VOICES: Tackling crime in Dayton: The power of data-driven solutions

Dayton, Ohio, like many cities across the country, faces a persistent crime problem that requires innovative and forward-thinking solutions, including the skyrocketing juvenile crime problem. Too often, the conversation centers on law enforcement, but we need to shift our focus toward data-driven strategies that address the root causes of crime. By using data to analyze crime patterns and inform policy decisions, Dayton can reduce crime and create a safer, more vibrant community. As a Professor and Chair of the University of Dayton’s Criminal Justice and Security Studies Department, I believe that collaboration between academic institutions, agencies, and community organizations is key to solving this problem. Universities are home to cutting-edge research and data analysis tools that can significantly enhance the ability to understand and combat crime.

Crime in Dayton, as in other cities, follows distinct patterns. With proper data analysis, agency officials can pinpoint these patterns — whether related to geography, time, or socio-economic conditions — and deploy resources more effectively. Predictive analytics, for example, allows us to forecast where crime is most likely to occur, so that preventative measures can be taken before incidents happen. Using this data-driven approach, Dayton can strategically focus its efforts on high-risk areas, ensuring that community resources, such as increased neighborhood engagement or public safety improvements, are directed where they are most needed. Other cities that have adopted predictive policing and data analysis have seen positive results, and Dayton can do the same by fully embracing this approach.

One of the most significant contributors to crime in Dayton is economic inequality. Poverty, lack of employment opportunities, and limited access to education are often at the root of criminal behavior. However, with the help of data, Dayton can better understand the specific economic conditions driving crime in particular neighborhoods, allowing for more targeted solutions. For instance, if data shows that crime spikes in areas with high unemployment, job training and workforce development programs should be prioritized in those neighborhoods. Similarly, data linking low educational attainment to increased criminal activity can guide funding for after-school programs, tutoring, and mentorship initiatives. Universities like the University of Dayton can play a key role by partnering with agencies to conduct research, analyze trends, and design interventions that address these underlying economic factors.

Dayton has been severely impacted by the opioid epidemic, and drug addiction is a major driver of crime in the region. Rather than relying solely on traditional criminal justice responses, Dayton needs to use data to identify where mental health and addiction services are most urgently needed. By mapping out overdose rates, drug-related arrests, and emergency room visits, agency officials can direct addiction treatment and mental health services to the most affected areas.

Data can also be used to create early intervention programs that address substance abuse and mental health challenges before they escalate into criminal behavior. By collaborating with health agencies and universities, Dayton can develop models that predict where interventions will be most effective, ensuring that resources are deployed in ways that not only reduce crime but also promote long-term recovery. As a professor at the University of Dayton, I see firsthand the potential that academic research and expertise can bring to public policy. Universities have access to a wealth of knowledge, research tools, and innovative ideas that can be applied to solving real-world problems like crime.

By forming closer partnerships, Dayton’s local government, law enforcement, and social services can benefit from the cutting-edge work being done at these institutions. For instance, joint research initiatives can help identify the most effective interventions, while data analysis projects can provide insights into crime trends and the socio-economic factors driving criminal behavior. These collaborations not only help reduce crime but also ensure that interventions are evidence-based and targeted for maximum impact.

Credit: Marshall Gorby

Data-driven approaches offer more than just the ability to analyze crime — they also provide a means to measure success. By tracking the outcomes of different interventions, we can determine which strategies are working and which need to be adjusted. This level of accountability ensures that resources are used efficiently, and that the city continues to adapt its approach based on what the data reveals. For example, if a community revitalization program designed to reduce property crime isn’t delivering results, data can provide insights into why. Did it fail to reach the intended population? Were there external factors that weren’t considered? This feedback loop is crucial for ensuring that Dayton’s efforts to reduce crime are both effective and sustainable.

Dayton is at a crossroads. The challenges we face with crime are significant, but so are the opportunities. By embracing data-driven solutions and fostering closer collaboration between agencies and universities, Dayton can take meaningful steps toward reducing crime and creating a safer, more prosperous community. The University of Dayton Criminal Justice and Security Studies Department stands ready to partner with leaders to provide the research, data, and expertise needed to tackle these complex problems. With the right approach, we can build a future where crime rates are reduced not just through enforcement, but by addressing the economic, social, and health issues at the root of the problem. Now is the time for Dayton leadership to invest in data-driven solutions — and to invest in a brighter, safer future for all its residents.

Scott H. Belshaw, Ph.D. is a professor and chair of the Criminal Justice and Security Department at the University of Dayton.

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About the Author

Scott H. Belshaw