3 cities in the U.S. have ended chronic homelessness: Here’s how they did it
Nine more have ended veteran homelessness. It’s part of a national program called Built for Zero that uses a data-based approach to help officials figure out exactly who needs what services. Now it’s accelerating its work in 50 more cities.
[Source Image: valigursky/iStock]
BY ADELE PETERS8 MINUTE READ
In late February, the city of Abilene, Texas, made an announcement: It had ended local veteran homelessness. It was the first community in the state and the ninth in the country to reach that goal, as part of a national program called Built for Zero. Now, through the same program, Abilene is working to end chronic homelessness. While homelessness might often be seen as an intractable problem because of its complexity–or one that costs more to solve than communities can afford–the program is proving that is not the case.
“By ending homelessness, we mean getting to a place where it’s rare, brief, and it gets solved correctly and quickly when it does happen,” says Rosanne Haggerty, president of Community Solutions, the nonprofit that leads the Built for Zero program. “That’s a completely achievable end state, we now see.” The nonprofit, which calls this goal “functional zero,” announced today that it is accelerating its work in 50 communities.
[Image: courtesy Community Solutions]
One key to the process is data, and a visual dashboard that lets agencies track people experiencing homelessness in real time. In Abilene, with a population a little more than 120,000, for example, the city located every homeless veteran, gathered information about each individual situation, and stored this information in a “by-name list” that was continually updated. “It basically just forced us to continuously look to change improvements to our system, and how to use real-time data to improve our performance,” says John Meier, the program manager for supportive services for veteran families for the West Central Texas Regional Foundation. “We’ve always had lots of data sitting around, but haven’t had it in one place and [haven’t been] utilizing it to our advantage.” Every agency in the city began working together and meeting to discuss how to get each veteran–21 people, as of February 2018–into housing. While watching the data, they could test interventions like working with local landlords and the public housing agency to prioritize people on the list. The average amount of time to house a veteran shrank from more than 40 days to 26. By November 2018, 10 months after joining the Built for Zero program, Abilene had reached the goal of “functional zero” for veteran homelessness. (It made the announcement in February in part because it was waiting for federal confirmation, which was delayed by the government shutdown.)
Community Solutions had previously worked with 186 cities in a campaign that got more than 100,000 homeless people into housing in less than four years. But it wanted to go further. “We got to a point where we helped communities house a lot more people and get better at housing people,” Haggerty says. “But we still didn’t see them ending homelessness, and that’s where Built for Zero came in. It really is a very radical idea that without real-time, person-specific information, communities just can’t pool everything they’ve got together and be accountable at solving the problem.”
The nonprofit partnered with the Tableau Foundation, a philanthropic arm of Tableau Software, to use the company’s data visualization tools. Being able to easily track the data helped communities in the program shift “from incremental improvement to transformational results,” Haggerty says. Tableau saw parallels to the work that it had done in Zambia to help the country track its work to eliminate malaria; before using a data visualization tool, the government there had struggled to see who was contracting malaria and how they were being treated. In planning meetings, the government had been using outdated data from the previous year. As in American cities tackling homelessness through multiple agencies, Zambia wasn’t seeing a systems-level view of the situation and couldn’t respond strategically. After it started working with real-time dashboards, it was able to reduce malaria deaths by more than 90%, and reduce malaria cases by more than 80%.
[Image: courtesy Community Solutions]
The company saw the potential for a similar transformation of work on homelessness. “For decades, homelessness organizations would collect data, and they would send it to HUD,” says Neal Myrick, global head of the Tableau Foundation. “Once a year, HUD would produce a massive report that nobody was really reading. And the information wasn’t really usable to the people who needed it on the ground to make active decisions about what to do day-to-day to better solve the problem.”
Communities in the program use a coordinated approach. Bergen County, New Jersey, with a population of nearly 1 million, was the first in the country to end chronic homelessness, reaching the goal in 2017. (Six months earlier, it had also ended veteran homelessness.) The county created a “command center” that brought together various organizations working on homelessness, and then began using real-time data about each person experiencing homelessness so that everyone could work together to get them housed. Like many places, Bergen County also committed to a “housing first” approach, meaning that people move into permanent housing as a first step before also getting help with finding a job, mental healthcare, or other issues.
The data revealed trends, like the fact that their population of those who were chronically homeless–homeless for more than a year–was growing because people were sitting on a waiting list for so long that they were passing the one-year threshold. The county was able to begin prioritizing those who were close to the one-year mark to get them into housing faster; now, no one has “aged in” to chronic homelessness for months.
Some advocates for people experiencing homelessness are concerned about this type of data-gathering and the risk that data could be misused by law enforcement. In communities using the Built for Zero system, law enforcement may be part of a local team working on the problem but typically doesn’t have access to the data. Community Solutions says that there haven’t been any cases of law enforcement trying to seize the data or use it inappropriately.
[Image: courtesy Community Solutions]
Continuing to use real-time data helps the county identify new problems that are emerging; right now, for example, they’re seeing an uptick in both young people and seniors who are homeless. “The data is so important because by the time you know it’s a problem, it’s too late,” says Julia Orlando, director of the Bergen County Housing, Health and Human Service Center. “So if you can start seeing trends before it’s a really bad problem, you can start adjusting your policies or trying to get additional services in your facility to try to address that.” For example, they can now start planning to add skilled nursing care to their shelter and searching for different types of grants to support eldercare.
The county had the resources to achieve the “functional zero” goal, Orlando says. But the focus of the program and its use of data helped it actually accomplish it. While cities and organizations working on the problem of homelessness often point to a lack of resources, it may be the case in many communities that the right resources exist–or can be mobilized–with a more strategic approach. “Once communities can actually see what’s going on, they can make informed decisions about where to put resources and where new resources are needed,” says Haggerty. In Montgomery County, Maryland, the government used specific data to say exactly how much money it needed to end veteran homelessness, and that helped get it the funding to reach the goal.
The next opportunity for cities or counties to join the program and get training will happen in October. The challenges may be largest in cities like New York or San Francisco or Seattle–none of which are yet part of the program–where homeless populations are very high, in part because of expensive housing markets. But that’s not to say that ending chronic and veteran homelessness is impossible in those cities. Resources are not necessarily the only issue; homelessness is increasing in New York City even as it spends more than $2 billion a year on homelessness programs. One issue is bringing together all of the organizations in a community that need to collaborate and commit to a “functional zero” goal, Haggerty says.
Some cities do have related programs. San Francisco, for example, also has a platform that tracks individuals to help connect them to housing more quickly. Built for Zero goes further, however, because it serves as an analytics platform that helps communities better understand the whole picture so that they can spot and solve issues at a systems level.
“We are doing a lot of thinking about how do we change norms so that the expectations shift so that more and more people understand that this is a solvable problem, and just kind of sitting it out and just complaining about resources or the other guy is just not going to be acceptable anymore,” she says. “We find ourselves thinking a lot these days about marriage equality, smoking, drunk driving–some of these movements in our recent lifetime were an issue went from ‘What’s to be done,’ to ‘We are going to commit ourselves to a different set of behaviors now. We’re going to own different norms.’ And I think that needs to happen on homelessness.”
To date, nine communities have reached the goal of “functional zero” for veteran homelessness, and three communities have reached the goal for, chronic homelessness. Another 39 have made measurable progress toward those goals by gathering meaningful data. The Tableau Foundation is now committing more than $1.3 million in software, services, and funding to help 50 communities that are currently involved in the program to accelerate their progress, with the aim to help 13 achieve functional zero goals by the end of the year. “We thought by focusing on the 50 cities it would become a tipping point, where the discussion around whether or not homelessness could be solved really was put to rest,” says Myrick. “It becomes more about, how are we going to solve it? With limited resources for everything, we think it’s really important to just start solving the problems that can be solved.”
ABOUT THE AUTHOR
Adele Peters is a staff writer at Fast Company who focuses on solutions to some of the world's largest problems, from climate change to homelessness. Previously, she worked with GOOD, BioLite, and the Sustainable Products and Solutions program at UC Berkeley, and contributed to the second edition of the bestselling book "Worldchanging: A User's Guide for the 21st Century."
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Square’s new Assistant is an AI bot that aims to do one thing well
Instead of trying to teach its chatbot to do too much, Square focused on one small-business task: confirming, canceling, and rescheduling appointments.
[Animation: courtesy of Square]
BY JARED NEWMAN3 MINUTE READ
It turns out that a lot of people will avoid picking up the phone to reschedule things, even if it means being a no-show for an upcoming haircut or nail appointment.
For that reason, Square is now letting business owners automate the rescheduling process with a chatbot called Square Assistant. Business owners that are using Square’s existing Appointments service can now confirm appointments with customers—or let them cancel or reschedule them—via text message, without any human involvement. It’s the first product to come from Square’s acquisition of conversational AI startup Eloquent Labs earlier this year.
[Image: courtesy of Square]Square says that in early testing of the service, sellers saw a 10% drop in no-shows, which might seem surprising until you learn that Square sellers engage more with customers via text messaging than they do by phone or email.
“For some of our customers, SMS is just a more efficient way to interact,” says Ellen Blaine, a former Eloquent Labs engineer who is now a product manager at Square. “With Square Assistant, you can reschedule or confirm an appointment just by texting a couple of words.”
To be clear, the rescheduling part doesn’t happen entirely over text. Once Square Assistant figures out that customers want to change an appointment, it still links them to a web-based calendar, similar to what Square Appointments uses for its initial scheduling.
[Photo: courtesy of Square]
The AI component, Blaine says, comes from trying to determine what users are trying to accomplish in the first place when they send a text message to the business. Square uses Amazon Mechanical Turk—that is, inexpensive human labor—to train its AI models by annotating different kinds of requests. But the company says the Assistant itself doesn’t involve any human intervention. (Customers are also told upfront that they’re interacting with a chatbot, so as not to let them feel tricked.)
“There are a whole lot of ways to ask, ‘Can you reschedule my appointment?’ or ‘Can you confirm my appointment?’ and it would be pretty impossible to enumerate all of them,” Blaine says. “With AI, we’re able to extrapolate from a few examples.”
A LESS AMBITIOUS CHATBOT (FOR NOW)
Just a few years ago, chatbots were all the rage in the tech business, with major companies such as Facebook and Microsoft pushing them as a replacement for apps. The idea was that interacting with a service over text—or at least in a conversation view akin to text messaging—would be much simpler than downloading an app and figuring out how to use it.
Most of those companies have since scaled back their chatbot plans or acknowledged that simulating the back-and-forth exchange of a text message isn’t all that useful. Less ambitious chatbots have stuck around, though, especially in the area of customer service, where automating answers to common questions can save precious time and resources.
[Video: courtesy of Square]
Square Assistant falls into that low-key category. Instead of promising to solve all kinds of customer service issues, it’s focused on one particular issue that can sap a small business’s resources. And because of that narrow focus, it only has a few potential actions—confirm, cancel, reschedule—so there aren’t many things that could derail the conversation.
Blaine says that Square listened closely to feedback from its customers as it created its purpose-built bot. “There are plenty of chatbots out there, and a lot of them promise a magic
AI hammer that solves every problem. A couple of years ago, there was all that hype,” she notes. “But in general it’s so important to work with real sellers as we build these conversational AI solutions for them and their customers.”
That’s not to say Square Assistant won’t become more ambitious over time. In a way, it’s like the inverse of Google Duplex, the AI that Google rolled out last year for booking reservations over the phone. Duplex’s big idea was to let users make electronic reservations even if the restaurant or salon only booked over the phone, with a human-like voice assistant making the call to bridge the gap. Square Assistant, by contrast, is working backward, by putting the automation in the hands of small businesses, which can then extend it to customers.
Square won’t say where that idea might go from here but says it looks forward to exploring how
AI can solve the problems of the customer base, which is heavy on local service providers, retailers, and other independent outfits without major technology resources of their own.
“Many of our sellers are smaller businesses, and that’s really exciting to us because small businesses traditionally haven’t had access to enterprise-quality conversational AI,”
