This study was conducted as part of the Proactive Policing Lab, a project led by Professors Lum and Koper, at the Center for Evidence-Based Crime Policy at George Mason University. The lab is funded by the Laura and John Arnold Foundation.
One of the most significant reforms in modern policing has been the push for law enforcement to be more proactive in reducing crime or building trust and confidence with their communities. While there have been controversies surrounding certain types of proactivity such as stop, question, and frisk and zero tolerance policing, research continues to find that other proactive approaches can be effective in not only preventing crime and disorder, but also improving citizen satisfaction with the police.1
Nonetheless, little is actually known about the realities of proactive policing in the United States. Law enforcement has become much better at recording crime and calls for service with modern information systems. However, many of these systems are not built to measure officers’ activity when they are not answering calls for service. In other words, how, when, and to what extent officers engage in proactive activities is often not captured. Nor have law enforcement agencies systematically incorporated measures of proactivity into officer performance, rewards, assessments, or promotions. This information is important, especially as law enforcement agencies move toward more proactive engagement with community members to prevent crime.
The Proactive Policing Lab: Measuring Proactivity in Prince William County, Virginia
At the Center for Evidence-Based Crime Policy at George Mason University, Professors Lum and Koper have established the Proactive Policing Lab—funded by the Laura and John Arnold Foundation—to dive deeply into basic questions about police proactivity. This article shares some preliminary findings from the Proactivity Lab based on fieldwork conducted with the Prince William County, Virginia, Police Department (PWCPD), an agency serving a rapidly growing suburban population of 450,000, located just outside of Washington, DC. The authors spent more than 120 hours in the field with 55 officers and also analyzed computer-aided dispatch (CAD) data to examine how PWCPD officers define and practice proactive policing.
The preliminary findings were illuminating and provide important lessons for other agencies. When describing what proactivity meant to them, officers most often cited traffic enforcement (79 percent), patrolling high-crime places (55 percent), looking for suspicious activity (50 percent), or looking for illicit drugs (43 percent). Other mentioned activities included providing visibility (29 percent), performing foot patrols (26 percent), and carrying out checks of parks or schools (20–24 percent). Only about half of the officers (48 percent) said their supervisors expected them to be proactive, while over a third mentioned an implicit understanding within their squad culture that proactivity is simply what good officers do. Over a third also said that expectations for being proactive depended upon particular supervisors or shifts. Finally, many officers said that while they were not formally recognized for being proactive, they did feel rewarded “informally” (44 percent) or “intrinsically” (24 percent).
Were officer perceptions matched by the observations and data analysis? In the observations, which were conducted primarily during daytime hours with officers in a central and more populous area of the county, 164 instances in which officers acted proactively were recorded. In total, these activities accounted for 18.5 percent of the officers’ observed time. The observations suggest that officers’ time for proactive work might be more limited than commonly thought, particularly in suburban jurisdictions where officers’ travel time to and from calls and events is substantial or where the population is increasing. Hence, using resources in the most optimal and targeted ways can be especially important in places like Prince William County.
The observations revealed that the two most common proactive activities officers engaged in were patrolling areas that they considered high-crime places (37 percent) and traffic enforcement (33 percent). Activities specifically focused on engaging with the community occurred in just 2 percent of the proactive activities observed. Officers were most often prompted to carry out proactivity by something they immediately saw or noticed (35 percent) or by their previous experiences, particularly in a place of interest (34 percent). None of the proactive activities observed were prompted by any formal intelligence or crime analysis, nor by specific information provided by a supervisor. Choices about when, where, and how to be proactive seemed largely ad hoc and discretionary. This is likely a common situation in many law enforcement agencies, even those with crime analysis units.2
Also important, 60 percent of officers’ proactive work was not officially recorded. This was especially true for place-based patrols, which were also found to be shorter (about 4–5 minutes on average) than the 10–15 minutes that is considered optimal for visits to hot spots.3 This finding that a great deal of proactivity is not being tracked or recorded is significant—and again, a finding that is suspected to be common among agencies. Yet, if law enforcement agencies want to increase proactivity, manage it in the most optimal ways, and measure its benefits and costs, tracking it is essential.
An analysis of CAD data mostly supported the researchers’ observations. Of the CAD events identified as proactive activities, most (74 percent) were focused on traffic enforcement. Place-based patrol was often not recorded. A geographic analysis of proactive activities recorded in the CAD system against calls for service and traffic crashes suggests that officers generally focus their efforts in high-crime and traffic problem areas, but further analysis is needed to determine how accurately the activities target the most serious micro–hot spots. The use of analysis could sharpen this deployment. PWCPD will be making new predictive analytic and crime mapping tools available to officers, crime analysts, and to the public at large in the near future to facilitate officer proactivity. However, providing officers with that information and motivating them to use it strategically can be challenging if officers value high levels of discretion.
In many agencies like PWCPD, officers are trying to be proactive and are personally motivated to do so. This a positive development in U.S. policing as proactivity is important to an agency’s ability to control crime and maintain trust and confidence with community members, when applied properly. Helping officers to expand their proactivity tool kit and better focus their efforts in ways that are lawful can not only help to reduce calls for service, but might also help to improve officer safety and strengthen relationships with community members—all of which might also improve officers’ job satisfaction. At the same time, major obstacles can exist to law enforcement’s interest in becoming more proactive. Given these findings, the following action items are suggested:
•Provide officers with training, mentoring, and guidance in expanding their proactivity toolkit, including how to conduct basic crime assessments of their area, to engage in problem-solving, and to optimize their deployment approach. Free ideas officers can use are available in the Evidence-Based Policing Matrix, the Evidence-Based Policing Playbook, the POP Center guides, or the Case of Places Guide.4
•Build systems or codes to more formally record proactive activities through the CAD. Use this information to optimize the types and quantities of officers’ proactive efforts.
•Establish managerial and promotional systems that link officer activity in between calls for service with rewards and promotions to advance police proactivity.
•Use crime analysis to guide officers in focusing their proactive efforts on the places, people, times, and situations that pose the greatest risks for crime and other problems.
1Cynthia Lum and Christopher S. Koper, Part II Evidence-Based Approaches to Policing, chaps. 4–7, in Evidence-Based Policing: Translating Research into Practice (Oxford, UK: Oxford University Press, 2017).
2Christopher S. Koper et al., Realizing the Potential of Technology in Policing: A Multisite Study of the Social, Organizational, and Behavioral Aspects of Implementing Police Technologies, Final report to the National Institute of Justice (2015); Cynthia Lum, Christopher S. Koper, and James Willis, “Understanding the Limits of Technology’s Impact on Police Effectiveness,” Police Quarterly 20, no. 2 (June 2017): 135–163.
3This principle is known as the “Koper Curve Principle” for hot spots deployment. See Christopher S. Koper, “Just Enough Police Presence: Reducing Crime and Disorderly Behavior by Optimizing Patrol Time in Crime Hot Spots,” Justice Quarterly 12 (1995): 649–672.
4Center for Evidence-Based Crime Policy, “Evidence-Based Policing Matrix,” George Mason University (GMU); Center for Evidence-Based Crime Policy, The Evidence-Based Policing Playbook, GMU; Center for Problem-Oriented Policing, “POP Guides;” Center for Evidence-Based Crime Policy, Case of Places Guide, GMU, More ideas can be found in Lum and Koper, Evidence-Based Policing: Translating Research into Practice.
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Please cite as
Cynthia Lum et al., “Measuring Police Proactivity,” Research in Brief, The Police Chief (August 2017): 16–17.