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Visual Thinking for Design
The field of information visualization is still relatively young. The milestones that mark its history can be listed and briefly described with the exhalation of a single deep breath. Only a few information visualization events today can be anticipated with guarantees of significance, including:
- IEEE’s annual InfoVis Conference, which always provides glimpses of a few new and promising innovations
- Edward Tufte’s seminar, if you’ve never been before, which will encourage you to strive for excellence
- A presentation by Hans Rosling, which will inspire you to use visualization to solve the world’s problems
- A new major release of software from Tableau or Spotfire, which will convince you that visualization can reach a broad audience when properly designed and commercially packaged
Godin’s Silly Rules for Great Graphs
Seth Godin invited a reaction last week when he ventured into unfamiliar territory by publishing a blog post entitled “The three laws of great graphs.”
- One story
- No bar charts
- Motion
He was apparently engaging in a bit of hyperbole—a statement that is intentionally exaggerated for the purpose of making a point—when he listed as one of his rules: “No bar charts.” When Jesus made use of hyperbole to warn that great wealth can lead to corruption—”It is easier for a camel to pass through the eye of a needle than for a rich man to enter into the kingdom of heaven”—I suspect most listeners understood that he was using an exaggerated analogy to make his point. Godin’s spare but sweeping statement, “No bar charts,” however, runs the risk of being taken literally by many who struggle with data presentation, and have an undiscerning appetite for simplistic rules.
Nudge Me Tender, Nudge Me True
Richard H. Thaler and Cass R. Sunstein, both of the University of Chicago, have written a thought-provoking book full of practical suggestions for improving the decision-making process, …
The Brain’s Spam Filter
The June/July 2008 issue of Scientific American Mind includes an article entitled “Your Inner Spam Filter” by Andrew W. McCollough and Edward K. Vogel of the University of Oregon. In it they explain that superior abstract reasoning appears to be related to better use of working memory and that the difference between those who reason effectively and those who don’t might be due to differences in the brain’s ability to filter out information that is not relevant to the task. Research has demonstrated for years that working memory is limited to about four chunks of information at a time. You might be surprised by how little we can hold in working memory, the area in our brains where information is temporarily stored while we’re thinking about something. Better use of working memory’s limited capacity results in better abstract reasoning—the kind of reasoning that handles data analysis. So, the analytical process is improved by the brain’s ability to filter out irrelevant information, a function that works a bit like working memory’s spam filter.
Data analysis software, in an effort to support the process, should eliminate all non-essential content, thereby reducing the need for an analyst’s brain to filter it out. By doing so, …
Google Bullet Graphs
Trevor Lott of www.DealerDiagnostics.com, a service that provides performance reports for auto dealerships, wrote to me recently. Here’s what he said:
I’ve been a fan of your work for several years and have always been impressed with your willingness to share, be it innovations, ideas or feedback. It’s only fitting that I had you in the back of my mind when I was testing the Google Charts API a few weeks ago to explore the potential of the web service to create bullet graphs. I’m happy to report that it’s possible but wanted to take it one step further: to promote bullet graphs and help to increase their accessibility. To that end, I wrote up a quick guide to creating bullet graphs using the Google Charts API. Please consider it a small tribute for what you’ve given to me and the data visualization community over the years.
I appreciate Trevor’s kind tribute—especially the fact that he delivered it in the form of a practical solution to a real need. If you’re interested in producing bullet graphs using Google Charts API, take advantage of Trevor’s fine work, which he’s provided as a simple series of clearly explained steps. You’ll find it in Trevor’s blog.
Handbook of Data Visualization — Good content, but a dysfunctional publishing model
I try to maintain a comprehensive library of books and articles about data visualization, so when I recently read that Springer published a new book entitled Handbook of Data Visualization, filled with chapters from respected experts in the field, I set out to get a copy. Ordinarily, I purchase books for my data visualization library—that is, I pay for them, rather than requesting complimentary desk copies, which are often offered to educators. This book’s $319 price tag, however, discouraged my normal practice. I decided this was an exceptional situation, so I tried to take advantage of my faculty position at the University of California, Berkeley. In response, I was told that I could get a copy to examine, but would have to return it if I decided against using it as a textbook for one of my courses. Once my hands touch a book, they don’t let go, so I tried a different approach. I offered to review the book in my blog, which earned me a copy, and today I am fulfilling my promise.
Last week, I spent many hours ….
A clear signal in the midst of Excel-generated noise
Several months ago I received an email from a fellow named Michael Alexander who wanted my opinion of his technique for producing bullet graphs in Excel. We interacted a bit, and before long Michael mentioned that he was writing his second book for Wiley’s “…for Dummies” series, titled Excel 2007 Dashboards & Reports for Dummies. He asked if I might be willing to write a foreword for the book. I was very honored by his request and indicated my willingness, assuming that I liked what I saw when given the chance to review an advanced copy of the book. Deadlines got in the way of pursuing this plan, which I regret, because I have just read the book and love it.
Michael has managed to do something that’s rare. He has eloquently interwoven the conceptual and technical areas of knowledge that are needed to build effective dashboards in Excel. Technicians often can’t get their heads out of the bits and bytes, and those of a more conceptual ilk often lack technical expertise. Michael has his feet planted firmly in both of these worlds. Technicians often don’t know how to write, but Michael is a refreshing exception to this stereotype as well. This book reads like a conversation.
Unlike most software manuals, this book is rooted in a clear understanding of information—how people use it, why they use it, what really matters to them when they use it, and how to use it effectively. This includes an understanding of data presentation. Michael supports the mission of data visualization evangelists such as Tufte and myself by preaching the gospel of simplicity. He issues clear warnings against the graphical excesses that Excel 2007 encourages. Why? Because it drowns out the clear voice that information needs to tell its story.
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Zen and the Art of Presentation
Garr Reynolds gets it! His new book Presentation Zen demonstrates this fact beautifully. He and I both strive to improve communication, largely through simplicity of design. He once promoted my work in his blog at presentationzen.com (the most visited website on presentation design) and now I have the opportunity to return the favor, without reservation, by recommending his book.
What I strive to do for quantitative data presentation, Reynolds does for presentation in general, especially oral presentations to groups that are accompanied by slides (PowerPoint and Keynote). Presentation Zen is not a PowerPoint manual in the manner of most software books. It isn’t procedural, filled with step-by-step instructions for using features and functions. Rather, it teaches an approach to presentation that is rooted in science, informed by an entire philosophy, and overflowing with common sense that is all too uncommon in presentations today. I want to give you a tiny taste of the wisdom and practical advice that awaits you in this book; just enough to send you to the bookstore with conviction and haste.
As the title suggests, Reynolds finds inspiration for the principles that he advocates in the teachings of Zen:
The principles I am most mindful of through every step in the presentation process are restraint, simplicity, and naturalness. Restraint in preparation. Simplicity in design. Naturalness in delivery. All of which, in the end, lead to greater clarity for us and for our audience.
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Apgar Scores and the Sometimes Unexpected Benefits of Measuring Things
The history of obstetrics is interesting. (Yeah, I know this is a strange opening sentence for a blog about visual business intelligence, but bear with me.) Its history even includes a bit of unexpected intrigue, such as the early history of forceps. Because forceps delivery was so wildly successful for complicated births, the London-based Frenchman who invented the procedure and his family of physicians refused to reveal the technique for three generations, hiding it even from the mothers giving birth through use of a drape, until they passed it on to a physician in Amsterdam who kept it to himself for 60 more years. A particular event in obstetrical history actually has something to teach us about the importance of performance measure, which we can apply to business. It involves something called the Apgar score, which I learned about by reading Atul Gawande’s wonderful book about healthcare, Better: A Surgeon’s Notes of Performance (Metropolitan Books, New York, NY, 2007). You’ll get a flavor of Gawande’s writing in a couple of quotes from the book below.
During the 20 years or so leading up to the 1950s, great progress was made through tighter medical standards and the introduction of antibiotics, especially penicillin, in improving the odds of the mother surviving the delivery. Up until the mid-1930s, childbirth was the single most dangerous event in a woman’s life. By the 1950s, the risk of death decreased from one of every 150 births resulting in the death of the mother, to only one in 2,000. Despite this dramatic improvement, babies still weren’t faring much better than before. One in 30 still died at birth.
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Bullet Graphs for Not-to-Exceed Targets
When I designed the bullet graph back in 2005, I did it to solve a particular problem related to dashboard displays. The graphical widgets that software vendors were providing to display single measures, such as year-to-date sales revenue, consisted mostly of circular gauges and meters, which suffered from several problems. Most of them conveyed too little information, did so unclearly, and wasted a great deal of space on the screen. The bullet graph was my alternative, which was designed to convey a rich story clearly in little space.
Since their introduction, a number of dashboard vendors now support bullet graphs, either as a predesigned display widget or as a display that can be easily constructed using their design tools. Now that bullet graphs are being used a great deal, they are being put to the test, and best practices are being developed to use them effectively.
One challenge that is faced by any graphical display of a single measure compared to another, such as a target, is the fact that the target usually functions as a point that the measure should reach or exceed, such as a sales target, but sometimes it functions as a point that the measure should stay below, such as an expense target. Here is a series of bullet graphs, which are designed in the typical manner:
Two of the measures—expenses and defects—work the opposite of the others in that the goal is to remain below the target. The background fill colors on these bullet graphs, which vary from dark gray to indicate “poor performance” through to the lightest gray to indicate “good performance,” are arranged from poor on the left to good on the right for revenue, average order size, and new customers, but in reverse for expenses and defects. The reversed sequence serves as a visual cue that expenses and defects should remain below the target. This cue, however, is not strong. It would be useful if something that stood out more signaled this difference.
We might be tempted to replace the varying intensities of a single color—in this case varying intensities of gray—with distinct hues, to make the reversal of the qualitative scale more apparent, such as by using the traditional traffic light colors that are so popular on dashboards.
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