Data-Driven Approaches to Homelessness Prevention

Date: Friday, May 23

Time: 10:15 a.m. – 11:15 a.m. (AICP-CM: 1)

Holiday Ballroom 1

Speakers:

  • Chad Bojorquez, Chief Program Officer at Destination: Home
  • Jessica Orozco, Program Manager, Office of Supportive Housing at Santa Clara County
  • Brendan Perry, Assistant Director of Replication & Scale, Wilson Sheehan Lab for Economic Opportunities at University of Notre Dame
  • Ross Tilchin, Director of the Economic Mobility Catalog, Solutions Team at Results for America

Resources:

Data-Driven Approaches to Homelessness Prevention (presentation slides)

The United States is experiencing a homelessness crisis unlike anything the country has seen before. A national census in 2024 counted 770,000 people living on the street or in a sheltered setting – an 18% increase from 2023 and the highest number ever recorded. In recent years, governments at all levels have invested billions in housing and other services for people experiencing homelessness. However, there’s a more effective and common-sense strategy that American communities have barely tapped into: preventing people from becoming homeless in the first place. This is the method that Santa Clara County, California has implemented, and a rigorous evaluation shows that their model is working.

This session offers a deep dive into Santa Clara County’s Homelessness Prevention System and data-driven approaches to prevent displacement. Attendees will learn about Results for America’s toolkit on Building a Homelessness Prevention System, based on Santa Clara’s model, and leave with a greater understanding of how they can adapt and implement this model to address homelessness in their communities.

This session is eligible for Certification Maintenance credits with the American Institute of Certified Planners. If you are an AICP member and attend the session in full, you can add credits to your CM log by searching for the “National Economic Mobility and Opportunity Conference 2025” in the CM Search menu and selecting specific sessions from those associated with the event.