estimates, it simulates thousands of possible outcomes based on task uncertainty ranges (optimistic, most likely, pessimistic), providing probability distributions for completion dates.
Why It Matters
Monte Carlo matters because: 1) Realistic estimates - accounts for uncertainty, 2) Probability insights - know likelihood of meeting deadlines, 3) Risk identification - reveals high-impact uncertainties, 4) Better planning - confidence intervals for planning, 5) Stakeholder confidence - data-driven commitment dates.
Tasks
5Best Case
33 daysExpected (PERT)
55.3 daysWorst Case
87 daysHigher iterations = more accuracy, slower results
Project Tasks
| Task | Optimistic | Most Likely | Pessimistic | Distribution | PERT | Actions |
|---|---|---|---|---|---|---|
| 5.2 | ||||||
| 8.5 | ||||||
| 25.8 | ||||||
| 12.7 | ||||||
| 3.2 |