You can’t manage what you can’t measure: the importance of data in policing

In recent years, politicians and reporters have highlighted the lack of data on many policing outcomes, with a sharp focus on how little we know about police use of force in both the United States and internationally. Specifically, the death of Michael Brown in Ferguson (MO) in 2014 highlighted the fact that no entity within the United States tracks police use of force, even deadly force. This lack of data leadership prompted several news agencies to begin tracking civilian deaths at the hands of police, the most well-known of which is The Washington Post Fatal Force database (Nix et al., 2017; Shjarback & Nix, 2020). Yet while use of force is a crucial responsibility of police and more information is certainly needed (Bennell et al., 2022; Matusiak et al., 2022; White, 2016; Williams et al., 2019), it is not the only aspect of policing that could benefit from more and better data. Historically, police accountability has been measured by outcomes that are easily countable, such as arrest and case clearance rates, citations, traffic stops, and response times. While important, these data fall short of assessing the myriad responsibilities that police organizations are tasked with measuring, and they tell us little about the nature and extent of these community encounters. These outcomes are, however, of critical importance to community members and larger police reform efforts.

Police departments do collect a great deal of interesting and informative data that can add context to the discourse about police work at both the individual and organizational levels. Recent research has touched on the ways in which police data impacts various facets of police work and highlights the possibilities for new, innovative uses for police data. For example, Lum et al. (2021) and Ratcliffe (2021) demonstrated the difficulty inherent in reallocating police calls to other, non-police entities for many calls traditionally yielding a police response. Muller and colleagues find that scant information is known about police responses during calls involving mental health crises. Gillooly (2021) asks important questions about how dispatchers shape police responses to incidents independent of incident data. White et al. (2018) interrogate the use of body-worn camera footage to reduce the use of force in encounters with community members. Yet despite these and other studies using police data, many questions remain about the utility of administrative data in law enforcement agencies. This special issue begins by exploring data sources and asking some important questions about the nature of policing for researchers across the globe.

In this special issue, several papers include new ways to utilize incident-level data of offense-specific trends. Pearce and Simpson (2022) use Computer Aided Dispatch (CAD) data to better understand the nature and extent of welfare checks – an understudied responsibility of local police that often does not involve law enforcement. Barnett-Ryan (2022) uses calls-for-service data and incident reports from municipal and university police agencies to analyze the spatial co-location of property crime. Haberman et al. (2021) and Scott et al. (2021) both make use of the U.S. Federal Bureau of Investigation’s National Incident-Based Reporting System (NIBRS) data. Haberman et al. (2021) use these data to better understand robberies within one agency, while Scott et al. (2021) compare clearance rates for sexual assault cases across multiple agencies. Holistically, O’Connor et al. (2022) add to recommendations for agencies about the role of police analysts in a shift to evidenced-based policing in Canada.

Other studies in this special issue emphasize the benefit of merging different types of data. Kroneberg et al. (2022) combine official police crime data with survey data of students’ perceptions of crime in Germany. Specifically, they link data from a four-wave longitudinal study of more than 3800 students to spatially-aggregated data from crime statistics to examine the sensitivity of local crime data collection practices. In London, Buil-Gil et al. (2022) use violent crime data recorded by police, ambulance services, two surveys and computer simulations to determine the true incidence of crime.

While we need more accessible data and increased transparency to understand policing and its related outcomes, we should also do more to leverage existing data sources like the authors in this special issue. We strongly believe that we can’t manage what we can’t measure and so much of police work is currently hidden. Further research should address these gaps in the literature, both in terms of how police data are used and addressing deficiencies in police data sources themselves.

Additional information

Notes on contributors

Melissa Schaefer Morabito

Melissa Schaefer Morabito is an Associate Professor at University Massachusetts Lowell in the School of Criminology and Justice Studies. Her research interests include the police response to public health issues such as mental illnesses and substance use as well as sexual assault case attrition.

Janne E. Gaub

Janne E. Gaub is an Assistant Professor in the Department of Criminal Justice and Criminology at the University of North Carolina at Charlotte. Her research interests include police technology, police misconduct, specialized police units, and gender and policing.