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S P E C I A L R E P O R T

Fight Crime With Big Data and Predictive Analytics Predictive analytic technologies can help identify where crime might occur and how to respond. By Adrienne Zimmer

E very law enforcement agency col- lects an immense amount of data. Without turning the data into actionable intelligence, however, one could argue it remains, for

lack of a better word, useless. For the last decade or so, a lot of conversation has centered around technology that can take large amounts of data and turn it into something more. Enter predic- tive policing.

The National Institute of Justice writes that, “Predictive policing, in essence, is taking data from disparate sources, analyzing them and then using the results to anticipate, prevent and respond more effectively to future crime.” Using data to anticipate trends isn’t new. In fact, many law enforcement agen- cies, most notably in larger urban areas, have been using predictive analytics and accompanying software for close to a decade—and the usage is slowly growing.

“I think more and more agencies are looking at predictive analytics,” says Scott Landau, senior business development manager, public sector at Panasonic. “There is a really big influence of wanting to do smart policing and intelligence-led policing and the move towards predictive analytics supports that.”

Analyzing data allows agencies to confirm what they already know and discover new information. In many cases it has become a critical tool in the abil- ity to anticipate crime and has created efficiencies. “Predictive policing never tells you exactly what’s going to happen, but it tells you there is a high likelihood of an incident based on prior events,” says Landau. “So what agencies are doing is using predictive analytics and positioning their resources, keeping the community safer by having police in an area where they are needed in a time when they are needed.” In the age of technology and

information-sharing, fusion centers and real-time crime centers have emerged nationwide serving multi-agency policing needs. These centers, in a simple sense, can gather information from many data- bases and analyze trends based on that data. In fact, your department may be one utilizing one such center right now. But what about smaller agencies that don’t have the resources to handle all of the big data? Technology is emerging to help even the smallest department man- age data in a usable way.

Big data at the patrol level Landau reports that today’s agencies are looking for their technology to do more. “Now that there is technology to cap- ture fingerprints and facial recognition, officers are asking, ‘How do we take that to the edge?’ he says. “They can take an image from a fixed camera and do facial recognition in a real-time crime center but they are asking for the ability to do some of that information right at the scene, at the field level.”

Smaller agencies need help turning data into actionable intelligence. Landau believes that as information-sharing and partnerships continue to increase in the future, solutions will emerge to get big data at the patrol level. “Imagine being in your patrol car, responding to a domestic,” he says. “Now imagine hav- ing the ability to use the technology on the laptop or tablet, already available in your car, to look across a half-dozen databases to build a profile of the situ- ation before you even get there.” In this example, Landau notes that an officer may be able to find a DMV photo, learn if there are any registered firearms, know if there is a restraining order or look at mental health. In the time that the officer is responding, they gathered a profile in one place. Using data at the patrol level may help officers better anticipate a situation.

Technology is constantly changing and improving, and predictive analytics is just one way law enforcement can do their jobs better with less resources.

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