Tackling Leadership Dilemmas with the Simsi Suite

It would be an understatement to say the landscape of modern policing, particularly in the United States, has changed since 2020.  Policing has always been a challenging profession, but the public’s demand for police accountability and transparency has understandably intensified.  The confluence of ever-changing social and political climates, coupled with expectations for agencies to responsibly use analytics and evidence-based practices, has placed more responsibility on the shoulders of today’s law enforcement leaders.

A challenge police leaders face is to meet the full spectrum of expectations from community members, local government officials, people within the agency itself, and other external stakeholders.  Such expectations rightly include using data-driven approaches for both crime reduction and prevention.  Proactive, transparent engagement with various facets of the community that spurs ongoing dialogue and problem-solving is also a priority.

It would seem that a framework to operate in such a way does not exist for police departments.  ‘Community Policing’ in the traditional sense aims to achieve this but has struggled with concrete definitions of what, precisely, constitutes community policing-related tasks and strategies, or who should be responsible for developing and implementing them. Thankfully Risk Terrain Modeling (RTM) and its application in Risk-Based Policing (RBP) help police commanders meet these lofty goals. 

Just as expectations have progressed, so has the technology that supports policing.  Rather than waiting for crimes to occur and then reacting, police departments, other municipal departments, and community stakeholders can join forces and utilize analytics to address criminogenic contexts at vulnerable places. They can better manage places to make safer spaces that ultimately deter opportunities for crime to emerge.  Put another way, it is better to prevent opportunities for illegal behavior by focusing on the environmental conditions that enable crimes to occur or persist at particular places as opposed to trying to arrest our way out of a crime problem after it spikes or becomes a crisis.

Police need data analytics that embrace and inspire the human elements of crime analysis, problem-solving, and prevention.  One of the prevailing principles of RBP is to solicit and value input from various roles and ranks of government personnel and multiple other community stakeholders.  At its core, RBP is a data-driven approach that invites many voices to be heard as to what may be driving crime or disorder in specific areas.  Those same voices also have a stake in taking actions to address the issues and solve the problems identified by the group and validated by the RTM analyses.

Examples of RTM analysis and place-based prevention are on full display in Kansas City, Missouri.  The Kansas City, Missouri Police Department (KCPD) has implemented RBP in various iterations, scopes and scales dating back to 2010. One of the more recent initiatives, a RBP deployment from Spring of 2019 through Spring of 2020, yielded significant reductions of gun-related violent crime – well over 20%.  These reductions were also achieved with an observed decrease in officers’ proactive enforcement-related activities in the focus areas. In contrast to reactive strategies such as saturated patrol or ‘zero tolerance’, the KCPD decided to engage with numerous municipal departments, business owners, and other citizens by sharing the RTM analytic reports and discussing how it informed the collective strategy for crime prevention citywide.

Interest in RTM and RBP remained despite the tumultuous years of 2020 and beyond, to include a municipal ordinance enacted by the City Council in late summer 2023. The ordinance established a multi-disciplinary task force required to use RTM and other analytics to identify settings throughout the city worthy of multifaceted interventions by many city agencies and community partners. Whereas the RBP strategy was police-led, this shift by the City to a DICE™ model of operations reduced the burden on KCPD while providing additional resources to mitigate environmental risks and fix chronic hot spots.

The task force is relatively new, yet preliminary assessments show two out of three treatment areas to already be experiencing meaningful crime reductions. The combination of field work and multiagency meetings has resulted in improved communication between the KCPD and other municipal departments, most notably those with whom the police department may not have routinely engaged with otherwise, such as the City’s Health Department.  The task force is also harnessing its growing capacity to bring non-government organizations into its work as partners.

Time-and-again citizens thank KCPD and other task force members for their transparent approach focused on places and prevention, not just people and reactive arrests.  During a recent site visit to a high-risk area, citizens marveled at how KCPD and municipal departments stood shoulder-to-shoulder walking down the street observing environmental risks needing their specific agency’s attention, noting quality of life issues, and treating citizens as equals in their joint work to improve public safety.  To that end, both KCPD and the community came to realize another unexpected benefit of DICE™:  the capacity to forge better partnerships and stronger communities through collaboration and information-sharing.

Looking back on my time as a patrol officer which began over 20 years ago, I can only wish RBP had been available to me.  Instead of attending community meetings with stale crime statistics, I could have used RTM analytics and risk narratives for meaningful dialogue with citizens.  The KCPD has long valued strong community-police relations. RBP shines as one of the few strategies utilized throughout our history with the potential to strengthen community relationships and partnerships to provide lasting public safety in ways that meet operational needs and local expectations.