Why Data Works: Our Submission to the United Nation’s Habitat Conference

Every 20 years the United Nations hosts a conference on Housing and Urban Stability called Habitat. This year is Habitat III, an opportunity to adopt global standards of achievement in sustainable urban development. Our CEO and President Nan Roman will be attending the conference in Quito, Ecuador in mid-October.

In preparation for the conference, the United States created U.S. 20/20, a report reflecting on the last 20 years, while looking forward to the next 20. Here is a peak at my submission to the report.

In the 20 years since Habitat II, a revolution has occurred in our approach to homelessness in the United States—a revolution driven by the use of data. In 1996, the year of Habitat II, it was estimated that 800,000 people were homeless on a given night in the United States. This was among the first reliable estimates of homelessness in the United States. When it was made, using a survey of homeless assistance programs, there were extremely limited sources of data on homelessness.

Today, according to the most recently available national data, the number of people homeless on a given night is approximately 565,000. Because jurisdictions across the United States have been required to produce these annual counts since 2005, we can look beyond the point in time to examine trends and evaluate progress toward ending homelessness. That is not all. Beginning in the late 1990s jurisdictions were also required to collect administrative data on homelessness, which gave us a more nuanced picture of the people who became homeless and what help they used while they were homeless. The United States has used this data to improve practice and policy and continue—despite the Great Recession of 2008—to reduce the number of people who are homeless. How was this accomplished?

Up until the early-to-mid 1990s, the primary national response to homelessness had been food and shelter. Food programs represented the largest portion of homeless assistance; emergency shelters represented the second largest response. Few resources were spent on helping people transition from homelessness to housing, and little was known about the people being served or the effectiveness of the programs serving them.

In the late 1990s and early 2000s, using data collected on people experiencing homelessness in a few major cities in the United States, researchers found patterns in time spent homeless and demographic and behavioral characteristics and used them to create typologies of homelessness among individuals and families. From these typologies and innovative local efforts, new interventions emerged, data tailored them to specific populations, and evaluation proved their effectiveness. These interventions, permanent supportive housing and rapid re-housing, grew in popularity and spread across the country.

The emergence and spread of permanent supportive housing and rapid re-housing serve as examples of how data can be used to improve policy and practice. From the start, research on these interventions showed promising results. Over time, evidence showed their cost-effectiveness. For example, data on disabled homeless people, when merged with data from corrections, healthcare, and behavioral healthcare systems, showed that permanent supportive housing was less expensive than letting this high-cost population stay homeless. Similarly, as more and more communities implemented rapid re-housing, the model was shown to have better outcomes than usual care and at much less cost. The evidence mounted, and permanent supportive housing and rapid re-housing grew from local experiments to widely adopted strategies that are the backbone of federal efforts to end homelessness.
Read the full essay here.