The theory is that predictive analytics might work better on property crimes because the targets are stationary and the nature of the targets doesn't change that much over time, he says, unlike crimes where the victims are mobile and change their behaviors.
Criminologists find it's easier to predict these types of crimes because there are patterns regarding where and when they occur. For example, burglaries tend to be clustered in terms of time and location and the individuals committing these crimes tend to have predictable patterns--usually they commit them somewhere near their homes or near familiar locations.
Additionally, property crimes are not displaceable crimes, which means if police departments target these crimes in particular areas, the criminals won't simply move two miles to another location.
Zach Friend, a crime analyst at the Santa Cruz Police Department, says his department is the "operational test case agency" for the system, although Santa Cruz didn't set its program up as a controlled experiment, as did the LAPD.
"What [the researchers] did before was just test crime data, but we were actually willing to test it in the field," he says.
Friend says data from the department's records management system is fed into the computer program on a daily basis, and then transferred to Microsoft Excel software where it's cleaned, ordered and geocoded. Next, the data is combined with a master Excel database of all pertinent crimes for the past seven years and run through the UCLA algorithm.
Hotspots on Google Maps
"We recalibrate on a daily basis and the algorithm produces 10 Google hotspot maps every day of approximately 500 feet by 500 feet where burglary or vehicle theft is likely to occur in our city on that day," he says.
Officers are given the hotspot maps at roll call. The officers check those areas during their "free" patrol times, when they're not obligated on other calls, and they document their activities for tracking purposes. Because the city of Santa Cruz is only 13 square miles, the hotspot maps significantly reduce the area that officers need to patrol.
"Law enforcement in the past has taken a reactive approach to enforcement--if crime occurs in one place you need to go to that place," Friend says. "This is breaking that mold. You don't necessarily have to go there. Maybe it will send you to a separate location to prevent the next crime from occurring."
The point of predictive policing is not to make arrests but rather to reduce the numbers of the targeted crimes from happening in the first place. And it seems to be working in Santa Cruz.
"In the first month, July 2011, the only variable we introduced was the application of this model and there was a 27 percent reduction year-over- year of the targeted crime types, because there was a police presence in the area where maybe there wouldn't have been a police presence at all," Friend says.
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