Producing accurate estimations for software projects is notoriously challenging, but why? It all starts with understanding what it takes to make a good estimate.
What is a good estimate?
An estimate is an approximation of something, implying that it is based on uncertainty. Clearly a good estimate is accurate, but since this isn’t always possible, it’s more useful if it at least encodes how uncertain we are.
If I say that a project will be completed in 4 months, it removes an important piece of information — my confidence in the estimate. It’s unlikely that the project will take exactly 4 months, but is it a low risk project which might take between 3-5 months, or is it based on so many unknowns that it could take over a year? The estimate isn’t more useful with a narrow range if it is based on little to no understanding of the problem.
This is the point made by Steve McConnell in “Software Estimation: Demystifying the Black Art”, where he argues that the illusion of accuracy can be more dangerous for project estimation than a wide estimate. If we can acknowledge that the estimate is not solid, then we can at least start to improve our knowledge of the problem and begin to make it more accurate.
“Estimates don’t need to be perfectly accurate as much as they need to be useful.” – Steve McConnell.
How good are your estimates?
Perhaps unsurprisingly, most people overestimate their own ability to make accurate estimations.
To show this, McConnell provides a test (which you can try for yourself here), where you have to estimate the answer to 10 questions with a 90% confidence that the correct answer is in the range of your estimation.
Try it, and come back here. How did you do?
Very few people answer these questions with 90% confidence, partly because we are conditioned to believe that a good estimate is a narrow estimate.
In fact, a lot of the comments on the answers page argue that the questions are poor, because you’d have to be an expert to produce any meaningful (accurate, narrow) estimates. But this is precisely the point!
If you can answer with 90% confidence, but with a very wide range, then you are at least acknowledging that you don’t have enough knowledge to accurately answer the question.
And that’s the first step to fixing the problem.
This is a repost of a blog I wrote over on the AetherWorks Blog earlier this year.