Judgment Under Uncertainty
Tom Peters’ blog has this post about Judgment under Uncertainty: Heuristics and Biases, by Daniel Kahneman, Paul Slovic and Amos Tversky.
They are psychologists, but Kahneman won the Nobel Prize in economics for prospect theory.
The issue — making decisions in a world of uncertainty — seems quite relevant to Agile. For the customer, for the business side, for the Scrum Team (including the Product Owner).
Suffice to say my bias is that people aren’t always as rational as we want to think they are.
People have the idea that (a) I collect all the data needed, (b) I analyze it and (c) I make the right decision. Most business people know this is not a realistic model of the real world. As the head of Google (Schmidt) said, he wants to get more “at bats” than anyone else.
(This comment makes sense if you understand the Ted Williams story about batting averages. Ted Williams holds the highest career batting average in the majors of anyone with more than 500 home runs. It is .344. That means about 2/3 of the time, he failed.)
The basic idea is that we must gather quickly the best information that we can, and then make some quick decisions and have a feedback loop that tells us, to some degree, whether the decision was good or bad. That allows us to make corrections or improvements.
Is the model described in the above paragraph the one and only model for all of reality? No, but it applies to us doing Agile quite a lot. More on this later.