Big Data Rolls In, Pick a Wave

New York -- When they’re literally riding a wave, surfboarders wait for a swell they especially like before committing to the ride.

Even if the analogy doesn’t match the task, organizations likewise hope to budget time and resources to investments that bring momentum and gratification before they dig back in against the tide. They won’t always be right, but they prefer to avoid bad choices.

It feels the same way with big data right now. We are starting to see use cases, some of which are promising. But if you are presently short of instinctively seeing a project to grasp, you may not gain a whole lot just for being first into the water, no matter how much everyone is urging you in at the moment.

Big data might be an exploratory undertaking for most trials at the moment, but they’ll work best when you have an idea of what you are trying to do.

There is plenty to be excited about in business analytics, collapsing storage/computing costs and even more developments than were covered this week at the IBM Smarter Analytics Summit I visited in New York this week, and GigaOM’s Structure Data conference. So much attention is going to these events (and more conferences like Strata) that it’s plain that people are piqued and peaking on promise.

It’s also time to say that some people are talking about big data like buying a new iPad. Short of hiring it all out, that’s certainly not the case for most of us. It’s a lot of research and work to be done, once you think you know where you’re going.

The best thing about IBM’s summit was having a few real customers on hand. We heard from Seton Healthcare’s VP of Analytics and Health Economics Ryan Leslie, who described how he’s looking for the unstructured clues in doctor and other caregiver notes that hold great potential for research into care.

“[In health care,] if you haven’t been billing for it, you haven’t been collecting the data,” Leslie said. Psychosocial factors, he's finding, whether patients have support networks, or a ride to appointments in collateral documentation that can bear powerfully on outcome research.

There were other projects at IBM’s event with representatives from Sprint and McKesson, anecdotes of how BestBuy reduced advertising spend with improved target marketing, how others targeted fraud and so on. It was evocative, but not clear how real or mature some of these projects were however, or how hard the results were.

Steve Mills, IBM’s SVP of software/solutions, delivered statistics about the growth of big data and newly forming economies of scale for computing and storage; that IBM has spent $14B in acquisitions since 2005, has 9,000 analytics consultants worldwide and the biggest non-private math department on the planet.

There was IBM SVP Mike Rhodin, talking about new roles for the CFO, CMO and CDO characterized not by spreadsheets, but tools and analytics evolving from enterprise data to big data.

And IBM’s Bridget van Kralingen said that big data presents clients with both their biggest threat and biggest opportunity. By that I think she was referring to security, competitive and opportunity risks of not playing along right now.

It feels like being on the cusp of something. As big as big data is, business goes on, which makes now a great time to sense opportunities and investigate (unless you’re printing encyclopedias or something else where the writing is already on the wall).

Whether you “have to” do big data now depends on the dynamics you’re facing, and as usual, there are no silver bullets available.

But if you have not, maybe it is time to check out a show. I can relate that the energy at the Grand Hyatt was palpable, judging from familiar and long lost contacts, more familiar analysts than I’d seen in one place in 10 years.

IBM did the work and spent the money required to bring all these people together. Let me also confirm that the analyst community here is flush, pundits are smiling and people are being hired right now.

Okay, that would make a contrarian nervous.

But it’s increasingly fair to say that dabbling in big data looks much less risky than moving into ERP was a decade or two ago -- or MDM might be for others today -- not that any company I know dabbles resources unnecessarily.

The arrival of big data is no less a matter of rationale than of fact. You can be wise to look for your own digestible project before the salesman raises his eyebrows because you’re not immediately compelled to invest.

And if you are focusing on this topic like you are every other project, you’ll recognize the use you need when you see it.

(Correction: This article originally quoted Steve Mills of IBM stating that IBM has spent $16B in acquisitions since 2005. The correct figure is $14B)

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