1. Translating Data for Community Planning
Dawn Gilman, Changing Homelessness
Margaret Palmer, CSH
Kimberly Schmitt, All Chicago
Colleen Velez, CSH

2. Welcome and Introductions
Translating Data for Community Planning
Dawn Gilman, Margaret Palmer, Kimberly Schmitt, Colleen Velez
Welcome and Introductions
[Colleen leads]

3. Agenda and Today’s Aim Aim:
Translating Data for Community Planning
Dawn Gilman, Margaret Palmer, Kimberly Schmitt, Colleen Velez
Agenda and Today’s Aim
Aim:
Communities will learn how they can utilize existing data for homeless system planning
HMIS system leads will generate ideas on how to develop techniques to translate data for CoC leadership so that it can be used for planning
HMIS Leads and CoCs will learn how to best partner together in order to increase and investment in homeless system planning
Agenda:
[Colleen leads]

4. Activity: Using Data within Day-to-Day Decision-Making
Translating Data for Community Planning
Dawn Gilman, Margaret Palmer, Kimberly Schmitt, Colleen Velez
Activity: Using Data within Day-to-Day Decision-Making
During an average day, what are examples of how you use data within your decision-making during work? Next, what are examples of how you use data within your decision-making during your free time?
According to the 2015 Annual Homeless Assessment Report (AHAR), “Nine in ten homeless people in families with children were staying in shelters (185,824 people). Only 20,462 people in families were counted in unsheltered locations on a single night in January 2015.”
How do you think you could present this data to your community’s school system in a way that could impact its decision-making in its efforts to alleviate family homelessness within the community?
[Margaret]
Activity:
After I finish describing our activity on using data within day-to-day decision-making, turn to the person next to you, briefly tell each other your names, agencies you work for, and decide who will answer the questions within the first bullet point on the slide first. This first person will have one minute to talk through his/her responses with his/her partner. After the minute is up, the second person will talk through his/her responses with his/her partner. If you’re in a group of three, please make sure everyone in the group has at least a little time to respond.
The first question I’d like for you to respond to is: during an average day, what are examples of how you use data within your decision making during work? For example, you might generate a report showing that a grant’s match is currently 10% less than the funder’s required percentage, so you begin discussions within your agency about how underutilized resources could potentially be accessed.
Next, provide examples of how you use data within your decision making during your free time. For instance, when purchasing items online I seek out items with the highest customer ratings and have second thoughts about purchasing items that don’t have any reviews yet.
Alright, now please turn to the person next to you and begin.
[Make an announcement when about 1 minute has passed. Then announce when time is up]
Now that you’ve had some time to talk through examples of how you and your partner use data within your day-to-day decision making, I’d like you to take a couple of minutes discussing the question posed within the second bullet point on this slide.
The slide provides data to consider: According to the 2015 AHAR, “Nine in ten homeless people in families with children were staying in shelters (185,824 people). Only 20,462 people in families were counted in unsheltered locations on a single night in January 2015.”
The question posed is “how do you think you could present this data to your community’s school system in a way that could impact its decision-making in its efforts to alleviate family homelessness within the community?” Keep in mind, how you present this data could differ based on a number of factors – for example, if you’re sharing it with a school social worker versus a new school principal who may have limited knowledge of homelessness.
Okay, now please turn to the person next to you and begin.
[Make an announcement when a couple of minutes has passed that time is up]
Thank you. I’d like to hear some responses to the question posed. Can someone please let me know what you and your partner discussed on how you think you could present this data to your community’s school system?
[Allowing for responses]
Thank you for participating in this activity. I wanted us to set the context for how data is used every day, from small to big decisions, which really shows that how we present this data for others can potentially impact their decision making and ultimately impact our communities’ plans to alleviate homelessness.

5. Defining What We Mean By Translating Data for Community Planning
Dawn Gilman, Margaret Palmer, Kimberly Schmitt, Colleen Velez
Defining What We Mean By Translating Data for Community Planning
Method of translation: Use of data translation techniques like dashboards, scorecards and other graphics to make the data digestible for planning purposes
Outcome: Having a common language and understanding in terms of data
[Margaret]
Our exercise broke out how we use data within our decision-making and how we present data to others may look differently depending on factors such as familiarity with homelessness. To get to a point where we are able to ensure stakeholders within CoCs are making decisions that positively impact our community, we absolutely have to think about the methods we use to communicate the data so that it’s very clear how they can take action.
This is essentially what we mean by translating data for community planning. We should make sure we have a common language and understanding in terms of the data. The methods we use to get to that common understanding are our translation techniques – methods like using data dashboards, scorecards, and other graphics that make the data digestible.

6. Identifying Why Translating Data is Important
Translating Data for Community Planning
Dawn Gilman, Margaret Palmer, Kimberly Schmitt, Colleen Velez
Identifying Why Translating Data is Important
Sharing data is identified within the federal strategic plan to prevent and end homelessness, Opening Doors, as part of a strategy to accomplish the aim of increasing leadership, collaboration, and civic engagement
To assist mainstream system providers unfamiliar with a community’s homeless crisis response system with understanding how they currently and could potentially have impact
Understanding the needs of individuals and families who are homeless is pertinent for a CoC to develop a plan coordinating implementation of a housing and service system
Efforts to improve planning by effectively translating data ultimately means there is an aim to benefit individuals and families experiencing homelessness
[Margaret]
Importance: to HUD/federal entities - One of the aims identified within the federal strategic plan to prevent and end homelessness, Opening Doors, is to increase leadership, collaboration, and civic engagement. Use this to finish notes for this item:
Importance: to mainstream system providers – how they fit, ie fire department example
Importance: to providers within the system
Continuum of Care planning. The Continuum must develop a plan that includes:
(1) Coordinating the implementation of a housing and service system within its geographic area that meets the needs of the homeless individuals
Importance: to clients who are homeless

7. Example of When Data Translation Techniques Could Be Beneficial
Translating Data for Community Planning
Dawn Gilman, Margaret Palmer, Kimberly Schmitt, Colleen Velez
Example of When Data Translation Techniques Could Be Beneficial
“Active” Lists: A real-time, up-to date list of all people experiencing homelessness, which serves as a means to deepen the understanding of homelessness at a local level as well as supports communities’ planning efforts for reducing and ending homelessness
Consider what data translation techniques communities are/could be using that can lead not only to stakeholders’ understanding of the active list data, but also to developing ideas on how to take action
[Margaret]
As a lead up to hearing in-depth about data translation occurring within communities from Kim and Dawn….Communicate the data so that it’s very clear how our stakeholders can take action…
What is an “Active,” “By-Name,” or “Master” List?
A real-time, up-to date list of all people experiencing homelessness
Can be filtered by categories like Veteran status, common assessment score, chronic status, etc.
Allows communities to know every person experiencing homelessness by name
Facilitates community decisions around where to appropriately house individuals experiencing homelessness
Can be used to measure progress toward system goals
Importance of Using Lists
Serves as a means to deepen understanding of homelessness at the local level
Supports communities’ planning efforts for reducing and ending homelessness
Improves collaboration through case conferencing meetings among entities working to house individuals on the lists
Provides communities with the ability to track exits from homelessness
Allows for measuring community goals and performance

8. Community Experiences of Data Translation for Planning
Translating Data for Community Planning
Dawn Gilman, Margaret Palmer, Kimberly Schmitt, Colleen Velez
Community Experiences of Data Translation for Planning
[Colleen leads]

9. Changing Homelessness Jacksonville, Florida
Translating Data for Community Planning
Dawn Gilman, Margaret Palmer, Kimberly Schmitt, Colleen Velez
Dawn Gilman
Changing Homelessness
Jacksonville, Florida

10. Kimberly Schmitt All Chicago Chicago, Illinois
Translating Data for Community Planning
Dawn Gilman, Margaret Palmer, Kimberly Schmitt, Colleen Velez
Kimberly Schmitt
All Chicago
Chicago, Illinois

11. Chicago Ending Veteran Homelessness Initiative (EVHI)
Translating Data for Community Planning
Dawn Gilman, Margaret Palmer, Kimberly Schmitt, Colleen Velez
Chicago Ending Veteran Homelessness Initiative (EVHI)

12. Chicago Ending Veteran Homelessness Initiative: The Data
Translating Data for Community Planning
Dawn Gilman, Margaret Palmer, Kimberly Schmitt, Colleen Velez
Chicago Ending Veteran Homelessness Initiative:
The Data

13. Veterans Remaining Housed:
Translating Data for Community Planning
Dawn Gilman, Margaret Palmer, Kimberly Schmitt, Colleen Velez
Veterans Remaining Housed:
Initial Housing Project or Subsidy Type and Disability

14. Veterans Remaining Housed:
Translating Data for Community Planning
Dawn Gilman, Margaret Palmer, Kimberly Schmitt, Colleen Velez
Veterans Remaining Housed:
Initial Housing Project or Subsidy Type and CH Status

15. Translating Data into Action Tools:
Translating Data for Community Planning
Dawn Gilman, Margaret Palmer, Kimberly Schmitt, Colleen Velez
Data
Review
Discussion
Action
Assessment
Translating Data into Action Tools:
Continual Process for System Improvement
Start: Effectively understand data and use it to take action
Middle: Data becomes the mechanism for system change
End: Reassess impact of actions and further review data

16. Effectively Understand Data and Use it to Take Action
EVHI Leadership Team:
Effectively Understand Data and Use it to Take Action
Translating Data for Community Planning
Dawn Gilman, Margaret Palmer, Kimberly Schmitt, Colleen Velez

17. Spreadsheet to EVHI Leadership Team Tool
Translating Data for Community Planning
Dawn Gilman, Margaret Palmer, Kimberly Schmitt, Colleen Velez
Spreadsheet to EVHI Leadership Team Tool
300 in 30 Days Project
Home for the Holidays Event
290 Veterans enrolled in RRH and awaiting housing
256 Veterans enrolled in RRH and awaiting housing

18. HMIS Project Level Data to EVHI Leadership Team Tool
Translating Data for Community Planning
Dawn Gilman, Margaret Palmer, Kimberly Schmitt, Colleen Velez
HMIS Project Level Data to EVHI Leadership Team Tool

19. HMIS Project Level Data to Team Data Analysis
Translating Data for Community Planning
Dawn Gilman, Margaret Palmer, Kimberly Schmitt, Colleen Velez
HMIS Project Level Data to Team Data Analysis

20. Translating Data for Community Planning
Dawn Gilman, Margaret Palmer, Kimberly Schmitt, Colleen Velez
HMIS Project Level Data to Team Data Analysis to Community Action Items
EVHI leadership should communicate to Providers and Veterans the effectiveness of Rapid Rehousing and encourage them to consider available units as a viable housing option for the Veterans they are seeking to place.
EVHI should continue with its current efforts to accelerate the move-in process to PSH while simultaneously respecting Veterans’ choice.
When Veterans choose to stay with friends and family for a “permanent tenure,” EVHI and Providers should develop a systematic process to work directly with families and friends to ensure their readiness to house the client.
Building on this initial descriptive analysis, UL, All Chicago and selected EVHI community team members should develop a more sophisticated risk assessment tool to predict how likely a Veteran is to return to homelessness. The EVHI prevention work group will convene a case conferencing meeting to focus on early identification of Veterans at risk of returning to homelessness.

21. Translating Data for Community Planning
Dawn Gilman, Margaret Palmer, Kimberly Schmitt, Colleen Velez

22. Discussion Translating Data for Community Planning
Dawn Gilman, Margaret Palmer, Kimberly Schmitt, Colleen Velez
Discussion
[Colleen leads]

23. Activity: Identifying Data Translation Challenges and Solutions
Translating Data for Community Planning
Dawn Gilman, Margaret Palmer, Kimberly Schmitt, Colleen Velez
Activity: Identifying Data Translation Challenges and Solutions
Purpose: To hear from you the challenges you’ve experienced with translating data within your community as well as to hear what you have already implemented or think would be good strategies to improve the effectiveness of translating data ultimately impacting homeless system planning.
Instructions: A series of questions will be posed to the group. For each question, we want to hear from as many of you as possible.
One person talk at a time
Please limit your comment to 1 minute max
No one gets a second turn until everyone else has had a chance
[Colleen]
Note: depending on how much time we have left at the end – could give X # of minutes for audience to respond to each question

24. Translating Data for Community Planning
Dawn Gilman, Margaret Palmer, Kimberly Schmitt, Colleen Velez
Questions:
What are the major challenges in translating data for providers/CoC leadership so that it can be used for planning?
What are solutions you’ve developed or could develop to address these major challenges?
What is one way you’ve successfully used a technique to translate data for providers/CoC leadership?
After today’s session, what is one way you will translate data in a new way to a person or entity important to homeless system planning within your community?
[Colleen]

25. Questions? Translating Data for Community Planning
Dawn Gilman, Margaret Palmer, Kimberly Schmitt, Colleen Velez
Questions?
[Colleen leads]

26. Translating Data for Community Planning
Dawn Gilman, Margaret Palmer, Kimberly Schmitt, Colleen Velez
Contact Information
Dawn Gilman
Kimberly Schmitt
Chief Executive Officer
System Implementation and Training Manager
Changing Homelessness
All Chicago
Margaret Palmer
Program Manager
Colleen Velez
CSH
Senior Program Manager
x2818