Police departments opt to use data for competitive advantage over crime, saving time and money in the process
Chicago — March 22, 2005 — Every workplace has its own supply and demand chain, and that means that there is always room to use its data for competitive advantage. In the case of police departments across the country, it's competitive advantage over crime.
For instance, many police departments have started using predictive analytics to optimize the deployment of officers, saving time and money while ensuring public safety.
In cities such as Atlanta and Richmond, Va., law enforcement officials are using technologies from SPSS Inc. 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 uses 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," commented 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 sift through crime data to identify patterns that help them determine how best to deploy forces to reduce crime."