Making Data Work For You - The Data Assemblyline
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Transcript of Making Data Work For You - The Data Assemblyline
Making Data Work for You
The Data Assembly Line 5/1/14
Lauren-Glenn Davitian, hostShelagh Cooley, Common Good Vermont
Michael Moser, Vermont State Data Center
1
Logistics
Watch on your computer.
Interaction – We want to hear from you!
Comments and Questions – Chat Box
Slides and Recording Afterwards.
Satisfaction Survey.
2
The Data Assembly Line
Setting the Stage
Data Audit
Data Collection
Data Management
Data Analysis
Data Utilization
3
Setting the Stage
Why is data important?
What results do you seek?
Who is your audience?
How will they use the information?
4
Question Cat
Who is YOUR audience?
5
QuickTime™ and a decompressor
are needed to see this picture.
“I can honestly say that not a day goes by when we don’t use those evaluations in one way or another.”
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Example: Foodshelf
Result: Food security for people in the region.
Audience: Board, funders, policy makers, staff
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PERFORMANCE MEASURESFoodshelf
# Clients Served
lbs. of Food Provided
% Nutritious Food
% Clients Satisfied with food choice
Staff-Client Ratio
# Clients not returning
-after 6 months- after 1 year
% of Clients not returning
-after 6 months- after 1 year
QUANTITY (#) QUALITY (%)
8
Question Cat
Who is YOUR audience?
9
The Data Assembly Line
Setting the Stage
Data Audit
Data Collection
Data Management
Data Analysis
Data Utilization
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Data Audit - PeopleWhat people do you have?
How are they involved?
Do they have “will” & “skill”?
Is it in their job description?
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Data Audit - Data• What data do you already have?
• What data do you need?
• What data is most useful?
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QuickTime™ and a decompressor
are needed to see this picture.
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Data Source Tracking SheetFremework Evaluation
QuestionData Source Indicator
Food How much food do we serve?
Inventoroy # pounds of food/day
Clients How many clients do we serve
Registration Forms #clients/month
Satisfaction How satisfied are clients with the food they receive?
Satisfaction Survey % of very satisfied clients/month
Quality of Food How nutritious is the food?
Receipts to Clients % of Food distributed that is nutritious
Food Security How many clients are food secure after 6 months? 1 year?
# Clients Receiving less than 5 lbs of food per month
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Question Cat
Where do you collect your data from?
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Data Sources
•Calendars: Events, Meals, Clinics
•Internal Databases: Clients
•Attendance Sheets: Youth
•Log Sheets: Services Received
•Surveys: Satisfaction
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Question Cat
Where do you collect your data from?
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The Data Assembly Line
Setting the Stage
Data AuditData Audit
Data Collection
Data Management
Data Analysis
Data Utilization
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Data Collection
Data You Already Collect Data Development Agenda
Data Audit
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Data Collection Value of the Performance Measure
System
Buy-in
Standard
20
Question Cat
What tools do YOU use to collect dat?
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Data Collection Tools
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Benefits of Using Tools
• Reduce human error, increase consistency.
• Standardizing data reduces time “cleaning data”
• Online (remote access for multiple sites).
• Automatic reports and organized data.
• Automatically backed up.
• It’s EASIER!!!
23
Question Cat
What tools do you use to collect data?
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The Data Assembly Line
Setting the Stage
Data AuditData Audit
Data Collection
Data Management
Data Analysis
Data Utilization
25
Data ManagementIs your data secure?
What is your time frame?
Do you have back-ups?
Who is responsible?
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Example of Dashboard
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Data ManagementDon’t mix up your data types.
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PERFORMANCE MEASURESFoodshelf
# Clients Servedlbs. of Food Provided
% Nutritious Food
% Clients Satisfied with food choice
Staff-Client Ratio
# Clients not returning
-after 6 months- after 1 year
% of Clients not returning
-after 6 months- after 1 year
QUANTITY (#) QUALITY (%)
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Data Management Example
January 1-15
January 16-31
January Average
February 1-15
February 16-28
February Average
2008 258 275 266.5 350 375 362.5
2009 245 272 258.5 324 370 347
2010 242 267 254.5 356 368 362
2011 235 265 250 333 362 347.5
2012 222 260 241 332 360 346
2013 216 262 239 313 345 329
2014 224 252 238 310 370 340
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Data Management Example
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Data Management ExampleJanuary 1-15
January 16-31
February 1-15
February 16-28
March 1-15
2008 258 275 350 375 297
2009 245 272 324 370 297
2010 242 267 356 368 279
2011 235 265 333 362 234
2012 222 260 332 360 285
2013 216 262 313 345 262
2014 224 252 310 370 155
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Data Management Example
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Data Management Best Practices1. Training2. Buy-In3. File Naming4. Security Practices5. Code Book
34
Stretch Break
Send in Your Questions!
35
The Data Assembly Line
Setting the Stage
Data AuditData Audit
Data Collection
Data Management
Data Analysis
Data Utilization
36
Analyzing the Data
Remember, who is your audience?
How often will the data be analyzed?
Time Series vs. Non-Time Series Data
37
Example of Survey Monkey
38
Trend Lines
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The Data Assembly Line
Setting the Stage
Data AuditData Audit
Data Collection
Data Management
Data Analysis
Data Utilization
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Data Utilization
Decision Making
Fundraising
Community Building
Education
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Data Utilization
Convene your audience.
What story does the data tell?
Are we achieving the results we want?
What will we do differently?
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Why Visualize Data?
“A picture is worth a thousand words”
Higher Engagement from audience.
Broader audience.
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Examples of Visualization
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Examples of Visualization
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Example of Visualization
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Sources: http://thegrio.com/2013/06/07/hunger-in-america-food-insecurity-disproportionately-affects-african-americans/#s:foodinsecurity2
http://www.vtfoodatlas.com/plan/chapter/4-1-food-security-in-vermont
Percentage
Food Insecurity
Very Low Food
Security1999-2001 9.1 1.82001-2003 8.9 32003-2005 9.5 3.92005-2007 10.2 4.62007-2009 13.6 6.22009-2011 12 5.4
Infographic Example:-Simple-Key information is highlighted-Effective Messaging
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Visualizing Data Tools
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Rules to Live By
Continue to adapt & improve measures
Learn from others
Be willing to invest if the information has value to you.
Keep it Simple.
Be realistic & practical
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Assembly Line Not Automatic
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PERFORMANCE MEASURES
HOW MUCH ARE WE DOING?
HOW WELL ARE WE DOING IT?
HOW WELL ARE WE DOING IT?
HOW WELL ARE WE DOING IT?
QUANTITY (#) QUALITY (%)
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PERFORMANCE MEASURESAfterschool
# Youth served
# Hours of Programming (academic vs. non-
academic)
# of Enrichment activities
% High Quality Interaction
% Youth Satisfaction
% Parent Satisfaction
Staff-youth Ratio
# Youth Honor Roll
# Youth 90% School Attendance
# Youth leading activities
% Youth Honor Roll
% Youth with 90% School Attendance
% Youth leading activities
QUANTITY (#) QUALITY (%)
52
PERFORMANCE MEASURESMental Health
# Clients Served Size of Waiting list
Average time to next appointment
# of Clients in school or working
# of Clients into institutional care
# of Clients to less restrictive care
% of Clients in school or working
% of Clients into institutional care
% of Clients to less restrictive care
QUANTITY (#) QUALITY (%)
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Upcoming Events
Let’s Talk Shop: Regional Mixers - Brattleboro 6/19
Leadership Vermont Luncheons-Burlington 5/21-Brattleboro 6/20-Barnet 10/1
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ResourcesIdealware http://www.idealware.org/ Helping Nonprofits Make
Smart Software Decisions
Youtube Video: How to Add a Trend Line in Excel: https://www.youtube.com/watch?v=svFSKnmAlKQ
An Introduction to Regression Analysis: Alan O. Skyes: http://www.law.uchicago.edu/files/files/20.Sykes_.Regression.pdf
CGVT Know More, Do More with Data Visualization http://blog.commongoodvt.org/2013/10/video-storytelling-with-data/
CGVT Surveys and Spreadsheetshttps://www.cctv.org/watch-tv/programs/making-data-work-you-
survey-spreadsheets
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References
Trying Hard is Not Good Enough, Mark Friedmanhttp://resultsleadership.org/product/trying-hard-is-not-good-
enough-by-mark-friedman/
Essentials of Utilization-Focused Evaluation (Sage, 2012) by Michael Quinn Patton
Edward Tufte, Data Visualization: http://www.edwardtufte.com/tufte/index
American Evaluation Association – Tools, Tips, Trainings http://www.eval.org/
Also, check out courses offered at area colleges.
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