The document discusses the process of transforming real stories into data, and then how that data can be revitalized back into compelling narratives and visualizations. It argues that effective storytelling in non-profits relies on understanding the historical context, current struggles, and impactful events, as well as advocating for the use of visual mediums like infographics and videos to engage audiences. It emphasizes the importance of maintaining a connection to the 'why' behind the data while navigating through its abstraction levels.

1. Data is boring.
Stories are not.

2. Modus Operandi
The “How?”
Must Come From
The “Why?”
Purpose ----> Method

3. Stories Become Data Becomes Stories Become Visuals
• A large number of real stories get aggregated
• Aggregated stories are abstracted into data
• Data is then analyzed and revitalized as stories
• “A picture is worth...”
Data lets us look at1,000,000 stories at once
(and sort them)

4. Example: APBA Baseball

6. Data Becomes Data Disks!
=

7. Hidden Data = More Story, Less Data!

8. “Abstraction”
• Each level assumes the previous so we can have
greater capacity: Gain Power, Lose The Details
{endorphins + fresh air + (“Can I grow this at home? = “True”) = “motivation”;
vitamins+(pancreas - sugar)+(“Are Doritos a vegetable?” = False) = “nutrition”;
chard + turnips + ladybugs + dirt = “gardens”;
(sasha + tobias + samwell + charleston) = “youth”;
[(youth + gardens) = (nutrition + motivation)]}
=
“grant pitch”

9. Drill Down: Abstractions and Levels of Data
what is this? do you care?

10. Who Cares?

11. Visual Story > Data

12. A Single Event : The Data of One

13. Levels of Data
1. A Single Event
2. Data as 1,2,3 Story
3. Standard Data 4. Behind the Curtain

14. Consumers of Data
Everyone
Potential Supporters
Current Supporters Auditors, Employees

15. Show All Three
1. Single,
Powerful Events 2. Show Some 3. Put it in a
Data (1,2,3) story

16. Non-Profit Data Becomes a Story
The Plot
history.
struggle.
your work.

17. Data Becomes a Story
In 1950, few people
history.
attended college.
Now it is expected,
struggle.
but crazy expensive.
We lower costs and
your work.
improve quality.

18. Your Turn : Think of Three Pieces of Data
1. Consider the
historical context
for your work
2. What is the
current struggle
your are work to
address?
3. In the scope of
history and this
struggle: What are
you doing?

19. Visualization = Another Abstraction
Gaining power! ...but Losing Detail.
Seize the power, but give a nod to all levels:
- Single Events
---> Data
---> Data-Stories
---> Visualizations

20. Visualizing Data-Stories : Icons
Icons give data a visual signifier

21. Visualizing Data-Stories:
info-graphics
free-for-all mash-up
of events, data, stories,
icons, etc.

22. There are not enough good info-graphics
There are a lot of bad info-graphics
Make one.

23. Data-Stories are
best told...

24. On Video.

25. Internet Videos = ...?

26. ...Online Giving

27. There are not enough good non-profit videos
There are a lot of bad non-profit videos
Make a great one.
It’s easy.
Every organization
should have one.

28. How to make a great data-story video for less
1. Find this guy:
Talented, young
video artist.

29. How to make a great data-story video for less
2. Get your most creative person and your
best data person to team up and write an
epic script; find $1000.

30. How to make a great data-story video for less
3. Animate and Share.

31. The Whole Story:
1. The “How?” comes from the “Why?”
2. Real events become Data
3. Data becomes stories
4. Know what the audience cares to know
5. Stories tell the history, struggle and your work.
6. Be cognitive of the abstractions, see the details
7. Never get too far from the “Why?”
8. Embrace the abstractions and visualize AMAP.
9. The Web demands concise visualization
10. Use Icons; make Info-graphics
11. Small screens are made infinite by... Video
12. Make a video for $1000

32. saxifrage school chalkboard video
http://vimeo.com/34760137