by Jeremy D. Barnum, Meagan Cahill, Dulani Woods, Kevin Lucey, Michael J. D. Vermeer, Brian A. Jackson

Despite the growth and evolution of data in policing over the past several decades, calls for better data continue to grow. In this context, better refers not only to improved validity, reliability, timeliness, and usefulness of information already collected by police agencies but also to the introduction of new metrics that can better capture key aspects of policing and public safety that matter most to members of the community. Even with recent improvements, challenges remain; extant data are often difficult to use and typically offer limited insights about the quality or outcomes of policing. Furthermore, it can be difficult to operationalize important policing activities or define community-based metrics.

RAND and the Police Executive Research Forum, on behalf of the National Institute of Justice, convened a workshop of subject-matter experts, representing police practitioners, researchers, private vendors, and community advocates to discuss current police data collection programs and identify high-priority needs to inform a research agenda for developing better metrics in policing and the criminal justice system. Through a series of interviews and group discussion sessions, the research team and participants identified and prioritized a total of 24 needs related to policing data. These highest-priority needs address problems related to creating a culture of data and measurement in policing, finding ways to standardize data collection efforts across key measures, automating data collection and analysis processes, auditing data to ensure validity and reliability, and improving data collection systems.

Key Findings

Despite various data collection initiatives, the usability of police data remains significantly limited

• The field lacks uniform rules for how calls for service are coded and processed after the initial response, which impedes meaningful insight from calls-for-service data.

• Data are often stored across multiple systems and are difficult to export or link; they also contain incomplete or inaccurate information.

• Many systems often do not support data analysis, interoperability, or even data extraction.

• Agencies face difficulties in managing and fully leveraging data platforms because their complex software usually requires someone with technical or programming experience.

• Even a perfect data platform cannot overcome fundamental issues pertaining to the validity, reliability, and completeness of the underlying data.

Instilling a culture that values data and building the infrastructure to support it are important steps toward achieving better measures of justice. Participants agreed on the importance of

• comprehensive and intentional plans for integrating data into the tasks of each person and unit throughout an organization

• meaningful career pathways, certification and accreditation programs, and a set of standards to foster the professionalization of law enforcement data roles

• mechanisms that intentionally integrate civilian data stewards into the larger sworn culture to help agencies leverage data to inform operations and advise on ways to improve data-related processes and procedures

• new metrics that capture unmeasured but important aspects of police work

• modern, efficient, and user-friendly data tools that agencies can acquire for a reasonable cost

• regular data entry checks or data auditing processes to ensure data validity and reliability.

Recommendations

• Law enforcement agencies (LEAs) should hire individuals with strong analytic skills into permanent positions, such as certified crime analysts, trained researchers, and practitioner academics (i.e., pracademics), and provide them on-the-ground training with law enforcement officers.

• LEAs should engineer data collection environments and tasks to create "intelligent workflows," which automate validation checks that identify where additional data collection would be useful, and to prevent and reduce the potential for human error.

• Data collection must be mandated. Engaging the Peace Officer's Standards and Training program or other state-level agencies, professional organizations (such as the Police Executive Research Forum), community members, and police unions will be needed to provide legitimacy "close to the ground" to determine data priorities and create communities of practice around how to use and analyze the data that are being collected.

• LEAs should work with information technology vendors to develop data collection systems with built-in functions that facilitate information linkability, sharing, and analysis (e.g., interoperability, exportability, application programming interfaces, and visualizations). States can create laws requiring data collection and minimum data system standards and provide funding to assist LEAs with implementing such systems.

• Federal guidelines should be developed on the best approaches for determining a person's race and ethnicity to ensure that LEAs collect race/ethnicity data in a manner that is comparable to sources of baseline population data. These guidelines should also include methodological guidance on how to use and compare such data and identify outliers.

Santa Monica, CA: RAND, 2024. 24p.