Going Pro in Data Science

Chapter 2. How to Get a Competitive Advantage Using Data Science

The Standard Story Line for Getting Value from Data Science

Data science already plays a significant role in specialized areas. Being able to predict machine failure is a big deal in transportation and manufacturing. Predicting user engagement is huge in advertising. And properly classifying potential voters can mean the difference between winning and losing an election.

But the thing that excites me most is the promise that, in general, data science can give a competitive advantage to almost any business that is able to secure the right data and the right talent. I believe that data science can live up to this promise, but only if we can fix some common misconceptions about its value.

For instance, here’s the standard story line when it comes to data science: data-driven companies outperform their peers—just look at Google, Netflix, and Amazon. You need high-quality data with the right velocity, variety, and volume, the story goes, as well as skilled data scientists who can find hidden patterns and tell compelling stories about what those patterns really mean. The resulting insights will drive businesses to optimal performance and greater competitive advantage. Right?

Well…not quite.

The standard story line sounds really good. But a few problems occur when you try to put it into practice.

The first problem, I think, is that the story makes the wrong assumption about what to look for in a data scientist. If you ...