Stop Thinking, Just Do!

Summary

• Article Source: Walter L. Perry, Brian McInnis, Carter C. Price, Susan C. Smith, John S. Hollywood, Predictive Policing; The Role of Crime Forecasting in Law Enforcement Operations, 2013 [1].

Recommendations

Our conclusions center on advice to three communities: police departments (the buyer), vendors and developers, and crime fighters. Our advice centers on the role of predictive policing in the larger context of law enforcement operations.

Advice for Buyers (Law Enforcement Agencies)

All departments can benefit from predictive policing methods and tools; the distinction is in how sophisticated (and expensive) these tools need to be. In thinking about these needs, it is important to remember that the value of predictive policing tools is in their ability to provide situational awareness of crime risks and the information needed to act on those risks and preempt crime. The question, then, is which set of tools can best provide the situational awareness a department needs?

Small agencies with relatively few crimes per year and with reasonably understandable distributions of crime (e.g., a jurisdiction with a few shopping areas that are the persistent hot spots) are unlikely to need much more than core statistical and display capabilities. These tools are available for free or at low cost and include built-in capabilities in Microsoft Office, basic geographic information tools, base statistics packages, and perhaps some advanced visualization tools, such as the National Institute of Justice–sponsored CrimeStat series.

Larger agencies with large volumes of incident and intelligence data that need to be analyzed and shared will want to consider more sophisticated and, therefore, more costly systems. It is helpful to think of these as enterprise information technology systems that make sense of large data sets to provide situational awareness across a department (extending, in many cases, to the public). These systems should help agencies understand the where, when, and who of crime and identify the specific problems that drive crime in order to take action against them. Key considerations include interoperability with the department’s records management, computer-aided dispatch, and other systems; the ability to incorporate “intelligence” tips from officers (e.g., via field interviews) and the public; the types of displays (“dashboards”) and supporting information the system can provide; and, of course, the types of analyses and predictions the system can support and under what conditions.

Advice for Vendors and Developers

The list of questions for purchasers doubles as guidance on desired capabilities for those who develop predictive tools. Looking ahead, it could be useful to move beyond predictions to offer explicit decision support for resource allocation and other decisions.

We emphasize that predictive policing tools and methods are very useful, but they are not crystal balls. Media reports and advertisements can give an impression that one merely needs to ask a computer where and when to go to catch criminals in the act. We ask that vendors be accurate in describing their systems as identifying crime risks, not foretelling the future.

Finally, developers must be aware of the major financial limitations that law enforcement agencies face in procuring and maintaining new systems. Licensing fees of into the millions of dollars are simply not affordable for most departments. We suggest that vendors consider business models that can make predictive policing systems more affordable for smaller agencies, such as regional cost sharing.

Advice for Crime Fighters

Generating predictions is just half of the predictive policing business process; taking actions to interdict crimes is the other half. The specific interventions will vary by objective and situation. (A number of examples are described in Chapters Three and Four of this guide; core resources on interventions are the Office of Justice Programs’ CrimeSolutions.gov and the Center on Problem Oriented-Policing.) However, we have identified some promising features of successful intervention efforts:

• There is substantial top-level support for the effort.
• Resources are dedicated to the task.
• The personnel involved are interested and enthusiastic.
• Efforts are made to ensure good working relationships between analysts and officers.
• The predictive policing systems and other department resources provide the shared situational awareness needed to make decisions about where and how to take action.
• Synchronized support is provided when needed.
• Responsible officers have the freedom to carry out interventions and accountability for solving crime problems.
• The interventions are based on building good relationships with the community and good information (“intelligence”).

Designing intervention programs that take these attributes into account, in combination with solid predictive analytics, can go a long way toward ensuring that predicted crime risks do not become real crimes.

References

[1] Walter L. Perry, Brian McInnis, Carter C. Price, Susan C. Smith, John S. Hollywood, Predictive Policing; The Role of Crime Forecasting in Law Enforcement Operations, 2013.