Using Data to Deliver Water Affordability
Access to safe, affordable water is a basic necessity, but for too many households, the process of getting help when water bills are unaffordable is burdensome or inaccessible. Cities across the U.S. are starting to change that by using data sharing and cross-agency collaboration to automatically enroll eligible residents in low-income water discount programs. These strategies help to reduce barriers, improve equity, and protect public health.
Join the Water Center at Penn, the Natural Resources Defense Council (NRDC), the National Consumer Law Center (NCLC) and the Mayors Innovation Project for a timely webinar that highlights successful local models for using data matching to enroll eligible residents in low-income water discount programs.

Access to safe, affordable water is a basic necessity, but for too many households, the process of getting help when water bills are unaffordable is burdensome or inaccessible. Cities across the U.S. are starting to change that by using data sharing and cross-agency collaboration to automatically enroll eligible residents in low-income water discount programs. These strategies help to reduce barriers, improve equity, and protect public health.
Join the Water Center at Penn, the Natural Resources Defense Council (NRDC), the National Consumer Law Center (NCLC) and the Mayors Innovation Project for a timely webinar that highlights successful local models for using data matching to enroll eligible residents in low-income water discount programs. We will explore case studies featured in NRDC and NCLC’s forthcoming report, including:
- Philadelphia, PA – A city using data-sharing agreements across local agencies to automatically enroll low-income households in its Tiered Assistance Program (TAP) and proactively identify vulnerable households, such as seniors and renters, to protect them from water shutoffs.
- Westminster, CO – A city collaborating with the state’s LIHEAP program to identify eligible customers and apply discounts through a low-tech but effective data match process with its billing system.