1. Data Walk
Directions:
Get a “Data Walk” handout, form a trio, review data, and answer questions on the handout
Data Sources:
Washington Department of Commerce
Census
US Department of Housing and Urban Development

2. Not Your High School Math: Using Data To Improve Homelessness Services
2017 Conference on Ending Homelessness
May 10, 2017

3. Welcome Presenters: Sarah Cotton Rajski, Building Changes
Kathie Barkow, Aspire Consulting LLC
Ian Kinder-Pyle, Department of Commerce
Data Support:
Talia Scott, Department of Commerce
Welcome: Kathie
Each introduce selves

4. Workshop Results At the end of the workshop participants will:
Understand how to use data to inform program design
Understand the value of prioritizing people from place not meant for habitation (unsheltered)
Have a framework for developing strategies to increase the number of unsheltered served in their community
Kathie
Results
Call to action: What we know about making improvements is about knowing where you are headed. The context for today is:
All unsheltered people in Washington State are served and get access to housing.
WHY this call to action to increase understanding value of prioritizing people from place not meant for habitation

5. Call to Action
All unsheltered people in Washington State are served and get access to housing

6. Ideas About How To Use Data
Data walk = tool to engage
Data informs program design and strategies
Disaggregation of data reveals disparities
“BAD” = best available data
Role of data quality
Sarah
A few other comments about data…
- data quality
- HUD priority

7. Checking In How familiar are you with data walks?
How useful is the data set?
How familiar is this? (show with thumbs) (pivot, few examples possibly)
How useful is this data set?
L/F: What would be more useful is county specific data, program specific data

8. Credit
Work comes from the Annie E Casey Foundation, Results-Based Leadership Programs
development/leadership-development/
Data tables extracted by Commerce

9. Adopting Baseline Whole Population History Current
WHAT IF NOTHING CHANGES?
This is the progression of the trend line if we don’t do anything. It’s what we expect to see with no intervention. Would we be satisfied with the result?
Whole Population
History
Current

10. Setting Target Whole Population History Current
WHERE DO WE WANT TO BE BY WHEN?
This question supports leaders to identify targets for the results work.
The degree of desired change.
The criteria for choosing the target.
The time period.
Whole Population
Where are we?
History
Current

11. Adopting Baselines and Setting Targets
WHERE ARE WE NOW? Establishes the baseline to guide the work and measurement of progress.
Trend line to the current moment
Questions to consider
What does the available data say about what is happening relative to the result we want to achieve?
How extensive are the problems we aim to solve?
What populations are affected most?
Whole Population
Where are we?
History
Current

12. Unsheltered Data
17% 2014
22% 2015
24% 2016
Target 35%
24%

13. Unsheltered Data by Race

14. Shift to County-Level Discussion
Conversation is … How is your county doing?
Above or below 35% for 2016?
Where you think you are now midway through 2017? (project)
Considering you have to increase by 10 percentage points next year … what will you do?

15. Unsheltered Data, by County
Adams
43%
Klickitat
33%
Asotin
31%
Lewis
22%
Benton
15%
Lincoln 8%
Chelan
13%
Mason
18%
Clallam
17%
Okanogan
Columbia
16%
Pacific
24%
Cowlitz
Pend Oreille 9%
Ferry
San Juan
Franklin
Skagit
27%
Garfield
Skamania
Grant
34%
Stevens
Grays Harbor
Thurston
21%
Island
Wahkiakum 2%
Jefferson
Walla Walla
King
26%
Whatcom
29%
Kitsap
Whitman
Kittitas
Yakima
35%

16. Map your County Trend Line
TARGET
History
Projection
Whole Population
Current
History
Current
Projection

17. Story Behind the Curve Story behind the curve and story behind the gap
To analyze the FACTORS that affect the trendline
To inform the change ideas
To inform selection of STRATEGIES
(based on evidence & best practice)

18. The Importance of Factors
If we conduct specific actions, then we expect specific changes will happen.
Factors inform decision making
We decide what to do “more of” and what to do “less of” or “do differently” in our actions.
Digging Deep: Ask yourself WHY
It’s important to get under “automatic explanation” and get to underlying factor, below the surface.

19. Getting to the Story Behind the Data Through Factor Analysis
Factors decreasing trend (restricting)
Whole Population
Factors increasing trend (contributing)
History
Projection
Current

20. What you can identify as factors?
What is driving down? (restricting)
What is driving up? (contributing)

21. Using Targets to Develop Strategies
Considering you have to increase by 10% next year … what to do?
Take a minute and write two strategies and be clear about which factor(s) they address

22. Targeted Universalism: Universal Goals/Targeted Strategies Mapping and Closing the Gap
Whole Population
Targeted Sub-Population
History
Projection
Current

23. Role of Targeted Strategies
Is it Better? Same? Worse? Story behind data?
Factors decreasing trend (restricting)
Factors decreasing trend (restricting)
Factors decreasing trend (restricting)
Whole Population
Target Population
Factors increasing trend (contributing)
Factors increasing trend (contributing)
Factors increasing trend (contributing)
History
Current
Projection
Maybe Call out a system example and a race example??
History
Current
Projection
History
Current
Projection
Whole Population
Target Population
Combined Population

24. Unsheltered Data by Race

25. Targeted Strategy Brainstorm
Revisit strategies and consider if there is an appropriate targeted strategy

26. A Few Ideas for Targeted Strategies
Hire staff/peers that reflect population served
Go to encampments more frequently that are comprised of overly represented populations
Ensure language access
Ensure cultural competence
Assess use of peers in program or outreach
Examine neighborhoods where housing is being offered from the lens of its racial composition
Build on multigenerational or extended family housing strategies where appropriate

27. Recap of Process Pick the data point you want to look at
Collect multiple years of data in order to create a trend line
Consider the direction of the trend line and where you want it to go; set a target
Brainstorm the factors that move the trend line in both directions – ideal to do this with partners
Brainstorm the factors that move the trend line in both directions for disproportionately affected groups
Pick one priority factor
Develop strategies to address the factor
Repeat to track progress

28. Call to Action
All unsheltered people in Washington State are served and get access to housing

29. Sarah Cotton Rajski Building Changes | Senior Manager 206. 805
Sarah Cotton Rajski Building Changes | Senior Manager o| c Kathie Barkow Aspire Consulting LLC | Principal c
For data, reach out…
CHG lead agency
And/or HMIS licensees.