How 'Big Data' is helping law enforcement
Police agencies are using Big Data to make connections and detect patterns so they can prevent and solve crime
With rare exception, law enforcement agencies across the United States are faced with economic realities requiring them to do more with less. Most agencies are seeing increases in the numbers of calls for service while at the same time dealing with a shrinking number of officers on the streets.
Consequently, police administrators are both politically and practically forced to identify new strategies that maximize emerging technology solutions such as gunshot sensors, surveillance video, social media, and the like. Utilizing such information can help agencies put officers in a position to more quickly and effectively prevent — or at least respond to — criminal activities.
The trouble is, when you start trying to pore over every imaginable type of data available via those networks, you get into an almost inevitable “information overload” situation. That’s where the concept of Big Data comes into play.
What Is Big Data?
The term “Big Data” essentially means the ability to mine huge amounts of data from diverse sources, understand the accuracy and reliability of that data, and then make critical analyses — and sometimes difficult decisions — based on what you’ve learned.
This capability is comprised of complex software solutions running on supercomputers coupled with a carbon-based treasure trove of information known as the crime analyst.
In addition to the aforementioned technologies, “big data” solutions incorporate things like zoning applications to sell liquor — bars and convenience stores have a well-known gravitational pull for certain brands of criminal behavior, after all.
Building permits and permits for renovations may signal the likelihood of theft of construction materials or heavy equipment in the short term and a change in the demographics of a neighborhood in the longer term.
The planned opening of a high-end (or discount, for that matter) retail store and other factor(s) that might contribute useful insight to a plan or analysis of a problem can and should be included.
Census data can also provide significant insights into understanding a community’s needs.
By gathering and understanding these types of structured and unstructured data, crime analysts can help police leaders better understand underlying economic and demographic factors for a given area that might help explain why trends occur. Appropriate responses can then be crafted.
Setting Up the Right Solution
One of the leaders in “Big Data” solutions for law enforcement is IBM, which for several years has been developing ways for municipalities to keep their citizens safe. For example, IBM’s Crime Information Warehouse (CIW) marries the concepts of crime analytics and predictive policing, and the IBM Intelligent Operations Center for Smarter Cities is designed to provide a holistic view of information across city systems and services such as transportation, water and other utilities, building inspection, social services, and whatnot.
“The emergence of Big Data has become the newest natural resource of law enforcement,” said James Lingerfelt, who serves as a senior consultant with IBM’s Global Smarter Cities Team. “Big Data is helping police agencies all over the world make connections and detect patterns to prevent and solve crime.”
Lingerfelt explained that there are several key factors that departments need to consider when setting up a Big Data analytics capability.
“First, all analysis must be based on the department’s mission — possibly its redefined mission,” said Lingerfelt, whose 24 years with the Metropolitan Police Department in Washington, D.C. culminated in his assignment as the department’s chief information officer .
“Everything should be focused on understanding what is necessary to achieve the operational goals that contribute to mission accomplishment.”
Lingerfelt cautioned that a department has to determine whether it needs its own analytics group, or whether inter-agency collaborative models may be more appropriate.
“Finally,” Lingerfelt added, “if they do set up a group, how should it be staffed? How should it be placed within the agency and how should it be used? Ideally most personnel can use predefined reports and analytical tools to support their roles. The analysts should be reserved for the sophisticated and complicated challenges.”
The Human Element
This brings up an incredibly important issue: the role of the crime analyst. As Big Data technologies provide the officers on the beat with more tools, they are also making the crime analyst much more central to the investigative process. It also demonstrates the analytical skills police agencies seek in new investigative talent.
“Probably the most unsung hero in law enforcement, the crime analyst’s role is pivotal to and increasingly at the center of today’s police work. Not only has this role become exponentially more important in solving crime, but it also has evolved into one that relies on instincts, historical knowledge, and computer savvy,” Lingerfelt said.
Whether a municipality (or state) is dealing with public rancor over perceived pension issues or a reduced tax base — or both — police administrators must identify new strategies for supporting increased police operations at lower cost.
The future of law enforcement will likely necessitate a different mix of employees — including more civilian specialists, more contract employees and increased use of part-time workers and volunteers — as well as shared resources, outsourcing, and contract services.
It may initially be a difficult “sell” in the squad room, but the hiring of (or multi-jurisdictional sharing of) the crime analyst into the ranks will ultimately end up serving the agency’s crime-fighting objectives.
The use of technology to gather data — and the use of skilled crime analysts to make the data useful for decision support — will be fundamental for successful day-to-day operations as well as long-term strategic planning in law enforcement.