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Data Systems for Policing in the 21st Century

Facilitating the Implementation of Incident-Based Data Systems

Don Faggiani Bruce Kubu Ramona Rantala

This project was funded by the Bureau of Justice Statistics under grant 2000-RG-CX-K003. The points of view expressed here are those of the authors and do not necessarily represent the official position of the Police Executive Research Forum or Bureau of Justice Statistics. Police Executive Research Forum, Washington, D.C. 20036 Published 2005 Printed in the United States of America ISBN 1-878734-81-4 Library of Congress Number 2005903798 Cover art and interior design by Jack Ballestero.


Foreword-- i Acknowledgments-- iii Introduction-- v Chapter I. Strategic Information Systems for Policing-- 1 Craig Fraser, MAXIMUS Chapter II. Implementing an Incident-Based Reporting System Compatible with the FBI's NIBRS Standards-- 13 1. Implementing NIBRS in Kansas-- 15 Mary Ann Howerton, Kansas Bureau of Investigation 2. NIBRS in Memphis-- 19 Walter E. Crews, Director of Police Services, City of Memphis Police Department 3. The Implementation of National Incident-Based Reporting by the Fairfax County (Virginia) Police Department-- 23 Colonel J. Thomas Manger, Chief of Police, Fairfax County Police Department 4. Incorporating NIBRS into the Custom Development of an Offense Reporting and Records Management System in Charlotte-Mecklenburg-- 29 Veronica L. Sorban, Charlotte-Mecklenburg Police Department

Cbapter III.

Making Sense of the Data: Providing Information for Problem Solving -- 33

1. The Measurement of White-Collar Crime Using Uniform Crime Reporting (UCR) Data-- 35 Cynthia Barnett, Federal Bureau of Investigation 2. Analysis of Motor Vehicle Theft Using Survival Model-- 45 Cynthia Barnett, Federal Bureau of Investigation 3. Mapping NIBRS Data: Using Massachusetts' Enhanced NIBRS for Examining Heroin Use, Sales, and Distribution across Multiple Jurisdictions-- 53 Dan Bibel, Massachusetts State Police; Don Faggiani, PERF; and Lindsay Robertson, Wyoming Statistical Analysis Center Conclusion­ 67


This guide is divided into five sections. The Introduction provides a general overview of the National Incident-Based Reporting System (NIBRS). The Bureau of Justice Statistics (BJS) funded a project that led to a National Symposium on NIBRS, and the publication of this resource manual. The remainder of the guide draws upon the papers presented at the conference. In all, there were 30 presenters at the conference, and selecting papers for this resource guide was not easy. A panel comprising PERF, FBI, and BJS staff, as well as several symposium participants, selected 10 presentations for inclusion in this resource guide. Seven of the ten presenters provided written versions of their presentations. The result was the seven papers that follow. Individually, these papers tell an interesting story, and as a whole they provide a fairly comprehensive picture of the process involved in making the decision to implement a NIBRS-compatible system. They describe the trials and tribulations that go along with that decision and illustrate how information from the new system can be used to solve crimes in the community.





The project and this resource guide were made possible thanks to the foresight and leadership of Jan Chaiken, former Director of BJS; Larry Greenfeld, Director of BJS, for providing continued support for this project; and Ramona Rantala, BJS statistician and project manager, who provided the guidance needed to bring this project and this resource guide to fruition. What follows is a list of individuals1 who had a direct impact, through their time and efforts to prepare and present a paper at the symposium or their behind-the-scenes work that contributed to the success of the symposium and the content of this resource manual. To all these people the authors are extremely grateful.

BJS Jan Chaiken Larry Greenfeld Ramona Rantala Broomfield, CO PD Diana Wilson Charlotte-Mecklenburg, NC PD Veronica L. Sorban City of Memphis, TN PD Walter E. Crews Wink Downen Connecticut State Police Gary Lopez David Porteous Fairfax County, VA PD Bill Heffron J. Thomas Manger FBI Yoshio Akiyama Cynthia Barnett Ken Candell Chris Enourato Victoria Major Harlin McEwen Robert Morrison Jim Noonan William Temple Susan Testman Dave Walchak JRSA Stan Orchowsky Lisa Walbolt

Kansas State Police Mary Ann Howerton Massachusetts Statistical Analysis Center Diana Brensilber Massachusetts State Police Dan Bibel New York Dept. of CJ Services Jan Whitaker Newport News, VA PD Mark Calhoon PERF Craig Fraser Lorie Fridell Judy Lim Chuck Wexler Suffolk County, NY PD Bill Murphy UVA Don Brown Jason Dalton Vail, CO PD Kris Cureau Greg Morrison Vermont SAC Bill Clements Vermont State Police Max Schlueter Wyoming Statistical Analysis Center Lindsay Robertson

1 Individuals may have changed agencies since the time of the symposium.


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Measuring crime in the United States is a challenging endeavor. Originally designed as a resource strictly for use by law enforcement, the Federal Bureau of Investigation's (FBI's) summary Uniform Crime Reporting (UCR) system has served as the primary source of information on crime in the United States for more than 70 years. The aggregate data produced through the collection of summary UCR provides information on crime trends and rates to local, state, and federal law enforcement agencies. Law enforcement, the news media, and others began to use the figures produced by summary UCR to compare crime between cities, counties, and states. The effect of summary UCR reporting was so significant that in many places, the success or failure of law enforcement executives was defined by the fluctuation of crime rates within their jurisdiction. By 1994, the data reported through summary UCR were being used by federal agencies to determine funding levels for states and communities through the Local Law Enforcement Block Grant Program. Funding decisions to localities were based on the rate of violent crimes reported to the FBI through the summary UCR program. As the use of the summary UCR system grew, so too have the system's limitations. First, the structure and content of the UCR remains virtually unchanged from its original design in the late 1920s. While sufficient in the early part of the 20th century, by the mid-1980s technological advances and the need for more detailed crime-related information outgrew the intent defined by the system's original designers. A second problem with the summary UCR system is that it counts only the most serious offenses in an incident, and collects few other details. The law enforcement agencies collecting the data have long

lamented the difficulty of collecting these data, and have complained of their limited utility for solving crimes and informing public policy. For example, basic elements of a crime, such as the date and time an incident occurred, were not designed into the summary UCR reporting process. Victim-specific information was also omitted,1 making it impossible to identify the characteristics of high-profile issues, such as juvenile or elderly victimization, domestic violence, or the influence of drug or alcohol involvement. In September 1982, a special Bureau of Justice Statistics (BJS)/FBI task force completed a study that reviewed the current crime reporting systems and, based upon what they found, made suggestions for improvement. After nearly three years of meetings and conferences, the BJS/FBI task force released a document called The Blueprint for the Future of the Uniform Crime Reporting Program. This document essentially contained the blueprint for the National Incident-Based Reporting System (NIBRS). In the years that followed, the FBI began a program to implement NIBRS with the expectation that it would eventually replace the summary UCR system as the primary source for crime information in the United States. Many of the limitations of the summary UCR system are not present in NIBRS.

Structure and Benefits of NIBRS

NIBRS significantly altered the way law enforcement agencies reported crime to the FBI. NIBRS allows agencies to collect data in which the criminal incident, rather than a single offense within the incident, is the basic unit of measurement. Within each incident a variety of facts on victims, offenders, arrestees, offenses, and properties are collected, allowing for the possibility of true policy-relevant analysis.



Specifically, the NIBRS system provides incident-level details on 22 different categories of crimes covering 46 different offenses. A total of 53 different data elements are included in a NIBRS report, including basic incident details--such as arrest date, time, and type of arrest (onview, summons-based arrest, summons issued, etc.)-- along with many other incident-level factors. NIBRS also provides details specific to all individual offenses reported within an incident, demographics on all victims, offenders, and persons arrested, as well as details on property involved. While NIBRS was designed as a national crime database, it was also designed to replicate the basic foundation of a local law enforcement records management system (RMS). The intent was to provide a crime information tool with standardized data elements that are both useful at the local level and consistent across all law enforcement jurisdictions. The resulting data set is an invaluable asset to local law enforcement agencies, policy makers, other governmental organizations, and criminology researchers.

The Police Executive Research Forum (PERF), with funding from BJS, conducted an 18-month project designed to provide law enforcement executives with information to assist in the transition to an RMS compatible with the FBI's NIBRS reporting requirements. The project had two objectives: The first was to structure a conference based exclusively on the FBI's NIBRS program, and in July 2001, PERF hosted a conference titled "Data Systems for Policing in the 21st Century: Facilitating Local Law Enforcement Implementation of Incident-Based Data Systems Compatible with the FBI's Reporting Requirements." The conference committee's intent was to provide a forum where local, state, and federal decision makers could listen to a variety of presentations focusing on issues critical to the design, implementation, and uses of RMS that are compatible with the FBI's NIBRS reporting requirements. Presenters included law enforcement executives from major police departments, as well as representatives from the FBI, BJS, state police, and other criminal justice agencies. Local agency crime analysts and academic researchers presented papers on the uses of NIBRS for crime analysis and policy creation. The conference also included papers on a wide variety of topics focusing on such issues as the following: · Making the transition to a new RMS that is compatible with the FBI's reporting requirements for NIBRS, · Designing a records management strategic plan to meet agency information needs, · Employing incident-based reporting systems to facilitate effective local and regional analysis of crime, and · Using NIBRS for informing public policy and funding. The second objective of the BJS-funded project was to publish a NIBRS Resource Manual to provide law enforcement executives and other decision makers experiential information from police executives who have been through the NIBRS implementation process. Our hope is that readers will benefit from learning about these experiences with the implementation process.

Transition to NIBRS

For local law enforcement agencies, the transition to a NIBRS reporting system can be expensive, timeconsuming, and frustrating. In many agencies the entire RMS must be replaced. This can be a costly undertaking and may take years to complete. For other agencies, the transition can fall somewhere between a slight modification to a major overhaul of an existing system. There are more than 17,000 law enforcement agencies in the United States, and the responsibility associated with moving to a NIBRS reporting system, including the costs, falls to the individual departments. Therefore, the decision to move to a NIBRS-compatible RMS requires careful preparation, beginning with a well-defined strategic plan. Every step of the process should be guided by an understanding of all possible outcomes. The reality is that many law enforcement agencies rely upon partial or sometimes biased information to guide the implementation process. To address this vacuum BJS and the FBI developed the Handbook for Acquiring a Records Management System (RMS) that is Compatible with the National Incident-Based Reporting System (NIBRS) available online at http://www.fbi/ucr/nibrs/manuals/handbook.pdf for agencies to reference.

Overview of the Manual

The manual consists of three chapters. Chapter I consists of a single paper, a somewhat modified version of the presentation by Craig Fraser, Ph.D., former Director of


Management Services with the Police Executive Research Forum. Dr. Fraser's presentation on Strategic Information Systems for Policing set the tone for the conference. He approaches the decision-making process from an organizational perspective. His assertion is that if you ask the right questions, you will find the right answers. Dr. Fraser's premise is that a strategic information system is one that goes beyond merely collecting data; it is aligned with the goals of an organization and is designed to assist the organization in meeting its goals by improving system performance. For law enforcement executives, it is critical to approach the decision to implement a new RMS asking the right questions, especially when this decision could draw a considerable amount of money from their generally tight budgets. Chapter II includes four papers representing both state and local law enforcement agencies that recently made the transition to NIBRS reporting. The papers demonstrate the diversity of experiences encountered by each of these agencies. The first paper, by Mary Ann Howerton with the Kansas Bureau of Investigation (KBI), details the KBI's challenging implementation process. Kansas was one of the first state programs to implement an incident-based system, well before the FBI and BJS released their blueprint for NIBRS. In their effort to transition from collecting data through paper submissions to an electronic submission system, they encountered numerous problems, which forced them to rethink their entire data collection procedure. In February 2001, almost 20 years after the introduction of their first system, they were certified by the FBI to report NIBRS data, only to be faced with another delay just one month later. Implementing a NIBRS-compatible RMS in a large metropolitan police department is not easy. The second paper, by Walter E. Crews, Director of Police Services in Memphis, Tennessee, details the arduous 3-year transition to incident-based reporting that the City of Memphis's Police Department went through. With a population of more than 650,000 people, Memphis is one of the largest jurisdictions to report NIBRS data. Tennessee, like several other states, mandated that all law enforcement jurisdictions convert to incident-based reporting. The state had already developed an incident-based data repository called the Tennessee Incident Based Reporting System (TIBRS). In addition to the mandate to convert to TIBRS, Tennessee enhanced their state-level data repository to include 22 additional data elements not

required by the FBI. Director Crews offers excellent insights and advice for other law enforcement executives, particularly in medium- to large-sized agencies, who are in the process or are approaching the transition to an incident-based reporting system. Fairfax County in Virginia is also one of the largest jurisdictions reporting NIBRS. In the third paper, Colonel J. Thomas Manger, Chief of Police, leads readers through the process encountered by the Fairfax County Police Department during their transition from a mainframe police RMS to a system that would support NIBRS reporting. Particularly important in this process was the constant communication with all persons who might be affected by the system change. The paper recounts each of the problems encountered by the Fairfax County Police Department and how they were resolved. Additionally, Manger highlights the fact that by creating their own NIBRS application, the department took a risk but was also able to customize the system to suit their specific needs. Overall, Fairfax County's NIBRS implementation has thus far been successful. The last paper in Chapter II, by Veronica Sorban of the Charlotte-Mecklenburg Police Department, provides a more technical look at the achievement of a custom-built RMS. The department began building the system in 1998, following the initiation of a new technology plan that called for integrated databases that would support crime-based problem solving. One of the most prominent features of their system was the capability for officers to both collect and enter a report in the field. This was accomplished using laptop computers and a digital wireless network. By March 2001, the system was on-line and functional, and approximately 1,800 officers and civilians had been trained to use it. The paper ends with a valuable reminder: while the addition and maintenance of an incident-based reporting system will no doubt add to the complexity of the day-to-day work in law enforcement agencies, it also serves to increase the effectiveness of law enforcement on local, state, and national levels. Chapter III of this manual gives readers an idea of what the data provided by the NIBRS system can do when it is used in a practical manner. The chapter consists of three papers. Two of the papers are from the FBI's Criminal Justice Information Services (CJIS) Division. These papers by Cynthia Barnett are part of the FBI's NIBRS publications series. In the first paper the author notes the shortcomings of summary-based UCR data for


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understanding white-collar crime. She notes the added advantages the NIBRS data provide for defining and describing these crimes. The second paper was originally published in Crime in the United States for the year 2000 and deals with understanding motor vehicle theft and recovery patterns. Using 1999 NIBRS data the authors demonstrate the usefulness of this rich data source to estimate and analyze the recovery and survival rates of stolen motor vehicles. They also demonstrate the reliability of the NIBRS data by comparing the results obtained using data from NIBRS with data from the National Crime Information Center (NCIC). The final paper in Chapter III--by Dan Bibel, Don Faggiani, and Lindsay Robertson--deals with the strategic and tactical uses of NIBRS data for regional crime analysis. Using enhanced (addresses added) state data from the Commonwealth of Massachusetts, the authors examine heroin possession and sales incidents in Worcester, Massachusetts, and the eight communities immediately adjacent. The addition of address details to the standard NIBRS data allows crime analysts to examine the spatial patterns of drug offenses. Their paper

demonstrates that the standardized structure of the NIBRS data can easily transcend the needs of a single law enforcement agency. The addition of address details to the standard NIBRS structure, such as that implemented in Massachusetts, provides the added detail necessary to permit neighboring agencies the opportunity to conduct interagency, tactical crime analysis. The conclusion provides a brief summary of the contributed papers and speaks to the future of the NIBRS system.


Maltz, Michael D. (1999). Bridging Gaps in Police Crime Data. Washington, DC: Bureau of Justice Statistics.


In 1961 the FBI began collecting incident-level details on all homicides, including basic demographic information on victims, through the Supplemental Homicide Reports (SHR).


Data Systems for Policing in the 21st Century--Facilitating the Implementation of Incident-Based Data Systems


Craig Fraser, MAXIMUS

Strategic Information Systems for Policing

Chapter I



CHAPTER I Strategic Information Systems for Policing

Craig Fraser, MAXIMUS

Data Systems for Policing in the 21st Century--Facilitating the Implementation of Incident-Based Data Systems

The best information systems result from a design process that includes in-depth discussion of what information is needed by whom, what decisions need to be made, and when this information is needed. A strategic information system is one that goes beyond merely collecting data; it is aligned with the goals of an organization and is designed to assist the organization in meeting its goals by improving system performance. Recently, it has become more evident that law enforcement agencies need to spend time examining current information systems and consider revising these systems in light of modern business practices. Unlike other businesses, however, the bottom line in policing is not profit, but public order and safety. For the most part, police information systems have functioned as little more than expensive electronic file cabinets. While they have improved the efficiency of filing and retrieving a single file or piece of information, these systems have not helped to answer the question of how to best use the data collected. Older systems were not necessarily designed to address agency needs or core functions. Bill Gates (1999) says: The gap between what companies are spending and what they're getting [in information systems] stems from the combination of not understanding what is possible and not seeing the potential when you use technology to move the right information quickly to everyone in the company. Peter Drucker (1995) describes this issue by saying that few people in organizations ask critical questions about information. These questions are: What information do I need to do my job? When do I need it? In what form should it be? From whom should I be getting it? Answers to these questions can assist in determining the information needs of individual agencies. Drucker goes further and says that even fewer people ask: What new tasks can I tackle

now that I get all these data? Which old tasks should I abandon? Which tasks should I do differently? Furthermore, practically no one asks: What information do I owe? To whom? When? In what form?

Police as Knowledge Workers

Policing agencies in America are charged with a variety of functions. A group of police chiefs working with the Police Executive Research Forum (PERF) developed a list of four key reasons that American police agencies exist (Fraser et al. 1998). These functions include preventing crime; solving crimes that have already occurred; responding to varied service requests made by the public; and solving crime, violence, and disorder problems through community partnerships. The context in which these functions were outlined was a project designed to determine whether a private sector organizational development tool--process mapping--could be applied to policing to improve organizational operations. These police executives were working to define core policing processes so they could select the areas in which eight test departments would attempt to map these processes. Specifically, process mapping is a business technique used to determine how an application works. One way to define "process" is through a series of value-added tasks linked together and used to turn inputs into a product or service. Process mapping, then, is a method to describe the various inputs and operations that compose the entire enterprise. A business process has a specific beginning and end; it is composed of coordinated activities involving people, procedures, and technology; and it constitutes a significant portion of organizational costs.1 The implementer of a new business process must have a firm understanding of the requirements of the system involved and must be able to specify the system's purpose. The chiefs involved in the PERF project selected crime

Chapter I


solution as the core process to experimentally map. This particular process was chosen because it generally has an easily definable start (an apparent crime comes to the attention of the police2) and a discernable end (a case is presented to the prosecutor or the police set it aside because further investigation appears fruitless). Each of the eight departments participating as test sites selected some aspect of crime solution on which to construct process maps. The mapping teams struggled to apply this business concept to police work because, in the private sector, the clear purpose of each task is to add monetary value to the product or service that results from the process. As discussion evolved, it became apparent that in a policing context, the valuable task in the crime solution process was to improve the amount or quality of information available regarding the crime. A primary goal of the crime solution process is to have a successful investigation to present for prosecution. This outcome requires three levels of information: information that documents the elements of the offense and confirms that a crime did indeed occur, information that identifies the suspect, and information that allows the prosecutor to establish beyond a reasonable doubt that the suspect is the person who committed the crime. Each of the earlier steps, from when the police are first notified that a crime may have occurred until the investigation begins in earnest, is included in the data collection process. Witness and victim statements, informant tips, descriptions of property, recording of a modus operandi, fingerprints, DNA, and other physical evidence, such as footprints or tool marks, may all be discovered in the initial investigation and eventually be added to or refined during the more formal investigation. Traditionally, the police have regarded such documents as important information leading to crime solution. But crime scene evidence--including fingerprints, DNA samples, blood spatters, crime scene sketches, crime scene photos and video tapes, ballistic evidence, and tool marks--are also essential pieces of information. In their raw form they simply represent data, but subsequent analysis converts these elements into information that may help identify a suspect and link a specific suspect to the crime. Data collected from other, unrelated crimes, may also help solve the current crime. These may include data from pawn shop databases, known associates files, field interview databases, and crime tip lines. These sources may further assist the investigator in assembling a case that can be presented to the prosecutor. When one thinks about the investigation of a crime as a process of assembling knowledge, one begins to recognize the premise that police are knowledge workers. The basic sets of raw materials that police work with are information

and interactions with people. How the police deal with these materials is determined to some extent by the skills and education police have. Most dealings, however, are based on past practices and habits that sometimes have not changed for years. Although there is value in understanding past practices, it should also be apparent that police need to reevaluate these practices in light of current information processing technology. Although we may think of police as mere collectors of information, an important part of their function must also include the dissemination of useful information. Part of any dissemination strategy should on some level be based upon what external actors will do, or should do, with new and better information. Some information might be given out based on providing news, without much expectation that people will take any specific actions. Other information might be provided to the public with the hope that people will either offer information to the police to help solve a crime, or alter their behavior to decrease their chances of becoming a victim. This second point is the basis of the crime prevention campaigns in which police agencies have engaged for years. Examples include avoiding dangerous places and circumstances, looking in the back seat of a vehicle before getting in, locking doors and windows, buying and installing deadbolt locks, and having someone collect mail and newspapers from the house while on vacation. These crime prevention strategies are all based on police knowledge of crimes that occur and how victim action, or inaction, may facilitate crime occurrence. As departments develop Web sites that allow the public to plot crimes in their neighborhood, they should consider providing more than just dots on a map. For example, typical burglary reports might include such information as time of day, day of the week, items stolen, and means of entry. If many entries are occurring through unlocked back doors, then homeowners should be informed that it is important to lock the back door as well as the front door. If locks are being easily defeated, then the message should be to acquire deadbolt locks. In this way, the department begins to move past just supplying general information toward providing specifics that can assist the public in becoming safer.

Kinds of Police Information

In general, police administrators deal with two types of information--operational and administrative. Each type of information is necessary for the proper operations of the agency, and neither can be neglected for long without the core functions of the agency suffering. Operational data


Data Systems for Policing in the 21st Century--Facilitating the Implementation of Incident-Based Data Systems

may seem more important because it is part of the "public face" the agency shows. It may also be more time-sensitive because it deals with preventing, controlling, and reducing crime. Administrative information has a reduced public face and instead includes data issues such as collection, manipulation, and utilization. Although this information may seem more mundane than operational information, collection and use of administrative data promote efforts to improve effectiveness and efficiency within the agency. Examples of administrative information consist of tracking vehicle usage, mileage per car, tire rotation schedules, and the like. It also encompasses manpower allocation, mainly through tracking calls for service and personnel scheduling. Questions and answers arising from operational information, versus administrative information, are diverse in nature. These data can be used to prioritize enforcement activities, such as determining which of several competing projects might have the greatest payoff, or which type of patrol deployment will have the greatest effect on a specific crime problem. Could domestic violence be reduced if more information about victims or crime circumstances were known? Where should new officers be assigned to have the maximum effect? What strategies should be used to reduce convenience store robberies? Administrative data answers other sorts of questions: Who are the most productive employees? Which employees have the highest level of disciplinary infractions? Which cars need to be replaced or serviced? Are staffing levels appropriate for current service requirements? Another question departments should ask is: How could operations be improved if we knew more about victims? Enhanced victim information is one of the cornerstones of the FBI's National Incident-Based Reporting System (NIBRS), yet many departments have yet to think about how to use the information a NIBRS system can produce. NIBRS use can enhance and even customize crime prevention education. As certain types of crimes and circumstances (geographical, temporal, etc.) emerge from enhanced analysis, and these patterns show consistent victim types, the department can reach out to those victim types to provide specific, tailored crime prevention messages. Victim information could also be used to help conduct operations to try to catch perpetrators who seem to pick on a particular type of victim. Knowledge of potential victims may also play a part in directing patrol operations. For example, although most research studies have shown that the elderly are not more likely to be victimized than other segments of the population, they still are more fearful of criminal victimization. Data collected by the NIBRS system can help departments address this specific issue. Information can also be used as an evaluative tool. For example, departments are identifying hot spots of crime through the use of geographic information systems (GIS); for future operations to benefit, these operations must be

documented. Departments should go beyond identifying the problem to describing why the chosen tactics are expected to work and what changes can be expected. After the operation has been implemented, they should measure the effect and determine whether the expected results were achieved. A review of past operations should then be a required part of the planning for future operations. Creating on-line libraries of past projects (such as that kept by the San Diego Police Department on problem-oriented policing projects) should also help departments answer questions about the differential success rates of enforcement strategies. Sherman (1998) has described this as evidence-based policing. When police departments begin to compile and use the wealth of information available to them to solve the operational problems described above, they can become more effective in their long-term and day-to-day work.

Crime Analysis

One of the major uses of police operational information continues to be for crime analysis. Crime analysis depends on offenders committing more than one crime, or on having places where multiple crimes are committed (patterns). Crime analysis depends on the following assumptions: · A prediction can be made to intercept a crime in progress, · Offenses can be linked so that when someone is caught that person can be held accountable for a number of offenses, or that · Certain places generate disproportionate amounts of crime and police work, and the characteristics of such places can be altered to become less attractive locales for crime. Each crime analysis approach requires a somewhat different flow of information. When crime and geography is the focus, locations must have repeating crime patterns or problems. Sufficient information is needed so that an understanding can be developed about why the problems are occurring in that place, as opposed to another. The solution then becomes changing the characteristics of a location so as to discourage offending there. An appreciation of crime analysis has led to increased use of crime mapping. Police departments have long used maps with different colored dots or pins to examine crime concentrations and geographic patterns. Some jurisdictions, such as Baltimore County, Maryland, are experimenting with maps by adding precision-based features, such as building footprints, topographical data and vegetation from aerial maps, and global positioning data. Such maps can show, for example, where escape route footpaths have been created; this information would not show up in most conventional GIS maps. Burglaries can then be displayed to

Chapter I


show exactly where entry to a building was gained. This could allow a quick visual determination that a rash of neighborhood burglaries had the common factor of entrance gained through a back door or window. Officers canvassing the neighborhood might then focus their interviews with people who may have seen someone in backyards to help get a suspect description.

Administrative Information

As mentioned above, another dimension of information police agencies need to use more effectively is administrative information. Police can use administrative information to achieve efficient and effective operations in areas such as fleet management, CAD transaction processing, prisoner tracking, and investigative case management. As police managers become more data literate, they can ask questions such as: · Which patrol cars should be replaced this year? · Do patterns of leave time usage indicate a schedule or days-off cycle problem? · Are there trends in citizen complaints? In internal discipline? · Who are our most productive employees? Similar to the use of operational information, administrative information has not been used as well as it might have been to improve management. Most departments do not look at patterns of leave usage, trends in citizen and internal complaints, or employee productivity.

organization effectively and efficiently? What measures are important to the governing body and to the public? All these issues should be taken into account when planning for how a system can produce accurate information to satisfy accountability demands. It is important that the leadership of the department take ownership of information, since it is an essential tool for effective policing. Leaders must learn what they need to know so they can direct the construction of their information systems. This does not mean they must know technical details of the system, but that they must ask the right questions to ensure that the system is designed to produce the answers they will need. Additionally, the process of defining information requirements will not produce the same results in every law enforcement organization. Information requirements differ according to the department's approach to community policing, problemoriented policing, and crime analysis. One approach to help determine what information the organization needs is to create a list of the crime, violence, and disorder problems that most concern the agency. Then the organization can list the information it needs to solve these problems. This list may be extensive and may transcend crime incident reports. It can also help to identify "hidden data" within the organization, data that can complete the picture of the department. By thinking through the data needed and where in the organization it exists and what new information should be captured and assembled, the department can create what Bill Gates (1999) calls a "digital nervous system." Within the entire organization, the network could combine the abilities of individuals and create an institutional intelligence and a unified ability to act.

Information System Design

Police leaders must recognize that a database is not information. A database is an organized collection of various data elements. Information is data that is organized for a task, and can be directed toward specific performance or applied to a decision. It is easy to confuse data with knowledge, or information technology with information. Such confusion can set requirements for new systems that do not meet the information needs of a department. Agency leaders must seek answers to a set of critical questions about the organization to get at the information needs of their agency. Foremost, they need to know what information is needed and they need to know when they will need it.

When Do We Need It?

The timeliness of information is also of great importance. When information is needed is a critical component in system design. What do you need instantly, in "real time"? When do you need tactical information? When do you need strategic information? As an example, patrol sergeants need real-time information on calls for service and need to know what their officers are doing so that they can help direct responses from the field. Line officers need the most up-todate information on their immediate calls for service, but also on relevant past calls at the same location or from the same victim. They need to know if there is an arrest warrant outstanding, or if there is a gun registered at a given location. The time frame within which information is needed should influence not only the design of the system itself, but also the design of the data input process. Barriers to accurate and timely information are usually the result of poorly designed data capture processes. If reports sit in a box for several days before being entered into the system, commanders will not have up-to-date information on crime in their district.

What Information Do We Need?

Important questions for department leaders to ask are: What do we want to measure? What are the measurements of organizational, unit, or individual performance that are important, and that can assist us in managing the


Assessing Your Approach to Information Technology and Information Systems

Thomas Friedman (2000), in a brilliant book about globalization, presents a framework to evaluate an organization's "information quotient." This framework is adapted as a method to consider the quality of a police department's information technology operations. A critical first question is: Does your department's management get it? As one source (Jackson and Schuler 2001) puts it: Putting a rich store of knowledge at everyone's fingertips is of little value if no one is motivated to access it. Conversely, instilling an appreciation of the value of knowledge and learning is of little use if the knowledge or opportunity for learning is difficult to access. In most police agencies, the volume of data, the speed of hardware and software, and an understanding of what new information technology can produce is well ahead of the appreciation of value of potential knowledge. Most law enforcement agencies are awash in data. While departments are increasingly able to give all departmental members access to information, all too often there is little or no discussion as to how to best utilize these data. The Compstat process, developed in the New York City Police Department, is an example of an effort to use data to produce actionable knowledge. By collecting, computerizing, and organizing timely data about criminal incidents, police administrators were better able to understand and respond to emerging problems. It is troubling that in police agencies, too many senior managers seem to accept the absence of timely information as a given. This often results from sheer frustration with automated systems and data collection and entry processes. When timely, meaningful data are uncollected, not computerized, or difficult to extract from a records management system (RMS), the ability of administrators to work effectively is diminished. Part of the difficulty in designing the best in police information systems has been the lack of clearly defined information needs for different levels of law enforcement managers. At each level within a prototypical police agency hierarchy, there may be different information needs. These needs are based upon the requirements of the job, the geographical or temporal extent of the responsibility, or the number of personnel assigned to it. For example, the geographic commanders should have access to all information about their geographic area. Based upon this need, the implication for system design is that one organizing principle must be addresses and geography. Items

Data Systems for Policing in the 21st Century--Facilitating the Implementation of Incident-Based Data Systems

available and capable of being aggregated at the sub-beat level, beat levels, sector levels, and district level should include an address or group of addresses, calls for service, officer-initiated activities, incident reports, traffic crashes and citations, addresses of victims, witnesses, offenders, addresses of sex crime registrants, addresses of where field interviews took place and of all those subjects of the field interview, addresses at which an arrest was made, addresses given by arrestees, and vehicle registration addresses. Officers working in a beat should be able to exchange information with officers working on the shift before them and after them. If they are to be held responsible for beat crime and disorder, they will also need to know what has happened during their days off, so when they return they should be able to obtain a summary for the precise days they were not working. Another key question that managers must ask is: How much and what information should be available in the patrol car? This means grappling with the questions, What do we want patrol officers to do? We know that we want them to answer calls for service, and that they should have as much information as possible to deal with each call, but what other activities do we want them to spend time on? If we want them to arrest offenders, then a system should be designed so that typing the address into the computer-aided dispatch system automatically initiates a search of the warrant file for any open warrants for that person's address. If we want them to be experts in the crime and disorder problems of their assigned neighborhoods, then systems must be structured to provide them with information on all of the police activity in their neighborhood.

Is Your Department a Shaper or Adapter?

The issue is not whether a department acquires a new information system, since most systems provide a rich array of data. The question is whether departments will begin a new system of managing the agency by using the information they probably already have. Two examples of more effective policing through better use of data are community policing and Compstat. To an extent, these new programs or types of policing represent a paradigm shift. Moving from a traditional, reactive style of policing, to a proactive community policing approach was a dramatic shift in police thinking. Policing through Compstat represents another, but perhaps more subtle, shift that is only beginning to be recognized. The founding principle of the latter is that the police can reduce crime through the short-term intelligent conversion of data into information. What Bill Bratton and the New York Police Department did first was to adopt the principle that the police can reduce crime through more effective policing. The Compstat process has four major components (Bratton and Knobler 1988):

Chapter I


· accurate, timely intelligence, · rapid deployment, · effective tactics, and · relentless follow-up and assessment. For each of these, rapid collection and analysis of quality data are essential. By pushing data to a centralized analysis function daily and weekly, Bratton and colleagues confronted precinct commanders with the realization that they did not know enough about what was going on in their area even though they had access to the same data as did the central analysis function. By analyzing data in a timely fashion, it was anticipated that potential crime patterns in problem areas could be identified after only three or four incidents had occurred, rather than 15 or 20. Then, the effort became how to plan operations to interrupt patterns and to apprehend offenders. Another tactic was to crack down hard on illegal disorderly behavior as a way to intervene and prevent more serious crime. For example, by encountering people engaging in seemingly petty, but suspicious or illegal conduct, the police could use legal stop-and-frisk tactics to search for concealed firearms. Because many people of the fringes, as well as mainstream, of criminality were routinely armed, this more intrusive police activity could result in their arrest for weapons violations and interviews and interrogations regarding the source of the weapon. As this police intervention became common practice, two results occurred. The first was that people began to avoid the conduct that might lead to a frisk in order to avoid the possibility of weapons charges and confiscation, thus leading to a more civil level of public conduct. The second result was that it became more expedient to leave the weapon at home. This latter behavioral modification led to a further positive result. Many homicides result from poor anger management--two people get into an argument over petty issues, it escalates because of drug or alcohol ingestion, and whoever gets to their gun first shoots the other. Fewer armed people means fewer homicides and fewer aggravated assaults. Many departments are now adopting the core Compstat approach. This "new paradigm" to policing is interesting because it does not require police to collect more data than they should be routinely collecting. Rather, Compstat, as a strategic information approach, allows police to use more effectively and efficiently the data they already collect. If the results in New York City are indicative of the effects of this effort, a higher percentage of crimes can be prevented. Whether a department is a shaper or adapter in IT/IS is less a function of its current RMS and more a function of the quality of its thinking.

How Wired Is Your Department?

As a police department develops an understanding of who needs what information, it should plan to make it as easy as possible for each employee to access that information. Policing agencies should ensure the wide distribution of information such that it takes advantage of the ideas, perspectives, and curiosity of many in the department. The flow of information should not be restricted to just a few because there are not enough access points. One measure of the connectedness in a department might be the ratio of desktop computers to employees. Friedman (2000) talks about the degree of connectivity for a country, and the same principle applies in an individual organization. For police employees to do their finest work, they generally need to have information. Part of the problem in spreading information widely throughout the department may be the fact that most police employees work in the field, not at their desk. A department should think carefully about what information it wants to flow to and from the field. What approach will work best in supplying and capturing the desired information? A department's mobile data strategy should consider not only in-car data, but also what information should be captured or transmitted via handheld devices. A key restraint that an agency must deal with in the development of its mobile strategy is bandwidth. A department may encounter significant limitations in the speed at which information can be transmitted using its current technology. Consequently, the mobile data strategy should not only consider what it wants to send to and from the field, but the size and complexity of the various data streams. The department may have to establish priorities for its mobile data to capitalize on the technology it currently has in place. Departments should then consider their highest priorities in information transfer needs, and obtain new technological equipment according to these priorities.

How Fast Is Your Department?

Another of Friedman's (2000) evaluative questions that can be applied to police information technology is: How fast is your department? How quickly are decisions made? How quickly does your department learn to make the best use of new technologies? There are two dimensions to this final question. The first involves the willingness of top management to continually watch for ways to improve the timeliness of decision making. Information time frames vary. Depending on one's position and responsibilities in the department, the time frame for action will vary from immediate needs for field officers, to multi-year information for senior executives. Between these extremes are the daily, weekly, monthly, and annual needs for information. The


second dimension involves another question: How quickly does your department adapt to others' using new technologies? Here, "others" refers to both criminal justice agencies and other public agencies. For example, if a state agency sends out CDs with information about sexual offenders and compliance with Megan's law, then local departments will need a computer capable of reading and displaying the information and pictures that are digitized on the CD. In the digital future, police agencies will have to adapt to technology used by criminals. As technology advances, new avenues for criminal behavior are found, and new methods in "traditional" forms of criminal acts are born. A British government group, the Foresight Commission, has done some groundbreaking work on potential benefits and hazards of future technology for policing and for criminal behavior. By projecting out 10 to 15 years, they can give us a window into future potential problems. As they point out, crime has always fallen into one of two major groups, either acquisitive (obtaining goods or services) or expressive (acting out hostility, sexual urges, etc.). However, the types of goods available, along with the means to acquire them, will change as technology changes. The means, methods, and targets of expressive criminality will also change as society changes. For example, to acquire greater wealth, criminals will find ways to evade the biometric system intended to prevent cash cards, electronics, bank cards, cameras, etc., from working with any but the legitimate user. Components chips, smart cards, and precursor chemicals will be valuable commodities as criminals learn how to use them or sell them. A British Home Office report coined the acronymn CRAVED to describe which items criminals might view as desirable to steal. Such items will be Concealable, Removable, Available, Valuable, Enjoyable, and Disposable (Clarke 1999). Electronic services theft, knowledge and information theft, Internet fraud, and identity theft are already growing problems in many jurisdictions. How well will policing change and adapt to meet these challenges? Some first steps for police agencies include acquiring skilled employees and new technology to help detect, investigate, and arrest the perpetrators of these new crimes. As knowledge and technology become available, police agencies will have to keep abreast of new developments, train personnel, and acquire technology faster to be effective against the criminal order. The Foresight Group also discussed the future of expressive crime. That future includes such behavior as micro-chemical synthesis using advanced medical knowledge of the ways in which the human brain and body react to new combinations of substances. Such knowledge, coupled with the ability to design chemicals and substances, can make crack cocaine addiction look almost benign. Coping with this potential will almost certainly require new

technologies. Another type of expressive crime may involve digital stimulation through electronic images and interactions. Child pornography is one example. Again, successful combat against this problem requires the police to have the skills, knowledge, and technical tools needed to prevent offenses and to capture those who engage in such behavior. As a final example, some expressive crime will result from the alienation of skilled elders. In turbulent economic times, which now seem to be the norm rather than the exception, older persons with great technical expertise will be declared redundant. At least some will strike back at the perceived injustice of such layoffs. The development of methods to address such issues will again require much greater technological skill and knowledge.

Data Systems for Policing in the 21st Century--Facilitating the Implementation of Incident-Based Data Systems

Is Your Department Harvesting Its Knowledge?

Police agencies are awash with raw data. The police must learn how to retain data and use it effectively to transition from mere raw data to information and knowledge. Too often police agencies make no use of their internal knowledge because they don't recognize that they have it. The institutional knowledge of employees can be a fruitful source of information. For example, when long-time detectives retire, they may hand over their current cases to someone else with few clues about how to solve them. However, no effort is made to capture what these persons know generally about local crime and criminals. Such knowledge, when amassed over decades, might be useful in understanding not just crime and criminals, but also in dealing with specific local crime issues. Capturing and organizing the knowledge these veterans have may require that such retirees debrief key players in the department over several days before they leave. Organizing such knowledge and making it useful will require some skill, but the loss resulting from not making an effort could be tragic. Similar observations about crime and criminality, hot spots, and troubled neighborhoods should be sought from retiring patrol officers. Departments that attempt formal problem solving (e.g., via the SARA model) or special tactical operations should develop systematic formats for capturing as much information about these operations as possible. Collected information would include a statement of the problem, the tactics designed to deal with the problem and why they were selected, the expected results of the operations, and the actual results. This information should then be used in planning subsequent operations. Put simply, we need to know what works and what doesn't. Another source of information the department should consider is unreported crime figures, such as those captured by victimization surveys. Although most departments are not part of the National Crime and Victimization Survey (NCVS), they should look at the results and consider them in light of their own locality. Some effort could be made to

Chapter I


develop jurisdictional measures of victimization, perhaps through collection of data from hospital emergency departments, rape crisis centers, or other non-public safety agencies. Although many departments examine incident reports and crime reports, fewer use calls for service information as information sources. Dispatch records that track officer activity are another often overlooked source of information. By grouping these activities geographically, the department will discover locations that officers consider to be hot spots because they concentrate their self-initiated activities there. Other under-utilized data in many police agencies includes information gained from "Tip Lines" or "Crime Stoppers." These data sources are set up to provide anonymous means for people to inform the police of suspects and problem locations. The information provided should be examined for patterns of criminal behavior, and then cross-checked against other data sources such as crime reports, calls for service, arrest reports, and so forth. "Backtracking" solved cases is another way that a police department can harvest data. By selecting cases based on either crime type or personnel involved, and doing a complete case review, it may be possible to determine patterns of investigation and steps that lead to success. Are there common methods that all of the most successful investigators use? Can these methods be used to train those who are less successful to improve the overall capability of investigative units? An example of the latter use of information occurred during PERF's process mapping project (Fraser et al. 1998). The process mapping team from the Thames Valley (UK) Police Force wanted to further examine the requirement that Scenes of Crime Officers (SOCOs) had to process every burglary scene within 24 hours of the crime report. They analyzed successful burglary investigations to determine the role of evidence their SOCOs uncovered in solving the cases. They discovered that physical evidence helped to solve such a small proportion of the cases that the requirement seemed of little value compared with the resources needed to uphold it. The results brought up other questions as well. Did the lack of success result from the little worthwhile physical evidence at burglary scenes, or from the long lag time (as long as 24 hours) before the scene needed to be processed?

record management systems, fingerprint scanners, laptop computers, and mobile data terminals are being used in many agencies throughout the country. Training in emerging practices, like Compstat and community-oriented policing, are widespread. The police of today are generally better trained and better equipped than police at any other point in history. It is not enough, however, to buy new hardware and software, or to send officers for training. To best utilize the data that all police agencies have on hand, it is critical that they learn how to use their data to transform it into useful information. Academy or in-service training is valuable, but only to the extent that it enables officers to effectively serve the needs of the agency. Computerization is only one step in the process of transforming unorganized bits of data into something meaningful. To change information systems into strategic information systems, police administrators need to work through their entire business process. They need to understand their core mission and the processes involved in fulfilling that mission. Once that is accomplished, departments can move forward toward implementation of an information system that meets their individual needs. "I'm always on the lookout for examples of the importance of fixing business processes instead of just increasing computer systems speed and power. It makes no sense to computerize a flawed process" (Lovelace 2003).


Bratton, William, and Peter Knobler (1988). Turnaround: How America's Top Cop Reversed the Crime Epidemic. New York: Random House. Clarke, Ronald V. (1999). Hot Products: Understanding Anticipating and Reducing Demand for Stolen Goods. Police Research Series Paper 112. London: Home Office. Department of Trade and Industry (2000). Just Around the Corner: A Consultation Document. London: Office of Science and Technology. Available at: Drucker, Peter F. (1995). Managing in a Time of Great Change. New York: Truman Talley Books/Plume. Fraser, Craig B., Micheal Scott, John Heisey, and Robert Wasserman,(1998). Challenge to Change: The 21st Century Policing Project. Washington, DC: Police Executive Research Forum. Friedman, Thomas L. (2000). The Lexus and the Olive Tree: Understanding Globalization. New York: Anchor Books. Gates, Bill with Collins Hemingway (1999). Business @ The


In today's turbulent technological society, police work continues to be the maintenance of order, the protection of the vulnerable, and the apprehension of criminals. Many police agencies have embraced new technology to assist them in the everyday enhancement of their work. Improved


Data Systems for Policing in the 21st Century--Facilitating the Implementation of Incident-Based Data Systems

Speed of Thought: Using a Digital Nervous System. New York: Warner Books. Jackson, Susan, and Randall Schuler (2001). "Turning knowledge into business." Financial Times, January 15, p. 13. Lovelace, Herbert W. (2003). Information Week, January 6. Available at: ml?articleID=6504557. National Law Enforcement and Corrections Technology Center (2001). A Guide for Applying Information Technology in Law Enforcement. Washington, DC: NLECTC. Process Mapping Associates. Available at: Sherman, Lawrence W. (1998). Evidence-Based Policing. Washington, DC: Police Foundation.

1 Process Mapping Associates, 2 A possible crime may come to the attention of the police when a citizen calls the police because they have been a victim or witness, when a police officers discovers it, or when some other government entity reports it.

Chapter I

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Data Systems for Policing in the 21st Century--Facilitating the Implementation of Incident-Based Data Systems

Implementing an Incident-Based Reporting System Compatible with the FBI's NIBRS Standards

1. Implementing NIBRS in Kansas-- 15 Mary Ann Howerton, Kansas Bureau of Investigation 2. NIBRS in Memphis-- 19 Walter E. Crews, Director of Police Services, City of Memphis Police Department 3. The Implementation of National Incident-Based Reporting by the Fairfax County (Virginia) Police Department-- 23 Colonel J. Thomas Manger, Chief of Police, Fairfax County Police Department 4. Incorporating NIBRS into the Custom Development of an Offense Reporting and Records Management System in Charlotte-Mecklenburg-- 29 Veronica L. Sorban, Charlotte-Mecklenburg Police Department

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CHAPTER II Implementing NIBRS in Kansas

Mary Ann Howerton, Kansas Bureau of Investigation

Data Systems for Policing in the 21st Century--Facilitating the Implementation of Incident-Based Data Systems

Who We Are

In 1982, the Kansas Bureau of Investigation (KBI), with the aid of a local users' group, began studying the utility of establishing an incident-based reporting (IBR) system. As a result, in 1986, the first Kansas Incident-Based Reporting System (KIBRS) was implemented to collect relevant information on the occurrence and composition of crime in Kansas. Pursuant to state statute, law enforcement agencies at the state and local level began reporting standardized data on criminal offenses in their respective jurisdictions in a format approved by the state's Attorney General. The state program then converted the data to UCR format for submission to the Federal Bureau of Investigation (FBI). By the late 1980s, the only law enforcement agency not participating in KIBRS was the state's largest, the Wichita Police Department, which dealt with 50 percent of all crime and arrest reports in the state. Fifteen of the remaining large agencies were submitting KIBRS data either on tape or floppy disk. The data entry staff at the KBI converted on data paper submissions to UCR format and submitted them monthly to the FBI. The database was continuously used for crime analysis purposes: to identify recovered stolen property not entered into the National Crime Information Center (NCIC), to identify potential suspects by crime type and victim, and to identify leads in specific types of crime. We had succeeded and we were proud of it. Our publications were timely and informative. We could quickly respond to special requests for data. Then, it all began to unravel. modify the existing IBR program to meet NIBRS requirements. The committee quickly determined that it would be more efficient to implement a new program rather than to try to add all of the missing data elements and linkages required for NIBRS participation. KBI hired a programmer, purchased a case tool, and then, in January 1993, disaster struck. We went from having 15 agencies submitting data on tape to three submitting on floppy disk. Several vendors tried to build electronic files but found the requirements confusing and difficult to follow. The first data entry program had delays of 30 seconds to two minutes between screen changes within a single incident. As a result we had to develop a new data entry program in D-base and, by the time it was released, we were already six months behind on data entry. With the added learning curve, we quickly developed a 12month backlog and were keying more data because fewer agencies could submit data electronically. The results of our mistakes have been long-lasting. For example, Kansas has not been represented in Crime in the United States since 1993, Crime in Kansas has not been released since 1994, and the most recent data on our Web site is for 1998. When we started testing with NIBRS, the error rate and types of errors confirmed that we were in big trouble.

KIBRS Gateway

In 1997, the state of Kansas implemented the Kansas Criminal Justice Information System (KCJIS) Improvement Project. The project focus was to create an integrated criminal justice system involving state and local agencies. Since the KBI is the central repository for criminal history records, the initial focus of the project was to improve the core systems at the KBI. The KCJIS Advisory Board included representatives from

Chapter II

What We Did

With the release of the final specifications for the National Incident-Based Reporting System (NIBRS), and because of the availability of federal money, the KBI formed a committee of local and state law enforcement agencies to

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the project and from the agencies affected. As a result, the KIBRS Subcommittee was created and included representatives from Kansas' four largest police departments (serving populations larger than 100,000 persons) and two smaller agencies. The four major agencies represent 75 percent of the incidents and arrests reported in Kansas. If KIBRS was going to succeed, these agencies had to support it. The KIBRS Subcommittee reviewed and supported the existing data elements in KIBRS. They recommended that we continue to use the state standardized incident and arrest reports, but that agencies be required to report data based on the requirements of NIBRS and not necessarily state statute requirements. Most importantly, they developed the concept of a KIBRS Gateway. The KIBRS Gateway is a software application that contains the KIBRS and NIBRS required edits. It provides, free of charge to local agencies, a standard method for submitting KIBRS data using "securemote" and the Internet. Agencies using their own records management system can create an interface to the gateway and submit their KIBRS data electronically to the KBI.

2000. The Overland Park Police Department, one of the four largest agencies, was the first agency to successfully interface and submit data through the Gateway. Since that time, 12 additional agencies have interfaced and been certified to submit production data. Two major agencies, the Kansas City and Wichita Police Departments, have started locally testing the KIBRS Gateway. The fourth largest agency, the Topeka Police Department, is currently implementing a new records management system using the same vendor as two other agencies in Kansas that have been certified KIBRS-compliant and are submitting production data through the Gateway. Vendors for agencies that have met KIBRS requirements and are certified to submit data through the KIBRS Gateway include New World, Spillman, Starfire Inc., and SLUETH (Access Data Corporation). Several other vendors are currently working on interfaces. The Gateway approach eased system development with the agencies and their vendors. Each agency is provided with an Interface Control Document, KIBRS Gateway Users' Manual, and the Gateway software. This allows the agency and the vendor to test the interface locally, and by the time they connect to the state most of the agency's edit issues have been resolved. The last step toward certification requires the agency to submit test data to the KBI, where it is checked for reasonableness. The length of time between developing, testing, and implementing the interface has varied among agencies. Because the Gateway gives the local level edit responsibility, many agencies are struggling with the quality of the reports their personnel submit. As a result, the KBI has conducted KIBRS workshops throughout the state; attendance of agency personnel is often mandatory.

Contracting with Vendors

In 1998, the state awarded contracts to Paradigm4 for the development of a KIBRS data entry program at the KBI, a KIBRS database, and the NIBRS conversion program. A contract was also awarded to Business Software and Equipment to develop a local law enforcement records management application and the KIBRS Gateway. The local case management system was developed in Microsoft Access. It contains the Kansas Standard Offense Report (KSOR) and Kansas Standard Arrest Report (KSAR). The software allows an agency to transfer data between the KSOR and the KSAR and onto a fingerprint card and the Kansas Disposition Form. It also accommodates supplemental case reporting, the data entry of the Kansas Accident Report form, evidence tracking, even creating a separate file for field contacts and warrants. The KIBRS Law Enforcement Application (KIBRSLE) was released in May 1999 to 125 agencies. Version 1.6.0 with the KIBRS Gateway was released in October 2000. Initially, 21 agencies using KIBRSLE were submitting data through the Gateway. In October 2001, Business Software and Equipment ceased operations. The KBI quickly retained the application developer and, in February 2002, released version 1.8.0 to 90 Kansas agencies. The KIBRS Gateway was implemented in October


1. Error rates. The KBI started testing with the FBI's NIBRS program in January 2000. We made 16 submissions with an ending error rate for both arrests and incidents of less than 0.4 percent. Kansas was certified NIBRS compliant on February 16, 2001. Paradigm4, the vendor responsible for the KIBRS database and KIBRS to NIBRS conversion, went out of business in March 2001. This set us back several months and we did not start cycle testing until January 2002. However, the first KIBRS implementation was a breeze. The second implementation failed, but taught us what do differently the third time around. 2. Software development. The local case management


software and its development still remain a concern. Many of the small local agencies in Kansas have little expertise in database management and most do not have access to information technology staff. We continually deal with installation issues and corrupted databases. Unfortunately, the KBI does not have the staff to support agencies having these problems, either over the phone or in person. 3. Technical support. The access platform limits the number of simultaneous users and the size of the database. Lack of technical support and funding prevented us from moving the software to an SQL platform.

Data Systems for Policing in the 21st Century--Facilitating the Implementation of Incident-Based Data Systems


For implementation of KIBRS to succeed, agencies must submit their data electronically through the use of either the KIBRSLE application or the KIBRS Gateway. Nevertheless, the KBI data entry staff cannot significantly reduce the backlog of data entry to meet the deadline for publication in Crime in the United States. And as we all know, data must be timely if it is to be useful as a crime analysis tool. For the project to be considered a total success, we will need significantly more training. We need to have personnel in the field to contact local agencies one-on-one using the KIBRSLE application as well as the KIBRS Gateway. We also need to complete development of an interactive Kansas crime statistic site for the public, as well as a second secured site with pre-release data for the participating agencies. Finally, it is important that Kansas data once again appear in the FBI's annual publication Crime in the United States.

4. Database management. Developing a "thin client" case management system housed and maintained at KBI headquarters should have been considered. This would have eliminated the issues with installation and corrupted databases. Also, KBI should have provided each agency with free training personnel and hands-on training to as many staff members as possible. This would have increased user confidence and may have resulted in more agencies using the software to submit data electronically, as opposed to printing out a form for the KBI staff to key in at the state level.

Chapter II

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Walter E. Crews, Director of Police Services, City of Memphis Police Department

Data Systems for Policing in the 21st Century--Facilitating the Implementation of Incident-Based Data Systems

Who We Are

The City of Memphis Police Department provides services to more than 650,100 people in a 313-square-mile area, and is the 18th largest city in the United States, according to the 2000 Census. During the weekday work hours, the population swells to 1 million in the city limits. The department employs 1,853 sworn officers and 898 civilians. These numbers include dispatchers, police service technicians, clerks, neighborhood watch coordinators, and school crossing guards. In 2000, we responded to more than 868,000 dispatched calls for service and reported 59,510 Part One Offenses under the UCR Summary Reporting Program. According to the preliminary figures released by the FBI for 2000, we ranked in the top 10 for various Part One Offenses for cities with more than 200,000 people. We ranked 10th in auto thefts, outranked only by New York, Chicago, Los Angeles, Houston, Phoenix, Dallas, Philadelphia, San Diego, and Las Vegas. Though these are preliminary statistics, they are aligned with the final statistics released by the FBI and published in Crime in the United States. Furthermore, we ranked seventh in burglaries, ninth in robberies, and ninth in rapes. The National Incident-Based Reporting System (NIBRS) is helping us to more accurately report crimes. Though no computer system handled our NIBRS reporting until July 2000, all of our officers were trained and using our newly designed NIBRS reporting forms beginning in the fall of 1999--we did not want to switch to new report forms, a more complex way of reporting crime, and a new computer system on the same day. To do all this at once would have been a sure recipe for disaster. More than six months before actual conversion to NIBRS from summary reporting to incident-based reporting (IBR), we were utilizing NIBRS values and more accurately reporting crimes. However, our computer system did not support the collection of all the data we were gathering.

Overview of NIBRS

NIBRS is a far more advanced, complex, and accurate form of crime incident reporting than IBR. The traditional UCR Summary Reporting Program requires the collection of data on only eight specific serious crimes, or Part One offenses. IBR requires the collection of data on 22 categories of serious crimes within 46 specific crime offenses (Group A Offenses) and an additional 11 nonserious offenses (Group B Offenses), which are reported only in arrest situations. The traditional UCR Summary Reporting Program has remained virtually unchanged since it was implemented in 1930. UCR Summary Reporting requires few edit checks or validations for crime incidents reported. The FBI applies only a reasonableness-of-data standard to UCR Summary Reporting. All the agencies reporting UCR data have received form letters from the FBI regarding the reasonableness of data. That is, as long as an explanation is reasonable, the FBI accepted it as plausible. Under UCR Summary Reporting, there is no requirement to validate specific reports. The FBI still uses the reasonableness-of-data approach with NIBRS reporting, however, NIBRS provides more data. Crime incidents reported in a NIBRS format are subjected to more than 1,000 computer edit and validation checks for errors on reported crime incidents. The number of checks and validations varies, based on the specific offenses reported for each crime incident. No such edit or validation checks are performed on UCR Summary data.

Chapter II

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Our department requires each officer to train for at least 80 hours on the data collection (report) forms and the computer software that performs the edit and validations checks of crime incident reports. The checks are based on crime offense classifications as they relate to elements of the specific incidents and offenses. One of the reasons we believe our NIBRS implementation was so successful is because we did "due diligence" before releasing a request for proposal (RFP) for computer software. The numerous interdepartmental and multi-jurisdictional committees tasked with evaluating our development, implementation, training, and software needs all recognized that the NIBRS program was designed to make data capture easy for a computer system, not necessarily for the officer taking the report. Almost all of the NIBRS forms we evaluated--whether local, state, or federal agencies--had one thing in common: the need to enter a numeric, alphabetical, or alphanumeric code for each data element required in NIBRS Reporting on the field crime incident report. Examples include the following: · Enter code "120" if the offense is a "robbery." · Enter "13A" if "aggravated assault." · If the incident involved a hate crime and was considered to be "anti-black" enter the code "12." · If the property stolen is a gun enter the code "13" for "firearms." The consensus of the committees was to not require officers compiling NIBRS crime incident reports to refer to a list for a code. We adopted a "no code" strategy in designing our NIBRS reporting forms, using a "check the box" or "fill in the blank" approach. We referred to this as our "NIBRS for Dummies" approach. No NIBRS codes appear on any of our field data collection report forms. The software determines the codes necessary for each NIBRS or state-specific data element, based on the checked box or text entered for the data field. This approach makes it easier for public safety agencies to go beyond their existing systems to a NIBRS format of reporting crime incidents.

crime reports per month. We never adequately measured Part Two Crimes because our old computer system could not properly collect that data. We anticipate submitting between 120,000 to 140,000 crime incident reports in total in 2001 using the NIBRS format. The transition from the traditional UCR Summary reporting of crimes to incident-based reporting (IBR) was difficult and expensive. Implementing NIBRS took more than 3 years of planning, research, and development. In the state of Tennessee, we have a program called TIBRS, Tennessee Incident-Based Reporting System. TIBRS added 22 additional state-specific data-collection elements, beyond what NIBRS requires on the federal level. Participation in the NIBRS program is voluntary on the federal level, but state law mandates participation in TIBRS. For certification as a NIBRS Reporting Agency, our state program requires an agency to submit NIBRS data for three consecutive months with less than a 4 percent error rate. If we exceed a 4 percent error rate for any month of reported data, we lose certification and to be recertified, we have to repeat the process of three consecutive months with less than a 4 percent error rate. The penalty for lack of certification, or the loss of it, is the withdrawal of state and federal grant monies. The Memphis agency receives and depends upon millions of dollars from such grants. The department, through a desired and mutual agreement with the Shelby County Sheriff's Office (SCSO) planned, researched, trained, and coordinated our NIBRS implementation with the SCSO. Both agencies use the same custom-designed IBR reporting forms, and our department provides the software and computer system support for the SCSO's crime incident reporting. The SCSO has 511 sworn employees and 1,621 civilian employees, which are mostly deputy jailers. Combined, we have more than 2,300 sworn personnel and 2,500 civilian personnel committed to public safety in our jurisdiction. We do not have a metro form of government, but if we combine the NIBRS and public safety efforts of the department and the SCSO, we estimate we would rank about the eighth largest public safety agency in the United States. After several years of preparation, on July 1, 2000, the department and the SCSO began the actual transition from the traditional UCR Summary Reporting to NIBRS, using a newly purchased computer software system called Vision. Four months later, the Tennessee Bureau of

What We Did

As a result of switching to NIBRS, we are averaging between 10,000 and 12,000 crime incident reports a month. These numbers include Group A and Group B Offenses, or what are called Part One and Part Two Crimes under UCR Summary Reporting. In UCR summary reporting, we averaged about 5,000 Part One


Investigation (TBI) certified both our department and SCSO. Both agencies had less than a 1 percent error rate for each month. Obtaining certification within a fourmonth period is unprecedented--never before accomplished by any agency of our size implementing NIBRS. In June 2001, our error rate for NIBRS was 0.3 percent, or 48 errors in about 14,000 incident reports.

most successful state IBR programs in the nation. In Tennessee, 97 percent of the law enforcement agencies are both NIBRS certified and are reporting NIBRS. The success of our implementation would not have been possible without support, training, and guidance provided by our state program and we congratulate and thank the TBI for their assistance. 4. Simplification of NIBRS. Throughout our years of research, planning, and development to implement IBR, we struggled with how to make this complex style of reporting easier for the officers taking crime reports. We continue to refine data collection methods, but we believe our agency has made more in-roads and progress relating to simplifying IBR reporting than any other agency.


Many factors contributed to our successful NIBRS implementation, including the following:

Data Systems for Policing in the 21st Century--Facilitating the Implementation of Incident-Based Data Systems

1. Technology and software to support the implementation. NIBRS cannot be implemented in medium or large agencies without adequate network infrastructure or computer software to support IBR. The NIBRS edition of the Uniform Crime Report Handbook published by the FBI clearly states that an automated computer system is required. We did not have in-house programmers or funds to customize a records management system to address our specific business needs and IBR. Thus, we relied on an outside vendor to meet these needs. 2. Unconditional support by your department's command staff. A frequent complaint we heard from small and large agencies during our research and from our annual state conferences on IBR was that the chief and other decision makers in the agency did not understand the complexity and needs required for IBR reporting. Our command staff was actively involved in the planning, research, development, training, and implementation of our IBR program. Our research showed that the most frequent complaint from agencies implementing IBR was not having support from police administrators; we did not wish to repeat that mistake. Upper-level administrators' ignorance about the effects of transitioning from UCR Summary to IBR reporting significantly impeded implementation for many agencies we consulted. Police administrators frequently failed to fund training, data entry, computer hardware, and software support for IBR. They also failed to realize how IBR would influence their crime statistics. The FBI's research concludes that an agency switching from summary to IBR reporting will see an increase of 5 to 7 percent in reported crime. Our experience suggests that the percentage may be much larger. We now have our first year of NIBRS data, and it will be another year before we can complete statistical research and compare how the change in incident reporting affected our statistics. 3. Excellent state program for NIBRS. The Tennessee Bureau of Investigation (TBI) has developed one of the

Lessons Learned

Offense Classification We discovered, just as other agencies have, that we had incorrectly classified many reports under UCR Summary Reporting. Our past training and oversight procedures for crime incident reporting were flawed. The implementation of NIBRS brought these issues to the forefront. For example, a person fails to return a rented car. Ten days later the rental agency reports the car stolen and we take a motor vehicle theft report. That was wrong under both UCR Summary and NIBRS reporting standards. The incident should have been reported as a fraud offense. We inflated our auto theft numbers by not correctly classifying these types of crimes. The lesson here is that agencies still reporting under summary standards must ensure that crime incident reports are properly classified. Both the UCR Summary and NIBRS use the same basic definitions for offense classifications, which come from Black's Law Dictionary. Definitions of crime offenses have not significantly changed from Summary to IBR; IBR just has more classifications. We improperly classified crimes in the past, and even with the transition to NIBRS, we still struggle with getting our personnel to correctly classify criminal offenses. Correctly reporting all the criminal offenses that occur within a single crime incident is the most difficult challenge any agency will encounter with NIBRS. The most important process of NIBRS implementation is learning the offense classification definitions. All other parts of the process will fall into place once your personnel

Chapter II

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understand and learn the proper crime classifications. Data Entry Our agency did not anticipate the increased amount of data entry NIBRS requires. The time to take a crime incident report in the field increased by about 10 minutes, once the officers became familiar with IBR procedures. However, the time it took to put the report into the computer system increased by about 30 minutes. This was because of the additional data captured and the time it takes to check and correct computer-generated errors for reports not properly completed by officers. Plan and hire additional data entry personnel when you switch to NIBRS. Funding Our department received no state or federal funding for NIBRS, and still receives no outside funding, nor do we qualify for state or federal assistance with our ongoing IBR efforts. The cost for our agency to switch to IBR exceeded several million dollars, all of which was funded locally. We were fortunate that our local elected officials were committed to IBR and recognized that it would improve public safety through better crime reporting. The complexity of IBR did not lend itself to a "short explanation" to our local elected officials. To ensure proper funding, any IBR plan must embrace this thought, and elected officials must be educated on the benefits of switching to IBR. Funding from state and federal resources for the switch to NIBRS is not very available to large and medium-sized agencies. Clerical and Data Entry Personnel During our research we discovered that most agencies implementing and reporting NIBRS in our state found it easier to train their clerical and data entry personnel to meet the reporting standards. Ultimately these agencies gave up training their officers on how to take IBR reports properly. This was the path of least resistance for them--it is easier to train a few clerical personnel than to impose standards on the masses. We estimate that 80 percent of the agencies in Tennessee reporting NIBRS have taken this approach, which is not good for the respective agencies, but it satisfies the NIBRS requirements. Some agencies in the state of Tennessee are completely dependent upon clerical staff for NIBRS reporting. Members of the Judicial Districts Drug Task Forces in our state are a good example: A single clerk for each district reviews all the collected data and creates a NIBRS report, and we have seen the same process applied by many other

law enforcement agencies in our state. We too have developed a dependence on clerical staff for proper NIBRS reporting, but we strongly suggest that any medium-sized or large agency implementing NIBRS try to improve upon the processes we have implemented. We have three specially trained data entry clerks with a superior knowledge of NIBRS, who daily review every incident report in the computer system for proper crime classifications and NIBRS compliance. We call this unit the Data Assurance Team. Additionally, we pay our computer software vendor to provide an on-site specialized NIBRS consultant/trainer, who works directly with these three individuals to ensure compliance, identify shortcomings in the software that need further development, and identify training needs for our personnel.

These remarks were made by Walter E. Crews, Director of Police Services, City of Memphis Police Department, on July 19, 2001, at the National Symposium: Data Systems for Policing in the 21st Century, hosted by the Police Executive Research Forum at the Wyndham Baltimore Inner Harbor, Baltimore, Maryland.



CHAPTER II The Implementation of National Incident-Based Reporting by the Fairfax County (Virginia) Police Department 1

Colonel J. Thomas Manger, Chief of Police, Fairfax County Police Department2

Data Systems for Policing in the 21st Century--Facilitating the Implementation of Incident-Based Data Systems

Who We Are

Fairfax County is one of three counties nationwide whose population exceeds 250,000 that is submitting data to the National Incident-Based Reporting System (NIBRS). In the earliest requirement review, we studied the potential effect NIBRS would have on the Fairfax County Police Department. We recognized that it would replace the UCR as the basis for the department's crime statistics; inform the public of the county's crime rate; enhance the department's ability to analyze crime meaningfully; provide more detailed information for management, training, and planning decisions; and, someday, affect local and state funding to our agency. The Fairfax County Police Department's involvement with NIBRS began in the early 1980s when we responded to a national survey Abt Associates was conducting. Over the next several years, the department participated in numerous initiatives sponsored by the Commonwealth of Virginia to provide models for NIBRS implementation. While we supported initiatives to provide smaller agencies in the state with turnkey systems from statecertified vendors, we chose to rebuild our mainframe records management system (RMS) in-house and develop a customdesigned, fully integrated system. The primary contractor was Fairfax County's Department of Information Technology (DIT), with our Information and Policy Services Bureau responsible for the project management. We began planning for NIBRS implementation by defining the changes necessary to bring our existing mainframe Police Records Management System (PRMS) into compliance with Virginia's expanded NIBRS requirements. The department needed to completely redesign our Field Investigation Report, to develop new data entry screens and a new database back-end, and to upgrade our technology infrastructure. Beginning in 1991, we developed a strategic information plan. Our initial goal was to redevelop all PRMS applications into a modern relational database. The final phase of this multi-year project was the redesign of our case history application as the capstone of a fully integrated NIBRScompliant RMS. We worked to ensure that NIBRS components were included in applications being developed for other county criminal justice agencies, including a Judicial and Warrants System and a Live Scan Fingerprint System. What We Did It quickly became obvious that systems development was a massive undertaking, requiring substantial funding from the county, not to mention several years of designing and programming. To be successful, it was critical to have the cooperation of everyone in the agency. From the earliest stages, we advised all department personnel of the project and its implications. This dialogue, which was essentially a sales pitch, continued at all levels of the organization and proved to be a valuable asset when the new PRMS was installed. Positive Results The redesign of our Field Investigation Report (FIR) to capture the detail required by NIBRS illustrates the success of our approach. Because this would be the most visible change the rank-and-file officers saw, it was critical to the system's acceptance. In many ways, the task was a business process redesign as well. The FIR that officers used to document the incidents they worked on was a two-page form with an attached overlay to help the officers complete a series of coding blocks around the outside margins of the form. Several of the sample NIBRS-compliant forms reviewed were four to six pages long. We thought the officers might resist using a multi-page

Chapter II

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form, and decided to limit our NIBRS form to two pages. Once we defined the NIBRS databases, we created a prototype FIR and field-tested it at two of our seven district stations. To introduce the project and explain the role they were about to assume, officers were given the same presentation on NIBRS's background as our command staff. The officers and their supervisors were trained in using the form, which, because of our two-page design, was similar in format to the existing FIR. The prototype was printed on yellow paper so it could be readily distinguished from the existing form. The field test officers wrote each of their reports on both forms. In addition, a comment sheet was provided so they could note any suggestions, criticisms, or questions regarding the new form. This parallel data entry was a good foundation for comparison. Using the feedback from the field tests, we finalized the form and began extensive training of patrol supervisors and central records staff in a train-the-trainer approach. Concurrently, our in-house development team (personnel in DIT and the Information and Policy Services Bureau) used their knowledge of the existing system, along with a thorough analysis of NIBRS reporting requirements, to build the new system. The system redesign was completed in October 1999 and initial test data were sent to the Virginia State Police in November. In January 2000, at the conclusion of the testing period, we were certified as a NIBRS agency. Negative Results As with any major project, regardless of the advance planning, problems occur and difficulties arise. Implementation issues continue, particularly data entry backlog, error correction, and integration with new IT initiatives. As the transition continues, we are collecting NIBRS data and continuing to rely on UCR-format statistics. Project management. Perhaps the most serious deficiency in overall project management was our failure to understand the importance of staff continuity. Three years into the redesign the lead technical analyst left the DIT. This set back the project at least a year as her replacement tackled the steep learning curve. The overall design concept lacked formal documentation and a lot of high-level work had to be revisited. Other IT projects required the attention of the NIBRS project staff (e.g., the Y2K effort of 1999), further delaying the work. While no one can control the comings

and goings of staff, it is important to ensure that there is accurate up-to-date project documentation, and as much crossover among personnel as possible. Agency buy-in. There was still a general lack of attention to and understanding of the implications and pitfalls of the project, despite attempts to inform the agency about NIBRS. In particular, the area of staffing and the consequences of the additional data entry were not addressed until the data entry backlog reached near-crisis proportions. Staffing. Deficits occurred in more than one area of staffing as a result of NIBRS implementation. For example, because NIBRS requires that more information be collected than does the Field Investigation Report, officers spent more time writing reports and less time patrolling, especially for the first few months of implementation. Data entry backlog. For the past several years, we have averaged writing more than 150,000 reports annually. We expect this number to increase as our service population increases and our community policing philosophy matures. Completing a NIBRS report takes almost twice as long as the previous UCR version. More than 500 reports a day are sent to our record room for entry, i.e., nearly 200,000 in 2001. With about 50 percent of the reports failing the NIBRS validation and requiring correction and re-entry, a considerable backlog results. Needless to say, this quickly overwhelmed data entry staff. The backlog went from six weeks to six months in the span of a few years; at worst we were nine months behind. Year 2000 data are still not fully reported at the time of the conference. In some ways, the project's initial result was a sophisticated NIBRS-compliant RMS without adequate resources to support the system's desired outcome. Initial response to problems. Our first steps toward resolving the data entry backlog were to apply additional personnel and to postpone the correction of reports that did not pass NIBRS validation. Staffing. A review of the data entry backlog problem showed that increasing the number of staff at the Central Records Division was the quickest way to catch up. After establishing policies regarding training, supervision, and security we hired 10 clerks on a temporary basis. Data entry backlog. Staff concentrated their efforts on the initial entry of incident reports because it became more important to get the data into PRMS than to ensure that all NIBRS requirements had been met. (We had already


informed the State Police, as the NIBRS agents for Virginia, that 2000 data would be incomplete.) Though these extraordinary measures are chipping away at the backlog, much work remains. Some agencies faced with the same problem have elected not to report NIBRS data at all, a direction we are committed never to pursue. The problems we encountered will have consequences that need to be resolved. It is important to note that the data entry backlog did not mean we designed a bad RMS. The backlog had been slowly growing for some time before implementation of NIBRS. Our information not being upto-date implies serious consequences for the department. For example, crime analysis is more difficult and our data are not timely enough to assist management in making strategic planning decisions. State and federal funding. Our eligibility for grants tied to NIBRS compliance could be jeopardized and the level of funding we receive from the state of Virginia could be reduced because reported crime statistics do not accurately reflect what is occurring in Fairfax County. Public awareness of NIBRS statistical reporting. Once the move from UCR to NIBRS statistics is complete, it is important to be aware of possible public reactions to NIBRS's counts, in which crime may appear to increase. Comparing UCR with NIBRS is as useful as comparing apples with oranges. While crime rates may appear to go up in NIBRS, the increase is actually a function of the differences between NIBRS's detailed reporting and UCR's summary reporting. We must educate our citizens about this change by conducting media briefings and ensuring that local government officials understand it. Budgeting. Because the project was done in-house using existing technology, the only budget considerations were for personnel. Neither DIT nor the Police Department needed additional staff or contractor assistance. Temporary staff was brought in only to reduce the data entry backlog. We must assess the workload at our Central Records Division and consider additional permanent staff. We know that information technology personnel levels are below the optimum level in our Information and Policy Services Bureau and in the DIT. Police Records Management System. At this point, we have a fully integrated RMS in place, developed entirely inhouse in an up-to-date relational database with a CICS user interface. The various applications within the RMS (e.g., arrest, warrant, investigation management, and real property) are fully integrated, reducing redundant data entry as much as possible.

While the system is NIBRS-compliant, we are only reporting partial crime data because of the backlog and because of quality control issues. We had planned to move ahead with enhancements to the PRMS user interface, but instead evaluated replacing the system. As a result, extensive modifications of PRMS have been deferred, except for changes mandated by Fairfax County or the state. Related automation projects. Other automation initiatives that will affect how we proceed are closely related to records management. As of fall 2001, and after significant delays, our CAD system was upgraded to PRC Altaris. Installation was expected late in 2002. A by-product of that project is the acquisition of a mobile field reporting application that will allow officers to complete their reports on mobile data computers in their cars. Development of this application is dependent upon the completion of the CAD and has been independent of RMS development. Mobile field reporting (also known as in-vehicle reporting) is seen as the long-term solution to our data-entry and quality control problems. The originating officer will enter data into the application. Point-of-entry validation and error correction edits will not allow the report to be submitted for supervisory review until it is correct. Once approved the report will be uploaded directly into the RMS. Recommendations No matter the outcome of a project, lessons learned will facilitate the next effort. Our look back at the NIBRS experience noted several areas we can improve on and some pitfalls we will try to avoid. 1. Sponsorship. When someone mentions sponsors, we commonly think of television commercials. In the case of NIBRS implementation, sponsorship involves a commitment to the project from everyone in the agency, including the chief, data entry clerks, and patrol officers. Without this commitment, the project is doomed. 2. Executive sponsorship. Sponsorship by the Chief of Police and the executive team is critical to successful transition to IBR. But there is more than one way to approach a project. Top leadership must narrow options and choose one plan as "the plan." Once this is done, there are several areas in which the chief should exercise some degree of influence. New products, technology, and ideas will arise after the course of action is chosen. The chief can ensure that once the agency has devised and approved a sound plan, it will have a chance to proceed without the "scope creep" that new requirements cause, along with the accompanying extended

Chapter II

Data Systems for Policing in the 21st Century--Facilitating the Implementation of Incident-Based Data Systems

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schedule and expanded budget. Chief executives can also assist the project manager in overcoming obstacles arising outside the agency (with the parent government, for example), ensuring that appropriate staff support and funding streams are in place and secure, and smoothing inter-agency cooperation. 3. Command buy-in. While sponsorship is a responsibility of the executive level, everyone in the department should know what is happening, why it is necessary, and the goals of the project. Often, the only notice stakeholders have in an automation project is at the end, when they are asked to test the application. Early participation by representatives of all stakeholders in planning and requirements definition will give a sense of ownership that can help overcome the natural resistance any organization has toward change. If resistance to the project is noted, the causes should be quickly identified and addressed at the appropriate command level so it can be alleviated. The longer resistance is allowed to linger, the greater its potential to damage the project. 4. Project planning and project management. In project planning and management, several guiding principles cannot be overlooked. Know what is in place before beginning. Existing systems rely upon business rules and operational procedures. Data structures may have to be converted or expanded. Ignoring an existing system might require expensive changes after the new system has been installed. The project should have a well-defined goal. The goal of our project was to complete the modernization of the PRMS by redesigning the case history subsystem to be NIBRScompliant. Minimizing staff turnover gives the project its best chance for success. For example, avoid naming to the project someone near retirement (although this may be your most experienced staff member) or someone who is about to be promoted or transferred. Staff turnover can cause serious delays. To minimize this risk, assign staff members who are likely to be available for the duration of the project and require that they keep accurate records of major decisions and requested changes. Whether the system is being developed in-house or with a vendor, make sure there is adequate commitment for staff support, both managerial and technical. Monitor the project timelines and enforce accountability. Be prepared to address potential reductions of staff support and effort over time because of competing projects. Avoid "scope creep" during the design phase of the project--a situation where "every time you turn around, something gets added." At some point, new requirements are

not permitted. Build quality control and maintenance from the bottom up. In the case of a NIBRS project, officers need training in the proper report-writing protocols and must understand the critical need for accuracy. It is difficult to exaggerate the importance that a well-planned training program across the agency can have to the success of the entire project. 5. Define specific requirements. Because the goal of this particular redesign effort was to meet the very specific NIBRS requirements, a baseline for its development was easily defined. We worked directly from the Data Dictionary and Functional Specifications, which the Virginia State Police provided to all Virginia local law enforcement agencies. These documents presented the FBI-NIBRS requirements as well as additional data elements for VirginiaNIBRS. This clearly defined what modifications were necessary and eliminated the need for an extensive requirements analysis. To meet reporting requirements, it is critical to have a clear picture of what the system must do and how the database must be designed. 6. Miscellaneous. Other key points should be carefully considered and included in the requirements. For example, give data entry to the person responsible for the report, i.e., the officer or detective. This way the report can be validated against the NIBRS edits as it is entered. Ensure that supervisory review of each preliminary report is consistent and thorough. If possible, design custom interfaces for different users, for example, one for officers and another for data entry professionals. Determine whether newer database technology is necessary, and if so, confirm that technical and programming staff has enough knowledge of the current system to convert historical data to the new format. Avoid having one system for old data and another for new. Make sure to build sufficient capacity for growth and expansion. Future Decision Points Several issues will need attention as we continue fine-tuning our NIBRS system and plan for future development. These include how we will handle quality control, and the future of records management. Data Quality and Report Errors Validation of our report data for NIBRS submission is a problem that must be solved. The key lies in initiating quality control practices at the point of entry--that is, with the officer writing the report. Additional training may be necessary to ensure that officers and first-line supervisors


understand the basics of NIBRS requirements, particularly for the most common incidents that result in written reports. Our proposed mobile field reporting application will include point-of-entry validation at the data element level and should resolve these issues. Staff at the Central Records Division must also understand the importance of accurate data entry for the documents processed there. Automated random checks of NIBRS reports can be used to test the thoroughness of our quality control procedures. A New RMS

Data Systems for Policing in the 21st Century--Facilitating the Implementation of Incident-Based Data Systems

option we feel is best for us? · Will funding be available? · Is the level of risk involved in a project of this magnitude acceptable and manageable? · Are our expectations for a new system realistic recognizing that a new RMS alone will not resolve all the current issues? · Are we prepared for a major IT project that could take several years to complete? · Are we prepared to commit the internal resources necessary to manage this project to a successful conclusion?

We are considering replacing our current RMS. Our research began by developing a request for information (RFI) that was distributed to information technology (IT) vendors registered with the county's purchasing agency, as well as others we identified as major players in RMS development. The RFI generated more than a dozen responses. This information will help us prepare a statement of work and contract with a consultant to conduct a major, agency-wide user requirements analysis as the first steps towards acquisition or redesign. Several broad questions must be answered: · Will we be able to build a consensus regarding what our requirements are? · Are we willing to change current business processes to accommodate a commercial-off-the-shelf (COTS) application rather than a custom-developed system? · What level of customization is required if we choose a COTS product? · As we evaluate proposals by conducting a gap analysis to compare them with our current system, what is an acceptable level of change and how much can we afford? · Can we improve or expand current interfaces with other public safety agencies? · What platform should the new system use? · If the new system is independent of county IT support, can we achieve the staffing levels necessary to support an operation 24 hours a day, seven days a week? · Can we define information requirements that will allow us to provide effective community policing? Acquisition planning. If we decide to pursue a new system, we must decide how the purchase will be handled. Again, many questions remain: · Should we pursue a competitive process as defined by the county and state of Virginia? · Would a sole-source purchase be a better alternative? · Can we make the business justification to support the


The decisions we make as we implement NIBRS come with risks. For example, although 16 vendors are certified for NIBRS applications in Virginia, we decided to build our own. We reached this decision after comparing the advantages that we would gain from a custom system with the reduced risks associated with an off-the-shelf product that was proven to work. When planning an IT project, we must temper the desire for new, "bleeding edge" technology with the need to practice responsible financial stewardship. We are a government agency, using taxpayers' money. As such, we are accountable to the public for decisions and planning. We must also recognize that the list above is just the beginning of questions and decisions. Along the way, there will be thousands of decisions, ranging from mundane to momentous. Unwavering executive sponsorship will be necessary to facilitate the desired outcome. An appropriate level of empowerment must be established for the project team to know what level of decisions they may make (without subsequent second-guessing or offensive attacks) and which decisions must be elevated to the executive sponsor or steering committee. While the project team decision makers should be held accountable and should be expected to articulate their reasoning, they should not be put into a position of defending every aspect of their involvement in the decision process. Thus, it is imperative that the executive sponsor be a full and active participant in the process, serving as the final arbiter of directions and the overall leader of the project, with the unwavering commitment to the final goal. Like Fairfax County, many jurisdictions have mandated applications for all forms of IT development. If none exist,

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industry standards can be reviewed for application development and procurement. A meticulous adherence to this plan will provide not only guidance and direction, but most importantly, the framework to avoid failure, embarrassment, and the inappropriate expenditure of tax dollars. It is essential to ensure the use of, and adherence to, a tested and accepted life cycle plan. This plan can be modified as necessary, ensuring the best chance for success. The result of a successful plan will be a fully developed, well-conceived system capable of supporting not only today's development of policing capabilities, but those of the future. NIBRS implementation has been a continual struggle for us. Ultimately, Fairfax County and all of us who are faced with this challenge can succeed and obtain the full benefit of NIBRS for our agencies and the communities we serve.

1 This article is based on a presentation by Colonel J. Thomas Manger, Chief of Police, at the Police Executive Research Forum National Symposium on Data Systems for Policing in the 21st Century. 2 At the time of publication, the author is Chief of Police for the Montgomery County (MD) Police Department.


CHAPTER II Incorporating NIBRS into the Custom Development of an Offense Reporting and Records Management System in Charlotte-Mecklenburg

Veronica L. Sorban, Charlotte-Mecklenburg Police Department

Data Systems for Policing in the 21st Century--Facilitating the Implementation of Incident-Based Data Systems

Who We Are and What We Did

In May 1998, the Charlotte-Mecklenburg Police Department (CMPD) began work on a custom-built offense reporting and records management system (RMS). The system was part of a strategic technology plan called Knowledge-Based Community Oriented Policing Systems (KBCOPS). The plan called for an integrated set of databases to support problem-solving and communitybased initiatives, as well as crime investigation, case management, analysis and research, and local and state crime reporting. All of the applications were planned to take advantage of new technology in client-server computing, laptop personal computers, and wireless transmission that replaced outdated mainframe applications and multiple personal computer databases. The Oracle Corporation was the major developer; a project team included management, development, and support staff from both Oracle and the Police Department. The original plans for the offense report and records management module (KBCOPS-RMS) called for compliance with the crime reporting requirements of the North Carolina Incident-Based Reporting System, Level 2.1 Although the North Carolina system supported a version of incident-based reporting (IBR), as well as summary UCR data, it was not compliant with the National Incident-Based Reporting System (NIBRS). When our project began, there were no plans to revise the state system. However, midway into our RMS project, the North Carolina program developed a new set of NIBRS-compliant data standards (NC-IBRS, Level 3), and they encouraged us to revise our project requirements to include them. They also assisted us in applying for a grant, Showcasing Modern Law Enforcement Records Management Systems, sponsored by the Bureau of Justice Statistics and the FBI. This grant was to assist with modifying what had already been developed and with the new development that would be required. The KBCOPS-RMS module was needed to replace an aging mainframe RMS that supported the entry of traditional offense and arrest data. The old mainframe system contained minimal elements from each police report, mainly related to offense type, location, basic victim demographics, stolen property records, clearance types, and arrests. Records staff matched the paper reports to the correct call-for-service records from the dispatch system, read the reports to determine the correct crime classification, coded the various data elements, and then entered the data records. There were few crime-specific modus operandi (MO) data and no suspect information for non-arrested persons linked to the offense. For investigative assignment, cases were routed manually with copies of the paper report. Standard reports for monthly administrative crime statistics and UCR submission were not flexible; they were written in Common Business Orientated Language (COBOL) and were run by the city's computer operations staff. On-line data retrieval mainly allowed the system to act as an index to search for reports by limited criteria. Officers who wanted information on the cases had to get paper copies from the Records Bureau. Data retrieval for analysis or projects had to be done by COBOL programmers or by daily data downloads into files used with mainframe SAS, personal computer (e.g., Access, Excel), or GIS software. There were few edits on the mainframe system for error checking, and any downloaded address data had to be separately geocoded, with additional manual geocoding for records that did not match the GIS street file. When information in the report was missing or inconsistent, coding and data entry clerks often used their own interpretation or default data. There were minimal updates to data originally entered on each report--generally just additions or changes to clearance and property records. The

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system maintained few audit data to assist in tracking changes to records or problems in the monthly UCR and department reports. Interfaces with other systems were difficult to program and maintain, and no new features had been added to the mainframe system since it was adopted in 1984.

the development schedule. The first step was to assess what needed to be changed in the existing fields and tables. However, many issues had to be resolved during this process. Data compatibility. The original design for the system incorporated a dual crime classification that referenced both state statute categories and corresponding UCR categories. The NIBRS crime coding did not fit easily into the tables that matched state to national offense groups. It also affected the "hierarchy" lists that were created for UCR and for case management. The NIBRS data values of some fields were not what officers and analysts had requested for problem solving, investigation, and tactical analysis. For example, the NIBRS Location Type was not sufficient; officers working on problem solving wanted to know if the offenses in parking lots in an area were related to a specific business type, such as a bar or hotel. Some data values were not compatible for integration with other systems, either within CMPD or with local county systems (jail, magistrate, etc.). For example, the charge codes in the local arrest system, maintained by the County Sheriff, had an attached UCR code that did not accommodate some of the more specific NIBRS breakdowns, such as the multiple categories for fraud or gambling. NIBRS-required links and edits. Some links between NIBRS files and fields are not what CMPD officer and investigator groups recommended. In cases with multiple offenders, NIBRS calls for multiple relationships for victim to offender. Originally, the data structure called only for one relationship and did not specify a link to a specific offender. Some NIBRS Group A crimes--like drugs, prostitution, gambling, and weapons violations--required a link to an offense report where officers were not required to submit an offense report with the arrest. (This issue was resolved when NIBRS modified its rules to allow these arrests to be submitted without a linked report.) Validation edits require the system to check data from different screens, some of which may not be entered in the order needed for on-line error checking. Using a batch process to create the NIBRS segments and validate the elements as part of the monthly reporting process would require recontacting numerous officers to correct their reports. Technical issues complicated by NIBRS edits. Officers' laptops are set up as "thin client" in our infrastructure. The wireless network requires a relatively small packet size for each screen load, so that increasing on-line edits overwhelmed the packet and exceeded page load time limits. Much of the application had been developed

Requirements for the KBCOPS-RMS

One of the main requirements for the new RMS was to allow officers to create the offense report directly on laptop computers in the field and to submit the report through the wireless Cellular Digital Packet Data (CDPD) network into the database servers. Other features included the following: · On their laptop computers, officers could retrieve and update reports, attach narrative supplements, and monitor cases in their assigned response areas. · The report screens would include on-line edits for some fields, drop-down boxes and selection lists for standardized data entry, and mandatory entry for some fields. · Reports would automatically appear in the shift supervisor's queue for approval, or return to the officer for correction and resubmission. · Cases would be routed to the appropriate unit for investigation based on current business rules incorporating both the UCR classification and other factors, like the victim's age or the value of property stolen. · Street address validation and geocoding could be done automatically at the time the report was submitted. · The relational database would be in a standard platform so that interfaces to other databases would be easier to create and maintain. · Crime-specific templates would incorporate the crime and MO elements in distinct fields so that data entry in individual databases kept by crime analysts or investigative units could be discontinued. · The use of data fields rather than a dependence on narrative would allow standard searches to be built for investigations and problem solving. Analysts would use the database tables with other tools (e.g., SQL, SAS) to analyze trend and profile data, or to provide ad hoc support for non-standard searches. · UCR reporting would be automated, and the same reporting formats could be applied to patrol districts and response areas on-line. NIBRS Development When the CMPD agreed to incorporate North Carolina's NIBRS-compatible requirements into the system, the development team had already created a substantial portion of the code, tables, and screens. With the assistance of the grant from BJS and the FBI, the NIBRS work was added to


using a standard tool (Oracle Developer 2000) to automate code development. Some changes required fairly extensive manual modification or the creation of new code.

in an area can exclude cases inside the convenience stores. (Question 15 is a conditional field for state requirements; it is only mandatory if the premises type is a residence. It indicates whether it was the residence of the victim, offender, or other person, and we can use it in risk assessment and crime prevention as well as in investigative analysis.)

Lessons Learned

Resolutions: Data Compatibility Issues

In working out these issues, CMPD sought resolutions that did not include the loss of the data values and fields for investigations, and sought to address problem solving that had been requested in meetings with community coordinators, detectives, and other officers. Where the change in the data values did not have significant consequences, we changed them. On the Bias Motivation field, for example, we changed our values list to match the list the FBI uses for NIBRS. Minor modifications were made where data values could be mapped by a translation table to the NIBRS values. For example, we adjusted some weapons values so they would coincide with the NIBRS values. When value lists could not be directly rolled up into NIBRS values, we set up a secondary field or created an algorithm that combined the values in more than one field, as seen in the following examples: Using a secondary field. When an officer selects an offense type from the local crime listing and it has a direct match to a NIBRS type, the NIBRS type is automatically entered in the NIBRS offense field. If there is no direct match, a pop-up window shows the possible appropriate choices. The officer selects one from the window and the choice automatically populates the NIBRS field. Using an algorithm. When a combination of fields can be used to create the NIBRS value, we set up business rules in the system to interpret them. For example, we have two related location fields to better identify crime sites. Question 13 indicates whether the location was an indoor site, a parking lot or deck, or a non-parking outside location. Question 14 refers to the type of premises or associated premises. If an offense occurred inside a convenience store, the officer chooses "Indoor" and then selects "Convenience store" from the premises type list. The rules indicate that "Convenience store" is reported when the NIBRS segment is created. But if the offense occurred only in the lot outside the convenience store, the officer chooses "Parking lot" and "Convenience store." The rules will then submit "Parking lot/Garage" to NIBRS. An analyst working on problems associated with convenience stores can locate crimes both inside convenience stores and in their associated parking areas, while someone looking only for parking lot problems

Resolutions: Links and Validation Issues

In the few instances where the data fields were not linked, as NIBRS requires, we modified the data structure. For example, the weapons field was originally linked to the victim table and the victim's injury level rather than to the offense type. We changed the data structure to make the link between weapon and offense. Since each offense has to be associated with a victim in our system, we can still recover the connection between victim and weapon. However, it adds complexity to a data query or analysis relating to victim's injury and weapons--it now requires merging three data tables (victim, offense, and weapon) instead of two (victim and weapon). We resolved the multiple victimoffender relationship issue by creating a screen matrix that automatically links each victim with each offender. The user on this screen chooses the relationship from a drop-down box attached to each linked pair. We are still considering the best way to handle validation edits that require the system to check data from different screens. Edits that require validation across multiple segments can be done more easily from the NIBRS segments than from the primary data tables. However, a batch editing process as part of the monthly UCR or NIBRS reporting process makes the correction process difficult when dealing with the volume of reports our officers complete each month. We create and store the NIBRS record segments as part of the on-line submission process for each report rather than as part of a batch process. Thus, when an officer indicates that a report is ready to be submitted for approval, the system creates and checks the NIBRS segments. The segments are stored for the monthly reporting process if they pass the validation edits. If they do not pass, then specific error messages indicate to the officer the field or screens that are causing the error and must be modified. For example, if the user chooses "Simple Assault" as the offense, but lists a serious injury in the "Victims" screen or a gun, knife, or other weapon on the "Weapons" screen, the system will notify the user of the inconsistency. At that point the user must correct either the choice of injury, weapon, or NIBRS offense before the report can be resubmitted for approval.

Data Systems for Policing in the 21st Century--Facilitating the Implementation of Incident-Based Data Systems

Technical and Infrastructure Issues

The laptops and desktops officers use in cars and offices

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have a standardized image set up mainly as "thin client" for applications such as the KBCOPS-RMS. The KBCOPS applications employ a Web-based front end; working through the department's Intranet either over the CDPD wireless network (through Packet Cluster /Cerulean Cloudserver or through Infowave "middleware" for wireless Web applications) or over the local wired LAN. Each screen in the application includes a navigator sidebar where users select the parts of the report they want to work on and where they can track screens already entered. The data in each screen are saved independently in the database on the server, even before the user indicates that the report is complete and submits it for approval. Originally, no application codes or lists of values were stored on the laptop or desktop. The reasons for this include storage capacity, as well as the difficulties involved in updating all laptops whenever the applications were changed. But, as packets increased, performance decreased (i.e., slow load times, time-outs, etc.), so developers were able to break out some of the codes and attached lists to make them reside on the laptop. They also created a way to update those files over the radio network, incorporating an automatic check for the new files whenever a user enters the KBCOPS-RMS. In addition, the decision to incorporate some of the NIBRS edits into the report's final submission process, rather than in the individual screens, will help limit the impact on system performance. One of the most serious drawbacks from the addition of NIBRS was the amount of manual programming that had to be done. This has increased the development costs and time for the project, because original estimates were based on using a larger proportion of generated code from the Oracle development tools. While the grant for NIBRS assistance paid for some of the additional work, department and city developers rather than contract programmers are continuing the tasks for completing and testing the NIBRS edits and the state reporting process.

(including some of the NIBRS edits), and modifications requested by various units or officers. Priorities in development now include the completion of the functions in the offense module for NIBRS editing, the creation of the data segments, and finally, testing those functions at the state level. However, the development of the arrest module to supply the NIBRS arrest segments has been delayed, in part by a related interagency project to develop an integrated arrest, jail, court management, and information system and also by the local and state budget adjustments for most agencies this year. In the interim, we are exploring ways to capture the data from existing systems to submit full NIBRS data to the state. The KBCOPS-RMS was designed to allow us to continue adding and modifying its functionality and it is expected to be a work-in-progress for some time. An arrest module, interfaces with other systems, and additional search and analysis capabilities will be integrated as development continues. While adding NIBRS capability has certainly increased the complexity of the system, we expect the addition not only to enhance our own department's efforts to analyze patterns and changes in crime, but also to facilitate work with local, state, and national efforts to increase the effectiveness of law enforcement.

Crime reporting in North Carolina is administered by the Division of Criminal Information at the State Bureau of Investigation.



The CMPD conducted a pilot for the offense-reporting portion of the system in August 2000, and brought the entire department on line in February and March 2001, training approximately 1,800 officers and civilians. Since then, new features have been completed, adding to its functionality. These features include a case management module with automated case routing, notifications to investigators for overdue follow-up or supplements added by other officers, a set of basic incident data searches and some investigative queries, new edits for data checking



Data Systems for Policing in the 21st Century--Facilitating the Implementation of Incident-Based Data Systems

Making Sense of the Data: Providing Information for Problem Solving

1. The Measurement of White-Collar Crime Using Uniform Crime Reporting (UCR) Data-- 35 Cynthia Barnett, Federal Bureau of Investigation 2. Analysis of Motor Vehicle Theft Using Survival Model-- 45 Cynthia Barnett, Federal Bureau of Investigation 3. Mapping NIBRS Data: Using Massachusetts' Enhanced NIBRS for Examining Heroin Use, Sales, and Distribution across Multiple Jurisdictions-- 53 Dan Bibel, Massachusetts State Police; Don Faggiani, PERF; and Lindsay Robertson, Wyoming Statistical Analysis Center

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CHAPTER III The Measurement of White-Collar Crime Using Uniform Crime Reporting (UCR) Data

Data Systems for Policing in the 21st Century--Facilitating the Implementation of Incident-Based Data Systems

Cynthia Barnett, Federal Bureau of Investigation

This article was reprinted from the FBI Criminal Justice Information Services (CJIS) Division.

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Data Systems for Policing in the 21st Century--Facilitating the Implementation of Incident-Based Data Systems

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Data Systems for Policing in the 21st Century--Facilitating the Implementation of Incident-Based Data Systems

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Data Systems for Policing in the 21st Century--Facilitating the Implementation of Incident-Based Data Systems

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Data Systems for Policing in the 21st Century--Facilitating the Implementation of Incident-Based Data Systems

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CHAPTER III Analysis of Motor Vehicle Theft Using Survival Model

Cynthia Barnett, Federal Bureau of Investigation

Introduction Motor vehicle theft, as defined by the Uniform Crime Reporting (UCR) Program, is the theft or attempted theft of a motor vehicle including automobiles, trucks, buses, motorcycles, motor scooters, and snowmobiles. The definition also includes the temporary possession of a motor vehicle by those persons not having lawful access and joy riding. Farm equipment, bulldozers, airplanes, construction equipment, or motorboats are not included in this definition. (UCR Handbook, 1984, p. 28). The staggering cost to the public in terms of lost property has been a real concern for the victims of motor vehicle theft, policy makers, and law enforcement. Understandably, the law enforcement community has attempted to better understand, prevent, and solve this crime for years. In an effort to assist law enforcement and all individuals and organizations concerned with

Data Systems for Policing in the 21st Century--Facilitating the Implementation of Incident-Based Data Systems

crime, staff members of the Federal Bureau of Investigation (FBI) collect, compile, and disseminate crime data. In addition, they conduct detailed studies and analyses to inform the public about the dynamics of crime and the preventive measures that can be taken against the loss of property. In that regard, this study has been prepared to take a closer look at a crime that affects millions of the Nation's citizens. Americans consider their automobiles a primary means of transportation, and the loss of a vehicle creates a great deal of temporary inconvenience both in terms of lifestyle and cost. In many cases, stolen cars have also been used in the commission of other serious crimes. According to the UCR Program, nearly 43 million motor vehicles were stolen from 1960 to 1999 (see Figure 5.1). Although it was not a steady increase, the trend shows that motor vehicle theft increased significantly during those four decades. Declines in the 1990s, however, show major













0 1 9 6 0 1 9 6 5 1 9 7 0 1 9 7 5 1 9 8 0 1 9 8 5 1 9 9 0 1 9 9 5 1 9 9 9


This article was reprinted from FBI (2000). Analysis of Motor Vehicle Theft Using Survival Model. In Crime in the United States 2000. Washington, DC: FBI.

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reductions in motor vehicle thefts both in terms of volume and declining marginal rates. Obviously, some cars that are stolen are later recovered. The rate by which stolen vehicles are recovered in terms of days or weeks, and information pertaining to the frequency of incidents based on the day of the week, the month of the year, and the location type are vital in understanding motor vehicle theft. Such information is crucial in designing preventive measures both by the general public and law enforcement agencies. In 1982, an FBI study titled "Recovery Analysis of Stolen Vehicles Based Upon the National Crime Information Center (NCIC) Records" was conducted by Dr. Yoshio Akiyama. Using 1977 data from the National Crime Information Center (NCIC), the study pointed out that 77 percent of all stolen vehicles are recovered. This study also determined that 50 percent of the stolen vehicles are recovered within 3 days after the incident. It is clear that the more time that elapses, the smaller the probability of recovering the vehicle becomes. The whole phenomena of motor vehicle theft is influenced by a variety of factors including seasonality, geographic location, population, day of the week, unemployment, and income. It may be difficult to answer all questions related to motor vehicle theft in one or two studies, as the problem must be examined from different angles using different research methodologies and data. This study will address the issues itemized in the section titled Objectives. The methodology and the data used in this research are specified and detailed in the sections bearing the titles Methodology and Data. The results of the estimations, including related discussions and analysis, are also presented in this text. Finally, the conclusion of the study and its implications are addressed in the Summary and Conclusion. Objectives The objective of this study is to learn more about motor vehicle theft and convey the UCR Program's research findings on the topic. The specific objectives of the study are to: 1. Estimate and analyze the recovery and survival rates of stolen motor vehicles. 2. Examine the pattern of motor vehicle thefts and recoveries by day of the week and by month of the year. 3. Tabulate and analyze incidents by location of the incident. 4. Analyze clearances in comparison to recoveries. 5. Compare the results obtained using data from the UCR Program's National Incident-Based Reporting System (NIBRS) and NCIC. (Incidentally, this approach seems to indirectly validate NIBRS as a reliable source of information.)

6. Interpret the results and articulate some of the factors and attributes affecting the outcomes of the study. Methodology The continuation of the stolen (and lost) status of a motor vehicle is viewed in this study as the state of "survival" in concert with statistical methodology. A survival function will be specified, and the Kaplan-Meier estimator of the survivorship function (Kaplan and Meier, 1958) will be applied in order to estimate the survival rate of a vehicle. In this case, the status change in survival implies recovery of the vehicle based on the amount of time that elapsed since the incident date. Survival analysis is a type of statistical method for studying the change of a certain status in time as in clinical studies that measure the occurrence of death, equipment failures, job terminations, earthquakes, retirements, recidivism, automobile accidents, divorce, etc. Since the same methodology is applicable to many situations, it is customary to adopt the term "survival" in various fields of discipline. In this study we used the Kaplan-Meier estimator to estimate the rate of survival of a stolen vehicle. The specifications and description of the survival model are shown in Appendix A. Data Sources NIBRS and NCIC are the two main sources of data used in this study. NIBRS is an incident-based reporting system for which data are collected on each single episode, called an incident. NIBRS data are a product of local, state, and federal automated record systems. Data are collected on each single incident and arrests within 22 offense categories made up of 46 specific crimes called Group A offenses. In addition to the Group A offenses, there are 11 Group B offense categories for which arrests are reported (NIBRS Handbook, 1992, p. 1-2). On the other hand, NCIC is a computerized data filing system that provides documented criminal justice information "concerning crimes and criminals of nationwide interest" to all local, state, and federal law enforcement agencies (NCIC 2000 Operating Manual, 1999, p. 1). The system serves criminal justice agencies in the 50 states, the District of Columbia, U.S. Territories, and Canada. Both databases are managed by the FBI. Motor vehicle theft data for 1999, including the incident, clearance, and recovery dates, and the characteristics of the property (such as type, value, make, model, and color) are derived from the above data sources for this study. A major difference between these two databases is the extent of their representation. NIBRS data are collected from only 18 states, but NCIC contains information from every jurisdiction in the Nation. In this study, only


single-offense NIBRS incidents related to a single stolen motor vehicle are considered for the ease of analysis. Results and Analysis This section presents the analysis of motor vehicle theft. It is organized into four parts: incident, recovery, clearance, and survival analysis. In some of the sections, estimates from NCIC data are presented for comparison and confirmation purposes against the results obtained from the NIBRS data. Motor Vehicle Theft Incident

Data Systems for Policing in the 21st Century--Facilitating the Implementation of Incident-Based Data Systems

Table 5.2 Percent Distribution of Motor Vehicle Theft Incidents by Month

Month January February March April May June July August September October November December Total Percent 7.93 6.62 7.14 7.88 8.20 8.11 9.15 9.22 8.64 9.33 8.58 9.20 100.00

According to the Uniform Crime Reporting Handbook, NIBRS Edition, an incident is defined as "one or more offenses committed by the same offender, or group of offenders acting in concert, at the same time and place" (p. 25). These incidents can take place at different locations, geographic areas, days of the week, months of the year, etc., as illustrated in the following tables. Table 5.1 presents the percent of incidents as recorded by NIBRS and NCIC by the day of the week. NIBRS data are based on 70,196 incidents, and NCIC data represent the national total of 599,857 cases for the calendar year 1999. In both systems, Monday, Friday, and Saturday show higher frequencies of incidents. Higher frequency during the weekend is in concert with the general pattern of criminal activities as supported by additional NIBRS statistics from 1998.

Table 5.1 Percent Distribution of Motor Vehicle Theft Incidents by Day of the Week

Day Sunday Monday Tuesday Wednesday Thursday Friday Saturday Total NIBRS 13.55 14.14 13.43 13.40 13.66 15.69 16.13 100.00 NCIC 13.31 14.85 14.21 14.28 14.14 14.97 14.24 100.00

Table 5.3 relates to the location of motor vehicle thefts. It is seen that more than three out of four autos are stolen at residences, parking lots, or streets. These locations represent places where autos are most commonly parked. Over one half of the incidents take place where autos are parked in areas without attendants (residences and streets).

Table 5.3 Percent Distribution of Motor Vehicle Theft Incidents by Location

Location Residence/Home Parking Lot/Garage Highway/Road/Alley Unknown Location Commercial/Office Building Bar/Night Club Speciality Store Service/Gas Stations Hotel/Motel Convenience Store All Others Total Percent 35.31 22.75 17.96 6.96 4.87 2.53 1.65 1.27 1.18 0.94 4.58 100.00

Recovery of Stolen Motor Vehicles The close similarity of results drawn from both NIBRS and NCIC data has great implications in validating NIBRS as a reasonable and representative source of national crime data. This information not only confirms the quality of NIBRS data, but also assures law enforcement agencies, researchers, and other users that NIBRS data are reliable. Table 5.2 shows monthly variations (in percent) of the motor vehicle thefts based on NIBRS data where the date of the incident is known. Because the data represent only one year, no statistical seasonality pattern can be observed. In NIBRS, motor vehicle recoveries are reported. Since motor vehicles are frequently recovered without identifying or apprehending the offenders, the recovery has to be distinguished from clearance or arrest. Also, a recovery does not imply that the autos are returned to the owner in their original shape prior to the theft. Table 5.4 reflects the percent distribution of recoveries of stolen motor vehicles by the day of the week that they are recovered. The total number of recovered motor vehicles is 37,271 according to the NIBRS data, representing

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a 53.1-percent recovery. The corresponding number for NCIC, 308,535, represents a 51.4-percent recovery rate. The striking similarity between the two sources of crime data is another important and confirmatory finding, which is consistent with the earlier finding in Table 5.1 A higher percentage of autos are stolen during the weekend and recovered during the earlier part of the week (see Tables 5.1 and 5.4).

Table 5.4 Recovery of Stolen Motor Vehicles by Day of the Week

Day Sunday Monday Tuesday Wednesday Thursday Friday Saturday Total Recovered NIBRS 13.06 15.92 15.74 14.27 14.09 13.94 12.98 100.00 NCIC 11.14 16.08 16.42 15.80 15.13 14.16 11.27 100.00

Table 5.5 shows the percent of autos recovered by month. Because most stolen vehicles that are recovered are found within a few days, this table is consistent with the figures found in Table 5.2.

Table 5.5 Recovery of Stolen Motor Vehicles by Month

Month January February March April May June July August September October November December Total Percent Recovered 9.55 7.22 8.00 7.80 7.89 7.96 8.87 9.16 8.58 8.68 8.03 8.26 100.00

be cleared by exceptional means, several criteria must be met. The agency must have 1) identified the offender; 2) enough evidence to support an arrest; 3) identified the offender's exact location; and 4) a reason outside the agency's control that does not allow the agency to arrest, charge, and prosecute an offender. Examples of exceptional clearances include the death of the offender (suicide, justifiably killed by police or private citizens, etc.); the victim's refusal to cooperate with the prosecution after the identification of the offender; or the denial of extradition because the offender committed a crime in a another jurisdiction and is being prosecuted. (Additional details regarding exceptional clearances can be found on page 42 of the UCR Handbook and page 34 of the NIBRS Handbook.) The tables below are based on all 1999 NIBRS single-offense incidents that involved the theft of one motor vehicle, so that the numbers of incidents, offenses, and autos stolen are identical. Table 5.6 reflects the relationship between the clearance and recovery rates of stolen motor vehicles. Generally, clearance and recovery rates are not directly related to each other. The table indicates that for incidents where autos are recovered, NIBRS data show that there was a 17.15 percent clearance rate, i.e., the remaining 82.85 percent of the incidents are not cleared (although the autos are recovered). For incidents with no recovery, there was a lesser rate of clearance, 7.75 percent. For motor vehicle theft, the recovery rate (53.10 percent) is much higher than the clearance rate (12.95 percent).

Table 5.6 Percent of Clearances for Motor Vehicle Thefts by Recovery Status

Cleared Recovered Not Recovered Total 17.15 7.75 12.95 Not Cleared 82.85 92.25 87.05 Total 100.00 100.00 100.00

Clearance of Motor Vehicle Thefts In UCR, a crime is cleared "either by arrest or exceptional means" (UCR Handbook, p. 41). When elements beyond a law enforcement agency's control preclude the agency from clearing an offense by arrest, the agency can clear the offense by exceptional means. For an offense to

Motor vehicle theft clearances generally result from arrests (and to a limited degree from exceptional clearances). Therefore, the following arrest statistics were compiled to examine the age, sex, and race composition of the persons arrested. According to the NIBRS data, the total number of arrestees in 1999 for motor vehicle incidents where only one vehicle was stolen was 9,291. Table 5.7 shows that the age group, "12 to 17" years old, has the largest number of arrests for both sexes and for any race. The next highest group is "18 to 24" years old.


Table 5.7 Age, Sex, and Race Composition of Motor Vehicle Theft Arrestees

Male Age 6-11 12-17 18-24 25-29 30-34 35-39 40-44 45-49 50-54 55-59 60-64 65 U Total W 13 1,853 1,434 484 349 299 189 91 34 17 6 8 36 4,813 B 18 1,016 818 197 254 195 111 36 23 4 2 4 8 2,686 I 0 32 18 6 3 2 4 0 0 0 0 0 0 65 A 0 28 9 4 1 0 1 0 1 0 0 0 0 44 U 0 31 23 10 9 8 0 1 0 0 0 0 3 85 W 2 617 217 122 105 76 34 16 4 2 2 0 7 1,204 B 0 115 79 44 51 34 18 3 2 0 0 0 1 347 Female Total I 0 13 2 2 1 2 0 0 0 0 0 0 0 20 A 0 10 4 0 0 0 0 1 0 0 0 0 0 15 U 0 5 5 1 0 0 0 0 1 0 0 0 0 12 33 3,720 2,609 870 773 616 357 148 65 23 10 12 55 9,291

Data Systems for Policing in the 21st Century--Facilitating the Implementation of Incident-Based Data Systems

W = White, B = Black, I = American Indian, A = Asian, U = Unknown

Survival Estimates Since NIBRS data allow us to express recovery time in terms of days, the lapse of time for recovery was grouped into intervals (in days) as shown in Table 5.8. As illustrated in Table 5.8, Column 1 represents the time intervals. Column 2 lists the number of recovered vehicles within the specified interval given in Column 1. Column 3 indicates the number of ultimately recovered vehicles that have not yet been recovered at the beginning of the interval. The number 37,271 on the first row is the number of autos eventually recovered out of the aforementioned 70,196 stolen vehicles. Column 4 indicates the conditional probability of recovery that a car is recovered within a given interval. It is obtained by dividing Column 2 by Column 3.

Table 5.8 Recovery Pattern of Stolen Motor Vehicles

Time Interval (in Days) (1) 0-1 2-6 7-20 21-50 51-140 141-320 321-680 over 680 Number Recovered (2) 21,274 8,329 3,896 1,766 1,250 591 164 1 To Be Recovered (3) 37,271 15,997 7,668 3,772 2,006 756 165 1 Conditional Prob. of Recovery (4) 0.5708 0.5207 0.5081 0.4682 0.6231 0.7817 0.9939 1.0000

number of days. Column 3 is the complement of Column 2, and cumulatively represents the percent of autos recovered after a specified number of days.

Table 5.9 Cumulative Recovery Pattern of Recovered Vehicles

After Specified Days (1) Percent Not Recovered (2) Percent Recovered (3)

0 1 6 20 50 140 320 680

100.00 42.92 20.57 10.12 5.38 2.03 0.44 0.00

0.00 57.08 79.43 89.88 94.62 97.97 99.56 100.00

Table 5.9 describes the recovery pattern of stolen autos. Column 2 represents the percent of autos that are eventually recovered but were not recovered after a specified

From Tables 5.8 and 5.9, it must be noted that the first few days are critical in recovering stolen vehicles. The longer the vehicle is in the possession of criminals, the smaller the chance of recovery. Additionally, the recovery may be difficult depending on the nature of the criminals. The law enforcement community is aware that there are those who are engaged in this business as a way to obtain expensive automobile parts that may be sold separately for lower than market prices and those who steal autos to take them abroad for their own use or for resale. Also, some criminals steal autos for use in committing other crimes. Figure 5.2 represents the recovery pattern of stolen vehicles based on the 37,271 autos that were eventually recovered. The vertical axis represents the percent of yetto-be-recovered autos, and the horizontal axis denotes the number of days elapsed. The behavior of the function is almost vertical in the first few days indicating a higher

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0.00 0 200 400 600 800


percentage of recovery. After a few days (e.g., a week) of the incident, the graph is flat indicating that virtually no changes in recovery are expected. Table 5.9 cumulatively depicts the recovery pattern of autos that were eventually recovered. Table 5.10 describes the recovery pattern of all stolen autos irrespective of whether they are eventually recovered. Therefore, the latter is based on the 70,196 incidents. Column 2

represents the percent of stolen autos that have been recovered after a specified number of days. Table 5.11 describes the chance in terms of percentages of a stolen motor vehicle's recovery after a prescribed number of days. For example, if a stolen vehicle has not been recovered after six days, then there is only an 18.89 percent chance that it will every be recovered. From the table, it is clear that the chance of future recovery drastically decreases as the number of days increases.

Table 5.11 The Percent Chance of Future Recovery Aft er a Specified Number of Days

Table 5.10 The Recovery Pattern of Stolen Vehicles, Out of 70,196 Stolen Vehicles

After Specified Days (1) 0 1 6 20 50 140 320 680 Percent Not Recovered (2) 100.00 69.70 57.82 52.27 49.76 47.98 47.11 46.90 Percent Recovered (3) 0.00 30.31 42.18 47.73 50.24 52.02 52.89 53.10

Time Lapse (in Days) (1) 1 6 20 50 140 320 680

Commutative Number Recovered (2) 21,274 29,603 33,499 35,265 36,515 37,106 37,270

Yet To Be Recovered (3) 15,997 7,668 3,772 2,006 756 165 1

Not Expected to be Recovered (4) 32,925 32,925 32,925 32,925 32,925 32,925 32,925

Percent Chance of Future Recovery (5) 32.70 18.89 10.28 05.74 02.24 0.50 0.0


Summary and Conclusion This study has made several important findings related to the patterns of motor vehicle theft, clearance, recovery, and the similarities between NIBRS and NCIC data. The tabulation of incidents by days and months could provide important information both to the law enforcement community and the general public in understanding motor vehicle theft. Both NIBRS and NCIC data indicate that the percentage of motor vehicle theft incidents are higher on weekends than weekdays. Another important finding of the study is that the recovery rates of stolen motor vehicles for both NIBRS and NCIC are strikingly similar. Also, both sets of data indicate that a higher percentage of the recovery of motor vehicles takes place on the first 3 days of the week. This finding implies that if a stolen car is recovered, it will most likely be recovered within the first 3 or 4 days of the incident. The longer it takes to recover, the less chance there is of recovery. This fact is substantiated by the results obtained from the survival analysis model which is discussed in the section titled Survival Estimates. The rate of recovery, the probability of recovery within a certain number of days, and the chance of future recovery are discussed and illustrated in this section. This study also analyzes the rate of clearances including arrests by age, gender, and race. The clearance rate appears to be much lower than the incident and recovery rates. Due to the nature of motor vehicle theft, the proportion of clearances to the number of offenses or recoveries is usually low. However, this study and further analysis based on age, sex, and race may help policy makers, law enforcement agencies, and the general community to design and implement effective measures to preempt further increases in this type of crime. The above findings have very significant implications beyond simple similarities. Even though the operation of NIBRS is limited to few states, NIBRS is validated by NCIC as a viable and nationally representative crime data reporting system. This result may generate a sense of encouragement to expand NIBRS beyond the current 22 states that are certified and contribute incident-based data. Based on these findings, it is safe to say that the Program is heading in the right direction. Since the findings are based on only 1999 data, the interpretation must be limited to this year. Further study based on time-series data for a variety of crime categories may be needed for further comparisons and confirmations.

as t, is obtained from the equation which is generally specified as:

Data Systems for Policing in the 21st Century--Facilitating the Implementation of Incident-Based Data Systems

Therefore, for each time i, there are ni stolen vehicles at risk of not being recovered. The symbol di represents the number of cars recovered at time ti, and S(t) stands for survival function. The equation shown above states that for a specified time t, one must take all the event times that are less than or equal to t. The term in the bracket is interpreted as the conditional probability of surviving time, given that one has survived at time ti. For t less than t1 (the smallest event time), the survival rate is defined to be 1. The above equation uses only the points at which the value of the estimator changes and it becomes very cumbersome to tabulate or graph the Kaplan-Meier estimator of the survivorship function when extensive data like NIBRS and NCIC are used. We solve the problem by grouping the data into intervals. The only downside to this approach is that the choice of intervals is often arbitrary, which may lead to some loss of information. Since the intervals in this study are not wide apart, however, it does not appear that there is any loss of information. Once a set of intervals has been defined, the construction of the estimator follows the same procedure as specified in the above equation. Bibliography Akiyama, Yoshio. "Recovery Analysis of Stolen Vehicles Based Upon the National Crime Information Center Records." Prepared for the Director of the Federal Bureau of Investigation, Washington, D.C., 1982. Kaplan, E.L. and Meier, P. "Nonparametric Estimation from Incomplete Observations." Journal of American Statistical Association, 53 (1958), 457-481. U.S. Department of Justice. Federal Bureau of Investigation. National Crime Information Center 2000 Operating Manual, December 1999. Washington, D.C. U.S. Department of Justice. Federal Bureau of Investigation. Uniform Crime Reporting Handbook, 1984 edition. Washington, D.C. U.S. Department of Justice. Federal Bureau of Investigation. Uniform Crime Reporting Handbook, NIBRS Edition, 1992. Washington, D.C.

Appendix A The Kaplan-Meier estimator of the survival function was used in this study. This estimator, representing time

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CHAPTER III Mapping NIBRS Data: Using Massachusetts' Enhanced NIBRS for Examining Heroin Use, Sales, and Distribution across Multiple Jurisdictions1

Dan Bibel, Massachusetts State Police Don Faggiani, PERF Lindsay Robertson, Wyoming Statistical Analysis Center

Data Systems for Policing in the 21st Century--Facilitating the Implementation of Incident-Based Data Systems

Law enforcement's ability to monitor "hot spots" of crime and to anticipate changes in patterns of offending offers an important opportunity to engage in proactive, prevention strategies that target scarce resources where they may be needed the most. Crime mapping and other analysis techniques that help identify such crime patterns over time and location also support problem-oriented policing efforts (LaVigne and Wartell 1999). At the local agency level, these tactical crime-mapping efforts are enhanced significantly through effective utilization of a well-designed incidentbased data system. An incident-based data system permits monitoring of incident location and time, weapon use, types of structures, and other characteristics that can identify shifts in offending and reveal emerging patterns or trends within the locality. The same advantages that come from mapping crime within one jurisdiction also apply to mapping across multiple jurisdictions. Over the past decade, research has shown that offenders have become more mobile, making identification and arrest more difficult. As offending patterns have changed, it has become increasingly important for law enforcement to step beyond their boundaries and work in collaboration with neighboring agencies through multijurisdictional efforts. For example, multi-agency regional crime mapping can identify patterns of offending that extend beyond the borders of a single jurisdiction, such as displacement or regional crime series that would go undetected unless jurisdictions shared information. In response to changing offending patterns, many police agencies have developed effective means of responding to emerging and existing crime problems. For example, problem-oriented or community-oriented policing, directed patrols, and the like, all have been used to attack crime problems with varying degrees of success. But the overall

police response has been directed solely at problems within the agency's jurisdiction. Police power, after all, ends at the border of the political unit. Police agencies have become increasingly aware that the problem of crime and criminals is not solely a local issue. For many years, the burden of policing fell only on the local police agency--crime was a local problem, and the skills and abilities of the local police agency were the only barrier to the criminal. While individual police agencies may have good programs in place to respond to criminal events occurring within their boundaries, they typically have little knowledge and less control over events that occur in surrounding areas. In light of this, an individual police department will have little knowledge of displacement activities or regional crime series. However, crime and criminals easily cross political boundaries, resulting in a strong desire to develop effective regional crime-fighting tools and techniques. A number of factors have encouraged this effort. Many police departments are now computerized, since powerful hardware and software applications can provide even the smallest agencies with a sophisticated record management system. More police executives are now willing to discuss regionalization, and more line officers are knowledgeable in both computers and crime analysis. And fiscal pressures at the national, state, and local levels are squeezing resources, making the search for new and innovative crime-fighting tools more important. The multi-jurisdictional task force concept used extensively throughout the 1980s and 1990s to combat the rapid expansion of the crack-cocaine epidemic demonstrated how inter-agency tactical planning can be used to address emerging crime problems. While a locality may monitor the growth within its own boundaries, understanding the regional implications can help thwart the rapid expansion across jurisdictions. Thus, routine monitoring of local and

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regional trends can help identify changes in offending patterns and serve as a multi-jurisdictional early warning system. While many local agencies pursue regionalization, many problems remain. Wide-area crime analysis is a relatively new technique, with issues and concerns that do not arise in single-agency efforts. As Eck (2000) points out, a number of problems can occur when developing this capability--political, technological, organizational, and informational. Until the agencies in question address these issues, any potential positive effect of cross-border mapping and analysis may be limited. The intent of this chapter is threefold: · To discuss how the FBI's standardized Incident-Based Reporting Systems can help surmount several multijurisdictional data sharing obstacles, · To demonstrate how the Commonwealth of Massachusetts, through an enhancement of its statewide incident-based reporting system, overcame many of the barriers to regional crime analysis and mapping, and · To discuss several data quality issues critical to obtaining reliable results when sharing data between jurisdictions.

System (NIBRS) to replace the current Uniform Crime Report (UCR) summary crime reporting system, which primarily collects only a "snapshot" of information on the overall "serious" crime situation within local police agencies. Data collectors (police) and data users (everyone else) have long lamented the difficulty of collecting this data and its limited usefulness for crime solving and informing public policy. For example, except for homicide, no information is collected on victims of crimes--making it impossible to identify the characteristics of such high-profile issues as juvenile or elderly victimization, domestic violence, or the influence of drug or alcohol involvement in offending. NIBRS removes many of the limitations of the older UCR system by collecting data in which the criminal incident, rather than a summary of a group of incidents, is the basic data source. As such, a wide variety of information is made available on victims, offenders and arrestees, offenses, and property, allowing for the possibility of true policy-relevant analysis. While NIBRS is designed as a national crime statistics database it can also serve as the basic foundation for a local law enforcement RMS. The intent is to provide a crime information tool with standardized data elements useful at the local agency level and also to provide basic, standardized incident-level information consistent across all law enforcement jurisdictions. The resulting data set represents an invaluable asset to local law enforcement, as well as other governmental organizations and criminology researchers. From a problem-solving perspective, NIBRS has several investigative uses, including tactical and strategic crime analysis as well as rudimentary criminal investigative analysis. One of the most interesting strengths of address-specific crime data lies in its potential to allow police and policy makers to examine the distribution and possible crime patterns across political boundaries. A study by Faggiani and McLaughlin (1999) demonstrates the utility of NIBRS for tactical and strategic crime analysis across jurisdictions. Using NIBRS data from Virginia for 1997, they examined trends in the sale, distribution, and possession of narcotics. They found that NIBRS provides "significantly more incident-related detail than has heretofore been available for strategic crime analysis at the regional or state level. Moreover, NIBRS provides neighboring communities the opportunity to compare information on crime patterns that may extend beyond local boundaries." While their study used data from four non-contiguous jurisdictions and serves only as a conceptual example, it is significant in that it lays the groundwork for further research in this area. The NIBRS data contain a variety of data elements that have the potential to answer a wide range of questions previ-

Wide-Area Crime Analysis

Effective regional crime analysis efforts should optimally build on the incident-based records management systems (RMS) present in partnering agencies. One might think that with the advancements in technology the answer is simply to merge data systems for all agencies within a region to create a centralized data set that would be used to map crossjurisdictional incident-based data. As Eck (2000) notes, however, the reality of data sharing between jurisdictions is not always simple because differences in technology and data compatibility limit development of regional crime-mapping and analysis systems. In general, a local law enforcement agency's RMS is designed to serve the needs of the locality, not to support regional law enforcement efforts. As a result, the technical design of an agency's RMS may be incompatible with the information systems used by neighboring jurisdictions. The FBI's National Incident-Based Reporting System (NIBRS) is being tested as a viable solution to the data sharing problems historically encountered with local attempts at regional crime mapping and analysis.

The FBI's National Incident-Based Reporting System

The FBI developed the National Incident-Based Reporting


ously unanswerable with the summary-based UCR. Along with demographic information about victims and offenders, it also has data elements that can be used to pinpoint the date, time, and general location of offenses. With these data elements, useful temporal analyses can be performed. Most significantly, the NIBRS data set is case based. Each crime incident forms one record in the NIBRS system, and this incident is uniquely identified by its case number. With this data point alone, a single case (including information on victim, offender, arrestee, and property) can potentially be tracked. However, the smallest geographic unit of analysis in NIBRS is the reporting agency.

Data Systems for Policing in the 21st Century--Facilitating the Implementation of Incident-Based Data Systems

The federal implementation of NIBRS will allow for a variety of topical analyses, far beyond what is possible with the historic UCR crime data. However, the addition of a small number of data elements at the local level enables a richer analytical system--one that is more in tune with local needs and mandates, while also expanding our understanding of the dynamics of crime and offending.

value as an operational or tactical tool for large agencies, it may be helpful for the majority of agencies currently submitting NIBRS data, which are small- to medium-sized. These communities may not need to use crime maps to pinpoint "hotspots" of crime because "everyone 'knows" where these crimes are occurring. While the simple geographic location of criminal events may not be of great value to these departments, all police agencies can benefit from examining a wide range of crime area characteristics. By specifically locating the occurrence of crime, it is possible to merge crime data with other data sources: census information and public works information (location of street lights, bus stops, etc.), for example. Research has shown that changes made to the physical environment can result in crime reduction. Identifying and addressing negative physical patterns in high crime areas can eradicate crime and disorder. One of the initial decisions made when Massachusetts began the process of implementing the federal NIBRS data set was to work closely and cooperatively with the Massachusetts Chiefs of Police Association. This was done to gain their input and support for this major revision in crime reporting. Full information about the NIBRS data set was provided to the association, along with the rationale for moving away from the old summary crime reporting system. The members of the association's Executive Board were assured that the state would continue to operate a "voluntary submissions" system. They were also informed that it would continue to accept summary data provided that was the only way a department could submit it. As a result of this informative process, the Executive Board of the Chiefs of Police Association voted to accept NIBRS as the new standard for crime reporting in Massachusetts. The NIBRS structure presented to the chiefs in Massachusetts generally follows the federal standards. However, after the FBI came out with the final data structure and design, the Massachusetts program explored the possibility of incorporating several modifications. These modifications responded to both state statute (concerning the scope and detail of bias crime motivations) and to the feedback received from meetings of police officials and other concerned parties. The state Crime Reporting Unit (CRU) examined ways of encouraging the transition to and submission of NIBRS data. It was clear that many of the smaller police agencies did not have the ability to analyze or do even the most basic reporting on their own data. At least when reporting summary UCR data, the agency had a printed document that listed their count of murders, rapes, robberies, and the other

Development of the Massachusetts IBR System

The Massachusetts State Police Crime Reporting Unit developed the foundation for statewide and multi-jurisdictional crime mapping and analysis by using NIBRS data submitted by local police agencies. While the Federal Bureau of Investigation provides specific instructions on the structure and format of NIBRS data submitted from the various state crime-reporting programs, each state is free to add additional data values and variables to meet local needs or practices. In many cases, state programs added the ability to collect offense data using the state's own coding scheme. In others, data values were added to existing data variables to provide more specificity (adding, for example, additional values for victim-offender relationship, or additional categories of hate motivation). In many cases these modifications provide more detailed information on crimes and solvability factors. In Massachusetts, one such enhancement to NIBRS was the addition of incident address to the data set. Though NIBRS does collect information on "location type," this field only describes the type of location (e.g., residence, street, convenience store). Without a specific street address, the lowest level of geographic disaggregation possible is the agency jurisdiction. The collection of incident address allows for the identification of crime as a point on a map. While this has some

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index offenses. Reporting computerized NIBRS data would be an additional challenge to these agencies since they would have no easy way to know what crime data their computer system was submitting to the state. Through the 1990s, concern had been raised about the apparent slow pace of NIBRS implementation (though it took the summary UCR program nearly 40 years to achieve national coverage). There had been some thought at the national level of simplifying the NIBRS data structure (FBI 2002) as a method of encouraging hesitant departments to embrace the new system. The Massachusetts program took the opposite position. Rather than collect fewer data, the CRU proposed that local police agencies submit incident address information as a part of the routine data submission process. The rationale for this enhancement of the FBI data standard was simple. By collecting incident-specific address data, the CRU proposed to develop a centralized crime mapping and analysis application that would be freely available to contributing police agencies. The implementation of such a program would empower local police departments that did not have the technical skills or resources to develop such a program in-house. Moreover, by having a statewide database of crime data, each department would have the ability to examine the distribution of crime across political boundaries.

data and geocoded for mapping. Worcester was chosen for this 'proof-of-concept software for a number of reasons. As the second largest city in Massachusetts, a reasonably large number of NIBRS incidents were being reported to the state program--typically about 2,000 each month. In addition, their data quality was consistently high, in terms of the errors the state's NIBRS repository uncovers.2 The department also had some internal capacity for crime analysis; however, they did not at that time have any internal mapping capabilities. The success achieved with this test process (gathering address data from the Worcester Police Department, merging it with their incident data and geocoding it) indicated that mapping NIBRS data, was possible. What remained to be seen was how many departments had the capability to analyze the data. In the late 1990s, the Massachusetts Statistical Analysis Center began measuring through surveys the status of police technology in their state. Along with a series of questions concerning the types of hardware and software local police departments used, the survey also inquired into the capacity of departments to perform crime analysis and crime mapping. The results of these annual surveys were roughly comparable to the national survey conducted by the Crime Mapping Research Center in 1997­1998 (Mamalian and LaVigne 1999). The majority of large departments had both crime analysis and mapping programs. However, as the department size decreased, so too did the number of agencies with either program. The majority of police departments that supply NIBRS data to the state are these smaller agencies that have neither crime analysis nor mapping capacity. This reinforced the Crime Reporting Unit's interest in using NIBRS as the basis for an enhanced system of crime analysis and mapping. If address data could be incorporated into the data set, the state would have the potential of using it as a basis for a comprehensive analytical tool for police agencies. When it was presented to the chiefs that the collection of address information would facilitate regional crime analysis, the chiefs voted to support the modifications. Police software vendors were informed of the change, and the modifications were implemented by March 1999.

Exploring the Uses of Massachusetts NIBRS Data

The NIBRS data set as specified by the FBI contains a rich variety of data elements, and clearly that data could be useful at the state level for a number of policy-relevant analyses that would have been impossible to do using summary crime data. The addition of address information could add significant value to the data if the state "geocoded" it and made it available to smaller police agencies that did not have the manpower, technical expertise, or equipment (hardware or software) to do their own mapping. In 1998, the Massachusetts State Police Crime Reporting Unit began exploring the potential of incident mapping using NIBRS data. Although neither address data nor coordinate information were collected on the state level, it was clear that local data contributors had incident address data in their internal systems. As an experiment, Worcester, Massachusetts, provided a file to the State Police Crime Reporting Unit that consisted of their NIBRS-submitted incident case numbers and corresponding addresses for 1995. This data file was then merged with their incident

Using NIBRS to Identify Local Crime Problems

We began with an exploratory research question: Could the FBI's NIBRS data, with the enhancements provided by the


Massachusetts State Police, be used to overcome the issues restricting data sharing for regional crime mapping and analysis to effectively identify a crime problem within a specific area of the state? To address our research question we selected a target area comprised of Worcester, Massachusetts, and eight independent jurisdictions immediately adjacent to Worcester. This area was selected for two reasons. First, Worcester and the eight adjacent communities had reported IBR data to the Massachusetts State Police for the entire time period of the study (July 1, 1999 through June 30, 2000). Second, while Worcester is the second largest city in Massachusetts, all of the jurisdictions immediately adjacent to Worcester are relatively small and unlikely to have the resources to maintain separate crime mapping and analysis units within their departments. The analysis described below is similar to the early stages of the SARA model of problem solving (Eck and Spelman 1987). The SARA model is a four-step process used by many law enforcement agencies for local problem solving. Step 1 of the model is to scan and identify the problem. Step 2 involves an in-depth analysis that can provide details on the scope, causes, and effects of the problem. Step 3 is to define an appropriate response to the problem, and the final step is to assess the effectiveness of the response. Because our analysis is exploratory we focused on the scanning steps of the model.

populations exceeding 100,000 that reported NIBRS data in 1999, Worcester had the second highest incident rate for heroin. The only agency with a higher rate was Springfield, Massachusetts. The next highest city has a heroin incident rate of only 31.6 per 100,000 population. For those agencies immediately adjacent to Worcester the rate of heroinrelated incidents is also disproportionately higher than for all other agencies reporting through NIBRS in 1999 for a population of less than 50,000. Based upon the findings from Table 2 the remainder of our analysis focuses on heroinrelated incidents and arrests in our target area. LaVigne and Wartell (1999) note that a geographic information system (GIS) that combines police data with location information, visualized through a digital map can be a useful problem-solving tool because it helps to identify specific types of crimes and distinctive elements present in multiple incidents. In addition, they note that a GIS can assist in "breaking incidents down to identify a specific problem, trend, or pattern" (p. 312). Figure 1 maps heroin-related incidents for the period July 1999 through June 2000 for Worcester and the eight adjacent jurisdictions. The map shows a heavy concentration of heroin-related incidents in Worcester. The map also shows that two adjacent jurisdictions, Auburn, southwest of Worcester, and Shrewsbury, directly east of Worcester, also have several heroin-related incidents. Several of the adjacent towns also have single incidents during this time frame.

Data Systems for Policing in the 21st Century--Facilitating the Implementation of Incident-Based Data Systems

Scanning for the Problem

The Criminal Information Section of the Massachusetts State Police provided the starting point for our scanning. Through their investigations, they identified a drug trafficking route between Woonsocket, Rhode Island, and Worcester, Massachusetts, that was of concern. In addition, anecdotal information indicates that the city of Worcester may serve as a nexus for drug sales, specifically heroin, in the region. Using this information, we began our analysis by examining all drug-related incidents in our target area. Table 1 shows that, in Worcester, heroin-related incidents3 are more prevalent then even marijuana incidents (36 percent of drug-related incidents in Worcester involved heroin, whereas 28 percent involved marijuana). In 1999 there were 38 law enforcement agencies in the United States with populations larger than 100,000 reporting data through the FBI's NIBRS. Table 2 shows that the rate for heroin-related incidents in our target area is disproportionately higher than for all other agencies reporting through NIBRS in 1999. In fact, of the 38 agencies with

Heroin-Related Incidents in Worcester and Shrewsbury

Figure 2 demonstrates that the heaviest concentration of incidents involving both the sale and possession of heroin appears to be near the center of the city. The area encompasses five of the city's 41 census tracts. These five tracts account for 57 percent of the heroin-related incidents in the city. There is also a heavy concentration of heroin-related incidents on the northeast side of the city with one census tract accounting for 15 percent of the incidents. In Worcester, 45 percent of the heroin-related incidents are for the sale and distribution of the drug. The six census tracts with the heaviest concentration of incidents also account for 70 percent of the sale or distribution incidents in the city. The six census tracts with the highest concentration of heroin-related incidents account for 13.6 percent of the city's population (Table 3). Relative to the rest of the city these six tracts are characterized by a higher population density, a lower percentage of owner-occupied housing units, and a higher percentage of vacant housing units. The averChapter III

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Data Systems for Policing in the 21st Century--Facilitating the Implementation of Incident-Based Data Systems

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Data Systems for Policing in the 21st Century--Facilitating the Implementation of Incident-Based Data Systems

60 Figure 1

Figure 2

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age median housing values are also lower than for the rest of the city. These same areas account for 30 percent of all the property crime and 36 percent of all the violent crime in the city. A higher minority population, including a higher percentage of Hispanics, also characterizes these six census tracts. In their analysis of street-level drug markets Weisburd and Green (1995) found that the sale and distribution of heroin was more likely to occur along major thoroughfares and intersections. According to the information provided by the NIBRS data, 61 percent of all heroin-related incidents occurred on highways, roadways, or alleyways. Figure 3 provides an exploded view of the central area of Worcester showing the sales and possession of heroin. As Weisburd and Green found, the majority of these incidents occurred along a major thoroughfare in Worcester; in fact these incidents appear to be focused on a 15-block stretch of Main Street in the center of Worcester. This type of information can be important for problem-solving efforts. While Shrewsbury (population 27,000) does not have many heroin-related incidents, Figure 2 (p. 61) shows that its rate is relatively high. Two patterns in Shrewsbury become apparent from Figure 2. First, although all of the heroin incidents in Shrewsbury are related to possession, there appear to be no heroin-related sale or distribution incidents there. Second, similar to the findings in Worcester, the majority of the heroin incidents in Shrewsbury occur along major roadways. Table 4 (page 59) shows that all of the persons arrested in Shrewsbury were non-residents of the town, while in Worcester 87 percent of those arrested reside in Worcester.

the ability of these data to be used comparatively and about the accuracy and validity of the data. The FBI itself states in each annual edition of Crime in the United States that the data presented therein should not be used for comparative purposes (FBI 2001, p. 15). The reader is, therefore, cautioned against comparing statistical data of individual reporting units from cities, counties, metropolitan areas, state, or college and universities solely on the basis of their population coverage or student enrollment. Since data are supplied by thousands of police agencies, the accuracy of the data is open to question. The 1975 edition of Crime in the United States addresses this issue: "...the accuracy of the data assembled under this program depends upon the sincere effort exerted by each contributor to meet the necessary standards of reporting. For this reason the FBI is not in a position to vouch for the validity of individual agency reports" (FBI 1976). Chief Joseph McNamara (1984, p. 84) stated: "I do not know how a city that I am being compared with captures its data; I do not know what kind of quality control they have. It is an honor system, and we have periodically seen some questionable results of that system." His reference was to the then-current summary UCR data system, but the issue becomes much more significant if crime data are to be used for operational or tactical purposes.

Intra-Agency Data Quality Issues

NIBRS data are managed on local, state, and federal levels using software which have internal data quality controls. Data items that do not conform to specific standards are either not entered (on the local level) or exported to other agencies or to higher levels of aggregation. Even with edits such as this built in, however, the problems of data accuracy, validity, and completeness must be examined carefully. Although NIBRS provides the end user with a wide variety of potentially useful data, utilization will be problematic without a clear understanding of potential errors, omissions, and ambiguities. Intra- and inter-agency data quality issues must be examined before the development and implementation of any wide-area mapping and analysis program As with any system in which humans collect and enter data into a records management system (RMS), data entry errors are a basic problem. Police work is no different, and the potential for deliberate or inadvertent mistakes in typing data is ever present. However, the nature of police work also has some issues that may be somewhat unique. Data entry on one incident may have to be deferred because of the need to handle another more pressing incident. Some data may not be available at the time of initial data gathering--a

Critical Data Quality Issues

One of the key features of a wide-area crime mapping and analysis project is the need to use data collected by different agencies collaboratively. An underlying assumption of such a system of data sharing is that the data are measuring the same type of phenomena with the same data quality and with the same accuracy. In fact, accuracy and uniformity are key features underlying the entire Uniform Crime Reporting system. This has allowed the FBI and anyone else who is concerned about national, regional and local crime to have some degree of confidence that the data are in fact uniform across jurisdictions. However, for many years questions have been raised about


Data Systems for Policing in the 21st Century--Facilitating the Implementation of Incident-Based Data Systems

Figure 3

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victim may be unable to supply it. In other instances a victim may deliberately withhold or lie about certain details. As a result, software must be designed to allow incomplete data entry or "missing" information pending final approval of the data. Depending on the data element in question, and the problematic data entered into it, it may be possible to program in certain edits or checks on the data. For example, in a crime of violence like an assault, the incident will have at least one person who is a victim and at least one who is an offender. A victim should have an age, and the NIBRS specifications require a code specifying the relationship between the victim and offender. Since some relationships imply a relative age difference between victim and offender (a relationship of parent implies that the victim be older than the offender; a relationship of child that the victim be younger, etc.), edits can be set up to examine the mutual inter-related nature of victim's age, offender's age, and relationship. What many of the edits cannot do, however, is determine which of the variables in the edit statement is wrong. If the offense code indicates the crime is motor vehicle theft, but the property description states the property stolen was an aircraft, we have no way of determining which data element is coded improperly. In other cases, there can be no edit that can be used to pick out questionable data. If the data entry person mistakenly types in the code for white as the victim's race, rather than black, there is no implicit or explicit reason to question the validity of that one data point. This discussion has focused on incident-level errors and edits. These are instances that look only at the internal consistency and appropriateness of data elements within a single incident. A second level of data quality review examines aggregate data--looking at frequency counts of a variable collected from a number of incidents. In this type of examination, it may not be possible to determine whether the data from one single incident are correct. By looking at the distribution of the data, it may be possible to determine whether the overall collection of data is questionable. For example, a single incident of aggravated assault may code the victim-offender relationship as stranger. This is a potentially acceptable value. However, if we examine 100 incidents of assault from one agency and find that all of them are given a victim-offender relationship code of stranger, we can reasonably conclude that there is a coding problem in this agency. The same type of aggregate data quality analysis can be employed for a wide variety of data values in NIBRS. Crime data may not have a normal distribution in the sense of a statistical distribution, but common

sense and prior experience give us tools to use in order to evaluate the data. When an aggregate data set is composed of submissions from individual agencies, the problem of data quality is magnified. It should be obvious that the ideal situation would be for all agencies to have and use the same software, to collect data in a uniform fashion, and to share it in a common format. The reality of our fragmented criminal justice system is that this ideal situation occurs only rarely. The NIBRS data set does provide at least a common format for the sharing of crime incident data that can provide a significant advantage over other existing regional data sharing projects in which the conversion of data in disparate format can be an onerous job.

Uniform Quality

Although all agencies collect incident data with some level of detail, the quality of the data collected can vary widely, depending on the use that the data are put within the department. Quality in this context refers to both the error rate of each data element (what percentage of data are coded improperly) and the percentage of data for which data are coded as missing when an appropriate code could have been entered). An agency that has an active crime analysis and mapping unit, or that practices proactive policing will have a greater need for quality data and will most likely have quality data. Agencies that are more reactive to criminal events, or that have limited research and analysis functions will probably put their incident data to less use; consequently their data quality may be poorer. The issue of intra-agency data quality becomes a more important issue when data from different agencies are merged together. There may be a tendency to assume equivalent levels of data quality among the agencies involved in a wide-area crime analysis consortium. Auditing of incident data is rarely done on an agency, state, or federal level (although the FBI has announced that triennial audits of selected NIBRS agencies will be conducted in the near future), and therefore it is important that this issue be considered when comparing data across agencies.

Uniform Coverage

The issue of the "dark figure" of crime has been a topic of discussion among academics for some time--the fact that not all crimes are reported to or known by police. Any data system based on officially reported and recorded data is


effected by the fact that different police departments may be collecting data on varying levels of offending. Comparing or combining data from different agencies may give misleading results. Police-community relations may play a role in this. An agency that has worked on improving police-community relationships may expect a greater proportion of offenses to be reported; another agency that has an adversarial relationship with its citizens may find that many incidents do not come to their attention. Police-community relations are only one part of the problem. Jurisdictions with a large number of non-Englishspeaking populations may have less crime reported because of a language barrier. Some recent immigrants come from areas of the world in which the police were seen as agents of repression, and they would be less likely to approach the police for anything.

that quality data on past cases informs and protects them from future incidents. Case review must be an integral part of the process. At all levels of the organization, there must be an appreciation for the utility of quality data. In many departments, this is an inherent part of daily operations. From the chief on down, and from the line officers on up, each member depends on and values data. In some number of agencies, however, it is not clear that this appreciation has taken hold. Whether due to lack of training or resources, or a hostile working environment between management and labor, this quality is lacking.

Data Systems for Policing in the 21st Century--Facilitating the Implementation of Incident-Based Data Systems

Summary and Conclusions

As this paper demonstrates, the standardized structure of the NIBRS data can easily transcend the needs of a single law enforcement agency. The addition of address details to the standard NIBRS structure, such as that implemented in Massachusetts, provides the added detail necessary to permit neighboring agencies the opportunity to conduct interagency, tactical crime analysis. The ability to compare like information on emerging crime patterns and problems that extend beyond local law enforcement agencies' boundaries is a necessary tool in an environment where offenders see no boundaries. Easy access to data from neighboring agencies without complicated inter-agency agreements or specialized inter-agency committees would significantly improve the ability of local agencies to conduct cross-jurisdictional problem solving and crime analysis. Data from neighboring communities could then be used to follow, as well as, anticipate trends.

Jurisdictional Tolerance for Problems

Communities with high crime rates may require written reports only on the most serious incidents. Resource shortages may necessitate a triage of efforts. In communities with lower rates of offending, the standard operating procedure may be for officers to respond to and officially report all complaints from citizens. Both types of agencies may be responding appropriately to the needs and expectations of their citizens. For example, a city like Worcester with a high level of heroin use may have a more lenient approach to marijuana users. Shrewsbury or any of the other communities surrounding Worcester may deal with minor drug use with stricter standards simply because the number of cases they deal with on a daily basis is far less than that in Worcester. From an inter-agency problem-solving perspective an understanding of the different tolerance levels of all agencies is critical to truly define emerging regional problems.


Eck, J.E. (2000). Crossing the Borders of Crime: Factors Influencing the Utility and Practicality of Inter-jurisdictional Crime Mapping. Presentation at the Crime Mapping Research Center Conference Series, Washington, DC. Eck, J.E., & Spelman, W. (1987). Problem Solving: Problem-Oriented Policing in Newport News. Washington, DC: Police Executive Research Forum. Faggiani, D., & McLaughlin, C.L. (1999). "Using the National Incident-Based Reporting System for strategic crime analysis." Journal of Quantitative Criminology, 15(2): 181-191.

Appreciation for Data

It is axiomatic that in any data system, "garbage in-garbage out." The success of any data system relies on the quality of the data entered into it, but this data entry is a human process that depends on constant effort from all levels of the organization. The command staff of a police agency must insist on quality data, which they will use for making tactical, operations, and administrative decisions. The line officers must be trained to collect all appropriate data so that their incidents are fully documented, and must understand

Chapter III

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FBI (2002). State Program Bulletin 99-2. Washington, DC: Government Printing Office. FBI (2001). Crime in the United States. Washington, DC: Government Printing Office. p. 15 FBI (1976). Crime in the United States. Washington, DC: Government Printing Office. p. 16 LaVigne, N., and Wartell, J. (1999). "Crime Mapping for Problem Solving." In Solé Brito, C. and Allan, T. (eds.), Problem Oriented Policing: Crime-specific Problems, Critical Issues and Making POP Work (pp. 297-322). Washington, DC: Police Executive Research Forum. Mamalian, C.A., and LaVigne N. (1999). The Use of Computerized Crime Mapping by Law Enforcement: Survey Results. Washington, DC: National Institute of Justice. Weisburd, D., and Green, L. (1995). "Measuring immediate spatial displacement: Methodological issues and problems." In J.E. Eck and D. Weisburd, eds., Crime and Place. Monsey, NY: Criminal Justice Press; and Washington, DC: Police Executive Research Forum, pp. 349-361.

1 An earlier version of this paper appeared in Faggiuni, D.,D. Bibel and D. Brensilber. (2001) Regional Problem Solving Using the national Incident Besed Reporting System. In M. Rcuand, C.Solé Brito and C. Carrull (eds.), Solving Crime and Disorder Problems: Carrent Issues, Police Strategies and Organ tional latices. Washington, DC: PERF. 2 The FBI also certified that their data were of high quality as a result of a quality assurance review (QAR) conducted in the department in 1998. This QAR process indicated that the sample of cases reviewed had an error rate of less than 2 percent. 3 Our initial analysis is at an incident unit of count. That is, all drug-related incidents reported to the police even if an arrest was not made.



Data Systems for Policing in The 21st Century -- Facilitating the Implementation of Incident-Based Data Systems

Three issues should be clear from the materials in this NIBRS Resource Manual. First, as the paper by Craig Fraser discusses, law enforcement chief executives must view their data systems from a proactive perspective, designing a system that goes beyond merely collecting data. A well-designed RMS should serve as a strategic information system aligned with the goals of their organization. Second, the transition to a new RMS and data collection system is not an easy or short process. As we can see from the four papers in Chapter II, it takes time and a dedicated effort to achieve success. The result can be one that serves multiple organizational objectives such as problem-solving and community-based initiatives, crime investigation, case management, analysis and research, and local and state crime reporting. As Director Crews from Memphis notes there is a considerable amount of research and effort up front, well before any purchases are made. Chief Manger from Fairfax County notes the process to convert to a new RMS must be an agency-wide effort. For the transition to succeed everyone from the chief all the way to the patrol officer must be trained and on board for the new implementation to be successful. Finally, the two papers by the FBI in Chapter III demonstrate the depth of information the NIBRS data provide at a national level. The final paper in Chapter III demonstrates how adding a few extra data elements, such as address information, can turn the basic NIBRS data into a strategic and tactical resource for crime analysis and planning. As noted in the Introduction of this Resource Manual, the FBI's NIBRS was introduced as a replacement for the summary-based UCR system.

Originally designed in the late 1920s by the International Association of Chiefs of Police (IACP) and turned over to the FBI in 1930, the summary-based crime reporting system is outdated. If the summary-level UCR were an automobile it would be a classic 1930 Model A Ford in running condition. Nice to drive to a picnic or on back country roads but not very effective for keeping up with drug dealers driving custom BMWs on an interstate highway. NIBRS data, on the other hand, might be considered a new Crown Victoria with all the power and options needed to overtake the drug dealers in their custom cars. NIBRS is not a complete solution to the problem but it does provide information useful to meet many of the information challenges facing law enforcement in today's environment. Officially, data have been reported to the FBI in NIBRS format for 14 years. By September 2004 the number of states certified to submit NIBRS reports to the FBI has grown to 24. The number of reporting jurisdictions in the first 14 years has grown to 4,736. This represents approximately 20 percent of the U.S. population and around 14 percent of all reported crimes. Moreover, 13 additional states are working with the FBI testing their NIBRS systems. Another eight states are in the planning phase to develop a NIBRS system. Only five states currently have no plans to implement a NIBRS reporting system. One of the complaints people have voiced about NIBRS is that it has been slow in developing. With the numbers stated above it can be argued that NIBRS is developing quite fast, especially when compared to the development of the original summary-based UCR system. The old UCR took nearly 30 years to reach a point where it covered a large enough population to allow national crime figures to be reported. At its


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current level of implementation NIBRS is on a pace to reach a point where it is representative of the U.S. population in about half the time it took the summary UCR system. From a policy perspective NIBRS has already begun to demonstrate its utility. In a 1999 Office of Juvenile Justice Delinquency Prevention (OJJDP) report, the authors use NIBRS data to analyze the time of day for juvenile violence. They found that serious violent crime by juveniles is four times more likely to occur during the hours immediately after school than during the eight hours when juvenile curfew laws are in effect. This finding is significant because it can help to focus interventions aimed at reducing youth violence. Interventions such as juvenile curfews have good intentions but they reach a much smaller proportion of the problem. The research by Bibel, Faggiani, and Robertson, in Chapter III of this manual, demonstrates how the addition of addresses to the standard NIBRS data can provide strategic capabilities to the data. Using enhanced (addresses added) NIBRS data for the State of Massachusetts, they show that regional strategic crime analysis is possible without going through a special task force or waiting for interagency agreements to wend their way through the bureaucracy. They show that heroin sales and use in one jurisdiction can have an impact on heroin use in adjacent jurisdictions. This type of information can be useful in assisting neighboring jurisdictions to develop joint or multi-agency task force intervention strategies to reduce drug trafficking in a region.

Also in Chapter III the FBI's analysis of motor vehicle theft (MVT) provides validation for the use of NIBRS. A comparison of the motor vehicle theft findings from NIBRS and the National Crime Information Center showed that NIBRS produced very similar results. One final comment: There is a common misconception that NIBRS is a database being forced on local law enforcement. The fact is that the incidentbased information required for NIBRS already exists in most law enforcement records management systems. The structure and design of NIBRS is generally the same structure and design necessary for any incidentbased data system. The differences are that 1) the FBI performs edit checks to ensure data quality, and 2) state or local penal code definitions must be mapped to NIBRS crime definitions to allow for comparisons across states and jurisdictions. Still, almost all law enforcement agencies currently collect the same information the FBI requires for NIBRS.


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