IBM has cornered the analytics market, snagging the top spot on Wikibon’s annual Big Data vendor survey every year since it was first published in 2011. The enterprise IT stalwart achieved sales dominance by virtue of having a broad lineup of technology solutions for ingesting and processing information that, taken together with its practically unrivaled professional services portfolio, blows the competition out of the water in terms of sheer scope.

Despite Big Blue’s leadership position, analytics only accounted for a mere one percent of its total revenue in 2013, according to Wikibon’s survey. That figure is climbing slowly but surely as IBM CEO Virginia Rometty continues to invest heavily in the Watson cognitive computing engine (as our own Bert Latamore reported) and other components of her vision for cognitive computing—an umbrella approach to making sense of vast amounts of information that puts a particular emphasis on predictive analytics.

IBM’s Harriet Fryman

Harriet Fryman, Director of Big Data and Analytics at IBM, explained in a November theCUBE interview that helping customers drive proactive business decisions is placed high on IBM‘s agenda. She said it’s simply too big of an opportunity to ignore. “When something’s happening in real time, we can assess it,” Fryman told theCUBE cohosts John Furrier and Dave Vellante at IBM Information on Demand 2013. “We can predict what the outcome might be and we can suggest the next best action which is [going to] have a direct positive impact on the business—versus a month from now [saying], ‘Oh, I wish we had seized those customer chances a month ago.'”

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How IBM is applying predictive analytics

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Making it easier for organizations to identify potential revenue streams is one of two ways IBM is applying predictive analytics. The other way is realizing operational efficiencies, particularly in the manufacturing sector where, similar to the home appliance revolution set in motion by Nest, industrial equipment is being sucked up into the Internet of Things.

“We have a signature solution, particularly around predictive maintenance. So, cars, factory lines—you want to predict when they’re going to fail and put the maintenance in right there before it fails. Because it’s extremely costly to jump in and fix something once it’s broken.” Fryman explained.

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BMW revs engines with predictive analytics

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IBM is showcasing the technology at this week’s CeBIT exhibition in Germany alongside a case study from BMW. The luxury car maker utilizes IBM’s SPSS predictive analytics software (SPSS) suite to rapidly process workshop reports and analyze prototype test drives. Each run produces about 15,000 faults worth of sensory data, which Big Blue claims once took months to process but can now be ingested in days using its software. The resulting insights enable BMW engineers to spot potential design flaws before new models go into mass productions, streamlining operations.

In addition to accelerating time-to-market, IBM says that SPSS has made it possible for BMW to anticipate the maintenance needs of individual vehicles and issue targeted repair instructions to reduce the number of workshop visits customers have to make. For BMW employees, the platform provides about 250 commonly used queries that can be accessed on a self-service basis across the different business divisions and subsidiaries.

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Photo credit: Social BIz Solutions via photopin cc

Photo of IBM’s Harriet Fryman courtesy of theCUBE

Suzanne Kattau contributed to this article.