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5/26/2006
10:15 AM
Rick Whiting
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Businesses Mine Data To Predict What Happens Next

Real-time information is no longer fast enough for some companies. The trend is applying predictive analysis to everything from patient care to airline safety.

Crime Stoppers
In Richmond, Va., police use predictive analysis to determine the probability that a particular type of crime--armed robbery, auto theft, murder--will occur in a specific area at a given time. Police lieutenants who command the city's 12 sectors use desktop computers linked to the system to decide where to deploy a mobile task force of 30 officers. "Based on the predictive models, we deploy them almost every three or four hours," Police Chief Rodney Monroe says.

Officers have arrested 16 fugitives and confiscated 18 guns based on the system's guidance. In the first week of May, Richmond had no homicides, compared with three in the same week last year. Monroe attributes that outcome, in part, to moving officers around based on the calculated probability of shooting incidents. "It's more proactive," Monroe says. "We're not waiting for a homicide to occur."


Police Chief Monroe crunches data, then locks up fugitives. -- Photo by Dean Hoffmeyer/Richmond Times-Dispatch/AP

Police Chief Monroe crunches data, then locks up fugitives.

Photo by Dean Hoffmeyer/Richmond Times-Dispatch/AP
A 911 call is a real-time event; pre-empting that call involves predictive analysis. Vivek Ranadive, CEO of Tibco Software, the data-integration and middleware company, is convinced a growing number of companies are about to begin applying data forecasting. "I've spent all my life evangelizing 'real time,' but by its nature it's still reactive," Ranadive says. "You really have to get ahead of the curve."

Ranadive lays out his thinking in a new book titled The Power To Predict (McGraw Hill, 2006), which includes a for-ward by FedEx CEO Fred Smith. "Companies have always had to be nimble to succeed," Smith writes, "but the imperative to become proactive gets stronger each day." Smith envisions predicting what customers want "before they know they want it" and anticipating service disruptions before they occur.

Ranadive says he expects predictive analytics to be widely adopted over the next few years to make customers more loyal and supply chains more efficient and keep store shelves stocked with the right items. Tibco, of course, smells an opportunity. The company has trademarked the phrases "predictive business" and "the power to predict," and it has a hand in the game: Tibco Business Events is a rules engine that combs databases and applications to find patterns in data for identifying business opportunities.

Researchers have advanced the science by developing new algorithms with exotic names--the Markov decision process, stream mining, and support vector machines--that provide more ways to analyze data and find subtle patterns. And there's a practical reason a growing number of companies are interested in such tools: They need help making sense of all those terabytes of data they're accumulating. Cheaper, more powerful computers put it all within reach. "We have the ability to apply predictive analytics in ways that would have been impossible a few years ago," says Richard Vlasimsky, CTO at Valen Technologies, which markets predictive analysis software for the property and casualty insurance market.

But vendors need to be careful not to overpromise. The Richmond police will never be able to foretell the actions of lawbreakers in the way Tom Cruise's character, Chief John Anderton, did as a member of a "precrime" team in the Steven Spielberg film Minority Report.

"I watched that and thought, 'We could almost do that now,'" says Charlie Berger, an Oracle senior director of data mining technologies. Oracle has built predictive modeling into its database using data mining software acquired with its purchase of Thinking Machines in 1999, and it added predictive analysis applications for CRM and retailing through its PeopleSoft and ProfitLogic acquisitions. Tech vendors are automating the steps of building predictive models and preprocessing the data, making the technology easier to use by a wider audience, Berger says.

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