Juice Analytics

Clad in neon green from their jerseys to their shoes, the Baylor Bears advanced to the South Regional finals in the NCAA Men’s Basketball Tournament last night, leading by as many as 18 points in a game that was pretty hard to watch. Literally.

Can Color Create a Competitive Advantage?

Spectators had lots to say about Baylor in the Georgia Dome last night, but instead of commenting about their talent, skill and ball handling, most people talked about the obnoxious neon “green” color that the Bears and their fans were wearing. Their neon green uniforms (think “tennis ball” yellow) made it nearly impossible to keep your eyes off of them — yet for many of us, was a complete distraction from the game itself.

As I tried to watch, I thought about the critical role that color plays in the communication of data and information. By highlighting certain details with color, we choose to draw attention to them or put greater emphasis on them. At the same time, color has the potential to confuse or distract our audience if the color we select conflicts with the message or purpose we have in mind.

Can color impact outcomes, giving one team a greater (and perhaps unfair) advantage over another? Could the Baylor Bear’s neon uniforms be playing a part in their success?

What are your thoughts?

For more on color and tips for your next presentation, design or data visualization, see “Color Has Meaning”.

Spring is a great time to spruce things up.  While you’re at it, consider adding a little shine to you and your skills.

We’ve made it easy for you by adding five more videos to our resources page that will help sharpen your saw, as Stephen Covey might say, in this important area of your life.  From graphing to table design, color to typography best practices, you’ll find these video tutorials full of tips, tricks and tidbits that you’ll be using long after the pollen rinses away and your antihistamine goes back in the drawer.

And, just in case you’ve been fogged over, we launched a new page on our site a few weeks ago, Design Principles. If designing from the human perspective interests you, you’ll find this a valued extension to your knowledgebase.  

Achoo! (That is, here’s to you!)

How do you find the best of the best? The National Football League holds a combine every year where the top college football players run, jump and press. We took that data and put it into our leaderboard visualization to let you explore these physical freaks.

A leaderboard lets you focus on exceptions; the best and worst performers across different characteristics. Everyone or everything that’s not superlative (or lousy) is available but not emphasized.

By looking across multiple characteristics you can see one person’s strengths and weaknesses. Here’s a quick overview of how it works.

Or jump in and try it out with your own data. One note: this visualization requires IE 9 or higher or Safari/Chrome/Firefox.

We’re working on a revamp of the popular chart chooser that would include more tools like this so let us know what you think.

There is a funny list of awkward analogies by high school students that circles the Internet like a shark around a downed airman. There were some great ones in the list:

• She had a deep, throaty, genuine laugh, like that sound a dog makes just before it throws up.
• He fell for her like his heart was a mob informant, and she was the East River.
• The ballerina rose gracefully en Pointe and extended one slender leg behind her, like a dog at a fire hydrant.

A good analogy is priceless–it helps us understand the new by connecting it to the familiar. A bad analogy is like an empty tin can at the bottom of a well, it isn’t good to drink from.

Good data visualizations are like storytelling. Where does this analogy lie?

For practitioners of the craft, connecting our work to stories feels satisfying — it is a call to raise our standards and an opportunity to enhance the influence of our field. Stories evoke images of rapt audiences, dramatic arcs, and unexpected plot twists.

Unfortunately this analogy is a stretch. The truth is that many of the core elements of stories simply aren’t evident in data visualizations: characters, a plot, a three-act structure, a beginning and an end. Occasionally, the narrative flow of a story can be glimpsed in an infographic or dashboard.

At the same time, data visualizations have fundamental characteristics missing from traditional storytelling. Interactive data visualizations let the audience explore the information to find the insights that resonate with them. Visualizations should take shape based to a large extend on the underlying data. And as this data changes, the emphasis and message of the visualization is likely to change.

To be fair they aren’t entirely unrelated. One element that the two forms of communication share is the ability to build and resolve tension. Pose a problem, then deliver an insight that helps answer that problem.

Nevertheless, our community breezily equates visualization with storytelling. I was struck by the language used in Visual.ly’s recent post called From Data to Story: Dissecting a Well-Made Visualization. The author reviews a good visualization and discusses how it tells a simple story:

“This piece is particularly interesting because it tells a very simple story, yet the data itself is complex. Imagine the myriad ways that one could show the aggregated percent change for twenty different companies. The author of this visualization experimented with different views and arrived on the two that told the story most completely, most effortlessly.”

Ad Age’s Garrick Schmitt boldly states that “all of this data visualization is, of course, really just a new way to tell stories (or create experiences).”

We want to link our newest communication method to our oldest. The shoe doesn’t fit.

Ultimately, communicating with data isn’t about telling a specific story, but rather starting a guided conversation. It is more a Choose Your Own Adventure book, the color commentary of a basketball game, or the narrative structure of Call of Duty 3. It is more dialogue with the viewer’s understanding than monologue, and must be more influenced by the content than the unfettered creation of a storyteller.

Tis the season of indulgence. Sometimes it is indulgence without any semblance of restraint. Case in point, the “Cherpumple” — a combination pumpkin, apple, and cherry pie framed in icing.

When it comes to business dashboards, the gauge chart is often a case of indulgence without restraint. It can be equal parts waste of valuable pixels, low information, and visually deceptive. It would be a lot smarter to use a bullet chart — but who wants to pick the the fruit plate for desert?

Gauges have undeniable appeal to dashboard designers everywhere. Perhaps it is the “skeuomorphism” of a gauge chart. That is, it borrows from the look of something we are familiar with as a way to make us feel comfortable or understand its purpose.

In the past, I’ve fought the good fight against these charts. Now I’m resigned to the fact that eradication is impossible. If that’s true, can we at least find some ways to make them better through design? Tone down the brilliant sheen and high-contrast colors; turn up the information conveyed.

First we can start by making them look better. Web designer Christian Annyas shared a beautiful gallery of Chevrolet speedometer designs across the years. Here are a couple of my favorites:

Christian even offers a decent argument for gauges over simply showing a value:

“It’s easy for a driver to get used to a needle that rises and passes numbers that are located on fixed positions. A quick glance is all it takes to see and understand the value it represents.”

Let’s take one of those designs, overlay a few necessary data elements, and see if we can create something worth looking at.

1. Start with an classy Chevrolet design that lays out so as not to take up too much valuable vertical space
2. Add subtle indicator of good and bad zones with green and red dots
3. Show the current value with a bold label
4. Display distribution of recent history to communicate how the value has changed

While this chart is still far from efficient in its data-to-ink ratio, at least it communicates the small amount of information effectively. Any ideas for how to make it better?

Do you have your child’s drawing on the wall of your cube, office or maybe at home on the fridge? Can you remember visualizing the world that simply?  When was the last time you looked at anything quite that way? What if you did?

Well, we did just that. And, our effort resulted in a video to share with people about what we do here at Juice.  We hope you like it.

(P.S. Thank your kid for the artwork covering that stain on your wall — and for the great analogy.)

If you’ve ever tried to get anywhere in Atlanta at 5:30 p.m. on a Thursday, you’re painfully aware of the seemingly perpetual problem we have with traffic.  Last year, Atlanta was ranked as the 4th worst city for commuters.

Atlanta Journal-Constitution Atlanta Map:

That’s why Juice teamed up with the Atlanta Journal-Constitution(AJC) to help metro Atlantans better understand and visualize the magnitude of the initiative which encompasses projects across a 10-county region at a proposed cost of $6.14 billion. If voters approve the new transportation referendum in Summer 2012, it will be the biggest single transportation effort in the region in over 40 years. The referendum would add an extra one percent multi-county regional sales tax to fund the mammoth initiative over a 10-year period.

Juice designed a detailed map to accompany the AJC’s three-page cover story in order to help metro Atlantans better understand and visualize the magnitude of the initiative. The map provides readers with a bird’s eye view of the 118 proposed projects on the current draft of the referendum. The alpha-numeric coordinates along the “x” and “y” axis help readers find their bearings, while the color and pattern-coded keys help them easily identify degrees of traffic congestion and decipher roadway projects from transit projects, bike and pedestrian projects from aviation projects.

We are thrilled to have the opportunity to contribute to our community to do what we can to help solve one of the region’s key challenges when it comes to growth, economy, and environment. We’re looking forward to seeing how this story plays out and are hopeful that visualizations such as this one will help voters and decision makers alike consume, process the massive amounts of data driving this effort, and act.

Unfortunately, the AJC only ran the map and accompanying story in the subscriber edition of the paper, so I’m not able to share a link.

Telling stories with data. It is an increasingly common business intelligence refrain–and it may well be part of your job description. If it is, why not tap into the time-tested lessons of those who tell stories with words?  Just as words are the basic unit of written stories, visualization techniques (charts, visualizations, colors, font sizes, sparklines, etc.) are the tools we have when telling data stories. No matter the form, authors will agonize about choosing the right units of expression, finding a balance between being concise and being comprehensive, simplicity and sophistication.

On questions of vocabulary and style in written communication, there seems to be agreement about the pursuit of simplicity and ensuring that  the message, not the words, take center stage. Below are three common writing guidelines, and what they mean for your data communication choices.

1. Smaller, simpler words

“The finest language is mostly made up of simple unimposing words.” — George Eliot

“Don’t use words too big for the subject. Don’t say ‘infinitely’ when you mean ‘very’; otherwise you’ll have no word left when you want to talk about something really infinite.” — C.S. Lewis

My experience is that the simplest visualization  techniques (bar, line, table, single number, even pie) are effective for 80% of data communication. Like simple words, you can be assured that your audience will quickly understand what you mean. Refrain from advanced visualizations like treemaps and animated bubble charts but for the special situations where the breadth and nuance of your data requires more visual sophistication.

Nevertheless, there is value in knowing what can be done in data visualization. Exposing yourself to advanced visualization techniques (start here: Infosthetic, Flowing Data, New York Times visualizations) offers similar benefits to having a large vocabulary.

2. Too many words is a symptom of poor understanding

“If you can’t explain something simply, you don’t understand it well.” — Albert Einstein

“A man who uses a great many words to express his meaning is like a bad marksman who instead of aiming a single stone at an object takes up a handful and throws at it in hopes he may hit.” — Samuel Johnson

Most people don’t really want to hear you think out loud. In data presentation, it’s tempting to think out loud by showing all the data in every conceivable way.  We’ve all been a recipient of that awful 80-page PowerPoint report with seemly infinite variations on the same data.

Form an opinion. Lay it out there. Don’t wander around – or worse, allow your audience to wander too much off the path. Here’s a favorite example from the New York Times. This analytical tool knows exactly what it wants to accomplish and gets to the point immediately.

3. Words are for communication, not show

“Words in prose ought to express the intended meaning; if they attract attention to themselves, it is a fault; in the very best styles you read page after page without noticing the medium.” — Samuel Taylor Coleridge

“Any one who wishes to become a good writer should endeavour, before he allows himself to be tempted by the more showy qualities, to be direct, simple, brief, vigorous, and lucid.” — H.W. Fowler

It’s not about the data or the visualization; it’s about the message you are trying to communicate.  This is not simply a question of efficient communication; it is also a question of perception. When you use unnecessarily complex visualizations, you draw attention to the wrong things. Here’s a good example of a chart that is more about the chart than the data:

Our founder and CEO, Zach Gemignani, went on the road recently to speak to a group of Voice of the Customer (VOC) professionals and customer intelligence experts at the Allegiance Engage Summit in Park City, Utah.  (Thanks for taking one for the team, Zach.)

Zach’s overall objective was to demonstrate how attendees could gain clear, actionable insights from consumer data.  I’m told that Zach delivered his message about as well as he crafted the data visualizations he used to build it.  In fact, it is rumored that Zach was so engaging that he was compared to none other than Guy Kawasaki, who was also speaking at the Summit.  (Fellow Juicers made mention of head room issues following that comment.)

Allegiance Radio will be airing a podcast of an interview with Zach from the Engage Summit on June 7 at 3:30 p.m. EDT on www.blogtalkradio.com,  Join via VoIP, chat or via phone at (619) 996-1642.  www.blogtalkradio/allegiance/2011/06/07/allegiance-summit-an-interview-with-juice-analytics

You can go to their website anytime after that to review the interview in its entirety.  Following the podcast, we will post a copy of the interview here on our website, as well.

Following is a summary of key content from Zach’s presentation along with resources that may inspire you to get to know your consumer data better to gain insights to move your business forward.  If you have questions or comments, feel free to send them our way.

Know Your Audience

Consider and understand the context of your audience.  ”Actionable” has as much to do with the recipient as the information.  Is it something they have the power or the influence on which to act?

Know Your Tools

Whatever your tool is, it’s worth your while to get good at it.  This saves you time and frustration.

Choose the Right Data

The gourmet values data quality – the right metrics, the right context, presented effectively.  The gourmand, on the other hand, is more interested in quantity. A gourmand believes that more is better, in part because they aren’t sure what they’ll do with the data in the first place.  (See the entire “Data Gourmet” blog at www.juiceanalytics.com/writing/being-a-data-gourmet/

Focusing on just the right data is a concept perhaps best summarized by Amanda Cox. “Data isn’t like your kids.  You don’t have to pretend to love them equally.” – Amanda Cox, New York Times

Choosing the Right Chart

So, how do you choose the right chart?  This is the challenge. Work by taking the most important attributes of your data (based on the question you want to answer) — mapping to the visual elements that most effectively convey that information.

Resources include www.chartchooser.com, www.extremepresentation.com/design/charts and www.juiceanalytics.com/writing/chart-selection-art-and-science/

Tell a Story

You have choices about how data is presented.  Make your choices deliberately.  Consider your audience, their needs and the information.   Then tell a story that clearly resonates with them and compels them — inspires them —  into action.