The document outlines a framework for effective data storytelling, emphasizing the importance of origination, data diving, story weaving, and impact. It discusses key elements including ideation, data collection and analysis, narrative crafting, design choices, and communication strategies. The case-study approach provides examples and encourages readers to create their own data stories for impactful communication.

1. Data Storytelling for Impact
A Case-Study Approach to Best Practices for
Successful Data-Driven Communication

2. Outline
● Why Data Storytelling?
● The Framework
● Examples
● Your Data Stories

3. Why Data Storytelling

6. Framework

7. Anatomy of a Successful Data Story
● Origination
● Data Diving
● Story Weaving
● Impact

8. Origination

9. Origination
● Ideation: Where did the idea come from? When was the
'aha' moment for the project?
● Resolve: When, and how, did the decision get made to
move forward with the project?
● Target Impact: What was the ultimate public or
organizational impact, or impacts, that the project intended
to make?

13. Data Diving

14. Data Diving
● Data Collection: What was the source of the data? How
was the data collected? What unexpected challenges or
opportunities arose during the data collection process?
● Data Analysis: How was the data analyzed? Who did the
analysis?

17. Storyweaving

18. Story Weaving
● Narrative: How were insights drawn from the data? How
was the narrative crafted? What were the narrative goals?
● Design: Is the data portrayed visually? Narratively? Both?
What were the formats of the end product, and why?
● Press: How was the story communicated to the press?
Unintentionally? Methodically?

21. Impact

22. Impact
● Launch: How was the story ultimately launched?
● Response: What was the impact of the story?

25. Examples

31. Your Data Stories

32. Thank you!