Associate Professor Eric Piza Zeros In On Meaningful Crime Reduction Stats.
By Mary Anderson
Today, it’s obvious how much big data is driving society—from the algorithmic trading on Wall Street to the movie picks your Netflix suggests—but you could say Eric Piza, Ph.D., was big data before big data was cool.
Fresh out of Rutgers University and pursuing his masters degree in criminal statistics, Piza crunched numbers for the Police Institute, a research center that provided analytics to various police departments and enforcement agencies in New Jersey. “As an undergraduate, I never thought that there was a role for research and academic scholarship in practical policing. The research center showed me that there was.” And so would begin his path to becoming an Associate Professor of Criminal Statistics at John Jay.
Piza joined the North New Jersey Police Department in 2007 as a Geographic Information Systems (GIS) professional just after Cory Booker had been elected Newark’s mayor on a platform of fighting crime. At the time, the city had notoriety as being one of the nation’s roughest. “Crime analysis became a key pillar of the agency,” says Piza, who worked closely with the city’s new police director. “Rather than waiting to respond reactively to crime stats, the police had a mantra to get ahead of the problems and deploy out-of-the-box solutions.” Not too long after, Newark would be recognized by the federal government as having the largest homicide reduction of any large city in the country. While Piza worked in Newark, he was studying to earn his Ph.D. in Criminal Statistics from Rutgers University School of Criminal Justice. He joined the faculty at John Jay in 2013, just as Booker became a U.S. Senator.
For a numbers guy, Piza approaches stats like something of a humanist. “If crime went down five or 10 percent, you have to ask yourself, is that a real, meaningful change?” asks Piza. And just as importantly, he wants to get at the why. Take for example, a two-part study he conducted on a foot patrol initiative in a high-violence area of Newark,comparing crime trends in the target area to comparable areas in other parts of the city. “We saw that foot patrols worked as a crime reduction tool, but exactly what was it about the police officers’ activities that led to that?” he says. He pored over the action reports from those foot patrol officers, classifying them as traditional actions (arrests, summonses) and what Piza referred to as “guardian” actions—meeting with business managers, doing bus checks, having informal contact with citizens that weren’t related to law enforcement. “What I found was that the guardian actions were actually strongly associated with the crime reduction and none of the law enforcement actions were,” he says.
Piza sees great potential for such police community relations and how big data can help. The case study on guardian actions in fact became supporting evidence in his latest work, Risk-Based Policing, a sort of playbook of best practices for police and policing scholars which he co-authored to help agencies address crime hot spots. “We’re to the point where we have the capabilities to expand the scope of research and look at some other important factors in policing,” he says. “If we do a great job of reducing shootings, but we don’t do a great job of having police officers interact with community members in a positive way, it doesn’t matter how low the gun violence rate goes. The key is turning big data into smart data,” says Piza. “It’s not just having a lot of data at your disposal, it’s parsing the data out so that it’s actually useful to decision makers.”
See Piza’s video at jjay.cc/ericpizavideo