If you had asked me a few weeks ago, I would have told you that having a high standard deviation in your process was never a good thing. After all, being unpredictable isn’t good. That is what is drilled into our heads all the time when you study Six Sigma.
The conversation started with a group of people discussing sports and, in particular, the Oakland A’s, who figure prominently into the book “Moneyball.” As stats geeks, we admire all that went into making the A’s a great team on a much smaller budget than many others. But the A’s are boring. You might get excited about Moneyball but, at least from where I stand, the A’s don’t fare well. If you use attendance as a measure, the A’s rank near the bottom – between 27th and 29th depending on the site you use.
So, how do we rationalize this disconnect. Solid data suggests that a far less monied team can compete, but the fans don’t show up. And the reality is, ultimately sports is a business just like any other and you need the fans to show up. So, why is it that a better average performance didn’t draw in the fans?
Well, because predictable is… Boring. There are places where predictable isn’t good. High standard deviation is good. What do people remember about the Red Sox? Eighty some odd years of coming close and failing, then the excitement of a few years of wins and we are back to the flame out stories. We like it when the game is exciting. And for winning to be exciting, there must be losses. Frankly, I’ll turn off a game if it is a blowout. If you could design a team who was reliably better than every other team, I bet nobody would watch. Predictable outcomes aren’t fun outcomes.
Don’t believe me? Check out the analysis of JCPenny’s “no more coupons” approach.. Lower prices are more predictable and overall should be better for customers, but it doesn’t work. Sometimes we have to appeal to something other than a reliable, repeatable experience. It is important to figure out when is the time to be predictable – a lot of the time, but not all the time.