In 2005, Steve Jobs asked Intel CEO Paul Otellini to build a new processor for the first iPhone.

Otellini said no, and Intel was caught pants down as smartphones ate the world. Otellini owned up to his mistake after the fact:

"I couldn't see it. It wasn't one of these things you can make up on volume. And in hindsight, the forecasted cost was wrong and the volume was 100x what anyone thought…. The lesson I took away from that was, while we like to speak with data around here, so many times in my career I've ended up making decisions with my gut, and I should have followed my gut. My gut told me to say yes."

The problem was that Intel used data to back up what it already knew, and not what it could find out. The companies behind the best products of today understand that in order to survive, you have to reinvent yourself constantly. This means leveraging experience and collected data to drive a vision of the unknown.

Otellini's decision was completely logical and also completely wrong. Moving to a cheaper ARM chipset ran counter to 50 years of how Intel has pulled in profit-each year manufacturing a high volume of premium microprocessors, and selling them at wide margins.

Year after year, Intel has thrown billions looking at the same data for "forecasted" volume and costs. Instead, they should have been looking at how to use data to reinvent themselves.

Product development today is filled with a demand for "more data." But what's far more important than what you have at your fingertips are all the things that you can't know. Without context and a larger vision for the future, data means nothing. It fills out spreadsheets on a piece of paper and a couple of pretty graphs. You might as well build product by tracking the way sticks fall onto the ground.

This chapter of the ebook is not about how you accumulate data. It's about how you use data.