Project Controls 360Will the P6 date hold? Schedule risk analysis in Power BI
P6 gives one finish date, as if every duration were certain. A Monte Carlo simulation on a data centre schedule shows the real chance of meeting that date, a realistic P50 and P80 finish, and which activities drive the risk.
0.4%chance of meeting the deterministic P6 date
P50 / P80finish dates for realistic commitments
3-pointduration ranges per activity
Top driversactivities ranked by impact on the finish
The problem
A P6 finish date assumes every activity takes exactly its planned duration. On a real project, durations vary, and on a long driving path those small variations add up.
Management needs to know how likely the date is, what date can be committed to with confidence, and how much contingency is needed. A single deterministic date cannot answer that.
Approach
- Start from the P6 schedule. Activities and logic come from the XER, so the risk model follows the real network.
- Give each activity a range. Optimistic, most likely and pessimistic durations replace the single planned duration.
- Run the schedule thousands of times. A Python Monte Carlo engine samples durations and recalculates CPM in every iteration.
- Show the answer in Power BI. The finish date distribution, P50 and P80 dates, the probability of meeting the P6 date, and a ranking of the activities that drive the risk.
Walkthrough
Result
In the example shown, the P6 finish date had only a 0.4% chance of being met. The P50 and P80 dates gave management realistic dates to commit to, and the risk drivers showed where mitigation would help most.
- Commitments are based on a probability, not a single optimistic date.
- Contingency is sized from the gap between the P6 date and the P80 date.
- Mitigation effort goes to the few activities that drive most of the risk.