Prescriptive analytics: A thought experiment
Your algorithm prescribes adding the Fruity Pebbles cheesecake recipe to your web content. The counter-intuitive recommendation is only counter-intuitive the first time. The recommendation now becomes intuitive, routine. So each year, in late spring, you run another recipe just like this, Cap'n Crunch Cupcakes, Fruit Loops Parfait, and so on. But something changes. One year, the recipe no longer garners clicks. Visits are down. Will the prescriptive algorithm double down on its advice, run more breakfast cereal no-bake recipes? Or will it detect the root of the new trend? If it is just telling me what to do and not why, how does the managing editor know when to change course and in which direction? With dozens of statistical models forecasting every possibility, how to choose? Weather prediction has been banging up against this challenge for over a century. In business, we are always on the hunt for the disruptive change. Not only will prescriptive analytics miss the disruptive change, it will reinforce management's reliance on these now misleading analytics far longer than they otherwise might.