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The Visual Organization: Data Visualization, Big Data, and the Quest for Better Decisions (Wiley and SAS Business Series) Hardcover – March 24, 2014
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Q&A with Phil Simon, author of The Visual Organization
Why did you write The Visual Organization?
Jim Barksdale, former CEO of Netscape, once famously said, “If we have data, let’s look at data. If all we have are opinions, let’s go with mine.” I love that quote, and it’s in the book. Barksdale is probably happy right now. Today more than ever, professionals are being asked to argue their cases and make their decisions based on data. A new, data-oriented mind-set is permeating the business world. Blame or credit Google or Nate Silver. For instance, journalists, drycleaners, and football teams today are representing data in interesting ways, a subject I’ve discussed frequently on my blog and with colleagues and clients. Next, I believe that the book fills a vacuum. I reviewed many of the current books on data visualization. While enormously helpful, they tend to be how-to books. As such, they emphasize theory over practice. The title of my book is no accident: I am unaware of an existing text that examines how actual organizations, departments, and people have used contemporary dataviz tools to move the needle. This is particularly true with dataviz. As I discovered researching The Visual Organization, there aren’t too many original, insightful, and vendor-neutral case studies on the topic. This is a big problem. Far too many business books lack case studies—and suffer as a result. When done right, case studies can be enormously helpful, as they provide real-world business context and valuable lessons. The Visual Organization takes a “show me, don’t tell me” approach. Finally, and this is a purely selfish reason, I enjoy the writing process. At the end of months and months of work, it feels pretty good to hold your book in your hand.
Is The Visual Organization similar to your last book, Too Big to Ignore: The Business Case for Big Data? And how does it different from other data visualization books?
There’s definitely a bit of overlap, but these are very different books. Too Big to Ignore serves as a what I believe is a useful and jargon-free overview of a very important subject: Big Data. I detail the most prominent technologies, applications, and tools. Among the most important questions that book answers is, “How are organizations finding the signal in the noise that is Big Data?” That’s a really big question, one that necessitated much more breadth than depth. As such, Too Big to Ignore provides overviews of Hadoop, NoSQL, different statistical methods, natural language processing, data visualization, and other Big Data tools. Many books have been—and are being—written about each of those technologies. The Visual Organization is different on two fronts. First, it is much deeper than it is wide. Second, it is unlike existing dataviz books by Nathan Yau, Stephen Few, and Edward Tufte. The Visual Organization is fundamentally about how progressive organizations today are using a wide array of dataviz tools to ask better questions of their data–and make better business decisions. With a data-friendly mind-set, companies like Netflix, Wedgies, eBay, the University of Texas, and Autodesk are garnering amazing insights into their operations, users, customers, products, and employees.
You start the book with the story of the Tableau IPO? What did it signify to you?
In short, the arrival of The Visual Organization. Think about it. One year after the Facebook IPO bombed, Tableau’s stock skyrocketed 63 percent. Here is a company that does one thing: dataviz. That’s it. I found the contrast to the Facebook IPO riveting, not to mention endemic of a much larger trend.
You write about the recent proliferation of dataviz tools. Can you elaborate here?
IBM Cognos, SAS, and other enterprise BI stalwarts are still around, but they are no longer the only game in town. Today, an organization need not spend hundreds of thousands or millions of dollars to get going with dataviz. These new tools have become progressively more powerful and democratic over the last decade. Long gone are the days in which IT needed to generate reports for non-technical employees. They have made it easier than ever to for employees to quickly discover new things in increasingly large datasets. Examples include Visual.ly, Tableau, Vizify, D3.js, R, and myriad others.
Yeah, but don’t most organizations already “do” dataviz?
Sure, to some extent. A simple Excel graph or chart certainly qualifies as rudimentary dataviz, but it’s unlikely to promote true data discovery. Many of the interactive dataviz tools I discuss in the book are far better suited for this critical type of exploration.
More generally, many CXOs are paying lip service to Big Data—and the importance of data in general. In my view, though, relatively few are truly harnessing its power. Of course, there are exceptions to this rule. I’d include Amazon, Apple, Facebook, Google, Twitter, and Netflix, among others. If you peel back the onion, you’ll see that employees these organizations are doing a great deal more than creating simple graphs, bar charts, and pivot tables. Employees here are interacting with their data, learning new things about their businesses in the process. That’s a major theme of the book.
Any advice on becoming a visual organization?
Buy and read the book. All kidding aside, remember the famous words of Peter Drucker: Culture eats strategy for breakfast. Tools matter, but an organization’s culture often plays a bigger role in its success. The same is true here.
Also, it’s a marathon, not a sprint. Sure, there’s low-hanging fruit. Remember that Google, like Rome, was not built in a day.
From the Inside Flap
Top Customer Reviews
The formal way visualization methods are assessed is in experiments with control groups, that is: out of any possible real context. These tests mainly focus on perception and memory. But information visualization is a complex media, a communication channel, a new writing, a one that goes way beyond techniques to convey specific numeric values and help memorize them. Those approaches are equivalent to assess a book by the reading quality of its font. Yes, with a very bad font the book can be ruined and a reader won’t understand, enjoy or memorize a thing; but you don’t asses a book solely by the font it uses. Another metaphor: imagine evaluating a tennis player solely by her mental and physical conditions, but not taking into account her performance on the court!.
As a visualization professional, I was long expecting lecture material about the real life of visualization: how it’s being used within organizations, which are the success and the failures cases, how complex a visualization should be in order to be innovative and compelling without generating fears, etc… I need that guide to help me delivering the best possible results to my clients.
Phil Simon did the job: he knocked doors at several companies (not all opened) and made the right questions. The Visual Organization is a book that reveals at least two important facts: 1. companies, regardless of their size, need to incorporate data to survive, and visual tools could be of great help, if not required, 2. this is not an easy step: the market of data science and visualization tools is a mess, and a company needs to research a lot and probably try different solutions. The book is definitively of great help for a company that wants to become a visual organization: Phil describes four levels that serve as a map to make consistent steps towards that goal.
I missed in the book more specific information. Except for a few remarkable cases, I was eager to know more about the specific visualization methods, how they work, how they were used, when they failed and succeeded and why. A book with such a degree of detail would be 1800 pages long, and, on another hand, the book provides you the necessary information to further investigation. I expect Phil will continue filling the hole in the water, and that others will follow his lead. Meanwhile, The Visual Organization is a must for visualization professionals that are concerned about how their projects perform in real life, and for companies that want to become more data(visual)-driven.
The book is relatively expensive -- $28.50 for the Kindle edition, as I type this -- but it's a very well-structured and readable resource on a hot topic domain.
The Visual Organization succeeds in its wealth of case studies and examples, which Simon uses to structure his arguments. His examples show how data visualization best practices can benefit businesses from the leanest startups such as micro-pollsters Wedgies to industry giants such as Netflix and AutoDesk.
Simon spends the first half of The Visual Organization establishing the worth of a visual organization and the second describing how to get there. While his central thesis gets bogged down by a largely abstract chapter on a four-level visual organization framework, The Visual Organization’s case studies, tips, tricks, and debunked data viz myths keep the book interesting from start to finish.
Overall, The Visual Organization succeeds in describing how businesses can harness the power of Big Data through data visualization. Simon’s storytelling-based approach easily clarifies complex business issues and keeps the book light and easy to read. The Visual Organization should find plenty of fans as data visualization goes beyond buzzword and into the mainstream.
This is an abridged and edited version of the review I published for Visually - [...]
The key, as he describes it, is to present data in visual form, which can help represent large quantities in a way taht lends itself to understanding. Dataviz, as Simon puts it, is the way to make the intangible more concrete and intuitive.
Netflix serves as one example, taking masses of streaming information and using them to capture key relationships. Much of this, of course, does not show up on a visual dashboard at all, much less call for humans to scan, spot, reflect, and decide. It all goes on without becoming visual at all -- which indeed is the power behind not only Netflix but amazon and many others. It is by bypassing the need for visual examination that these companies transform big data into effective decisions.
In sum, the principles here -- how to capture data in visual format for better decisions -- is a useful next frontier in the way that organizations generate and capture data. The Visual Organization is very readable and useful guide through the promises of big data, and can be usefully applied for making decisions that are smarter and more timely.