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

arXiv: https://arxiv.org/abs/2410.14825 · HTML: https://mlsanity.com/paper/2410.14825/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 18 Oct 2024.

## Built on by (most cited first, 4 of 4)

- [What Constitutes a Less Discriminatory Algorithm?](https://mlsanity.com/paper/2412.18138/) (2024)
- [Bayesian Modeling of Zero-Shot Classifications for Urban Flood Detection](https://mlsanity.com/paper/2503.14754/) (2025)
- [Urban Incident Prediction with Graph Neural Networks: Integrating Government Ratings and Crowdsourced Reports](https://mlsanity.com/paper/2506.08740/) (2025)
- [Contextual Budget Bandit for Food Rescue Volunteer Engagement](https://mlsanity.com/paper/2509.10777/) (2025)

## Abstract (arXiv)

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/.