Visualizing Progress: How Do We Translate Data?

One of the most important advances in the effort to end homelessness has been the shift toward evidence based, data-driven practices.  This requires analyzing large swaths of data from HMIS, HUD, and other related sources to see what efforts are actually moving the needle.   

That’s an awful lot of information to try to explain to anyone: a board member, a reporter, a policymaker, or just about anyone else that isn’t a researcher. And while complex spreadsheets might capture the data effectively, they’re poor tools for explaining what the data means. 

One of the most effective ways of communicating this kind of information is through data visualization. 

What is A Data Visualization? 

A data visualization is simply a representation of data in a graphical way.  Visualizing data means viewing the information in formats like bar charts, density maps, tables, scatter plots, tree maps, and even using interactive tools such as data dashboards or data stories.   

We use data visualizations for a variety of reasons.  Most importantly, they save the reader time.  Data sets of all sizes can be simplified to an easily understood image that gets processed by the brain more quickly than a narrative or series of numbers.  For example, they can make trends — like the implications of a system change — easier to spot, by showing them in the right type of charts. 

In recent years, more communities have embraced visualization of homelessness data.  This trend will only continue, and the visualizations will improve as the developers in the field hone their skills.  These visualizations provide a multitude of benefits in the world of homelessness data, including:  

  • Easily monitoring progress for each person in a caseload 
  • Viewing trends in lengths of stay and exits to permanent housing 
  • Easily seeing if the system is reducing homelessness in the community
  • Determining if the average length of time homeless is decreasing 
  • Understanding how many people return to homelessness after being housed 
  • Proving efficacy of housing programs like Rapid Re-Housing and Permanent Supportive Housing 

The Alliance’s Approach 

At the National Alliance to End Homelessness, data visualization is critical creating a more comprehensive State of Homelessness report.   

For example, the map below can show you overall homelessness or homelessness among a sub-population, and how many people were homeless by state.  It also can show the percentage change from last year or from 2007 (the first year of point-in-time data available).  At a glance, one could easily see the highest concentrations of homelessness are in California and New York.  Simply changing the “Population Filter” drop-down menu to “People in Families” changes the view; now the highest concentration for this group is just New York.   

Another visualization available in that same map allows the viewer to see which state made the most progress toward ending homelessness since 2007.  By selecting “Total Homeless” for the “Population Filter” and “Percent Change from 2007” for the “Count or % Change Filter” it quickly becomes clear that Michigan has made a 70% decrease in their overall homeless population since 2007.   

Writing narrative for all the possibilities in that one interactive map visualization would take many pages of text.  The visualization saves the viewer large amounts of time, and helps keep them engaged on the most important shifts and trends.  

A Vision for Data 

The future of our mission relies on using data to make informed decisions. Using well designed, thoughtful visualizations to help make those decisions will be an enormous help to every community who chooses to embrace it. 

Let Us Know What You Think 

The Alliance is continuously working to improve the State of Homelessness.  For this, we need your help. Does it inform your work?  How can it better serve your needs? Please share your thoughts by filling out our online survey.