Data mining technology
Once the value of analysis is understood, McCraw says the question is "How do you sift through the data and find the key elements that can help prevent an act of terrorism or crime?"
Law enforcement chiefs, sheriffs and other managers want to work smarter, cheaper and faster, says McCraw, former FBI assistant director of The Office of Intelligence.
"The way to do that is to do what the private industry has done and take advantage of the tremendous gains in information technology," he says, noting law enforcement should adopt the National Information Exchange Model for its records management systems.
"You want to be able to empower your personnel with the ability to find points of information they previously couldn't — and to find the links, the associations between data sets. That's very powerful."
Timely information also is key.
"You want to be able to exploit the data in your files as quickly as possible," he adds.
If it takes a week to show a supervisor the crimes that took place in one night, it's dated; it's not as useful as showing a supervisor last night's crimes, says Albanese, former chief of The International Center for the National Institute of Justice.
"The longer the time lag between the incident and being able to get it into a useable form, the less useful it is," he says, noting reports should be electronically entered (not handwritten) so data can be included in analysis and acted on quickly.
Using an analytical overlay or filter with remote data entry, an investigator could enter relevant information while at a crime scene and receive a rapid analytical response, McCue says.
Specialized databases can be created for crime or intelligence analysis. These databases might be offense-specific, such as a homicide or robbery database, or associated with a pattern of crimes. Records management databases generally were not made for analysis. Rather, McCue says they were created for case management and general crime counting.
Unfortunately, analytical software is not inexpensive and software specifically for data mining and predictive analytics falls into the high end of the price range, McCue points out. Agencies sharing information could benefit from pooling their financial resources for data analysis. Predictive analytics requires specialized software. Other data mining can be done without sophisticated software, but, she adds, "the software really helps."
Link analysis tools, used to identify relationships in data, such as telephone calls, can be an economical point of entry into data mining, she suggests.
Natural data miners
With today's friendly, commercial-off-the-shelf software packages, McCue believes most agencies are capable of analyzing their own data.
In fact, she says investigators and crime analysts are natural data miners. Based on her experience, she says it's far easier to teach them how to use data mining tools and apply them to law enforcement than it is to teach statisticians how to work in law enforcement.
For those somewhat afraid of numbers and run an incalculable distance at the mention of "statistics," McCue offers comfort: "Data mining is an intuitive process. It's not statistics."
What is important is knowing:
- what questions you want to answer,
- what you need to analyze the data and
- what you need the output to look like.
There also are rules of the road to avoid errors in analysis, but McCue reassures they're not very difficult.
"I think it's incredibly important that law enforcement agencies get over the fear and trepidation and technophobia or whatever they might have, and analyze their own data," McCue says. "Particularly in a specific department or region, agencies are going to have the tacit knowledge and domain expertise, and understand their data better than anyone else. I can't go in and learn a community to the depth they already know. They are going to have that domain or subject matter expertise on their community and department that's going to be necessary to evaluate the results and operationalize them effectively."