After I finished my book, got it all done and dusted, I had a revelation that I knew needed to be added to the book. As such, I’m adding in Chapter X – Why Predict? I’m releasing it first for free on my website, and in a few days, it will be in the printed and electronic versions. If you have already bought the book, or just want to read the chapter, follow this link. What follows here is a quick summary of the chapter.
Why add Why Predict? I realized that while I had been doing data science, I had just assumed the need for data science to be true. After some pondering and conversations, I was able to articulate the answer to the question…
Why predict? Because every goal contains, at a minimum, an implied prediction.
I’ve elaborated this into the new chapter, but I’ll summarize here. Take a goal, any goal. If you unpeel it, you will see a prediction buried within.
A Simple Matter of 5 Pounds
Let’s say I have a goal, “I want to lose 5 pounds.” Let’s look at the hidden prediction. In this case, the prediction is that if I don’t change my lifestyle, I won’t be 5 pounds lighter. The prediction is simply, that I’ll maintain my current slightly overweight status.
If, given my current lifestyle, the prediction was I was going to losing 5 pounds, the goal could be “after 5 more pounds, I need to stop losing weight.” Or if my prediction was that I’m losing weight too rapidly, the goal would be “I need to stop losing weight, I can’t afford to lose 5 pounds.” Similarly, the prediction could be that I’m going to gain 5 pounds and the goal may be to just not gain any more weight.
As you see, the goal is only meaningful in relationship to a prediction.
Data Science Gives Great Predictions
The simple realization that a goal is a difference from a prediction drives so much of data science. We can now predict with ore accuracy than ever before. We can predict the customers who will leave us next month. We can predict which products are likely to have problems shipping. We can predict how many coupons will be redeemed.
The question is: if that prediction comes true is that good enough?
If the results of the prediction is a situation that is good enough, then the good news is, you don’t need to change a thing. You’ll make your sales target, your customers will be happy, and your margins will be exactly what you need them to be.
Now you can focus your attention on those predictions that predict a future that isn’t good enough.
Remember: every goal is a change from a prediction.
More in the Chapter
The extra chapter goes into more detail on the linkage between goals and predictions. Also, in the chapter I cover more detail about the natural disconnect between people and predictions, as well as the pernicious problem of disingenuous predictions, and just as importantly, what predictions are socially unacceptable. I also cover the concepts of how, as we change from looking at historic data in order to make predictions into a world where data science provides the predictions, we also need to change the information we consume.
A copy of this post is on my blog.