If you’ve been reading this blog regularly for awhile, you know that I occasionally bemoan the sad state of most information graphics (infographics). Most of the folks who produce infographics lack guidelines based on solid research. In their attempt to inform, describe, or instruct, most of the infographics that I’ve seen fail-many miserably. I’m thrilled to announce, however, that a new book is now available that takes a great step toward providing the guidelines that are needed for the production of effective infographics.

If you were to browse the books in my library, you would soon discover that it’s easy to tell which I like the most: they’re the ones that have a large number of pen marks in them-mostly lines to delineate passages as important, with occasional checks and asterisks, along with annotations. If you flipped through my new copy of Visual Language for Designers: Principles for Creating Graphics that People Understand by Connie Malamed, you would see lines and notes on almost every page. Its contents are important, interesting, spot on, and beautifully expressed.

Visual Language for Designers: Principles for Creating Graphics that People Understand,
Connie Malamed, Rockport Publishers, Inc., 2009

Malamed is a cognitive scientist, artist, and educator. As such, she recognizes the need for infographics to be designed with an understanding of what actually works, based on empirical research. She proposes design principles that have emerged from an understanding of how the eyes and mind function, drawn from research in the fields of visual communication and graphic design, learning theory and instructional design, cognitive psychology and neuroscience, and information visualization. If the folks who produce infographics read this book and follow the scientifically-based principles that it teaches, they will move the field of infographics to a new level of usefulness.

This book is a great foundation on which to build more specialized principles for the design of effective infographics. To extend and deepen these guidelines beyond the general principles that Malamed has synthesized from related fields, the field now needs research that focuses on infographics in particular. Organizations that claim expertise in infographics and “visual thinking” should encourage this research, in part by reaching out to universities and other research organizations.

Visual Language for Designers is affordably priced: only $40 for a large hardbound book, printed in color. For this we can thank Rockport, the publisher of a growing body of work on graphics. Unfortunately, the paper that Rockport chose is a bit too glossy, which causes light to reflect off the pages into the reader’s eyes, making clear viewing of images a bit difficult at times. Using paper with a matte finish works better, which is a practice that Rockport should consider.

The only downside of the book’s contents is that some of the examples of infographics fail to effectively illustrate Malamed’s informative text. Malamed chose to illustrate each concept and principle using existing information graphics that were produced by others. Although this works most of the time, this approach fails at times to illustrate her points as clearly and specifically as possible. In some cases this might be because good examples don’t exist. In others, the examples fail because they include too much visual complexity to clearly feature the point that Malamed is trying to illustrate. In several cases Malamed could have illustrated her points more effectively by creating her own illustrations, specifically designed for the task. Several examples in the book fail in minor ways, but a few fail altogether. Despite the examples that fall short, many are wonderful examples of well-designed infographics. For instance, the well-crafted work of Nigel Holmes is prominently featured through the use of several examples.

It’s interesting that Malamed used examples only to illustrate the right way to design infographics. I believe the book’s ability to instruct would have benefited from the use of poor examples as well-examples of the common mistakes that are often made, which undermine effectiveness. Knowing the mistakes to avoid, understanding why they don’t work, and learning to recognize them in actual practice is a big part of learning effective design. In several of the examples that are included, mistakes can be found, but Malamed misses the opportunity to point them out.

If you design infographics, by all means buy this book, read it, put its principles into practice, and keep it handy for occasional review. Malamed has provided a wonderful resource for infographic design that is sorely needed. I suspect that Visual Language for Designers will become a classic. If it doesn’t, the field of infographics may continue to produce a great many ineffective displays.

Take care,

You’ve probably noticed that my approach to writing, both in general and especially when reviewing software, is not typical. I write in the first person, referring to myself as “I,” rather than as some unidentified voice or indirectly as “the author.” I want you to feel as if I’m speaking to you and I want to take full responsibility for everything that I say.

When I talk about products, even when reviewing them negatively, I refer to them and their makers by name. This includes individuals, such as Andrew Cardno of Bis², the creator of this company’s new Super Graphics, which I reviewed in the edition of the Visual Business Intelligence Newsletter that was published today. I don’t do this to make it personal—it is personal, and I choose to acknowledge the fact. It’s too easy to hide behind indirect references, pretending that products are made by abstract entities called companies. Real people are behind the products. Real people are behind marketing campaigns. Real people are behind every decision that’s made in a company. I believe that if I know who these people are, I should acknowledge them, not only when speaking favorably but unfavorably as well. I believe that, however difficult and at times painful, this is an act of respect, much like looking a fellow directly in the eyes when talking to him.

Just as governments are improved by transparency, by holding politicians and other decision makers liable for their acts, the business intelligence industry likewise benefits when we put faces on the organizations and products that comprise it. We should take responsibility for our work and our decisions. When we screw up we shouldn’t hide behind obfuscations such as “mistakes were made.” When we disagree with one another, we should face one another directly and argue our positions. No matter what the cost, if we care about this industry, we should always state the truth as we know it, not what’s convenient or self-serving. When a company makes false claims, we shouldn’t excuse those claims as “marketing,” as if that somehow justifies deceit. Lies and products that don’t work are toxic. Given the sad track record of the business intelligence industry to deliver on its promise, it’s no wonder people are wary. Our industry will benefit from honesty, directness, a personal sense of responsibility, and, of course, from products, services, and opinions that are actually worthwhile. Not only worthwhile to ourselves but especially to those who rely on those products, services, and opinions. This is the “next generation BI” that I’d like to see—not new jargon to reanimate tired old ideas, but real solutions that help people make sense of information, present it clearly, and use it to make wise decisions.

Take care,

I try to read every new book that’s written about data visualization. This is possible because the field is still represented by a relatively small number of experts who take the time to write books. The most recent addition to my library is Howard Wainer’s new book titled Picturing the Uncertain World: How to Understand, Communicate, and Control Uncertainty through Graphical Display. Wainer is a longtime expert in statistical graphics who works as a research scientist for the National Board of Medical Examiners and as an adjunct professor of statistics at the Wharton School of the University of Pennsylvania.

Picturing the Uncertain World. Howard Wainer,
Princeton University Press, 2009.

The first thing I should say about this book is that you shouldn’t misunderstand the title as I did initially. Without giving it enough thought, I excitedly assumed that the book focused specifically on visual means to represent levels of uncertainty in graphs. People quite often ask me if there are better ways to do this than error bars, which is a great question that I haven’t taken the time to thoroughly investigate. I was hoping that Wainer had done this for me. It is probably no surprise to those of you who are statisticians, however, that Wainer is using the term “uncertainty” in the sense that all statistical information is uncertain—statistics after all is the “science of uncertainty”. The book isn’t specific in any sense; it addresses a broad, disparate set of issues pertaining to the graphical representation of statistical data.

Similar to Tufte’s books, this is a collection of Wainer’s ideas, stories, and examples, which meanders freely through the landscape of statistical graphics. Both Tufte and Wainer are exceptional thinkers and writers who sprinkle their books with marvelous insights, but neither write books to address a specific topic in a cohesive way. Picturing the Uncertain World is a compilation of articles that Waimer wrote over the course of 11 years (1996 through 2007), mostly for the statistics journal Chance.

Before commenting further on the content of Wainer’s book, I’d like to mention that, unlike many books in the field, at $29.95 this book is quite affordable. Princeton University Press resisted the temptation to which academic publishers often succumb, which is to price the book beyond the reach of all but university libraries. They accomplished this, however, by paying less attention to the book’s design and printing than a book about graphics deserves. Unlike my books and Tufte’s, Princeton University Press produced Wainer’s book on the cheap. One example of the difference is that Tufte and I both work hard to place figures as close as possible to the text that references them, which involves a lot of time and expense. This prevents the annoying experience of readers having to flip through pages to find the figure and then having to find their way back to the place they left off in the text, which undermines the learning experience.

Now, on to the book’s content. This book is for statisticians. It assumes a fairly high level of statistical fluency, yet I’m not sure that Wainer fully appreciates this fact. About two-thirds of the way into the book in a chapter on statistical error, after using statistical terms and concepts throughout, Wainer includes a section titled “A Brief Tutorial on Statistical Error.” It struck me as odd that he didn’t recognize the need for any tutorials until then. In this sole attempt to inform the uninitiated (that is, readers who either never took “an introductory statistics course” or took one but no longer remember the material), he exclusively covers the calculation of statistical error (hypothesis testing, Type 1 and Type 2 errors, the problem of multiplicity, the Bonferroni method, sensitivity analysis, resampling, multiple imputation, and standard error). Wainer’s rapid tour of statistical error left my head spinning. I felt as if I’d been stomped on by the “Bonferonni method,” which left me in need of some “sensitivity analysis.”

The inside flap of the book jacket concludes with these words: “We live in a world full of uncertainty, yet it is within our grasp to take its measure. Read Picturing the Uncertain World and learn how.” This is a bit misleading. Only those who already possess a fairly good understanding of statistics will find this book accessible. Those who don’t will be left gasping like fish on dry land. Statisticians will no doubt enjoy Wainer’s examples and insights, but others will need to take a course (or two or three) before learning much other than how uninformed they are about statistics.

Please don’t misunderstand me. I’m not saying don’t buy this book. I’m merely trying to define the audience that will find it most worthwhile. Although I struggled a bit, I found several sections fascinating and useful. More than the articles, the two parts of the book that spoke to me most compellingly were the “Introduction and Overview” in the beginning and the “Epilogue” at the end, where Wainer the man shines through with grace, warmth, humility, and passion. The fact that he cares deeply about his work and longs to leave the world better off than he found it is evident. I appreciate this and Wainer’s fine service to the world and the statistical graphics community in particular.

Take care,

I’ve written previously about my concern that infographics—the mixture of text and images to tell stories, explain concepts, describe processes, or provide instructions—have no real research to back up their claims of effectiveness. Visual communication is all the rage today, and rightfully so because it has great potential when used effectively, but much of what’s being sold by expensive consultants simply doesn’t work. This is a travesty; infographics could be used for good if we could only figure out when to use them and how to properly design them. Research is needed, but in the meantime organizations are spending bundles of money on silly posters that are rarely more effective than a simple written document.

Take the following example that XPLANE is currently exhibiting with pride. For a mere $24,000 paid for its design, plus the cost of printing and shipping, a company named Weatherford has placed a copy of this poster in the workspace of every one of its HR representatives worldwide.

According to the HR Manager at Weatherford who commissioned the work, this poster depicts the “Work Life Cycle of an employee in an organization and the role played by PeopleSoft HRMS system in managing talent and partnering with HR as an enabler.” Why do they need a poster? “We lacked a consolidated, high impact message that could capture and communicate with our people. We needed a clear, concise way to deliver our message to all levels, languages and cultures while remaining cost effective.” How does this poster communicate to all languages? They produced 12 different versions of it; one for each language group. In other words, the pictures didn’t solve the language problem. In fact, the pictures add no meaning to the poster whatsoever. The human figures walking, sitting, and standing in various settings, which resemble graphics common in old video games, are at best evocative of meanings that we already know from the text. The pictures are mere eye candy—empty calories.

Is this the best that infographics has to offer? Are infographics about decorating concepts and instructions with silly pictures to entertain people, thinking that only then will they actually read the words? If so, rather than paying $24,000 to have a graphic artist arrange images from his clipart library on a piece of paper to make a set of instructions look like a children’s game, why not just type up a list of instructions and put a picture of a kitten at the top of the page, or better yet, different kittens in various cute poses next to each section of text?

Infographics can be done well. Images can be used in ways that complement the text by elaborating, explaining, or clarifying it when words alone don’t do the trick. I’ve seen many examples in news publications such as the New York Times and Newsweek, which combine text, quantitative graphs, and sometimes diagrams and photos, to tell the story of a current event. These are quite different from the visual wasteland that’s pictured above. When they’re effective, what makes them so? This is what we people who produce infographics need to figure out, based on solid research.

Once again I’d like to ask you who are infographic experts to prove the worth of your methods. The fact that organizations are willing to pay for your services proves nothing. These are probably the same organizations that are spending big bucks on so-called data visualization software that allows them to put lighting effects on pie charts and then make them spin. After spending $24,000 of his company’s money on a poster, what Human Resources Manager is not going to argue its worth in an effort to combat cognitive dissonance? I’m issuing this challenge because I know there’s something worthwhile here, but it’s jumbled in with the crap. Start thinking critically about this stuff; question your methods, put them to the test, and eventually you’ll establish guidelines for separating the wheat from the chaff.

Until then, we’ll be papering our walls and cluttering our brains with the likes of the recent infographic below from GOOD magazine, which exhibits so many problems it’s hard to imagine where to begin critiquing it, so I’ll leave that to you. I’m going to go lie down now and cover my eyes with a warm compress.

Take care,

My newest book, Now You See It, is finally available. Unlike my other books, which teach how to communicate information graphically, Now You See It focuses on principles and techniques for analyzing information graphically. Here’s the description that appears on the book’s back cover:

Before you can present information to others, you must know its story. “Now You See It: Simple Visualization Techniques for Quantitative Analysis” teaches simple, fundamental, and practical techniques that anyone can use to make sense of numbers. These techniques rely on something that almost everyone has—vision—using graphs to discover trends, patterns, and exceptions that reside in quantitative information and interactions with those graphs to uncover what the discoveries mean.

Although some questions about quantitative data can only be answered using sophisticated statistical techniques, most can be answered using simple visualizations—quantitative sense-making methods that can be used by people with little statistical training. Until “Now You See It,” no book has taught the basic skills of data analysis to such a broad audience and for so many uses, even though the need is huge, critical, and rapidly growing.

Take care,