Data Visualization: More Than Pretty Pictures
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Data AnalyticsStrategy Marketing Social Impact May 1, 2015

Data Visu­al­iza­tion: More Than Pret­ty Pictures

Data visu­al­iza­tion tech­niques are inte­gral to mem­o­rable and per­sua­sive messaging.

data visualization technique best practices

Lauren Manning

Based on the research of

Steve Haroz

Robert Kosara

Steven Franconeri

You have a great idea to grow your busi­ness, be it a new prod­uct, a clever mar­ket­ing strat­e­gy, or a nov­el approach to orga­niz­ing the com­pa­ny. The idea is based on sol­id data. How do you con­vince your skep­ti­cal boss, staff, or clients of your brilliance?

Show them your data visu­al­ly, says North­west­ern Pro­fes­sor Steven Franconeri.

Peo­ple might think that visu­al­iza­tions are pret­ty and they’re icing,” Fran­coneri says. That’s not true. They are indis­pens­able, absolute­ly indispensable.”

Around 40 per­cent of our brains are devot­ed to visu­al com­pre­hen­sion, Fran­coneri says. It’s crit­i­cal that you use that machine.”

And while data visu­al­iza­tion has been around for more than 100 years — Flo­rence Nightin­gale was an ear­ly pio­neer who used a visu­al­iza­tion to prove that more sol­diers died while lin­ger­ing in hos­pi­tals than on the bat­tle­field — it has got­ten far more sophis­ti­cat­ed in the past decade or two. The tech­nol­o­gy for dis­play­ing data has improved, and research is estab­lish­ing best prac­tices for com­mu­ni­cat­ing data visually.

This classic data visualization example was created by Florence Nightingale
This classic data visualization example was created by Florence Nightingale to show that more soldiers were dying from preventable diseases after battle (blue) than had died from wounds on the battlefield (red). Credit: Wikicommons.

This boom has led to some rules about how to best present your data. Yet Fran­coneri, an asso­ciate pro­fes­sor of Archi­tec­tures of Col­lab­o­ra­tion at the Kel­logg School (Cour­tesy) and of psy­chol­o­gy in the Wein­berg Col­lege of Arts & Sci­ences, says far too few peo­ple learn those rules. And it comes at a cost: bad visualizations.

If you do it wrong, it’s a dis­as­ter,” he says. It can be com­plete spaghetti.”

Boom in Visualizations

The way you dis­play your data depends on the sto­ry you want that data to tell. So it fol­lows that the peo­ple at the fore­front of data visu­al­iza­tion today are trained storytellers.

The folks who are doing the most inter­est­ing work on the sto­ry­telling front are jour­nal­ists,” Fran­coneri says. They are the peo­ple whose job it is to take com­plex ideas and dis­till them in digestible, mem­o­rable ways. The New York Times, for exam­ple, is doing high­ly inno­v­a­tive data visu­al­iza­tion, Fran­coneri says.

As jour­nal­ists have got­ten more sophis­ti­cat­ed in their visu­al­iza­tions, researchers like Fran­coneri have start­ed design­ing stud­ies of their tech­niques to deter­mine what styles of visu­al­iza­tion are work­ing best and why.

If you do it wrong, it’s a dis­as­ter. It can be com­plete spaghetti.”

Beyond act­ing as research top­ics, jour­nal­ists’ visu­al­iza­tions are a great place for busi­ness peo­ple to browse for inspi­ra­tion, Fran­coneri believes.

Take, for exam­ple, this inter­ac­tive graph­ic that looks at the ris­ing rate of motor­cy­cle deaths, and this one that looks at deaths from pre­ventable dis­eases. In both, from The New York Times, the view­er is guid­ed through sev­er­al sets of relat­ed data with an ani­ma­tion that caus­es one visu­al­iza­tion to flow into another.


Fran­coneri uses this exam­ple to show how our brains can sort quick­ly when giv­en visu­al infor­ma­tion. Look at the first grid (with no for­mat­ting) and try to pick out the high­est and low­est num­bers. Now, look at the final grid (in tan, white, and pur­ple) and try to do the same thing. You should find the task much eas­i­er, thanks to straight­for­ward col­or-cod­ing. The oth­er two grids are less effec­tive because the col­or-cod­ing is coun­ter­in­tu­itive (in grayscale) or dif­fi­cult to see (in red and blue). Cred­it: Steven Franconeri

It’s tak­ing a big com­plex data set and guid­ing peo­ple through one snap­shot at a time so that they under­stand the big pic­ture through a guid­ed tour,” Fran­coneri says.

And all the rules that apply to good jour­nal­is­tic visu­al­iza­tions also apply to the busi­ness world.

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Data Visu­al­iza­tion Best Practices

So what are those rules?

If you don’t know the answer, Fran­coneri says you are unfor­tu­nate­ly in good company.

Nobody ever gets taught these rules. You take writ­ing class­es in col­lege. You don’t take a graph­i­cal com­mu­ni­ca­tion class,” he says. Yet, this is a skill that peo­ple need to have. If you learn these rules, it will have a mul­ti­plica­tive impact on how well you can con­vey your ideas to peo­ple and how well those ideas will actu­al­ly sink in and then lead to action.”

Fran­coneri offers up a few rules of thumb.

If you have a rel­a­tive­ly sim­ple data set, cre­ate three or four dif­fer­ent visu­al­iza­tions. Make them as dif­fer­ent as pos­si­ble,” he says. Show those to some col­leagues. Ask them what sto­ry they see in each one. You’ll be sur­prised at the dif­fer­ences in what peo­ple extract from the same data.” Those inter­pre­ta­tions can then be used to shape your final product.

With a more com­plex data set, keep in mind that your view­ers can quick­ly get over­whelmed even if you and your design­er under­stand the visu­al­iza­tion com­plete­ly. Because the visu­al-pro­cess­ing cen­ters in our brains are so strong, it is easy for design­ers to feel com­plete­ly com­fort­able with a com­plex visu­al­iza­tion because they have been immersed in the data. View­ers, how­ev­er, strug­gle with­out that background.

Their brain is lit, but they don’t know what to do with it all,” Fran­coneri says.

Oth­er rules come from his research into spe­cif­ic types of visualizations.

One of his forth­com­ing papers looks at a new type of graph called a con­nect­ed scat­ter­plot. It takes a style of graph that is famil­iar to most of us — a sim­ple scat­ter­plot — but com­bines two time-relat­ed sets of data instead of just dis­play­ing each one in a sep­a­rate graph.

In this exam­ple from The New York Times, the con­nect­ed scat­ter­plot shows miles dri­ven by Amer­i­cans each year as well as auto fatal­i­ties each year. In a tra­di­tion­al scat­ter­plot graph, time would run along the x-axis with the y-axis show­ing either miles dri­ven or deaths. Instead, a con­nect­ed scat­ter­plot com­bines the data from the two y-axes and lets time run as an anno­tat­ed line across the graph. When Amer­i­cans on occa­sion reduce their dri­ving from one year to the next, the line goes back­wards. In one spot it even cre­ates a loop. Most view­ers do not expect a line on a graph to behave that way.

This sort of inno­v­a­tive visu­al dis­play is excit­ing to Fran­coneri. But he wants to know if it is actu­al­ly effec­tive. In a series of exper­i­ments, he had stu­dents and ran­dom­ly select­ed par­tic­i­pants look at con­nect­ed scat­ter­plots as well as more tra­di­tion­al graphs.

In one exper­i­ment, par­tic­i­pants were shown thumb­nails of six graphs, three of them con­nect­ed scat­ter­plots and three of them more tra­di­tion­al graphs. Par­tic­i­pants were giv­en five min­utes to explore the graphs and could click on any thumb­nail to view it larger.

Fran­coneri and his coau­thors, Steve Haroz, a researcher in Franconeri’s lab, and Robert Kosara of Tableau Soft­ware, found that par­tic­i­pants spent the major­i­ty of the first two min­utes look­ing at enlarged ver­sions of the con­nect­ed scat­ter­plots. This means that the for­mat is high­ly effec­tive at grab­bing view­ers’ atten­tion and that peo­ple are not imme­di­ate­ly turned off by the unfa­mil­iar­i­ty of the format.

In oth­er exper­i­ments, par­tic­i­pants were asked to answer ques­tions about their under­stand­ing of the con­nect­ed scat­ter­plot graphs. The researchers found that, for the most part, they under­stood the data quite well.

The places where view­ers got hung up led the researchers to offer some con­crete advice to design­ers of these graphs. For exam­ple, they rec­om­mend hav­ing clear anno­ta­tions for unfa­mil­iar fea­tures, like loops in the time line. It would also be use­ful to have linked views to small­er, more tra­di­tion­al visu­al­iza­tions of the data in spe­cif­ic spots that view­ers could click on.

Over­all, Fran­coneri deems this type of cut­ting-edge visu­al­iza­tion a success.

Bol­ster­ing Your Presentations

When Fran­coneri teach­es busi­ness stu­dents and lead­ers, he advis­es them to step away from the tra­di­tion­al bul­let-point­ed slides and start inte­grat­ing visu­als into their presentations.

Because our brains use the same sys­tems to process speech and writ­ten lan­guage, putting up text on a screen while talk­ing ensures that you won’t get your point across, because no one can read and lis­ten at the same time” he says.

But, he says, you can look at pic­tures and lis­ten at the same time at full blast.” To con­vince your audi­ence of your point, the visu­al­iza­tion part is not optional.”

Steve Fran­coneri teach­es in Kel­logg Exec­u­tive Education’s The Strat­e­gy of Lead­er­ship program.

Image cred­it belongs to Lau­ren Man­ning. Pub­lished under a Cre­ative Com­mons license. Image has been mod­i­fied by remov­ing labels.

Featured Faculty

Steven Franconeri

Professor of Psychology, Weinberg College of Arts & Sciences; Professor of Leadership (Courtesy)

About the Writer

Emily Stone is the research editor of Kellogg Insight.

About the Research

Haroz, Steve, Robert Kosara, and Steven L. Franconeri. “The Connected Scatterplot for Presenting Paired Time Series Data.” Manuscript submitted for publication.

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