Transforming City Operations with StatGPT

Abstract

Cities today face mounting pressure to deliver more effective services using fewer resources. To meet these challenges, performance management systems must evolve. This paper proposes “StatGPT,” a next-generation, technology-enabled approach that builds on the successes of traditional Stat models by injecting them with modern artificial intelligence (AI) and data capabilities. A responsive city measures what matters and then does something about it. Yet, the management systems that determine what should be measured, what data to utilize, and by whom, require modernization. That is especially true now as demands on local government continue to exceed resources, and the legitimacy of elected officials depends on fulfilling residents' expectations. Delivering on daily tasks that matter to residents creates a “responsive cycle,” where trust builds the legitimacy necessary for mayors to rally followers in times of crisis or towards large aspirations. Achieving these goals requires a new approach that leverages the power of generative AI (GenAI), the Internet of Things, ubiquitous mobile devices, open data, and advanced analytics. This new approach requires modernizing the Stat systems that cities have widely adopted over the past two decades, dating back to when New York City Police Chief Bill Bratton introduced CompStat to manage crime-fighting efforts and Baltimore Mayor Martin O’Malley applied CitiStat to municipal services. The Stat model combined data with accountability in a way city leaders had not seen before. Precinct commanders in New York, or department heads in Baltimore, would attend a high-level meeting where they would present their latest data on crime or service levels, which would be projected on large screens for everyone in the room to see. Then, senior executives – and sometimes Bratton or O’Malley themselves – would grill managers about the numbers. Why are robberies up on this block? Why are restaurant inspections down this quarter? Often, there was a theatrical element to these meetings. These events proved effective in keeping managers focused on results and surfacing hidden problems. Crime in New York plunged. Baltimore saved millions on employee overtime related to chronic absenteeism. When utilized correctly, Stat is today’s gold standard for performance management. Bob Behn, my colleague at the Harvard Kennedy School and an expert on Stat programs, underscores that using the model effectively requires hands-on leadership, timely data, regular meetings, active follow-through, a constructive culture, constant learning, and flexibility. These principles remain as cities rethink Stat, but now they are merely the table stakes for the broader transformation that leverages technology. This paper proposes a new approach to measuring and utilizing performance data as the gateway to management changes that lead to operational excellence