By David A. Rivero, Chief of Police, University of Miami Police Department, Coral Gables, Florida; and John P. Pepper, Crime Prevention and Emergency Management Coordinator, University of Miami Police Department, Coral Gables, Florida
atrol has been, is, and will continue to be the backbone of college and local policing. Response to emergency and nonemergency calls to patrol officers for service is a primary component of policing or, more specifically, reactive policing. Most law enforcement commanders would say they try to eliminate the need for their patrol officers to be reactive through the institution of various proactive patrol initiatives. It’s a valid concept in theory and in proven practice: prevent the crimes before they happen so reactive, after-the-fact response becomes unnecessary. The result is fewer persons victimized, less financial and personal loss, less overall crime, and more police recognition and appreciation. Everyone wins.
Though many college and local law enforcement agencies are often busy with reactive call response, most agencies would cite that, at any given time, there is at least one officer available and not assigned to any call. The question then becomes how to best utilize these limited available patrol resources to proactively prevent future reactive responses.
Random patrol has long been an accepted allocation of these available patrol resources. The University of Miami in Coral Gables, Florida, sought a better and more effective methodology for preventing crime that is focused and targeted at the times and locations where crimes are likely to occur.
Crime is often cited as unpredictable. To some extent, it is, but to some extent, it is not. It is basically impossible to know exactly when and where a specific crime is going to occur without good intelligence. It is, however, possible to identify general locations and corresponding times when crimes may be more likely to occur. Some law enforcement agencies have recognized this through crime analysis and crime mapping techniques. At certain times, in certain areas, and under certain conditions, crime will occur at an above-average rate; often, such situational convergences are referred to as “hot spots.” Some agencies use this information to direct available patrol resources to hot spots during the times of high crime incidence. Specific planned events also recognized the need for additional attention from current patrolling officers, as more people means more potential for crimes. Often, crime analysis data and event scheduling data lead to the issuance of general be-on-the-lookout (BOLO) notices and watch orders for regular on-duty officers. These are effective guidance tools. At the University of Miami, it was decided to institutionalize daily guidance to the officers through patrol scripts.
The University of Miami used to have a random patrol philosophy. Few BOLOs and watch orders were issued. On occasion, a special crime suppression detail was instituted. However, as far as proactive patrols went, individual officers determined their own random movement and random stationing throughout the campus when not assigned to a call.
Crime data. Crime analysis, data-driven proactive patrol tactics, and the process known as CompStat (Comparative Statistics) 1 develop crime information. Initiating a smaller version of the process at the University of Miami assured that crime data were regularly developed and shared with officers. The officers consider this information as they go about their self-guided random patrols, but without structure, this process lacks aggregation and formal use.
Event data. On the event data side, a multitude of calendars were maintained by the university and most of its organizations, groups, and event-planning entities. When examined together, these calendars give a comprehensive view of just about everything that is happening across the entire campus on any given day and at any given time. A regular harvesting of these calendars literally could generate all event data for the whole community. However, no harvest or even review of these calendars was being done for patrol consideration.
Given the University’s relatively low crime rates and reasonable officer staffing levels, patrol officers had a significant amount of time each day to devote to their random patrolling. However, it was felt that this unassigned time was not being fully utilized. The proactive patrol methodology and its success or lack thereof was completely dependent on the officer’s knowledge of events, complaints, BOLOs, past crimes, and other miscellaneous data.
All of the officers had a piece of the puzzle, but none were looking at the complete puzzle. The pieces needed to be aggregated, supplemented, and redistributed. The real question became how to put both the crime data and the event data together in an effective and continuous manner that was standardized, readily available, and able to be analyzed.
The crime triangle has long been the most simplistic, standard model of how crime problems develop. When an offender and a victim (target) come together at a time and place (opportunity), there is a crime (see figure 1). Without an offender, there can be no crime. Without a victim (target), there is nothing to attract the attention of the offender. If offenders and victims (targets) never come together at a single time and place (opportunity), there is no potential for physical criminal action. All three aspects must be present to make a triangle.
Surrounding this basic crime triangle is an outer triangle of crime control, also known as interventions (see figure 2). A handler can supervise the offender in ways ranging from physical control to intervention programs. Managers make the time and place less conducive (less opportunistic) for criminal activity by adding countermeasures such as lighting, security hardware, or other crime prevention through environmental design (CPTED) features. A capable guardian, such as a police officer, can protect the victim or target and deter offenders. Any of these three interventions can negate the formation of one of the three necessary sides of the crime triangle, thus preventing crime.
Working with building and campus facilities managers to implement CPTED practices was high on the University of Miami chief of police’s to-do list, but within the scope of improving patrol, the capable guardians—patrol officers—were his main focus.
Formalized crime and event data-driven proactive patrol tactics would undoubtedly increase patrol officer effectiveness in preventing and reducing crime.
Bill Walsh, former coach of the San Francisco 49ers, was widely known for the “West Coast offense” he created, which transformed the team into a National Football League (NFL) dynasty. His secret was scripting the first 25 plays of each game. The idea of scripts had previously been utilized by fellow NFL coaches Paul Brown, Don Shula, and others. The scripts were basically a game plan; each play was specific and predetermined through study and analysis of the opponent prior to game time. “The whole thought behind ‘scripting’ was that we could make our decisions much more thoroughly and with more definition on Thursday or Friday than during a game, when all the tension, stress, and emotion can make it extremely difficult to think clearly,” Walsh wrote in his 1989 book Building a Champion: On Football and the Making of the 49ers.
The idea stuck, and has now become an NFL staple activity. “It got to the point where our offensive team really wanted to know those plays,” Walsh said. “The players really appreciate the idea that you’re giving them a [head] start on the game. You can sleep easier, you have more confidence going into the game, and you’re more at ease. For the coaches, you can feel comfortable that the game is almost on automatic pilot when it starts.”2
The same theory of scripting can be applied to proactive patrols. Crime data and event data can be obtained, aggregated, and plotted on a unique daily patrol script by the department’s crime prevention professionals and shift sergeants prior to the start of the shift. The patrol officers then know ahead of time who, what, when, where, why, and how proactive patrols need to be conducted for that shift. No longer would the key crime and event information pieces be scattered. No longer would proactive patrols be dependent upon each officer’s will to seek out and integrate the information into their activities. Everybody would be on the same page. Everything would be standardized. Every record would be detailed and available for further analysis. In addition, not only would a crime and event data-driven scripted patrol likely prevent crimes, but it would give the community the perception that police are everywhere. In essence, that perception would be correct.
Obviously, police work is to a large extent unpredictable, and success requires officer fluidity. In no way should the scripts take away officer discretion to follow an immediately arising hunch, nor completely remove an available resource from reactive response, nor prevent officers from doing all the good things they already do. Officers set out each day with a prescript game plan on how they are to patrol the campus, but adjustments to that script are made as necessary as the day develops.
The actual layout of the script needs to be as simplistic as possible, as well as immediately accessible to all patrol officers and sergeants. Through the use of existing computer programs and the university’s computer network, both were accomplished at no cost. The actual patrol script was originally laid out in a modified spreadsheet file. A script file, consisting of four columns for headings and unlimited rows for specific events, was made for every future shift of every future day. The column headings were Time, Location, Activity/Reason, and Disposition (see figure 3). Later, a fifth column was added for Type of Patrol, to designate such specifics as walking patrol, Segway patrol, bicycle patrol, vehicle patrol, or something special such as traffic direction. Selection was generally dependent on several factors, such as time allotted and the size of the area needing to be covered.
For each individual event, the activity/reason described the crime or event data an officer was to focus on during the listed time and within the listed location. At the completion of an event or the shift, the scripted officers update the disposition to document that the scripted item was completed without or with incident (listing case numbers); or, if the item was not completed, why. Such reasons could be anything from “dispatched to call reference x” to “self-initiated traffic stop.” Again, the goal of the script is not to take away officer discretion or remove an officer from call response.
The script file itself is stored on a shared or common hard drive within the university’s computer network that can be accessed by any police user with authorized credentials from any networked computer on campus. Generally, while actually on patrol, a printed copy is used and the dispositions on the electronic file are updated at the end of the shift.
The scripted patrols have been in place at the University of Miami since 2007. In this time, they have been directly attributed to solving several major crimes and indirectly attributed to preventing countless more. One of the greatest successes occurred in December 2009 when a serial vehicle burglar was caught. Through the use of crime analysis, surveillance cameras, and reports, it was determined that there were vehicle burglaries occurring in the same parking lots, around the same times, on the same days of the week, with a specific suspect and suspect vehicle often reported in the area. Commanders on patrol within the confines of the data spotted and identified the suspect who was responsible for a multitude of recent burglaries.
Other law enforcement agencies can enjoy these same improvements by working with the department’s crime prevention professionals and sergeants to continually refine the crime data collection and documentation process and the script assignment disposition execution and reporting process. Preparation of the scripts costs the agency nothing aside from personnel time. In addition, through the use of a recently hired student programmer, the department has been able to convert the script file into a unique script program. It works similar to a basic spreadsheet program but has several new features that assist in the preparation, the dissemination, and the follow-up investigations through the use of a flagging feature. The simplicity of the program allows for streamlined operation.
When the elements of the crime triangle present themselves, resources may be more effectively targeted at potential problems through the use of patrol scripts. The goal is to prevent crime from occurring and the measure of success is the reduction or elimination of crime. One view is to consider crime not as a measure of performance, but as a measure of performance failure—and use those failures to generate success. Scripted patrols have proven themselves to be more successful than random patrols within the university community. ■
1Other articles published by the Police Chief on CompStat include “The Caruth Police Institute: A Comprehensive Approach to Staff and Leadership Development,” by Robert C. Davis and Robert W. Taylor (April 2010); “Community Policing and CompStat: Merged, or Mutually Exclusive?” by Ken Peak and Emmanuel P. Barthe (December 2009); “Predictive Policing: What Can We Learn from Wal-Mart and Amazon about Fighting Crime in a Recession?” by Charlie Beck and Colleen McCue (November 2009); and “The CompStat Process: Four Principles for Managing Crime Reduction,” by Jeff Godown (August 2009). For information, visit www.policechiefmagazine.org.
2 Luis Valdes, “Bill Walsh, Peak Performance Case Study,” Squidoo, citing excerpts from an NFL Insider/NFL.com article from 2002 by Ira Miller, http://www.squidoo.com/billwalsh (accessed August 25, 2010).
Please cite as:
David A. Rivero and John P. Pepper, "Proactive Patrolling through the Use of Patrol Scripts," The Police Chief 77 (September 2010): 66–68, http://www.nxtbook.com/nxtbooks/naylor/CPIM0910/index.php#/60 (insert access date).