Police Rely on Big Data for Next-Generation Crime Fighting
In today’s information age, vast amounts of digital data are collected, analyzed and used in ways many of us can’t even imagine.
This phenomenon, known as Big Data, is changing the way many organizations operate. Terabytes of data generated by sales at the supermarket now tell POS systems which coupons would be best to offer you. The power company uses years’ worth of customer data to ensure capacity for probable spikes in demand. A team of researchers has even used data from Twitter to guess stock market prices with more accuracy than other computer models.
In Santa Cruz, Calif., Big Data is also being used to fight crime. Last summer, the Santa Cruz Police Department launched an initiative to use data from the city’s records management system – years of information on when, where and what type of incidents occurred – to predict times and places future incidents are likely to occur.
This data is fed into an algorithm that produces maps given to the city’s officers with “hot spots” marked for a high probability of certain types of crime, allowing officers to better focus their patrol efforts. For example, if the data suggests a high probability of home burglaries in a certain area and time of day, officers can patrol the area to be on watch for any suspicious behavior.
When officers use their onboard mobile computers to check in while driving through predicted crime zones, it produces additional data that can be used to determine how effective the program has been.
In a recent interview on DorobekInsider.com, SCPD Crime Analyst Zach Friend said that in the first six months of the program, the city saw a reduction in targeted crime types.
“It’s a great equalizer for law enforcement agencies to ensure that everybody is patrolling the areas they should be patrolling at the right times,” Friend said in the interview.
“It doesn’t replace officer intuition. But what it does is normalize information across two elements of law enforcement – one is experience level and the other is talent level,” he added. “You clearly have officers that have been doing it for 25 years that maybe would say, well I already knew that eight of these ten locations would be predictable hot spot locations for the day. But if you have an officer that’s been on two months or two years, they just simply don’t have that experience yet.”
Friend said that more than 100 other law enforcement agencies have reached out to the SCPD for more information on the program after seeing it profiled in major publications including The New York Times and Popular Science.
He added that like many law enforcement agencies around the country, in recent years the Santa Cruz police department has seen its resources stretched thin with cutbacks in staff, but increases in the number of calls. The Big Data program is a way to address this by working smarter.
“The old solution of, we have a higher demand so we need more cops, is not going to be the answer that we can depend on moving forward,” Friend said. “So how do you allocate our finite resources more efficiently? That’s why I looked for something like this.”
Public safety is just one of the ways innovative, data-driven programs like these can be used to serve the public. We encourage Santa Cruz – and other municipalities – to look at the role Big Data can play in all areas of government. For example, public works agencies can leverage the same kind of historic data to proactively address street repairs, and fix potholes before irate citizens call. Anonymous data collected from years of health insurance forms could also be used by the Centers for Medicare and Medicaid Services to determine which treatments and medications are most effective.
In order to take advantage of this promise, agencies need the right technology. Panasonic congratulates the Santa Cruz Police Department on its resourceful approach toward tackling some of the biggest challenges facing law enforcement today. We look forward to continuing to provide the tools that support programs like these and others.