HUD needs to step up: establish comprehensive data collection standards, require service providers to track more detailed metrics, define program success clearly, and mandate open-source data access. These changes would enable stakeholders to identify and replicate effective strategies, ultimately driving real progress toward ending homelessness.
Addressing homelessness may seem straightforward, but in practice, it’s incredibly complex. I worked for a non-profit in San Diego dedicated to ensuring taxpayer money was spent effectively. One of our major initiatives was tackling homelessness. We organized extensive meetings with public and private funders, service providers, and philanthropists to establish universal standards for evaluating program effectiveness. These standards were crucial for making apples-to-apples comparisons, enabling funding to be directed toward programs that truly worked.
But defining what an “effective program” means isn’t simple. Different stakeholders have different metrics: one might prioritize outcome X, while another values outcome Y. As a result, funding is often spread across programs without clear evidence of effectiveness. Our goal was to shift this focus toward outcome A: a standardized definition of success.
It was a noble effort. We gained unanimous agreement on seven regional standards. Yet progress was stymied by bureaucracy and semantics. A prime example: the Regional Task Force on Homelessness (RTFH). Despite early cooperation, RTFH executives later refused to release critical data we needed to assess program effectiveness. Even more troubling, we were forced to destroy data we previously had after securing just one of the seven standards.
Here’s the problem: most funding for homelessness services comes from federal grants, often through HUD. But HUD lacks robust data collection protocols, clear definitions of success, and mandates for open-access data. Without these, it’s nearly impossible to evaluate programs or compare their outcomes. Studies on homelessness are rare, not because of a lack of interest, but because the data is inaccessible, poorly managed, or buried in unreadable formats like PDFs.
The result? Policies and solutions are often based on subjective observations rather than concrete evidence. Without reliable data, we can’t identify what truly reduces homelessness, let alone scale or optimize those solutions. The fact that we’re entering 2025 and haven’t solved this issue is shameful for a country like the United States.
Again…
HUD needs to step up: establish comprehensive data collection standards, require service providers to track more detailed metrics, define program success clearly, and mandate open-source data access. These changes would enable stakeholders to identify and replicate effective strategies, ultimately driving real progress toward ending homelessness.