Peak Analytics and Novelty

Suppose for a moment, that your favorite sports team has completely adopted analytics. Your (American) football coach stops giving the inefficient running back so many carries. Your mediocre basketball center no longer dominates the ball for post-ups, instead serving as a willing passer to 3-point shooters. And your baseball team focuses itself around TTO, eschewing lower risk (but low reward) strategies such as stolen bases and bunts. Fantastic! Peak analytics has been achieved!

But, as this takeover occurs, will it be at the expense of novelty? Writing for, Kevin O’Connor made some fascinating observations about novelty and sports analytics. He started wondering what happens if analytics reveals that there is only one right way to play the game, and strategy thus becomes homogeneous:

Statistics tell us this is the right way to score the most points in the most efficient way possible. But when every question has an answer, it’s not as fun to ask in the first place. If there is a right choice to make in every basketball sequence, will that kill the magic of watching a team or player offer their own solution?

For example, what if your basketball team insists on taking the first three-point shot it can on each possession because it is the most optimal solution? While this may result in more victories (at least in the short-term, before defensive adjustments), it may also result in a less excited, less engaged fandom.

So perhaps you aren’t a sports fan. Let me put it to you in a different way. Many of us have had the experience of buying an item off Amazon and then seeing ads for it on Facebook and Instagram. Big data has clearly monitored our purchase and decided that we wanted to see more of the same. And indeed, this simple logic makes a lot of sense in the abstract. But just because I had chocolate cake for dessert yesterday does not mean that I intend to embark on an all-chocolate cake diet! Instead, what would be better is if analytics could be used to guess what dessert I’d want to try next, or even that I’ll be more willing to purchase healthy food due to yesterday’s sugar guilt. Rather than merely reinforcing trend, analytics could be used to expand the customer’s tastes and options.

The point of this essay is not to say that analytics and novelty are enemies, and I’m sure many examples could be given of analytics being used to create novelty. But ORMS may be at the exciting stage where we can worry more about analytics being too important or powerful, rather than fighting for analytics acceptance. If we are at that stage, I look forward to seeing what new problems emerge as a result.