Monthly Archives: April 2020

Version 3 of SPERT Beta Edition

Yesterday I began working on Version 3 of Statistical PERT (SPERT) Beta Edition. Since all of my spring and summer travel plans have all been scuttled, I thought I’d get started working on Version 3 sooner rather than later.

Since beginning the Beta Edition three years ago, this edition has always been in catch-up mode to the original, Normal Edition (which uses the normal distribution to model uncertainties). And that’s no different with Version 3 of SPERT Beta Edition, with one notable exception.

Like Version 4 of SPERT Normal Edition, I’m going to have a new worksheet that models uncertainties using Monte Carlo simulation (but with the beta distribution instead of the normal distribution). SPERT users can experiment with simulating an uncertainty they’ve modeled using 10,000 trials just by pressing F9.

Unlike Version 4 of SPERT Normal Edition, Version 3 of SPERT Beta Edition won’t have an agile burn-up chart. That chart is well-suited to using the normal distribution, so I don’t see creating a similar burn-up chart in the Beta Edition.

Version 3 of SPERT Beta Edition will get a new feature that’s not in Version 4 of SPERT Normal Edition (yet; this feature will be part of next year’s Version 5 of SPERT Normal Edition). And that is, SPERT Scheduler.

SPERT Scheduler is a feature added on to the existing Mixed Entry worksheet. The Scheduler will allow users to model a plan-driven project’s critical path activities using calendar work days. The specific Excel function is the WORKDAY function, which has been available since Excel 2007.

Using the SPERT Scheduler, a modeler can see how long a project duration will be using different choices for the probabilistic duration estimates for each activity.

The key limitation of this feature is it can only model a project’s critical path, and it can’t address merge bias, which is what a full Monte Carlo simulation would do. But for many people who are simply looking for high-level project estimates based upon sequential activities, this will be a great solution for them.

If you’re interested, you can try-out Version 3 by visiting my GitHub repository, and selecting the Version 3 branch to download the latest iteration of SPERT Beta Edition Version 3. Just be aware that I haven’t fully tested spreadsheets in this branch; they’re still under development!

The April 2020 Webinar on Monte Carlo Simulation

Last week, I held another free webinar on probabilistic estimation. This time, it was on Monte Carlo simulation.

A lot of project managers and businesspeople have heard about Monte Carlo simulation, but not nearly as many people know exactly what it is (and what it isn’t), or how to use it to inform decision-making.

I created this spreadsheet and used it during this month’s webinar. In it, I explain how we can calculate the probability of rolling a “7” using a pair of dice just by simulating the problem.

Now, we know that the probability of getting a “7” is 16.7% (6 possible ways of rolling a “7” divided by 36 total possible outcomes from rolling a pair of dice). But what if we didn’t know how to solve the problem using a math formula? What if creating a math formula was too complicated? What if it were impossible? That’s when Monte Carlo simulation comes into play.

By simulating complex problems thousands of times, we can learn the probabilities of all kinds of possible outcomes. Then, we can use that information to help make decisions about what to do today.

I included some instructions inside the spreadsheet, and I also have an included worksheet that shows how to simulate a single project task, too.

Questions? Feel free to contact me to learn more about Monte Carlo simulation, and check out my future free, monthly webinars. I’ll be doing this particular webinar again probably later in 2020.