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Police Departments Fighting Crime with SPSS Predictive Analytics
Saving Time and Money
Source: www.spss.com
Copyright SPSS, Inc. 2005
03/21/05

This is a dated announcement. The material in this announcement could be superceded by more current announcements.

CHICAGO, 03/21/05 — Multiple police departments nationwide are using SPSS (NASDAQ: SPSS) predictive analytics to optimize deployment of officers, saving the departments time and money while ensuring public safety. In such cities as Atlanta and Richmond, Va., law enforcement officials are harnessing SPSS technologies to identify key patterns in crime data—such as incident reports, crime tips, and calls for police assistance—to make effective officer-deployment decisions.

Atlanta’s police department is using SPSS’ data mining workbench, Clementine®, to analyze data to create maps that notify officers of potentially high-risk areas on their beat. This information has enabled officers to better prepare themselves for criminal encounters and has decreased the element of surprise on their daily patrols.

Richmond’s police department also utilizes SPSS’ Clementine to determine which city areas most need deployed officers and to identify major crimes likely to escalate into violence. Clementine has been particularly beneficial on traditional high-crime holidays, such as New Year’s Eve, whereby deploying officers at traditional crime “hot spots” has reduced reports of gunfire by nearly 50 percent over previous years’ totals.

“SPSS predictive analytics software represents a revolution in our ability to access previously unobtainable data and pull meaning and value from it,” says Colleen McCue, a consultant to the Richmond Police Department. “This is as close to a crystal ball as we’re ever going to get."

“The law enforcement community is increasingly seeking to simultaneously reduce crime and costs,” said SPSS President and CEO Jack Noonan. “SPSS predictive analytics is saving law enforcement agencies time and money by enabling them to swiftly sift through crime data to identify patterns that help them determine how best to deploy forces to reduce crime.”