I just saw an ad for “Moneyball”, a new movie based on the book by Michael Lewis. A baseball manager (Billy Beane of the Oakland Athletics) used analytics (“Sabremetrics” in the baseball world) to choose players who were undervalued by the rest of the baseball world. Beane had a constrained optimization problem: he had to get as many wins as possible with a highly binding budget constraint. His solution to that problem was to concentrate on statistics that seemed to be undervalued in the market, notably “on base percentage” (if you don’t know baseball, this gets a bit opaque, but getting on base is not as “sexy” as hitting home runs: home run hitters are expensive; players that just get on base were cheap at the time).
There is a great line in the ad. A colleague (the “stats guy”) of Beane says:
This is the type of decision that will get you fired!
Brad Pitt, playing Beane, looks worried, but perseveres. See the
ad at about 25 seconds the official ad at about 18 seconds.
[Unofficial ad deleted.]
I love that line, since it really does sum up what operations research (and make no mistake: “Moneyball” is an operations research film) is all about. When you do operations research, you create models of reality. You do not create models of decisions. The decisions come from the models. And sometimes, the decisions don’t look at all like what you expected. And that is when it gets interesting.
Sometimes these unexpected decisions are due to modeling failures: you have forgotten a constraint, or a key modeling assumption turns out to not only be incorrect (assumptions almost always have some level of incorrectness) but critically incorrect. Optimization is really good at putting solutions right where the models are the weakest. And so you modify the model, not in order to change the decision, but in order to better represent reality. And you get new decisions. And you iterate between modeling and decisions until you reach a model that you believe represents reality. At that point, the decisions are of two types. They might tell you to do what you are doing, but do it better. And that is comforting and probably improves the decision making in the organization.
Or they tell you to do something completely different. And that is when you get to “Decisions that might get you fired.” That is when you need to decide whether you believe in your model and believe in the decisions it has generated. It would certainly be easy to change the model, not to reflect reality, but to force the decisions you believe are right. But if you really believe the model, then you need to avoid that easy path. You really need to decide whether you believe in the model and the resulting decisions.
I worked with a company a few years ago on their supply chain design. The results of the model came back over and over again saying two things: there were too many distribution centers, a result everyone believed, and it was far better for each distribution center to specialize in particular products, rather than have every center handle every product. The latter decision went deeply against the grain of the organization, and objection after objection was raised against the model. It would have been easy to put in a constraint “Every distribution center has to handle every product”. But there was no justification for this constraint except the ingrained belief of the client. In fact, we could show that adding the constraint was costing the organization a significant amount of money. Eventually, at least some of the organization bought into the decisions and began devising specialized distribution centers, but it was gut-wrenching, and perhaps career threatening. After all the discussion and fighting against the decisions, I am convinced those were the right choices: the organization had to change, not just improve.
“Operations Research: The Sort of Decisions That Will Get You Fired” doesn’t have the ring of “The Science of Better”. But the insights OR can get you may lead to radically different solutions than the incremental changes the SoB campaign implied. And those are the changes that can fundamentally change firms and organizations. And careers.