Seattle’s Predictive Policing Program

By Jessica Casey • April 11, 2013

Remember Moneyball? The book published in 2003, written by Michael Lewis? It argues that the Oakland A’s used data collected at the 161 games each season, year after year, to identify new indicators of success and completely revamp their scouting strategy.

By using readily-available time series data and statistical analysis it was determined that on-base percentages and slugging percentages were better indicators of offensive success than runs batted in and strikeouts. Using these indicators, the Oakland A’s changed their scouting strategy to secure undervalued players without breaking the budget. It changed baseball forever.

If sports teams have been using data to make predictive decisions and get more for their dollar, then why couldn’t local governments do the same thing? In fact, cities are already using predictive analytics to inform a number of decisions. Cities like Santa Cruz, Los Angeles, Seattle and others are successfully using existing data to fuel predictive policing analytic software.

Predicting criminal activity has been a major focus of the U.S. Criminal Justice System. One new approach is Intelligence-Led Policing (ILP). After 9/11, Intelligence-Led Policing kicked off as an approach for proactive policing, rather than reactive, by using risk assessment and risk management approaches.

Intelligence-Led Policing did not replace the community involvement and program-solving approaches of community policing models; it extended them to include research-based approaches, information and communications technology, and increased information intelligence in support of collaborative, multi-jurisdictional approaches to prevent crime, as reported by Charlie Beck and Colleen McCue in their article, “Predictive Policing: What Can We Learn from Wal-Mart and Amazon about Fighting Crime in a Recession?”

Designed at UCLA, the software is built on the same model used for predicting aftershocks from an earthquake. In Los Angeles, the software was piloted for one year and reduced crime by 13 percent, as reported on GeekWire. By generating prediction boxes that are as small as 500 square feet on a patrol map, officers are told to patrol the boxes that are flagged as potential crime areas in their spare time. As of July 2012, the program was implemented in five LAPD divisions that cover 130 miles and 1.3 million people.

The idea here is that police departments have a wealth of data that has been collected over a number of years for every neighborhood and block of a city. By using that pre-existing data that can tell a story about past experience, police cruisers can patrol areas that match the same characteristics to prevent crimes from occurring.

Predictive analytics also goes beyond pre-existing data, focusing on predicting future probabilities and trends based on observed events. It is a multi-perspective approach. Time Magazine reports that predictive policing uses a computer program developed by mathematicians, anthropologists, and criminologists, that integrates reasoning, pattern recognition and predictive modeling associated with domain knowledge.

Predictive analytics is about empowering cities to be proactive, instead of reactive, while still providing quality services and making progress towards goals and objectives.

In summer 2012, Seattle had an unexpected uptick in gun-related crimes. The city increased the number of officers patrolling the streets. As a result, the gun-related crimes decreased, but at high cost to the city. In response, the city began to consider predictive policing software.

In late February of this year, Mayor Mike McGinn announced that Seattle implemented predictive policing software in two precincts. The software uses data from 2008 to predict potential crime and it is estimated to be twice as effective as a human data analyst working from the same information.

By first piloting the software in two of five precincts and focusing on property crimes, such as theft and vehicle crimes, the plan is to revise and adjust the algorithm and methodology before broadening the software’s predictions to gun violence. Lt. Bryan Grenon, from Seattle’s West Precinct, comments, “As a community, we wanted to proactively target gun violence. We hope to implement that this summer.”

Seattle Police Department East Precinct
Seattle Police Department East Precinct

About the Author

Jessica Casey

Jessica is the Associate Director for the Project on Municipal Innovation Advisory Group. She recently served as the director of policy development and implementation for the Massachusetts Executive Office of Housing and Economic Development, where she led research and strategic policy development in the areas of housing production and economic development. Formerly, she worked with the Kitty & Michael Dukakis Center.