UPDATED 06:18 EDT / NOVEMBER 08 2012

Big Data for the Little Guys: Beyond the Fortune 100

Colin Shearer, the head of IBM’s advanced analytics business, took some time off during his company’s IOD conference last month to discuss IBM’s upcoming subscription-based analytics service with John Furrier and Dave Vellante.

Analytics Answers, set to launch within the next few months, couples big data with the cloud to make this technology available to companies that would otherwise not be able to afford it. Shearer says that the offering is not targeting household names, but rather the smaller firms that face the same business problems as their bigger peers but don’t have the resources to solve them.

Shearer identifies cost as one big barrier for these companies, but it’s only one of many. The software is not enough on its own – companies also need the in-house talent to operate it, and this requires even deep pockets as well as extensive training. This latter aspect points to yet another obstacle: the time it takes to realize a return on traditional analytics solution.

According to Shearer, Analytic Answers tackles all of these problems at once. IBM has developed four different “Answers” so far, one of which is a cross-industry debt collection solution. The remaining three address different issues for retailers, insurance companies and the academia.

After providing more details about each of these products, the executive goes on to describe the process of executing Analytics Answers. IBM representatives communicate with clients remotely more often than not, he says, and collect large amounts of historical data to be used in the end product. This information is used to create custom predictive models that are deployed in the cloud.  Shearer says that his company goes a step further by wrapping this in a simplified interface that can be leveraged by a regular business user.

For the full scoop on IBM’s upcoming solution and an insider’s perspective on consumer privacy and the channel, check out the full interview below.


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