Let us conduct a psychological experiment. Which formula do you think will yield a more precise and accurate result:
I guarantee that the majority of the readers will select the second formula as the one that would provide the best result. Unfortunately nothing can be further from the truth because any formula is as good as the data going into it. Some of you may have heard the following expression used by statisticians:
Garbage in, garbage out
It basically means that, no matter how complicated the formula is, if you “infuse” it with inaccurate data, the model will produce an inaccurate answer. Having said that take a closer look at the formulas above: the first model only has two ingredients, while the second one has multiple variables. Hence with a larger number of variables we end up with more room for estimation errors.
Why did I start this article with such a strange example? I have recently taught a project portfolio management course in London, UK and the following conversation took place between a Portfolio Manager of a large utility company and your humble servant:
PM: Oh, our executives will never sign up for PPM. We tried it before and it didn’t work
Me: Why didn’t it work?
PM: Well take a look here … (proceeds to show me a very complicated spreadsheet that incorporates not one, not two, but three scoring models for different types of projects at the same company. In order to assess the project proposal one has to answer several dozen questions by selecting appropriate choices from the dropdown menus. Once the choices are made, the spreadsheet “tells” you which scoring model to use. The models are also far from simple; close to a dozen scoring categories with five different potential scores for each variable …)
Me: So, did you use that model?
PM: Yes, we tried. We had about ten executives in the room with approximately 100 project proposals to assess. After two hours of deliberations we were able to assess only seven projects.
Me: And what happened next?
PM: Well, they left the room to attend other meetings and later told me that the model wasn’t working …
What are the lessons learned from this exchange?
Lesson 1: Keep your PPM models as simple as possible.
Lesson 2: Every time you are offered to consider yet another accurate and precise, but somewhat complicated model, ask yourself the following question:
“Would several executives be able to get through 100 project proposals in the course of a two-hour session?”
Lesson 3: The value is not in getting an actual score but rather in the discussion that happens in the room.
So, let me ask you for your opinion: which model would you choose?
- Simple one with potential shortcomings
- Complicated one but covering all potential scenarios and variables
About the Author
Jamal Moustafaev, MBA, PMP – president and founder of Thinktank Consulting is an internationally acclaimed expert and speaker in the areas of project/portfolio management, scope definition, process improvement and corporate training. Jamal Moustafaev has done work for private-sector companies and government organizations in Canada, US, Asia, Europe and Middle East. Read Jamal’s Blog @ www.thinktankconsulting.ca
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Jamal is an author of two very popular books: Delivering Exceptional Project Results: A Practical Guide to Project Selection, Scoping, Estimation and Management and Project Scope Management: A Practical Guide to Requirements for Engineering, Product, Construction, IT and Enterprise Projects.