Integrated Risk — Estimate Ranging + EV with Monte Carlo

What the full integrated method is

This is the most complete approach in the AACE quantitative-risk family. Earlier methods each used one or two techniques; 123R-22 deliberately brings the major ones together, because real projects carry several kinds of risk at once. Inherent variability (every estimate is uncertain), discrete event risks (specific things that may or may not happen), and their combined effect on a schedule network — this method models all three in a single, internally consistent simulation.

The three layers it combines

• Inherent variability — via estimate ranging — Every cost item and activity duration carries baseline uncertainty. Modeled as ranges/distributions on the inherent values (Lessons 10–11) — the "even if nothing goes wrong, it still varies" layer.
• Discrete risks — via expected value / risk drivers — Specific identified events with a probability and an impact, assigned to the activities they hit (Lessons 9 & 16) — the "if this happens, here's the consequence" layer.
• Combination — via Monte Carlo — Simulate both layers together over the integrated cost-schedule model thousands of times (Lessons 14 & 17), capturing the network, merge bias, and correlation in one run.

The synthesis of the whole track

This lesson is deliberately the last, because it uses nearly everything that came before. Look back at the journey: you learned to identify and assess risk (Module 5A), to size contingency by expected value, ranging, and distributions (Module 5B), to apply parametric models and Monte Carlo (Module 5C), and to integrate cost and schedule (Module 5D). RP 123R-22 weaves those threads into one method.

No single method is always right. The art, as every lesson stressed, is matching rigor to the stakes: a flat percentage or a table for a small job, expected value for a clear risk list, and the full integrated simulation for the major, complex, schedule-sensitive projects where getting contingency right is worth millions.

Using the full method well

Reserve it for the projects that warrant it: large, complex, and schedule-driven. It demands a sound cost-loaded CPM, well-characterized inherent ranges, a disciplined risk register, capable simulation software, and an analyst who understands every layer well enough to keep them distinct. Separate inherent variability from discrete risks cleanly, run the integrated simulation, and present joint cost-and-schedule contingency at a chosen confidence level — with the prioritized risk drivers that tell you where to act.

Ten things to remember

1. 123R-22 combines ranging, expected value, and Monte Carlo.
2. It's the most complete integrated method in the AACE family.
3. Risk has two sources: inherent variability and discrete events.
4. Ranging models inherent variability; expected value the discrete risks.
5. Monte Carlo combines both across the cost-schedule model.
6. One model captures interactions separate analyses would miss.
7. It outputs joint cost-and-schedule contingency at any confidence level.
8. It synthesizes the entire track — from assessment to integration.
9. Match rigor to the stakes — complexity is a cost, not a virtue.
10. Good risk management is judgment about methods, not just mastery.