Your SlideShare is downloading. ×
Introducing The Visual Organization
Upcoming SlideShare
Loading in...5
×

Thanks for flagging this SlideShare!

Oops! An error has occurred.

×
Saving this for later? Get the SlideShare app to save on your phone or tablet. Read anywhere, anytime – even offline.
Text the download link to your phone
Standard text messaging rates apply

Introducing The Visual Organization

608
views

Published on

An overview of my sixth book, The Visual Organization: Data Visualization, Big Data, and the Quest for Better Decisions

An overview of my sixth book, The Visual Organization: Data Visualization, Big Data, and the Quest for Better Decisions

Published in: Education

0 Comments
2 Likes
Statistics
Notes
  • Be the first to comment

No Downloads
Views
Total Views
608
On Slideshare
0
From Embeds
0
Number of Embeds
6
Actions
Shares
0
Downloads
0
Comments
0
Likes
2
Embeds 0
No embeds

Report content
Flagged as inappropriate Flag as inappropriate
Flag as inappropriate

Select your reason for flagging this presentation as inappropriate.

Cancel
No notes for slide

Transcript

  • 1. @philsimon 1 Introducing The Visual Organization Phil Simon philsimon.com
  • 2. Who am I? @philsimon 2 • Award-winning author of six books • Speaker, consultant, and technology expert • Huge Breaking Bad fan (more on that later)
  • 3. @philsimon 3
  • 4. Netflix Stats • Roughly 40M customers • Nearly $27B market cap • Responsible for nearly one-third of all US weeknight Internet traffic @philsimon 4 Data as of March 3, 2014
  • 5. Netflix Facts • Single biggest AWS customer – 2012 Christmas day outage • In September of 2013, Netflix became the first non-TV network to win an Emmy for House of Cards @philsimon 5
  • 6. @philsimon 6
  • 7. The Netflix Data Credo - 1 • Data should be accessible, easy to discover, and easy to process for everyone. @philsimon 7 Source: Netflix - tinyurl.com/tvo-netflix
  • 8. 77,000 Subgenres of Movies • Dark Suspenseful Sci-Fi Horror Movies • Gritty Suspenseful Revenge Westerns • Romantic Indian Crime Dramas • Evil Kid Horror Movies • Visually-striking Goofy Action & Adventure • Violent Suspenseful Action & Adventure from the 1980s @philsimon 8
  • 9. The Netflix Data Credo - 2 • The longer you take to find the data, the less valuable it becomes. @philsimon 9
  • 10. Example @philsimon 10
  • 11. Stats 50,000 Netflix subscribers watched all 13 episodes of Breaking Bad Season 4 on the day before Season 5 premiered. @philsimon 11 Source: The Hollywood Reporter
  • 12. The Netflix Data Credo - 3 • Whether a dataset is large or small, being able to visualize it makes it easier to explain. @philsimon 12
  • 13. @philsimon 13
  • 14. @philsimon 14
  • 15. @philsimon 15
  • 16. @philsimon 16
  • 17. What does Netflix know about each of its 40M streaming customers? • What they watch • When they watch • The device on which they’re watching • When they pause and/or resume watching @philsimon 17
  • 18. • He with the most data doesn’t win. • In an era of Big Data, success hinges on what an organization does with that information. @philsimon 18
  • 19. Story Behind the Book @philsimon 19 How do we make sense of all of this data?
  • 20. @philsimon 20 Today data and dataviz are everywhere.
  • 21. @philsimon 21
  • 22. A Tale of Two IPOs @philsimon 22
  • 23. @philsimon 23 • The visual consumer • The visual employee • The visual government • The visual citizen • The visual journalist • The visual athlete It’s not just organizations… @philsimon 23
  • 24. The Visual Consumer @philsimon 24
  • 25. The Visual Athlete @philsimon 25
  • 26. The Visual Athlete @philsimon 26
  • 27. Visual/Data Journalists @philsimon 27
  • 28. Where are all of the dataviz case studies? @philsimon 28
  • 29. @philsimon 29 Source: Google, 08.31.2013
  • 30. @philsimon 30
  • 31. @philsimon 31
  • 32. Characteristics of a Visual Organization • Eschew “set it and forget it” • Encourage data exploration and discovery • Recognize the limitations of reporting stalwarts • Buy and build new tools as necessary @philsimon 32
  • 33. Dataviz Myths • We must visualize all of the data • Only visualize good data • Visualization will always manifest the right action or decision • Visualization leads to certainty @philsimon 33
  • 34. Lessons from the book • UX: participation and experimentation are paramount • Walk before you run • Avoid the quarterly visualization mentality @philsimon 34
  • 35. Lessons from the book • Transparency is becoming increasingly important • All data is not required to begin • Iterate @philsimon 35
  • 36. @philsimon 36
  • 37. Connect with me www.philsimon.com @philsimon Book out now @philsimon 37