The future of crime data in policing
January 1, 2021 marked the end of an era when the FBI officially retired the nearly 100-year old Uniform Crime Reporting (UCR) system in lieu of a more comprehensive option known as the National Incident-Based Reporting System (NIBRS). The UCR, otherwise referred to as “simple summary reporting” (SRS) was introduced in 1929, and essentially reported aggregated counts of crimes at monthly and yearly intervals for participating law enforcement agencies. NIBRS was introduced in 1982 in an attempt to modernize the UCR, emphasizing incident-level data collection rather than aggregate-level. The purpose of this was to provide more detail and context about each incident (e.g. details on victims or offenders of crime, characteristics of the incident) to improve crime data quality (and quantity). The comprehensive data collected via NIBRS would allow for more opportunities to analyze patterns of crime and apply it to the field. However, one downside of NIBRS is that data are more burdensome for law enforcement agencies to collect. Further, participation in both UCR and NIBRS is voluntary for law enforcement agencies, meaning that additional burden might affect participation rates. Not surprisingly, participation rates are typically higher for the UCR, making it the preferred official source for reported crime data up until very recently.
The phase-out of UCR and the formal transition to NIBRS has been in development since 2015, when the January 2021 deadline was officially established. The main reason for this, as stated above, was to provide more detail on crimes reported to the police to increase opportunities to analyze and assess crime patterns in the United States. For example, the UCR approach would allow an agency to report only how many robberies occurred without any context regarding location, age of the offender, or other important characteristics. In contrast, the NIBRS approach relies on data captured in specific fields for a more comprehensive analysis. In the latter, an agency or researcher could examine the location type of various robberies, weapons used, information about the offenders involved, and other characteristics. Currently, this type of data is not available at a national-level, hence the push for NIBRS. Another key difference between NIBRS and the UCR is that the UCR uses the “hierarchy rule,” meaning that only the most serious crime of a particular incident is reported. As a result, if there were a robbery and a murder occurring within the same incident, the UCR would only count the murder, whereas NIBRS would count both the murder and the robbery. Further, because NIBRS data is finer-grain than UCR, it can also be easily aggregated to the SRS format if needed.
However, many are worried that participation rates will decrease due to additional burden put on law enforcement agencies. NIBRS has strict data quality rules and requires agencies to record detailed information in structured data fields, something that might be challenging or time-consuming to do depending on the department. Police agencies typically rely on a Record Management System (RMS) to store most of their data, which in theory can make data collection easier, but the quality and usability of the RMS can vary. For example, electronic RMSs have become commonplace for many law enforcement agencies, which makes structured recording of information more feasible. However, the data is not always easily extracted and may need to be converted into a proper format before it can be used. These types of operations typically require specialized staff and technological upgrades that many agencies don’t have and may not be able to afford.
In 2012, the FBI reported that NIBRS-contributing agencies represented only 33.4% of the agencies reporting to the UCR program. Considering how low the participation rates were, this sample was limited in producing a valid national-level estimate. In response, the FBI partnered with the Bureau of Justice Statistics (BJS) to form the National Crime Statistics Exchange (NCS-X) Initiative. The goal of the initiative was to increase the number of agencies contributing to NIBRS to make these national-level crime estimates more representative. The NCS-X project was a key component of the five-year transition from 2015-2021, and provided more than $120 million in financial support to assist police departments in their transition to NIBRS. NCS-X funds were used to provide technical expertise, data integration support, and other NIBRS-related training. In 2019, the FBI reported that NIBRS-contributing agencies represented 51.3% of agencies reporting to the UCR program. While this is a noticeable increase since 2012, it is not near the level of national-level representation. BJS expects this estimate to rise to at least 75% by the end of 2021, an estimate that would be more akin to historical UCR participation rates.
The BJS convened a group of law enforcement practitioners, state UCR representatives, and members of the research/academic communities to discuss their experiences with NCS-X and NIBRS and explore possibilities for streamlining data collection while improving data quality. The key themes from the meeting are outlined in this recently released BJS-funded report co-authored by RTI International and the Police Executive Research Forum. Some of the topics reported on in detail include leveraging crime data for data-driven policing, assessing and evaluating agency strategy and policy, and improving transparency with the public through comprehensive crime data and dissemination of data.
The report concludes with five key takeaways for law enforcement agencies (p 19):
1. Emphasize the value of accurate and complete data entry and convey to staff how helpful this can be for investigations and analysis,
2. Consider developing a customized and user-friendly data dashboard to increase internal access to data without sustained reliance on a specific staff member,
3. Consider how your agency is disseminating crime data to the public; perhaps incorporate visual data displays and/or infographics to enhance meaning beyond percentages and numbers when communicating with the public,
4. Optimize the use of social media engagement by targeting different platforms that might be able to assist in your mission of disseminating crime data; perhaps consider seeking out platforms in other languages depending on the needs of the community, and
5. Be open to collaborating with policing researchers and academics who have the same goal of studying crime data, evaluating which practices are effective, and refining promising practices to bolster their effectiveness.