Quick Look at the PMBOK® Guide: Monte Carlo Analysis

6PMBokQL-MonteCarloIn this blog series, we’ll get you up to speed on using the key tools listed in A Guide to the Project Management Body of Knowledge, (PMBOK® Guide) – Fifth Edition, including Monte Carlo Analysis.

The Monte Carlo analysis is a true risk analysis tool. As such it is a nontrivial process that requires training. However, if you are a risk project manager, then a deep understanding of the Monte Carlo analysis might be in order. Essentially, the Monte Carlo analysis lets the project manager run the ‘what if’ scenario in as many different permutations and combinations as desired. On a risky project, this gives the project manager an idea of where the project may end in terms of timeline, budget, or other imposed project constraint.

A tabular version of the Monte Carlo is shown below, however, this can also be shown as an ‘S’ curve if so desired:


With the example above, the Monte Carlo percentages are compared with the PERT numbers. You’ll notice that in areas where the pessimistic estimate is high, the Monte Carlo and the PERT percentages are significantly different.

For example, with component 3 the pessimistic estimate is 65 days. The PERT estimate is 27.2 days while the Monte Carlo percentage for that estimate is less than 30% as a confidence factor. Notice that when the Monte Carlo analysis is 50% the likelihood of hitting that percentage is 39.1 days.

This is an excerpt from the Global Knowledge white paper, Are All Those Project Management Tools Really Needed?

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