In the weeks that followed, recriminations among various agencies in different states shined a very bright light on how this dangerous, serial offender had moved freely about the country, was caught and released repeatedly. The data was all out there, but Clemmons was out on bail because nobody had connected the dots.
The role of technology and data in crime fighting becomes more critical each year. When I was elected prosecutor in Indianapolis in 1979, I inherited an office dysfunctional in many ways but highly advanced in one -- the use of then-cutting edge information tools that allowed deputies to target career criminals and make use of every detail available about their previous conduct. The tools were a bit crude and the data a bit simplistic, but it helped focus time and attention where it was needed most.
For much of the next eight years we tried every system that seemed reasonably likely to increase effective targeting of resources, and we made notable strides. We launched the first large-city, fully integrated criminal justice system in the country, made rudimentary efforts at digital fingerprints and mugs shots, and more. The limitations on these efforts now seem glaring -- we were doing our best to use information, but were limiting ourselves to reacting after the fact, rather than using data to peer into the future.
Data-driven criminal justice advanced significantly during the 1990s. Led by Commissioner William Bratton and Mayor Rudy Giuliani, New York City became the model for data-driven policing through its Compstat system. Compstat brought a sea change in police management, driving up performance and driving down crime rates in a way unimaginable a decade earlier.
The Lakeview tragedy, however, illustrates that law enforcement must take the next step in digital crime fighting. To dramatically increase crime fighting efficacy, we must combine Compstat-like tools with more predictive measures. We must integrate data, not only between all facets of criminal justice (law enforcement, prosecution, courts, and corrections) but between jurisdictions. Such advancement will act as a force multiplier.
The criminal justice community has made steady progress towards the improved use of data. Yet until recently technology has limited the integration of these systems. In the prosecutor's office I ran back in the late 1980s, technical barriers precluded the sort of cross-platform data sharing required to realize the full impact of data analytics.
That has changed. The technical barriers are largely gone, and all that is required is the leadership and commitment to embrace the digital future.
Consider the humble police records management system. These systems have traditionally focused on the stand-alone automation of police processes, such as bookings. These systems remain underutilized, as much of the information known to police remains uncollected and thus worthless. A casual walkthrough of any police department will reveal massive quantities of "paper" in the form of notes, memos and e-mails not included in these records databases. These data sets contain working knowledge that must be tapped to make predictive policing a reality. Similarly, prosecutors, corrections and parole officials lack the search and analytic tools needed to understand crime and criminals in their jurisdictions.
The introduction of new technologies and business practices will reduce the time needed to produce, store and retrieve error-free information resulting in significant time and labor savings, thus freeing officers to engage in direct crime prevention activities.
The most powerful aspect of all this enhanced information, however, may be the ability to predict future behaviors. Internet sites know more about the shopping patterns of the average citizen than police departments know about their most serious offenders. L.L. Bean has the technology needed to predict which shoppers are likely to purchase a reindeer sweater, and criminal justice needs to likewise invest in determining which petty offenders are likely to become career criminals, which prisoners are likely to use drugs in prison, and which parolees are ticking time bombs.
This predictive effort would not replace crime analysts; it instead adds new capabilities from the growing field of predictive analytics.
Instead of being viewed as a function of a police department's clerical work, the records departments will be transformed into a predictive knowledge management center. The Chicago Police Department's CLEAR program shows how much can be accomplished in this area. The CLEAR Initiative is built around a cutting-edge data warehouse which contains approximately 10 million crime reports, offender records, mug shots and other information. CLEAR is focused on three major aspects of law enforcement: criminal justice integration, police management and community partnerships. Program features include the Automated Arrest Application, which processes arrests electronically; Mobile Identification Devices, which collect and transmit photographs and fingerprints of arrestees in the field; and Portable Data Terminals, which facilitate high-speed wireless access to CLEAR records. Streamlining the reporting burden on police officers has resulted in significant time and labor savings.
Over the last twenty years criminal justice agencies have implemented a series of enhancements that now if connected and applied will produce truly remarkable contributions to more effective operations. Digital prints and mug shots, advanced 911 and 311 information, Compstat, problem oriented policing and citizen Web 2.0 tools among other enhancements set the stage for breakthroughs. As more cities take these steps, a more productive police and prosecutorial effort will be the inevitable result, with the ultimate benefit to citizens: safer neighborhoods.
