IACP on Leadership Interview

IBM's Fay Helps Police Go from Reactive to Proactive with Predictive Analytics

Cynthia “Cindy” Fay has a passion for helping law enforcement and keeping the public as safe as possible. She has been with IBM for nearly five years, serving as sales manager for crime prevention and prediction for Big Blue's SPSS Modeler predictive tool. When asked why she chose this specific niche, she was quick to answer: “Why not? You've read the news. They need the help. Police officers have the experience, and they certainly know where to go to look for criminals. But why not provide them with a solution that makes them even better? So, yes, I have a real passion for that. When you walk down the street, I know that if I sold someone my solution, you are safer because of it.”

Whip-smart and confident, she has had several opportunities at IBM to move into other sectors like retail and healthcare. “I won't move,” she declared, “and part of that is I'm just as passionate about what law enforcement does every day as they are. The best advice I've ever gotten is, ‘You just have to be one of them. You have to love what they do and be as passionate about it as they are.’ And I'm there. I'm totally there! I know that when I sell someone my solution, the streets are going to be much safer.”

A former executive at W.W. Granger, where she ran government teams there for almost four years, Fay's outgoing personality has served her well, considering that a major part of her job entails prospecting to law enforcement agencies. She and her colleagues have a presence at numerous trade shows each year, and they also put on workshops that IBM invites various police departments and officials to participate in.

“We do a lot of marketing to law enforcement,” she said. “We find out what they are doing today, what they are using today, and whether they are doing anything predictive. If they're not, then we ask them, ‘What keeps you up at night? If you could solve one thing in your agency, what would that be?’ And then we talk about the solutions that we have that would help them with that and how easy it is to get started. They are very relationship-oriented. I really enjoy going to the conferences, talking with law enforcement, and hearing what they're up against. It's a good feeling knowing that we can help them with their challenges.”

She also touts past success stories. For instance, the Tennessee Highway Patrol came to Fay and her team looking for help getting the state’s DUIs down. Fay recalled, “It took us some time to work it all out, because they were the first highway patrol to want to tackle this problem in this way. Today, they're getting amazing results. As a result, they're also seeing their seatbelt citations increasing because they are more focused, pointed, and targeted on where they need to be at a certain time and date. The next area they are going to take on is distracted driving. Where do we need to be? Where are our texters going to be? Where are the people who are on the phone who really need to pay attention?”

SPSS Predictive Analytics crime prediction and prevention software helps law enforcement gather data from sources like computer-aided dispatches (CADs) and record management systems (RMS), as well as so-called “unstructured” data from the Internet, such as weather patterns and upcoming concerts and sporting events. This combination offers police a more comprehensive picture of what lies ahead. The software then goes one step further with tools that help police departments decide how and where to best allocate resources and devise new enforcement strategies based on the trends identified by the technology.

A number of jurisdictions have been able to realize some impressive gains from their use of the software. The city of Memphis, Tennessee, for instance, registered a 28 percent reduction in serious crime. Lancaster, California, reduced its crime by 42 percent over a four-year span.

Acceptance of predictive analytics software has come a long way in just the short amount of time Fay has been on the job. When she first started at IBM in 2011, many police departments didn't even know what such programs were. “They all scoffed,” she said. “Now, when you say it, they listen. They come to the booth and they want to talk about it. They get it. The younger chiefs who are coming in, lots of them had to do papers on predictive analytics in grad school. It's just becoming more and more part of the conversation. IBM has been talking about it for so long, and we've just been able to market it very well.”

She continued, “A lot of departments are putting on additional police officers to combat their local crime. One of the things we tell commanders is that you are adding additional police, but you're adding a lot of rookies who won't have your 30-year veterans’ experience and gut feels. What our solution will do is help them get up to speed faster on where they should go and where they should be. We have had some good conversations with the chiefs about using the software just for that.”

Looking ahead, she hopes there will be greater communication and collaboration between state agencies and local government agencies. It would certainly make her job a bit easier. “If I could wave my magic wand and change anything,” she remarked, “I would have state departments talking to local departments. So that when the courts parole a prisoner, that data is passed to the police departments. That way, they'll know what they're walking up to when they get called out to a 9-1-1 call. I've found that a lot of departments work in silos, and they don't pass information. How powerful would it be if they all just talked and shared information?”

She and IBM are also looking forward to greater acceptance of cloud technology. “We only have one product right now that is in the cloud as far as predictive analytics,” she concluded. “So, we're looking at adding a lot of our products to the cloud. Law enforcement will be able to get up and running much faster. But there will be some resistance to overcome. I was just at a police conference last week. Sometimes it's hard getting them to see that we can help them [with the very latest technology]. We're coming out with a solution that's on the cloud now, and they are very skeptical about putting any of their data out there like that. They are still very much, ‘I want to keep it in-house.’ But we'll show them the evidence.”

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