Redesigning Service Level Agreements: Equity and Efficiency in City Government Operations

We study how government should allocate resources (e.g., maintenance of public infrastructure) over time, efficiently and equitably -- when these desiderata may conflict. In particular, we consider the design of Service Level Agreements (SLAs) in city government operations: promises that incidents such as potholes and fallen trees will be responded to within a certain time. We model the problem of designing a set of SLAs as an optimization problem with equity and efficiency objectives under a queueing framework; the city has two decision levers: how to allocate response budgets to different neighborhoods, and how to schedule responses to individual incidents. We first theoretically analyze a stylized model, deriving when the equity-efficiency trade-off is substantial in absolute terms and centralizing response efforts leads to relatively smaller improvements over optimal decentralized operations. We then develop a simulation-optimization framework to design and analyze policies in practice. Applying our framework to data from NYC, we find: (a) in practice, despite large potential trade-offs, equity improvements are possible with relatively small decreases in efficiency; (b) there exist policies that are both more efficient and equitable than status quo inspections; (c) the gain from centralization is {relatively small compared to the potential efficiency-equity tradeoff}. Our results provide widely applicable predictions about the scale of the equity-efficiency trade-off in similar resource allocation settings, and our data-driven simulation-optimization framework enables specific policy recommendations in government operations. Our code is available at https://github.com/nikhgarg/sla_design. Our theoretical statements have been formalized in Lean, available at https://github.com/nikhgarg/AppliedModelingLib/blob/main/papers/LG24ServiceLevelAgreements/.