I’m reading a book by Mike Cohn on agile estimation (not estimation for agile projects — there is a difference!). As I’ve been thinking about estimation errors this week, I noted in my reading of Mike’s book the several times where he points to specific research that underlines that the best estimates are estimates created by the persons who will do the work. Project managers can create an entire project using their own expertise in estimating, but that won’t be as good as working with an entire team of people who will be doing the work that the team, together, is estimating.
When I think about the potential for a mathematical error in using Statistical PERT instead of some other, better estimation technique — Monte Carlo simulation, or any other estimation technique — I’m convinced that those aren’t the errors that ought to be of concern to those who create, review, and approve estimates.
If I were a project sponsor, and my project manager gave to me a project estimate for time and cost, I would want to know how those estimates were created? Is this product of one person’s view of the project? Or is it the few of several people? Or of the entire project team? Did they use 3-point estimates? How? How did they choose the minimum, most likely, and maximum point-estimates? Were those three points subjectively chosen?
Project estimation is half-art, half-science. It’s easy to focus on the science of estimation because mathematics involves right and wrong answers, with nothing much in-between. But it’s the art of estimation where we gloss over the potential for error.
Perhaps you’ve had a manager look at your project estimates, and then shave them, believing that there were unnecessarily generous. Maybe they were, maybe they weren’t, but that’s just another place where estimation errors arise. I’ve never seen a manager trim my estimates and defend their action by presenting me with hard data that my estimates were wrong.
When I think about the errors that occur in the art-part of estimating, the potential for errors within Statistical PERT appear, to me, insanely small and wholly immaterial in circumstances where it’s a good fit for an estimation problem.