Making sense of big data to fight crime
With the right analytics tools in place, data — complemented with traditional crime-fighting methods — can be invaluable
By Tim Riley
Recently, the Metropolitan Police Department (MPD) released its latest crime statistics for the District of Columbia. While it saw a reduction in violent crimes, there was a significant increase in robberies. MPD has had success in combating the problem by increasing uniformed patrols, using plainclothes officers to stake “bait cars” and myriad other tactics to curb the increase in robberies.
In these types of situations, the challenge for any police force is targeting the right places. This goes beyond just neighborhoods — this includes specific streets, blocks, time of day, weather conditions, as well as other factors.
With the right analytics tools in place, such data — complemented with traditional crime-fighting methods — can be invaluable.
Sifting Sand for Gold
When used in the right context, such analytics technology can help law enforcement agencies make sense of the data. And it helps to derive real insight in a real-time or near real-time way to prevent crime — this is the power of predictive analytics.
When I served as a sworn officer for the Newport Beach, Calif., Police Department, the biggest innovation was computer-aided dispatch. The idea of sharing information beyond your own team let alone outside the department was a rare occurrence.
When I became CIO of the Los Angeles Police Department in 2005, the idea of harnessing data and sharing it internally, and with other police forces, was a new idea. During my tenure with the LAPD, we developed one of the first regional information sharing initiatives in the country. Information sharing is no longer an aspiration, but the table stakes for any successful police department.
Cities Large and Small
With this information, the LAPD could place resources in a potential robbery location. This led to identifying a suspect who was caught in the act. Twenty robbery cases were closed that day and would have otherwise remained unsolved without information sharing in place.
Technology is helping and reinforcing traditional police work, to speed the process and act as a force multiplier. It’s all about analyzing past events, recognizing trends and patterns, and rooting out commonalities and correlations. Technology is making things work faster and quickly bubbling up connections that would have taken days, weeks or months before. And it’s not just the larger cities like Los Angeles and New York that are complementing traditional police work with technology. Small- to medium-sized cities also understand the value of making their cities safer. And they are able to demonstrate a return on city expenditures, which over time, helps make communities safer.
An excellent example is the work that the Charleston Police Department is doing to reduce crime and increase the safety of its citizens. The department is piloting a predictive analytics system that will give its 400-plus officers a more holistic view into historical crime statistics and patterns in order to prevent crime before it happens.
This represents an interesting addition to policing practice. Departments constantly look for ways to better react and respond. Today, with the help of technology, law enforcement agencies also have a much better understanding of what patterns of crime are likely to happen and where, and are much more capable of deploying resources to head off those same crimes before they ever happen.
The job is still about catching bad guys. But today, it's also about stopping them before they commit a crime — to make our cities a little bit smarter and that much safer.
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