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Data-driven policing: More than just an abstract principle

We must continue to search for ways to articulate and support policy-relevant research and build police models based on data, science, and criminology rather than the gravitational pull of habit and tradition.

At the outset, I will assert that the phrase “data-driven policing” has been overworked and its importance diminished by overuse – a sad reality. Like the conceptual frameworks of “unified command” or “procedural justice,” the tendency to reduce important principles to mere aphorisms looks more dismissive than expansive – a way to cancel thoughtful examination rather than invite inventive, broad analysis.

But truth be told, the future of public safety and its institutions depends upon the scientific use of data and evidence in 2023 and beyond. This is a defining principle at Winbourne Consulting.

Let’s start with a seminal definition: Data-Driven Policing theory posits that data and evidence matter in developing leading-edge crime control and interdiction strategies and policies.

Substitute this phrase with “evidence-based crime policy” or “data-informed decision-making,” and the gravity of using reliable data to create policy-level, strategic, and tactical systems of prevention, preparedness, response, and recovery to public safety crises comes into sharp focus.

Admittedly, there is a big difference between evidence and anecdote. But, notwithstanding that many anecdotes have a foundation in reality, evidence – data – is the path to uncovering causality, which in turn lights the way to effective and potentially life-saving public safety strategies.

In my work with Winbourne, a critical way to exploit the value of data to inform best practices is describable as an “information access audit.” For example, suppose a police department seeks to understand at an evidentiary level. In that case, the impact of the dispatch of officers to people in a behavioral health crisis, a critical public safety topic today, does the data, if even available, have to be painstakingly retrieved, researched, and created from nothing or, preferably, has the data been pre-programmed to be immediately accessible and available for study and analysis.

Lessons Learned

If I knew then what I know now, I would diligently ensure that essential categories of data – officer activity at a granular level;  suspect demographics, debriefs and subject behavioral characteristics;  suspect and officer safety risk factors;  call resolution and officer/call center critiques; officer debriefs and suggestions for improvement; arrest adjudication, including financial and imprisonment outcomes; lessons learned – are consistently recorded and available for immediate, integrated review and analysis. In addition, RFPs, CAD-RMS projects, and contractor requirements must include explicit provisions for data retrieval according to the priorities of the public safety entity rather than the vendor.

In particular, geospatial (GIS) and temporal coordinates and correlations are consistent data-based characteristics in every important human event or activity.  For police, this includes criminal acts, victimization, the trajectories which bring people into and out of incident locations, and the presence or absence of people to observe or deter a crime. Through analysis of place, we open worlds of possibility to understand methods of addressing and ameliorating human suffering.

The “policing of place” – utilizing evidence-based approaches – is as essential to the history of the policing profession as any of our precedent, pragmatic public safety “revolutions,” from the Basic Car Plan to the Professional Model to the SARA model.

We must continue to search for ways to articulate and support policy-relevant research and build police models based on data, science, and criminology rather than the gravitational pull of habit and tradition.

We must redouble our efforts to encourage and support the next generation of police professionals and academic researchers toward seeing “research practitioners” in crucial roles in all data-driven public safety institutions.Clark Kimerer is a Winbourne Consultant, researcher, and subject matter expert. He retired as 2nd-in-command of the Seattle Police Department after a career of 31 years. He was inducted into the Center for Evidence-Based Crime Policy Hall of Fame at George Mason University and teaches at the Naval Postgraduate School Center for Homeland Defense.

By Clark Kimerer

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