Law enforcement agencies adopt new tools in an effort to be more proactive in getting resources where they're most needed.
Police can use data to 'change the environment,' says Berkow
On a Saturday afternoon last summer, Mark Rasch took his son to his baseball game at a park in Georgetown, Md. The ballpark is located in an area that has zone parking with a two-hour limit. Rasch was forced to park in a spot that was a bit of a hike from the ball field. He later eyed an opening closer to the park and moved his car there.
Game ended, Rasch packed up and was ready to pull away when he noticed a parking enforcement officer writing tickets. "I'm OK, right?" he asked, assuming that because he had moved his car she wouldn't know he'd been parked in the zone for longer than two hours.
Wrong. The officer not only knew that he had moved his car but when and how long he'd been parked within the zone. Fortunately, she didn't write him a ticket, as he was about to pull out. But the encounter left Rasch, who is a lawyer and a cybersecurity consultant, a little spooked at the realization of just how much information law enforcement is generating.
If there was a time when law enforcement agencies suffered from an information deficit, it's passed. Of the more than 18,000 law enforcement agencies across the United States, the vast majority has some form of technology for collecting crime-related data in digital form. The biggest city agencies have sophisticated data warehouses, and even the most provincial are database savvy.
So it's not surprising that law enforcement and criminal justice agencies are running into the same data-related problems that CIOs have been experiencing for years: ensuring data quality and accessibility, developing and enforcing standards for interoperability, and exploiting those digital resources in the most effective manner.
The era of data-driven law enforcement began in the early 1990s in New York City. It was there that police chief William Bratton sought to impress newly elected mayor Rudolph Giuliani with a radical approach to policing that came to be known as CompStat. CompStat put an emphasis on leveraging data--accurate, detailed, and timely--to optimize police work.
"Police departments are powerful collectors of data," says Michael Berkow, president of Altegrity Security Consulting, a newly launched division of security firm Altegrity. Before joining ASC last month, Berkow was chief of the Savannah-Chatham police department, and before that he was second in command to Bratton in Los Angeles after Bratton left New York to be chief of the LAPD.
Police departments were motivated to implement or upgrade IT systems by the Y2K frenzy, Berkow says. "By 2000-2001, everybody had some level of digital information," he says. That and CompStat led to a movement known by the initials ILP, which stand for "information-led policing" or, according to some, "intelligence-led policing."
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The concept is simple: leverage data to help position limited police resources where they can do the most good. It's an effort to be more proactive, to "change the environment," Berkow says, from the reactive, response-oriented methods of the past.
To a great extent, data is about the context of criminal behavior. "We know that the same small group of criminals is responsible for a disproportionate amount of crime," says Berkow. Police refer to that group as PPOs--persistent prolific offenders. Past criminal behavior, such as domestic violence, can be a strong indicator of potential future problems. When Berkow was chief in Savannah, his department went through data on recent homicide cases and noticed an interesting data point: Of twenty-some arrests for homicide, 18 of those people had prior arrests for possession of firearms. "We started this very detailed review of every aspect of our gun arrests," he says.
The Agile ArchiveWhen it comes to managing data, donít look at backup and archiving systems as burdens and cost centers. A well-designed archive can enhance data protection and restores, ease search and e-discovery efforts, and save money by intelligently moving data from expensive primary storage systems.
2014 Analytics, BI, and Information Management SurveyITís tried for years to simplify data analytics and business intelligence efforts. Have visual analysis tools and Hadoop and NoSQL databases helped? Respondents to our 2014 InformationWeek Analytics, Business Intelligence, and Information Management Survey have a mixed outlook.
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