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New Software Predicts Crime

Minority Report
Minority Report

November 20, 2008 By

The Department of Pre-Crime is intriguing conceptual material used in the 2002 science fiction film Minority Report, and it's inching toward reality for the Richmond, Va., Police Department. Instead of using the fictitious "precogs" who float in a pool of water while foreseeing crimes, the police department uses crime analysis and prediction.

The concept is based on the idea that criminal behavior follows identifiable patterns, more often than not, that can be used to predict criminal acts. By collecting previous crime statistics and external factors -- weather, time of day, day of week, moon phases, etc. -- officers can estimate when and where crimes might occur using business intelligence (BI) capabilities.

A new system was rolled out in a phased implementation beginning in 2006 that provides predictive crime analysis, data mining, reporting and GIS capabilities too the entire Richmond P.D. The result is that officers receive the most up-to-date information available, along with a screen of predictions of crime hot spots they can access before a shift. Data from the records management system is integrated and analyzed on a continuous basis.

The Richmond Police Department's innovative enterprise platform has produced dramatic results. By moving from a "reactive crisis management structure" to a "proactive problem deference model," the department lowered the city's ranking from 5th most dangerous U.S. city in 2004 to 15th most dangerous city in 2005, with a 21 percent reduction in major crime from 2005 to 2006. The department also won Gartner's 2007 BI Excellence Award.

"What we're doing is replicating the intuitive nature of the seasoned veteran cops, the guys that have been on the force for 25 years and know certain sections of city really well and operate almost out of complete intuition, who know more than a crime map might show them," said Stephen Hollifield, information services manager of the Richmond Police Department. "What our application attempts to do is the same thing, but provide that type of intuitive picture about areas and give them to our green officers who have been on the force for only two years and haven't developed that sense yet. This kind of speeds up the process and gives pictures based on all the crimes in the past, weather, times of day, day of week and moon phases."

Business Intelligence Approach Works

The Richmond Police began down the road of predicting crime in 2005, when the department named Rodney Monroe the new police chief of the department's 700 officers. With the immediate objective of lowering the city's crime rate for Richmond's 220,000 residents, Monroe met with BI software vendor Information Builders and analytical software vendor SPSS Inc. to see how technology could help.

At the time, the police department was data rich and information poor: A vast wealth of historical data was gleaned from its mature 911 system, computer-assisted dispatch and records management system, which all were used to track crime and ensure quality of service. Yet like many organizations, the police lacked a BI solution that could make use of the data.

Obviously data has become a valuable collected resource for numerous government organizations in recent years, but effective utilization of it -- through tools like BI -- has lagged behind. That's why BI has consistently ranked as a top priority for CIOs over the last few years, according to Gartner.

BI can offer an organization invaluable system analysis by collecting, analyzing and integrating data, while providing historical, current and predictive views of business operations. The integrated reporting and analysis allows managers to determine better management of an organization, improve services, identify effective strategies, enhance security and increase efficiency, among other things.

The first task for the Richmond Police was to identify data that would be used to create predictive crime reports -- factors that didn't have variables that could change drastically over short periods of time. This created a

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