Data Visualization, Big Data, and the Quest for Better Decisions – a Synopsis

the-visual-organizationYou’re time starved, right? So, in my never-ending effort to help you with an overflow of TL;DR things you were supposed to read, here’s my synopsis of a synopsis of a book by Phil Simon.

(Book image credit.)

Simon is an author, advisor, speaker, and thought leader. It says so right on his LinkedIn page. But before you judge him harshly, please consider the valuable service he provides. His job is making sense of things you don’t have time to study, research or assimilate.

Synopsis of a synopsis? That’s right. Pay close attention so you don’t lose track of how content whirls about the Innertubes these days:

This article pulls the salient points about Simon’s book from the Harvard Business Review review of a webinar featuring Simon talking about his book, sponsored by Teradata. If the word “derivative” comes to mind, then you are in the right room.

If you’re interested in Simon’s book, you should simply buy it.

If you’re not sure… read on.

Netflix Data Jones

Simon uses Netflix as a prime example of a company that gets data and its use “to promote experimentation, discovery, and data-informed decision-making among its people.”

Netflix focuses its analytics prowess on studying the connections between customers and content: You are what you watch. A month-to-month subscriber business model does not depend on you forgetting to check your contract; they have to make solid recommendations. It’s easy to buy a subscription, binge-watch all of House of Cards, and then cancel, so they have to be really good at matching individuals to relevant content.

They know a lot about their customers.

For example, the company knows how many people binge-watched the entire season four of Breaking Bad the day before season five came out (50,000 people). The company therefore can extrapolate viewing patterns for its original content produced to appeal to Breaking Bad fans. Moreover, Netflix markets the same show differently to different customers based on whether their viewing history suggests they like the director or one of the stars.

Netflix also buys data and metadata from brokers. No surprise. As a result, “Netflix can be confident that its original programing will be popular without needing to invest in 100 pilots to yield one well-liked show (as networks must) because it knows what customer segments will likely be watching.”

Visualization to the Rescue

The crux of their analytics is the visualization of “what each streaming customer watches, when, and on what devices, but also at what points shows are paused and resumed (or not) and even the color schemes of the marketing graphics to which individuals respond.”

While Netflix believes in data accessibility and all employees are encouraged to experiment, visualization lets more employees quickly sift through large amounts of data. Drag-and-drop is much easier to fathom and teach than SQL.

You need to become a visually oriented organization if you “realize that the world is constantly changing and that a data visualization tool that worked five years ago may not be the most effective tool
for today.”

You can be successful as a visually oriented organization if you “realize that (Excel) is mainly reporting software; it doesn’t encourage discovery as data visualization tools do.”

You can stay ahead of the curve as a visually oriented organization if you “buy and build new tools as necessary.”

You will not do well as a visually oriented organization if you believe:

  • “All data must be visualized.” If visualization is a hammer, remember that not all data are nails.
  • “Only good data should be visualized.” Sometimes quick and dirty is revealing.
  • “Visualization will always manifest the right action or decision.” Critical thinking is not going away soon.
  • “Visualization will lead to certainty.” You can torture data to say anything and you can make visualizations look like the Mona Lisa if you like.

Don’t forget to:

  • “Look outside of the enterprise for relevant data.” There’s more data in heaven and Earth than dreamt of in your internal databases.
  • “Don’t forget the metadata. Data about data can be extremely revealing.”
  • “Visualize both small and big data.” Customer segmentation can be vital, so don’t get caught up in only looking at the big stuff.
  • “Walk before you run.” Boiling the ocean takes time.
  • “Participation matters.” You’ve got to get people to use a variety of tools to find out which ones are working for them.
  • “Experimentation is paramount.” Like most things in life, this takes time to get the hang of much less master.
  • “Avoid the ‘quarterly visualization mentality.'” Discovery is key. Reports are not.
  • “Transparency is increasingly important.” “Knowledge is power,” does not mean hoarding information. It’s all about collaboration.
  • “All data is not required to begin.” You’ll never have all of it anyway. “Not having it all is no reason not to get started.”

And finally, when you can, take the time to read the whole book. The organization you save may be your own.

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