Homeless girl, Young beautiful red hair girl sitting alone outdoors on the stairs of the building with hat and shirt feeling anxious and depressed after she became a homeless person

How government data can be used as a road map to reduce homelessness

As cities grapple with rising homelessness, states struggle to distribute relief money. Using data, change is in reach.

In brief

  • Even before the pandemic caused millions in the US to lose jobs and income, homelessness was on the rise in communities across the US.
  • States are struggling to allocate federal relief funds, and cities are trying different approaches to provide housing to those in need.
  • By pulling together data that already exists, agencies can work proactively to prevent individuals and families from becoming homeless.

Governments and agencies continue to grapple with homelessness to varying degrees and with limited success. Too often, the approach is built on a flawed premise — that homelessness is a foregone conclusion.

To be sure, there are no easy answers. Recent research begins with no premise, only a bold question, “How can we stop homelessness before it starts?” The results are nothing short of groundbreaking.

More than 580,000 homeless in the US

Even before COVID-19, homelessness in the US was on the rise. On a single night in January 2020,more than 580,000 individuals were homeless in the United States, according to an annual study by the US Department of Housing and Urban Development (HUD).2 The one-day nationwide snapshot revealed a 2% rise in homelessness — the fourth consecutive annual increase. For the first time in years, homelessness among veterans and families did not improve.

The pandemic-driven loss of jobs and employment income will cause the number of homeless workers to increase each year through 2023, according to a January 2021 report from the nonprofit research group the Economic Roundtable.3 The study noted that without large-scale government employment programs, a “Pandemic Recession” is projected to cause twice as much homelessness as the 2008 Great Recession.

Housing costs consume an increasing portion of workers’ budgets as housing prices and rents continue to grow faster than incomes, according to the study. Over half of US families who are in poverty pay more than half of their income for housing.4

Addressing unused funding and programs

The federal government’s response includes the Emergency Rental Assistance (ERA) program, with a staggering $46 billion in funds. The Centers for Disease Control and Prevention (CDC) issued moratoriums on evictions. But unforeseen challenges on each of these fronts have left most of the money undistributed and millions of additional individuals and families unprotected against eviction:

  • ERA funds — A significant portion of the $46b is sitting idle. The money has been available since January 2021, yet roughly 90% remained unspent in August 2021. States, each with its own approach to distributing the money, are struggling to get it into the hands of those who need it. Among the most common reasons for this failure are:5
    • Tenants’ and landlords’ lack of awareness that funds are available to them
    • States’ need for third-party vendors, which requires a lengthy vetting process
    • Tech-related challenges, for the applicants as well as the states themselves
    • Non-intuitive, convoluted application processes that cause errors and holdups
  • Eviction moratoriums — The CDC’s first moratorium on evictions expired July 31, 2021. Its second moratorium would have expired October 3, 2021, but was cut short when the Supreme Court nullified it on August 26, 2021. A handful of states responded by setting their own eviction limitations, though most have expired.

Below, we cover a phased approach to addressing these difficulties that could help reduce homelessness.

  • Now: Actions to undertake immediately
  • Next: Actions to take once conditions are stabilized
  • Beyond: Actions to take once we’re able to shift focus to prevention
Caucasian homeless man. No money, No work, No home

Chapter 1

Now: Provide safe shelter while collaborating with key resources

Governments’ primary focus, providing safe shelter, has left little time for visionary efforts.

State and local governments, as they contend with rising numbers of those who are homeless or on the brink, must also focus on continuity of programs and protection of residents.

The critical first step is understanding who the vulnerable population is and getting them safely sheltered. The pandemic has changed our physical environments, with some facilities being temporarily or permanently closed, or completely repurposed. Cities’ efforts to increase capacity to shelter the growing number of homeless have run the gamut, from buying or commandeering hotels to building small communities on city land:

  • King County, Washington — The county’s Health Through Housing initiative immediately creates housing units by acquiring former hotels, nursing homes and other single-room settings.
  • Portland, Oregon — The city plans six “safe rest villages,” with locations across Portland. They are composed of sleeping pods and retrofitted shipping containers that will serve as laundry rooms, showers, bathrooms and kitchen facilities. The new sites join Portland’s growing network of outdoor village-style shelters.
  • New York City, New York — New York’s homelessness is reportedly worse than at any time since the Great Depression, according to the New York Coalition for the Homeless.6 Mayor Eric Adams has announced a plan to convert the significant number of closed hotels (estimated at 200)7 to supportive housing for the homeless.8

Reduction of risk and cost are key concerns as cities seek solutions around shelter location and capacity strategy. The immediate nature of the need heightens the requirement for efficiency. Collaborating with economic development and community planning resources can help the team develop a strategy and action plan and, later, analyze progress and impact.

Similarly, cities that are turning to sites such as shuttered hotels and civic arenas to fill the immediate need for shelter may be treading unfamiliar ground. Real estate industry insights will help with key tasks, such as assessing contractual obligations; reviewing regulatory compliance; and developing solutions for maintaining functionality and maximizing efficiency.

Homeless man shaking hand

Chapter 2

Next: Focus on unlocking data on the causes of homelessness

Agencies can connect data points to determine each resident’s needs.

As a city’s homeless shelter scenario begins to stabilize, residents should already be receiving the services they need to get back on their feet. By leaning into digital and focusing on unlocking their data, agencies are also unlocking the insights and agility that are essential for the next phase.

Applying a blanket approach across the entire population will achieve little. Each person is different, and there are myriad causes for homelessness. Some may be grappling with mental health, substance abuse or financial challenges; some are unable to work because of health conditions.

To deliver services that will get someone to a better place, governments must identify the specific factors that moved that person or family into homelessness. Data, specifically the powerful insights that it provides, makes this seemingly impossible task possible. And governments have a wealth of data at their disposal. Government programs receive and amass enormous stores of data covering a broad range of public services, from housing to health to childcare.

When agencies connect individuals’ many data points, they’re able to construct a “digital twin” of the residents they serve; user experiences drive improvements in this integrated service delivery model:

  • Digital twin — A digital twin is a digital representation of a real-world entity or system. In this case, data is aggregated and analyzed to enable a holistic view around an individual so that agencies can determine how best to support them so that they experience improved outcomes.
  • Experience-led transformation — Insights from user experiences will continue to give agencies a better view across needs and services so that residents can get the help that best fits their needs.

Without properly integrated data and with only a partial picture of the person who is in need, agencies won’t know how to help them. Without diving into the specifics and nuances of circumstances, an agency won’t be able to answer the two most foundational questions: what is their challenge, and can that government do anything to help?

Young african woman holding home keys while hugging boyfriend in their new apartment after buying real estate. Lovely girl holding keys from new home and embracing man. Happy couple in their apartment around cardboard boxes.

Chapter 3

Beyond: Using predictive modeling and data analytics to begin reducing homelessness

Studies show that data and analytics make early intervention to homelessness possible.

Governments can go beyond merely providing shelter after someone becomes homeless. By accelerating their capabilities to unlock their data and analytics, agencies can do more than react — they can prevent.

In 2019, research by Ernst & Young, LLP and Imperial College London’s Institute of Global Health Innovation9 explored the use of data and analytics by five health and human services providers around the world. The findings highlighted the ways data and analytics can improve people’s lives. Results at an East London borough are just one example of what’s possible:

  • London Borough of Barking and Dagenham (UK) — Local government officials wanted to address the borough’s challenges of unemployment, poverty and homelessness. Getting residents the right help and support in a timely way was challenging because their information was stored across case management systems. Caseworkers lacked the comprehensive overview necessary to keep risks from becoming crises.

“For too long, our residents faced a legacy of really poor outcomes,” said Rhodri Rowlands, the borough’s Deputy Director and Head of Programmes Community Solutions. “That, coupled with the challenges of rising demand and financial pressures, led us to a position where we wanted to think very differently about how we could better respond to address residents’ needs,” he said. 

For too long, our residents faced a legacy of really poor outcomes.

The borough turned to data and analytics software to integrate its data. When COVID-19 struck, the agency was able to predict more than 90% of its at-risk population and connect them with support. Over 8,000 residents in the borough received rapid assistance.

In a separate initiative,10 a case study involving a borough in Kent, England, predictive modeling was applied:

  • Maidstone Borough — In 2018, Maidstone had recorded a 58% increase in homelessness over the previous five years. Government funds had also been reduced. The Council sought a completely different approach to homelessness.

The borough transformed its service model from reactive to predictive, applying a proactive solution driven by data. Integrating data from multiple government systems helps agency workers understand what’s happening with an individual or family.

The results were nothing short of groundbreaking:

Because agency workers were able to identify a trend toward homelessness, they could intervene earlier, before individuals were actually on the street. The results were extraordinary by any standards: for the initial pilot group, in one year, the rate of homelessness fell from 40% to 0.4% — a 99% reduction in homelessness.

Harnessing data
Fewer homelessness cases were recorded after one year for the initial pilot group: from 40% to 0.4%.

An early-intervention case study

  1. The Maidstone Borough Council (MBC) was alerted that Mrs. A was at risk of eviction on Oct. 21, 2019.
  2. On Oct. 29, MBC sent a text message to Mrs. A stating that she was eligible for a discretionary housing payment.
  3. Mrs. A responded to the text message and was able to pay her rent, thus preventing a potential eviction and homelessness case.

Other examples of early intervention:

There are numerous ways agencies can intervene early to keep people from slipping into homelessness. These are real-life examples:

  • Benefits support and budgeting advice
  • Support to resolve tax debt
  • Housing assistance
  • Legal assistance
  • Employment services
  • Referral for mediation
  • Disbursement of loan

Opportunities close to home

In cities across the nation, homelessness affects the entire community — not only those needing help but the people who live, work and visit there. Efforts may be more effective on the local level.

There are fewer constraints at the local level, while federal agencies must grapple with systemic challenges. For example:

  • Federal funding programs are siloed. The funding stream for housing assistance is separate from the funding stream for food security — which is separate from the funding stream for medical services, and the one for mental health services, and so on.
  • There is no incentive for these individual divisions to work together because they are held accountable to a metric that applies only to their specific area of focus.

But as funding from the federal government level trickles down through the state and local governments, flexibility increases. The very structure of funding programs expands opportunities to set a different governance model.

Turning the focus to data

Eradicating homelessness will require more than money. That is not to say that the emergency funds are not sorely needed. Digital tools and knowledge resources can provide the states with tailored solutions that help them take full advantage of funding and remove obstacles around technology, third-party vendors and application processes.

Data, not money, holds the key. Fortunately, data is an abundant government resource. Government, with its place at the head of the table, has the opportunity to know more and do more than the innumerable private organizations, online groups and nonprofits that are trying to end homelessness.

Sharing information across agencies provides valuable insights into specific needs. Determining how best to meet those needs, whether for an individual or a family, requires that the government know the data that is available. Both of these aspects, knowing the real need and knowing your data, will affect the ultimate goal: connecting people with the resources that keep them from sliding into homelessness.


Of the many entities working to combat homelessness, government is uniquely positioned to know more and do more to end homelessness. The treasure trove of data that is available to the government is a precious and underutilized resource. Pulling together information from across agencies provides the full picture of the challenges and needs of an individual or a family. We now have evidence, from case studies and research, that it’s possible for agencies to use these insights to stop homelessness before it happens.

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