Success is impossible without knowing what it is you’re trying to achieve. Ironically, one of the biggest challenges in getting value from big data is usually working out where to start. Given a smorgasbord, the worst thing to do is to try to eat everything at once.
As a rule, we’re a species that enjoys self-improvement. Faced with a problem and motivation, most of us would rather solve it than live with it. We may not all have the ability to tear down a car for servicing, but given the right set of skills, the right opportunity, and the right motivation, anyone can innovate.
Consider James, our well-intentioned if slightly erratic innovator. In his journey to monetize his organization’s data assets, he recognized fairly early that analysis alone wasn’t enough. He sold his vision on the back of innovation and, one way or another, he had to deliver it. Unfortunately, he failed to understand what he meant by “innovation.” Because of that, many of his successes in his first year were underappreciated or outright overlooked.
Innovation sounds sexy. It’s also pretty amorphous; if it were easy, there probably wouldn’t be so many books on the topic. The best starting point is to remember that there’s a difference between innovation and invention. Invention is unique; it represents the original creation of something new. By contrast, not all innovations need be completely novel. In fact, the opposite is normally true—most innovations are simply ...