Determining Schedule Margin with Monte Carlo Simulation

Constructing a credible Integrated Master Schedule (IMS) requires placing sufficient schedule margins at specific locations to protect key deliverables. One approach to determining this margin is using a Monte Carlo simulation tool.

This probabilistic margin analysis starts by constructing a "best estimated" Integrated Master Schedule, with the work activities arranged in the best path network.

While some activities may have "slack," the Critical Path exists through this network for each Key Deliverable. This network of activities must show how each deliverable will arrive on or before the contractual need date. This "best path network is the Deterministic Schedule, which has fixed activity durations.

By assigning a duration variance for each class of work activity, the Monte Carlo model shows at what confidence level the probabilistic delivery date occurs on or before the deterministic date. The Monte Carlo simulation can then derive the needed schedule margin for each deliverable. This activity network is called the Probabilistic Schedule, which has activity durations of random variables.

With the schedule margin inserted in front of each deliverable, the Deterministic schedule becomes the basis of the Probabilistic schedule. Next is a cycle of adjusting the Deterministic schedule to ensure the needed margin produces the final baselined Deterministic schedule to be placed on baseline. As the program proceeds, this schedule margin is managed through a "margin burn down" process. "Assessing the sufficiency of this margin for the remaining work is then part of the monthly program performance report.

Here's an excerpt from an upcoming workshop on building and executing a credible Performance Measurement Baseline based on the Wright Brother's work. We need several things:

• The work to be performed can be a network of activities in a schedule or a collection of activities in a sprint. In both cases, we must approximate the time to accomplish the work. This means estimating the most likely duration or work effort to produce the needed outcomes.
• This Most Likely value can come from many sources. But it does need to be the Most Likely, not the average, not some made-up number, not some cockamamie guess

Here's how there's a Monte Carlo tool for determining the likelihood of completing on or before a given date when there is a schedule of the work with Most Likelies for the work durations and the variances in those durations