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How to Combat Homelessness Using Better Data

Rajiv Desai | August 17, 2023

4 Minute Read

Homelessness is a complex and pervasive issue that affects millions of individuals worldwide. It's a problem that's often viewed as insurmountable, with its roots deeply embedded in a myriad of socio-economic factors. However, housing agencies must still seek to find effective solutions. The question then arises: How do we tackle such a multifaceted problem? While there is no single solution, learning to leverage data can make a substantial difference.

Data has become an invaluable resource in understanding and addressing societal issues. When it comes to homelessness, modern data analytics capabilities are able to uncover insights that humans simply wouldn’t always notice on their own. By harnessing these insights, we can develop targeted strategies to combat homelessness more effectively.

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Understanding the Scope of Homelessness Through Data

The first step in combating homelessness is understanding its extent and nature. This includes data on the number of homeless individuals, their demographics, and their reasons for homelessness. For instance, data can reveal that a significant portion of the homeless population in a certain area is made up of veterans, indicating a need for targeted support services for this group.

Predictive Analytics for Prevention

One of the most powerful applications of data analytics in combating homelessness is predictive analytics. By analyzing various data points such as eviction rates, unemployment levels, and cost of living, we can identify individuals who are at risk of becoming homeless before they lose their housing.

For example, San Diego County has implemented a policy that uses predictive analytics to prevent homelessness. The system uses multiple data points to identify individuals who may be at risk of becoming homeless and offers various forms of support to these individuals.

Addressing Racial Disparities in Evictions

Data analytics can also help us address racial disparities in housing displacement. For instance, data has shown that in many areas Black renters are about twice as likely as white renters to be evicted. By tracking all eviction filings in a community and analyzing the data, we can spot troublesome patterns, like a disproportionate number of eviction cases against non-white tenants. This can help prevent unjust evictions and address housing discrimination.

Mitigating the Impacts of Gentrification

Gentrification often leads to housing displacement. As wealthier residents move into neighborhoods that have historically been home to middle and lower-income people, rents and property taxes increase, making it difficult for longtime residents to afford to stay.

By analyzing gentrification patterns, we can catch the trend early and take steps to mitigate its impacts. A centralized rental registry can provide a database of rental prices in a neighborhood, and the right software platform can translate this data into easy-to-read charts and graphs, making it easier to visualize and act on early warning signs of rising rents and gentrification.

Preserving Affordable Housing

Widespread housing displacement happens when the number of affordable housing units in a community is lower than the number of people who need an affordable place to live. Local officials can take steps to build new affordable housing and to preserve existing affordable units in their communities — but only if they have reliable data about where affordable units are and where they’re most at risk. 

A preservation database can help gather data about where affordable units are located, what program they were created under, when their affordability requirements expire, and even when affordable buildings are listed for sale.

Using Data to Supplement Existing Strategies to Combat Homelessness

When you have the data available to recognize those most in need of assistance, you can use one of several housing strategies at your disposal. Notice that within each of these, there are even more opportunities to leverage data, as we explain.

Offering Rapid Rehousing

Rapid rehousing aims to reduce the time a household experiences homelessness, to reduce the negative effects of prolonged homelessness. This method might involve assistance with rent and move-in costs as well. Data tools can help identify those most in need of rapid rehousing by analyzing factors such as length of homelessness, family size, and vulnerability to health risks. Predictive analytics can also help identify those at risk of becoming homeless, allowing for preventative rapid rehousing efforts.

Providing Permanent Supportive Housing

This strategy offers long-term rental assistance and supportive services to the most vulnerable community members suffering from chronic homelessness. Data tools can be used to track the effectiveness of these programs, identify areas where more supportive housing is needed, and understand the specific needs of the population being served.

Educating More Young People

Something as simple as a high school diploma can make a huge difference on whether someone ends up experiencing homelessness. State and federal grants can help provide assistance to those in need with everything from assistance with education costs and transportation to helping with residency and guardianship issues.

You can leverage data tools to identify youth at risk of homelessness, track their progress through educational programs, and evaluate the effectiveness of these programs. For example, data can reveal patterns in school attendance, performance, and dropout rates among homeless youth, helping to prioritize interventions more effectively.

Creating More Career Opportunities

Financial uncertainty is a major predictor of housing hardship, and there are funding opportunities to create employment options for low-skilled workers. Using data tools, you can better understand the employment needs of the population, track their progress through job training programs, and evaluate the effectiveness of these programs. For example, data can reveal patterns in employment rates, income levels, and job retention among those who have been through job training programs.

Expanding Healthcare Access

Experiencing a major health issue or chronic condition can be financially debilitating for those without insurance, and frequently creates a path to job loss and loss of housing. Data can be used to understand the health needs of the homeless population, track their use of healthcare services, and evaluate the effectiveness of healthcare programs. For example, data can reveal patterns in health outcomes, hospitalization rates, and access to healthcare among the homeless population.

Next Steps to Combat Homelessness

As we navigate the complexities of homelessness, it's clear that data is more than just numbers on a screen. Data acts as a compass guiding us towards more effective strategies, or a spotlight illuminating the unseen corners of an immensely complicated issue. It represents a tool that, when wielded with care and understanding, can transform lives and communities.

In this journey towards a world without homelessness, every step counts. One such step is developing strong tenant protection programs, using data tools and other modern technology. We invite you to delve into this topic with our free tenant protections guide. This resource is designed to show you how you can more efficiently support your tenant protection programs, reducing the odds that your city’s residents face housing loss.

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