FAQs

Statistical PERT is free so you will try using it

Project managers and product owners need better ways of estimating so they can quickly align the expectations of their stakeholders. Product owners and agile teams need simple, effective ways to forecast when new features and capabilities will be available, while project managers estimate project duration and cost.  Executives need better estimates so they can make better decisions today to secure better outcomes tomorrow.  Everyone needs an easier way to communicate their sense of confidence and risk about future uncertainties.

Statistical PERT® is a simple, powerful way to do all of that.

Everything about this site is intended to break down barriers to a better way of estimating.  That’s why all SPERT® spreadsheets and templates are licensed using the GNU General Public License (GPL), so you can freely download, use, modify and share everything on this site.  That’s why Statistical PERT uses Excel’s built-in statistical functions (so you don’t have to buy anything extra).  That’s why this site doesn’t require you to register before downloading, and why this site uses a secured, encrypted connection.

So how do you make money off this?

I don’t make any money off this. Statistical PERT is my gift to project managers, product owners, agile teams, and anyone else who needs to create probabilistic estimates. Statistical PERT is for anyone who needs to quickly align expectations and make better decisions today to secure better outcomes tomorrow. You’re welcome. 🙂 If you choose to watch my Pluralsight course, Easily Estimate Projects and Products, that will help defray the cost of running this website. I also accept Paypal donations, too. But you’re under no obligation to watch any video or make a donation. Statistical PERT is freely licensed under the GNU General Public License.

If you’re looking for a catch, you can stop looking. There is no catch.

Statistical PERT uses the normal because it’s good enough

PERT uses a special form of the beta distribution but Statistical PERT (SPERT®) Normal Edition uses the normal distribution because, for many estimation problems, using the normal distribution is good enough to make a good decision.

As long as the bell-shaped curve is only slightly or moderately skewed, Statistical PERT using Excel’s normal distribution functions will still yield results that are comparable to a Monte Carlo simulation of the same uncertainty modeled using the beta distribution.  Visit this blog post to learn more.

The key benefit of using the normal distribution is that Excel’s two normal functions, NORM.DIST and NORM.INV, are both useful and very easy to use.  PERT provides an estimate for the mean argument, and Statistical PERT creates the required standard deviation needed by those two Excel functions.

The goal of any estimation effort should be to develop an estimate that is good enough to make a good decision, and that is accurate enough to be within the estimator’s tolerance for error.  While using the beta distribution may be more accurate than using the normal distribution for modeling asymmetrical uncertainties, that fact alone is not a good reason to discard using the normal distribution.  For many estimation problems–even involving asymmetrical uncertainties–using the normal distribution leads to a “good enough” estimate that is within the estimator’s tolerance for error.

That said, on March 1, 2017, a new edition of Statistical PERT was released that uses Excel’s two beta functions, BETA.DIST and BETA.INV.  The Statistical PERT Beta Edition will accurately model skewed probabilities using the beta distribution’s two shape arguments, alpha and beta.

Statistical PERT uses a different formula than PERT does to find a standard deviation.  Why?

Statistical PERT replaces the PERT formula with a different formula that lets the estimator use subjective judgment, intuition, emotion, and/or private knowledge to rationally adjust the standard deviation.  The SPERT standard deviation formula is:  (Max – Min) * RSM, where RSM is the Ratio Scale Modifier that corresponds to the estimator’s subjective judgment about how likely is the most likely outcome.  The SPERT SD formula better conforms the implied distribution curve to a specific uncertainty.  You can learn more about this here.

Watch a Pluralsight course to learn more

You can learn more about Statistical PERT® by doing any of the following: