Easily Estimate Projects Using Statistics and Excel

Use Microsoft Excel's built-in statistical functions, course template files, and your own project knowledge to easily and confidently estimate project durations, work efforts, costs, agile sprints, and agile releases. Use the Unified Scheduling Method to confidently create a dynamic, right-sized project reserve for traditional projects.
Course info
Rating
(73)
Level
Beginner
Updated
Jul 15, 2015
Duration
4h 51m
Table of contents
Easily Estimate Projects Using Statistics and Excel
Foundational Underpinnings of Statistical PERT
Demonstrate Statistical PERT in Excel
The Unified Scheduling Method (USM)
Statistical PERT for Agile Teams
Description
Course info
Rating
(73)
Level
Beginner
Updated
Jul 15, 2015
Duration
4h 51m
Description

How confident are you when you create project schedules and budgets? How confident does your project sponsor want you to be? What would it cost to increase your confidence, or how much less costly would your project be if you accepted more risk? Using Microsoft's built-in statistical functions, you can easily create probabilistic project estimates using just a 3-point estimate (minimum, most likely, maximum) for any uncertain outcome and a subjective opinion about how likely the most likely outcome really is. Using the normal distribution probability curve and Excel's statistical functions, it's easy to see the difference between low risk, high cost, long schedule estimates from high risk, low cost, short schedule estimates. The key concept that this course introduces is called Statistical PERT, which goes well beyond the Program Evaluation and Review Technique (PERT.) Statisitical PERT can be used by both traditional and agile project teams to create project-related estimates. Using additional Excel statistical functions, this course also shows how traditional project teams can use the Unified Scheduling Method to create dynamic, right-sized project reserves for when their Statistical PERT estimates are exceeded during the project execution phase. Confidently create project estimates to fit any tolerance for risk you want using Microsoft Excel, Statistical PERT, and the Unified Scheduling Method!

About the author
About the author

William is an experienced, hands-on IT project manager who is passionate about achieving success and creating positive transformations by bringing new software solutions to life.

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Section Introduction Transcripts
Section Introduction Transcripts

Demonstrate Statistical PERT in Excel
Hello again. This is William Davis, and welcome to module 3 of this course entitled, Easily Estimate Projects Using Statistics and Excel. In module 2, we explored the whole foundation behind statistical PERT and saw how statistical PERT differs from PERT estimation, because with statistical PERT the standard deviation for the normal curve varies with the estimator's subjective judgment about how likely the most likely outcome really is. In this module, we'll start off by taking a quick look at the statistical PERT Excel template to see how we can create probabilistic estimates using a standard deviation value that varies according to the estimator's subjective opinion. After we take that quick peek at statistical PERT, we'll step back to examine this module's objectives. Then later we'll build a statistical PERT model from scratch and examine the SPERT Excel template more closely. So let's dive into Excel and see what the SPERT Excel template looks like.

The Unified Scheduling Method (USM)
Hi, this is William Davis, and welcome to module 4 of Easily Estimate Projects Using Statistics and Excel. In this module, we are going to learn about the Unified Scheduling Method, which is a technique to help project estimators create a dynamic right-sized project reserve for all the times when our SPERT estimates are going to be exceeded by the project team. By calculating a project reserve that is neither too big nor too little, we can avoid having our project go over budget or over schedule, and we can make thoughtful business decisions about the risk trade-off between a low-cost, small project reserve that is more likely to be insufficient, and a high-cost, large project reserve that may cost too much, take too long, and unnecessarily reserve organizational resources. In module 4, here's the ground that we'll cover together. First off, we'll introduce USM by learning about the binomial distribution in a little game called "Obversion". Then, we'll learn about the properties of the binomial distribution and the BINOM. DIST and BINOM. INV functions in Excel 2010 and Excel 2013. Next, we'll execute Project Obversion to understand how the Unified Scheduling Method works to create a project reserve. And finally, we'll examine the free USM template included with this course so you can begin to build project reserves that are perfect for your particular project. So let's begin.

Statistical PERT for Agile Teams
Hi, again, and welcome to the fifth and final module for this course entitled Easily Estimate Projects Using Statistics and Excel. I'm William Davis, and if you watch the preceding four modules, you know that we've covered a lot of ground using Excel's built-in statistical functions to help us estimate project tasks and create a right sized project reserve. In module five, we finish our course discussion by returning to the concepts of Statistical PERT, only this time we'll see how we can apply Statistical PERT within agile project management. Let's examine this module's objectives. As I just mentioned, our discussion starts off by looking at how estimation is done on agile project teams. Then we'll use Statistical PERT to estimate the number of story points an agile team can commit to for a given sprint. By doing this we will set expectations for how many story points the team will, at a minimum, likely completely for a specific confidence level of our choosing. We'll also examine how to use Statistical PERT to do release planning for an agile run project. To do that we'll estimate how many story points a release can finish on its delivery date with a specified confidence level. Let's start off by briefly examining agile project teams and how they estimate agile projects.