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The Visual Organization

Phil Simon
June 13, 2014
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The Visual Organization

The era of Big Data as arrived but, on many levels, most organizations are woefully unprepared. Far too many enterprises erroneously believe and act like nothing has really changed. As such, they continue to depend exclusively on reporting stalwarts like Microsoft Excel, static dashboards, basic query applications, and even traditional business intelligence tools. And they are missing out on tremendous opportunities.

Amidst all of the hype and confusion surrounding Big Data, though, a new type of enterprise is emerging: The Visual Organization. A relative handful of organizations has realized that today's ever-increasing data streams, volumes, and velocity require new applications. In turn, these new tools promote a different mind-set--one based upon data discovery and exploration, not conventional enterprise "reporting."

For instance, Netflix builds cutting-edge dataviz tools to better understand its 40 million customers. And it's hardly alone in its innovative use of new data visualization technologies. Employees at Autodesk use a remarkable and interactive tool that visualizes current and historical employee movement. From this, they can identify potential management issues and see what a corporate reorg really looks like. Through cutting-edge dataviz, startup Wedgies instantly serves up real-time poll results while monitoring poll traction and site issues. The University of Texas is bringing a visual type of transparency to academia. It makes unprecedented amounts and sources of institutional data available on its website. Anyone with the desire and an Internet connection can slice and dice UT data in myriad ways. And then there's eBay. Powerful data-discovery tools allow employees to effectively "see" what ebay.com would look like as a brick-and-mortar store.

In The Visual Organization, award-winning author, keynote speaker, and recognized technology expert Phil Simon demonstrates how progressive enterprises have turned traditional dataviz on its head. In their stead, they are embracing new, interactive, and more robust tools that help locate the signals in the noise that is Big Data. As a result, these enterprises are asking better questions and making better business decisions.

Rife with real-world examples and practical advice, The Visual Organization is a full-color tour de force. Simon deftly explains how organizations can do more than just survive the data deluge; they can thrive in it. It is required reading for executives, professionals, and others interested in unleashing the power of their data.

Phil Simon

June 13, 2014
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Transcript

  1. @philsi mon 2 • Award-winning author of eight books, including

    The Visual Organization • Speaker, consultant, and technology expert • ASU professor of technology and analytics • Huge Breaking Bad fan (more on that later) @philsimon 2
  2. @philsi mon 4 • Roughly 48M customers • Nearly $26B

    market cap • Responsible for one-third of all US weeknight Internet traffic Data as of June 9, 2014 @philsimon 4
  3. @philsi mon 5 • 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
  4. @philsi mon 6 • Data should be accessible, easy to

    discover, and easy to process for everyone. Source: Netflix - tinyurl.com/tvo-netflix @philsimon 6
  5. @philsi mon 10 • Dark Suspenseful Sci-Fi Horror Movies •

    Gritty Suspenseful Revenge Westerns • Romantic Indian Crime Dramas • Evil Kid Horror Movies • Visually-Striking Goofy Action & Adventure Films • Violent Suspenseful Action & Adventure Films from the 1980s Source: The Hollywood Reporter @philsimon 10
  6. @philsi mon 11 • The longer you take to find

    the data, the less valuable it becomes. @philsimon 11
  7. @philsi mon 13 50,000 Netflix subscribers watched all 13 episodes

    of Season 4 of Breaking Bad the day before Season 5 premiered. Source: The Hollywood Reporter @philsimon 13
  8. @philsi mon 14 • Whether a dataset is large or

    small, being able to visualize it makes it easier to explain. @philsimon 14
  9. @philsi mon 19 • What they watch • When they

    watch • The device on which they’re watching • When they pause and/or resume watching @philsimon 19
  10. @philsi mon 22 • Eschew “set it and forget it”

    • Encourage data exploration and discovery • Recognize the limitations of reporting stalwarts • Buy and build new tools as necessary
  11. @philsi mon 23 • We must visualize all of the

    data • Only visualize good data • Visualization will always manifest the right action or decision • Visualization will lead to certainty
  12. @philsi mon 25 • Look outside of the enterprise •

    Don’t forget the metadata • Visualize both small and big data • Walk before you run…at least for now
  13. @philsi mon 26 • UX: participation matters • Experimentation is

    paramount • Walk before you run…at least for now • Avoid the “quarterly visualization mentality”
  14. @philsi mon 27 • Transparency is becoming increasingly important •

    All data is not required to begin • Encourage interactivity • Iterate