Category Archives: Monte Carlo simulation

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.

SPERT and the Excel Histogram chart

Since releasing Version 4 of the Statistical PERT® Normal Edition this past January, I’ve had a few people contact me saying that they couldn’t use the new Monte Carlo simulation tab that I’ve included in that release.

After doing some investigation, I now think I know what the problem is. The Monte Carlo simulation worksheet in V4 uses Excel’s “Histogram chart” to visually depict the 10,000 trials of the simulation. However, Microsoft only introduced the histogram chart in Excel 2016. Excel 2010 and Excel 2013 don’t have this chart, so users of these older versions of Excel see an error message where the histogram is supposed to be.

If you’re using either Excel 2010 or Excel 2013, you can manually create the histogram chart yourself by Googling “histogram chart Excel 2013” and you’ll see results that explain a manual process for creating a histogram chart. Here are some of the result links I found:

Of course, you can always save yourself the trouble of manually creating a histogram chart by upgrading to the latest release of Excel.

BTW, Microsoft’s lifecycle support for Excel 2010 ends October 2020.

Version 2.1 of SPERT® Beta Edition Released

Yesterday I released a minor update to Version 2 of the Statistical PERT® Beta Edition. This minor release improves some formatting of the Vlookup tab so it uses the same, yellow-shading + blue text format for cells eligible for end-user inputs.

I also added another feature that was included in Version 4 of Statistical PERT® Normal Edition: “Click for help” buttons. On all interactive worksheets, there is a prominent, orange “Click to call” button to make it easy for anyone who wants free, email support to get it. The button links to my site’s “Contact Me” page where they can fill-in their name, email account, and question/issue.

This summer I’ll be working on Version 3 of SPERT® Beta Edition. Version 3 will include the same feature set as what the SPERT® Normal Edition has with its Version 4 release. That is, it will include the ability to use a specified standard deviation, it’ll have a Monte Carlo simulation worksheet, and have up to three scenarios on the Agile Forecast tab.

If you want to be notified whenever I release new versions of Statistical PERT, I’ve got a new way to do that: add yourself to my new email newsletter. Once a month, I’ll send a short newsletter offering a tip or trick for how to use Statistical PERT, plus I’ll send out notifications whenever I release new versions of these spreadsheets.

SPERT Normal Edition Version 4 Released!

Today I released a new version of Statistical PERT® Normal Edition! Version 4 of SPERT Normal Edition adds these new/enhanced features:

  • New Monte Carlo simulation tab for simulating 10,000 trials of a single, random variable
  • New Agile Burnup chart for creating an agile release forecast
  • More subjective judgment options (10) to choose from when determining how likely the most likely outcome really is
  • Revised ratio scale modifiers for use with the SPERT Standard Deviation formula
  • Enhanced agile forecast tab
  • Added a way to use your own, explicit standard deviation, which is especially useful if you have historical data
  • Minor formatting enhancements
  • A one-click way to ask for help using my free support service

Version 4 is currently available on the Statistical PERT download page, or you can download Version 4 from GitHub, too.

Palisade Risk Conference 2016

palisade-risk-conference-2016

I’ll be heading to New Orleans for the first time in my life in a few weeks.  The Palisade Risk Conference 2016 is being held on November 1 & 2, 2016.  I have used Palisade’s DecisionTools Suite since my first year in graduate school (in the MSPM program at George Washington University) back in 2010.  I love the power and utility of @Risk, the Excel add-in program for doing Monte Carlo simulations.  @Risk has helped me create Statistical PERT because I use @Risk simulations to compare against and validate my Statistical PERT approach and results.  Without @Risk, there would be no Statistical PERT.

I liken Statistical PERT to a screwdriver:  simple, easy-to-use, solves a lot of problems, inexpensive (Statistical PERT is free, actually).  By contrast, @Risk is complex, not-as-easy-to-use (but still easy for rudimentary modeling), solves a whole lot more problems, but is expensive.  Whereas everyone has a screwdriver in their junk drawer or garage, not everyone has, say, a miter saw or some other, expensive power tool.

If you’re planning attending the Risk Conference in New Orleans, hit me up!