When Larry Godwin took over as director of the Memphis Police Department (MPD) in 2004, crime across the metro area was surging, and city leaders were growing impatient. “The mayor told me I want this crime problem fixed,” recalls Godwin, a 38-year veteran of the MPD. But the new director understood that a business-as-usual approach to crime fighting would no longer be good enough. Early on in his tenure, Godwin convened a meeting of top law enforcement experts to formulate a fresh strategy to turn the tide in the city’s crime war. Among the participants in this mini-summit was Dr. Richard Janikowski, a professor of criminology at the University of Memphis, who specialized in using predictive analytics to better understand patterns. Fighting Crime with Analytics Janikowski proposed the idea of mining MPD’s crime data banks to help zero in on where and when criminals were hitting hardest and then “focus police resources intelligently by putting them in the right place, on the right day, at the
right time.” By doing so, he said, “you’ll either deter criminal activity or you’re going to catch people.” The idea made sense to Godwin and in short order the MPD and the University of Memphis— along with Project Safe Neighborhoods—teamed up in a pilot program that later became known as Operation Blue CRUSH, or Crime Reduction Utilizing Statistical History.

Questions for Discussion
1. How did the Memphis Police Department use data mining to better combat crime?
2. What were the challenges, the proposed solution, and the obtained results?