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Using Data-driven Strategies for Reducing Homelessness

Communities across the nation are making the most of limited resources, utilizing data analytics and creating browser-based applications that help connect homeless individuals to needed services.

This story was originally published by Data-Smart City Solutions

With so many American cities working to address homelessness, there is no shortage of innovative thinking about this urgent challenge. Phoenix and Salt Lake have made headlines for ending chronic homelessness among veterans through a ‘Housing First’ strategy, which draws upon a mix of federal and local sources to provide shelter and services. As part of a community benefits agreement, Zendesk has created a browser-based, mobile compatible application called Link-SF that provides information about services for homeless individuals in San Francisco.

Other approaches depend less on the availability of affordable land for new construction, or access to mobile devices. For example, despite the challenges of an expensive housing market and large population, New York City government has pioneered new approaches for preventing homelessness through the use of data and analytics.
 
Started in 2004, the HomeBase program combines a variety of services to families who have not yet entered the shelter system, including case management, mediation services, employment assistance and short-term emergency funding. HomeBase has incorporated program evaluation from its inception, since “prevention programs always have to show that our resources go to people who would otherwise be vulnerable,” said Sara Zuiderveen, Assistant Commissioner for Prevention Services at the New York City Department of Homeless Services (DHS). A randomized controlled trial found that relative to other existing services, HomeBase reduced the number of shelter applications by nearly 50% and reduced the number of days in shelter by 70%, resulting in $1.37 in savings for every dollar spent on the program.
 
In addition to assessing the program’s effectiveness, DHS has also partnered with academics to develop customized risk assessment tools that support caseworkers in determining the best approach for each client during the screening process. DHS is also exploring more proactive approaches, partnering with the SumAll Foundation to analyze data on eviction notices to predict which cases are most likely to result in homelessness. While the pilot is still being tested in specific neighborhoods, the analytics will eventually become part of the City’s data visualization project that allow staff to visualize neighborhood data such as shelter entries and eviction filings, while also being able to tell caseworkers which of the thousands of households or buildings on the map are actually most at-risk of shelter entry.  By tailoring outreach efforts and reducing barriers to access, DHS can provide more services to more at-risk families.
 
In designing systems like this, Zuiderveen emphasized that the focus should be on “how to create the most practical, useful tool for the case managers and workers on the front lines – how do we use data to do the best job possible?” This focus has enabled DHS to make the most of limited resources, and continually search for new ways to improve services and outcomes.