Homesafe
A service intervention to mitigate the unhoused crisis in California
Category
Service Design
Role
Research & Strategy
Team
Jayesh Jain, Uditsingh Thopte
Overview
Our group was tasked to choose a systemic issue and design an intervention to help solve it. As recent transplants to San Francisco, we were disturbed by the unhoused crisis we witnessed. Thus, we designed for the unhoused crisis in California.
After 2.5 months of desk research, mapping actors and diagraming systems flows, we created a service intervention that streamlines data and services between providers for unhoused. We also suggested policy changes to boost housing supply.
My Contributions
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Research - Performed in-depth desk research and analysis, looking at policies, laws, statistics and trends on the local, state and national levels.
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Concept Development - White boarded and co-developed solutions by mapping interactions, timelines and services between stakeholders
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Writing - Synthesized our solutions in two 10+ page reports.
Solution
“Homesafe” is a plan that involves changing relationships between service providers, reducing gaps in providing services, and modifying policies on the local and state level to increase affordable housing supply. At the heart of the intervention is an improved unhoused tallying system taken twice per year, whose timely and detailed data is used to better pair the unhoused with short-term to long-term services. In parallel, the plan increases affordable housing stock by extending project Homekey - a successful program that incentivizes landlords to use vacant properties for housing - and by modifying the construction review process to eliminate needless delays due to NIMBYISM and some environmental regulations.
Rather than inventing new components within the system or simply contributing more funding to a problem that has received more than $13 billion in the last three years, it instead simplifies and streamlines relationships between existing actors.
Access our comprehensive, final report HERE.
The Prompt
For Systems class, our professor prompted us to investigate a systemic issue and design a solution for it. We initially decided to focus on homelessness in the United States. It seemed to be a "wicked" problem that we were increasingly perplexed by. We had questions:
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How can such a wealthy nation not ensure basic living standards?
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Why is it worse in some places than others?
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Who and what are contributing to it?
Exploratory Research
First we needed to gain a shared understanding of the forces involved in causing and perpetuating homelessness in the U.S. This was crucial we all had different lenses and biases around the phenomenon. We decided to compare four U.S. states (NY, TX, FL, CA) who have had different successes with mitigating it and lie across the political spectrum. We also examined healthcare and addiction and how that may exacerbate homelessness.
My contributions:
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Mapped our assumptions on homelessness
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Synthesized data from reports on homelessness in 4 U.S. states
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Mapped healthcare and addiction services in relation to homelessness
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Identified homelessness risk factors against socioeconomic trends and policies
The Big Picture
From our research, we came to understand three major causes of homelessness: racism, drug abuse, and lack of affordable housing (there are many more). There are also different categories of homelessness (i.e. sheltered, temporary, etc.). We used the "iceberg model" to explore the causes and categories within the system of homelessness. This helped us identify the intervention points within the system.
We ultimately decided to focus on California for our project for its extremes: it is the state with the highest number of unhoused at 40.9 per 10,000 individuals, yet has spent massive amounts on quelling it (13 billion within 3 years, to be exact).
Zooming in on Affordable Housing Supply
After several weeks of desk research of mapping the forces involved with homelessness (and the differing opinions on those), we decided to investigate the dynamics of the affordable housing supply. Why? Our research pointed to it being a particularly strong factor in the unhoused crisis in California.
I helped:
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Perform contextual inquiry around policy and economy on housing
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Analyze public policies on different levels and how they affected solutions
Affordable Housing Supply
There is an affordable housing shortage in California. According to a Little Hoover Commission report, home builders there would have to construct 220,000 housing units every year for the next two decades to meet demand. And there are many reasons for this shortage:
Regulations and Zoning
- The Discretionary Review process slows down new project permit approvals
- California’s Building Standards Code requires new buildings to be energy efficient, driving up prices
- Bills favoring single-family zoning
Delayed Construction
- The California Environmental Quality Act (CEQA) delays a construction project by avg. 2.5 years.
- Both high and low-income residents have different reasons to push back on construction for affordable housing (NIMBYism)
Higher Cost of Living
- Since 2012, rents in CA have risen by 13%, compared to 8% nationally (PPIC)
- Incomes are not keeping up with cost of rent, so a cascade effect happens where high-income residents push out lower-income residents from the housing market
Mapping Actors and System Behaviors
We had to understand how the affordable housing supply system behaved and who was involved in order to find the easiest leverage point to make change within the system. Through research we found environmentalists, landlords and local residents to be significant actors within the system, whose relationships had both an immediate and long-term influence on affordable housing supply in California. Why? State-specific environmental building codes, vacancy incentives, and construction processes prevented timely supply of affordable housing.
My contributions:
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Mapped out actors and feedback loops based on affordable housing supply
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Analyzed policies on the local and state levels affecting housing supply
The System's Behavior
We created a systems map around affordable housing supply in California, including feedback loops, to see at a glance who and what are affecting it, and how. In the map, we see that there are pushes and pulls on affordable housing stock by different actors. We detailed these findings on the actors, housing stock, and the overall state of homelessness in California in our preliminary report here.
Developing Concepts around Constraints
We wanted to design an intervention that was grounded in real constraints: politics, funding, time, and actor relationships. So, we focused on the easiest leverage points: improving data collection, closing policy loopholes, and expanding low-cost incentives that have proven effective. Acknowledging that homelessness is both an immediate and long-term challenge, we created phases with the most pressing issues being addressed first.
My contributions:
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Synthesized reports from different perspectives on policy fixes with regards to funding and political feasibility
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White-boarded solution space with teammates
Modifying Existing Programs
While doing research, I found that two programs were often cited for their influence on reducing homelessness: California's tallying system, and Project Homekey. Because of their importance, our intervention relied heavily on them.
Tallying System
Currently, the state of California carries out a yearly “Unsheltered Point-in-Time (PIT) Count and Surveys” to determine the number of unhoused people and various data. This is undertaken by 44 California Continuums of Care (CoCs), which are collectives of service providers across sectors. There are many shortfalls: it's performed infrequently, data is inconsistent and out of date, it doesn't account for different categories of homelessness, and more. That's why our solution proposes more regular and detailed data capture.
Project Homekey
In 2018, there were more than 1.2 million vacant homes in California. Recognizing this, California launched “Project Homekey” that provided grants for building owners to convert their existing structures into temporary and permanent housing for the unhoused. In 2021, the program successfully housed over 8,000 individuals at nearly 1/3 the cost per unit of building new. Unfortunately, this program was set to end in May 2022, which is why our solution proposes an extension of this project.
Mapping the Changed System's Behaviors
Our intervention essentially meets gaps: gaps in estimating services and gaps in housing supply. We mapped our intervention's intended feedback loops to ensure these gaps were fixed.
My contributions:
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Researched services and providers
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Sketched hypothetical feedback loops on different actors and services
Mapping Service Flows
Our intervention aimed to close gaps by simplifying information flows and relationships between providers. So, we diagrammed the service and information flows by phase to help us see where there would be potential bottlenecks and pushbacks.
My contributions:
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Defined the actors and exchange of services between them
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Analyzed bottlenecks to help simplify relationships
Final Thoughts
Considerations
Privacy around unhoused individuals' demographic data is a concern, as is assuming that individuals would willingly disclose it. The data gathering method would be the next aspect to investigate and design around since it poses the highest risk to the intervention's success. Our intervention also grossly assumes that all individuals will comply with the temporary and permanent housing placements.
What I would change
Primary research. I would have talked with the actors in our intervention (NGOs, government entities, developers, and unhoused individuals) to gain insights rather than rely strictly on desk research. I would also eliminate the hosting aspect of phase 3, since that would need to involve additional government sectors that I did not consider.