My colleague Ben Gilad posted a terrific essay on the shortcomings of “data-driven” decision-making.

I love data. I spent 15 years playing with the PIMS database alongside luminaries such as Michael Porter, Sidney Schoeffler, Robert Buzzell, and more. Many years later, I can run a few hundred million simulations before breakfast and tell you what they mean before the coffee’s temperature drops to 80 degrees F. I told you, I love data.

But data isn’t learning, and learning isn’t just about the amount of data. Is one data point enough for learning? How about a trillion?

When smart people fail, their failures are often (not always) because what they think they know is wrong. There’s often a deeper failure, a failure of knowledge, learning, and framing, rather than a failure of execution or data.

To see why, let’s look at rats.1

Read More →