[evanwarfel]

There is one, and only one reason to be 'data driven'. Or to test one's hypotheses, for that matter. And that is to make sure you aren't fooling yourself; that you haven't fallen prey to the myriad cognitive biases; to prevent your preconceived notions from clouding your judgement of reality, aka what is actually going on.

While data always provides more information, the less strong your prior beliefs, the less informative your experiment will be -- If you believe something and it turns out to be majorly false, you get a nice shift in expectations. If you believe in something and it turns out to be very true, you gain lots of information in terms of quantifying the effect you are looking into.

If you are Google, looking to eck out every last 1/1000th of a penny on ads, yeah, maybe a/b testing the shade of blue of a button can be justified.

The more other companies are "Data Driven" [like the somewhat unfortunate examples the author chose], as opposed to "Hypothesis Driven", the more there is room for somebody else to fry bigger fish.

In other words, it's not the "data's" fault, it is ours.