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Using Analytics to Address Disparities in Housing Displacement

Rajiv Desai | December 8, 2022

4 Minute Read

analytics to address disparities in housing displacement - image of houses next to a graph

Data is the most powerful tool local leaders have for battling disparities in housing displacement. With good data, it’s possible to map the risk of displacement in a community and direct resources to the people who need them most.  

Data analytics can help local leaders spot trends in eviction filings, and assess any racial disparities in those filings. Analytics can reveal where rents are increasing, so local leaders can take steps to mitigate the impacts of gentrification. They can even show where affordable housing units are in shortest supply, so cities can put policies in place to preserve existing affordable units, and to build more.  

Without this data and the tools to analyze it, it’s impossible to make sound policy decisions, and manage local housing programs efficiently and effectively. But many local governments don’t yet have the tools to gather good data on housing in their communities, or put it to use to prevent housing displacement.

Fortunately, collecting and analyzing this data is fairly straightforward with the right software platforms for managing housing programs.  

Here are a few ways local governments across the country can use analytics to address disparities in housing displacement.  

How Analytics Can Help Gentrifying Communities 

Gentrification is the driver of a tremendous amount of housing displacement. As wealthier residents begin moving into neighborhoods that have historically been home to middle and lower-income people, median rents and property taxes increase, making it difficult for longtime residents to afford to stay in the neighborhood.  

Often, the people who lose their homes due to gentrification have deep roots in the community. When they’re forced to move, they may be pushed far away from their work, family members, and friends, extending their commute times and cutting them off from social support.  

If local leaders want to prevent this kind of displacement, a good system to analyze gentrification patterns is essential. It’s easier to mitigate the worst impacts of gentrification when you can catch the trend early; once the change is visible on the street, it may be too late.  

A centralized rental registry provides a database of rental prices in a neighborhood, and using the right software platform, city and county leaders can quickly translate this data into easy-to-read charts and graphs. Then the early warning signs of rising rents and gentrification are easy to visualize and take action on.  

When a neighborhood begins to show the signs of gentrification, local leaders can act to increase the supply of affordable housing, preserve the affordable housing that already exists, and put tenant protections in place that protect residents from unfairly being pushed out of their homes.

Taking steps like these proactively is essential; once the pattern of gentrification and displacement is deeply ingrained, it’s much harder to shift.   

The right municipal software solution also creates a lifeline between residents facing displacement and their local government. More cities are rolling out “virtual city halls” for taking care of municipal needs, like paying a parking fine or making a report to 311—but these tools can be used to address housing issues as well.

Residents can also turn to their city’s virtual city hall for information about tenant protection programs, housing assistance, and community groups that can help them remain in their homes through tenant organizing, legal support, and other resources.

With this type of digital solution in place, it’s much easier to use analytics to uncover insights such as which services are most searched for or used, and by who. 

Even for citizens who are impacted by the “digital divide” and have limited access to these online resources, making more city services available online can help free up in-person support for the residents who need it most.  

Learn more about how new digital tools are narrowing the digital divide in many cities 

How Analytics Can Address Racial Disparities in Evictions 

Evictions are an area where stark racial disparities in housing displacement are evident.  

For example, Black renters are about twice as likely as white renters to be evicted. Some of this disparity can be explained by economic factors. The impacts of systemic racism have created a racial wealth gap that makes falling behind on rent more likely for Black renters, and harder to overcome.

Black households on average have lower incomes, less money in savings, and fewer resources to draw upon (such as family and friends) when they hit a financial rough patch. All of these factors can make eviction more likely.  

But, some of the racial disparity in evictions cannot be explained by economic factors. Reporters have documented that some landlords are up to four times more likely to file eviction cases against Black renters who fall behind than against white renters in similar circumstances.  

This pattern reveals housing discrimination, and is highly damaging to Black communities. It’s also a pattern that’s difficult to spot without a good eviction management system (EMP).  

An effective EMP can help prevent unjust evictions by: 

  • Creating a centralized hub to track all eviction filings in a community and the affected residents, then analyzing the data so program managers can easily spot suspicious patterns, like a disproportionate number of eviction cases against non-white tenants.  
  • Gathering and preserving all of the documentation required for each eviction, including communication between renters and landlords. This can help tenants who choose to fight their eviction in court defend their right to remain in their homes. 
  • In cities and states with a Just Cause Eviction law, EMPs also document the landlord’s stated reason for evicting the tenant, so program managers can verify that it is a legal reason.  
  • Deters illegal or “self-serve” evictions and tenant harassment that disproportionately targets non-white renters, especially in gentrifying communities.   

Using Analytics to Preserve 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. Unfortunately, that is the case in many cities and counties throughout the country.

The problem affects non-white residents disproportionately, as they spend a greater share of their income on housing than white residents and are more likely to be housing cost burdened.  

Local officials can take steps to build new affordable housing and to preserve existing affordable units in their communities — but only if they have good data about where affordable units are and where they’re at risk.  

Collecting information about a neighborhood’s rental prices is the first step in preserving affordable housing there. A preservation database allows city workers to gather data about where affordable units are located, what program they were created under, if any, when their affordability requirements expire, and even when affordable buildings are listed for sale.

The right platform will make it easy to visualize this data and spot units that are at risk, so local leaders can target their interventions where they’re needed most.  

Analytics for Strong Communities 

Housing stability has enormous benefits, from helping children perform well in school, to reducing financial stress on families, to keeping people close to their work and their social support.

It’s important that everyone in the community gets to experience these benefits, especially residents who are already facing economic hardship. That’s why many local leaders are interested in using analytics to address disparities in housing displacement.  

To learn more about the digital tools that can help cities ensure stable housing for every resident, check out this guide