Tom Springer: Three Promises and Perils of Big Data

TOM SPRINGER: So we see huge opportunity in application of big data to our clients' toughest business problems. But there's also tremendous hype around big data perpetrated by solution providers that are out there selling wares that our clients may or may not be ready for. And so to break through the hype, we coach our clients to think about three promises and perils of big data.

Promise number one is that the solutions are going to find the value all by themselves. Well, it's true that the solutions typically have automated components that assist the insight and solution development process. But they have to be directed by a business executive that owns a problem and an outcome. That's always been true. That will be true in the era of big data.

Promise number two is that more and more data will necessarily equal more and more value. Well, as a broad statement over time and on average, that's probably true. But when you're trying to solve a specific problem, it's the right data you need to solve the particular problem.

You can actually drown a team in too much data on their way trying to get over the goal line to a solution. And so we find that it's important to start with what you got, and iteratively layer on more data as the team becomes comfortable with bigger and more complex data sets.

Promise number three is that the data scientists are going to go off and find the value for you and just bring it back. And you can just go have a coffee or go to sleep while that's happening. Well, that's just patently false.

These folks have to be matched with all the folks around the company that understand the context and potential solutions to the problem, and be brought together in a cross-functional Agile process to get to a solution. That's one of the keys to unlocking value from big data.

Read the Bain Brief: Three Promises and Perils of Big Data