Anyone who recently bought an exploding smartphone or spent hours sleeping on the floor at Heathrow’s Terminal 5 might be inclined to agree with American inventor Danny Hillis’s definition of technology as “everything that doesn’t work yet”. 

As a society, we continue to be obsessed with the latest technology. And as data visualisation enthusiasts, we continue to be seduced by the latest tools, rarely questioning whether novelty leads to better results.

Readers often ask me what software we use to make charts at the Financial Times. No chart has generated more questions of this type recently than the Sankey diagrams, which we have used frequently this year to explain shifts in voting patterns in elections across Europe.

A Sankey chart showing changes in French election allegiances
A Sankey diagram showing French election results

Although there are several terms for this type of diagram, they are today most commonly named after the eponymous army engineer, Captain Matthew Sankey, who popularised them in the 19th century. Sankey was an engineer whose discipline nurtured a rare talent for information visualisation. Sankey diagrams are suited to showing “flow” movements in data, as the FT Visual vocabulary shows. But how do you actually make one?

graphic showing how to make a flow chart

This is flow-chart production circa 1939, courtesy of Willard Cope Brinton, another engineer — and author of one of the first comprehensive books about how to produce data graphics. If you think Brinton’s flow-chart instructions require dedication to follow, then you should also try his recipes for producing a pie chart (using a typewriter) or using piano wire to produce a 3D map. The full texts of his classic volumes Graphic Methods for Presenting Facts (1914) and Graphic Presentation (1939) are available online; both make for fascinating reading from a period when data visualisation was in relative infancy.

The books reveal Brinton to be a passionate craftsman and, when it came to creating graphics, a master of divergent thinking. To Brinton, typewriters, carbon copying paper, guillotines and piano wire were all valid and available technologies for helping him in his mission to inform and educate. 

His work contains parallels with the late Professor Hans Rosling, who used Ikea crates to represent population distributions. Such physical visualisations can resonate more profoundly with their audiences than screen-based equivalents.

Graphic showing how to produce a pie chart on a typewriter
'It takes as long to describe it as it does to do it ' - creating a pie chart on a typewriter

Andy Cotgreave, a data visualisation expert and co-author of a new book on business dashboards, believes Brinton’s methods remain relevant today. “Brinton wasn't afraid to try new approaches, as long as the novelty served the purpose of creating clarity,” he says. 

Mr Cotgreave has produced a website dedicated to Brinton that aims to parse his ideas for the modern world. For a field so seemingly anchored in technology, this is a valuable exercise.

Alberto Cairo, Knight professor in visual journalism at the University of Miami, reflected on Twitter recently on the role of technology and data visualisation: “ . . . we focus way too much on technological innovation and wondrous coding skills . . . but way too little on thinking. This includes scientific and quantitative reasoning, logic and moral philosophy. This is dangerous,” he tweeted.

Prof Cairo’s remarks generated a good deal of discussion. Ben Welsh of the Los Angeles Times argued the case for technological literacy: “You can’t make a good viz or a bad viz if you can’t make a viz at all.” 

And it seems many agree. The fact that lots of data visualisation practitioners list the tools they use first and foremost in their Twitter profiles ahead of the methods or philosophy of their work, seems to reinforce Prof Cairo’s point.

Modern computer hardware and software certainly boast extraordinary data handling efficiency. Many of Brinton’s charts would have been out-of-date by the time he produced them and extremely difficult to update. I am sure, if he were working today, he would see the appeal of using Microsoft Excel, RStudio, or many of the other wonderful data tools in between. But I would like to think he would not have felt so tied to them as many practitioners do today.

Technology can constrain our thinking — we can become impatient if we cannot produce something instantly. Emphasis on speed and reusability can obscure divergent thinking and oblique strategies for problem solving. Loyalty to one particular tool can drastically constrain opportunities to innovate.

Worse still is not knowing how to exploit the full power of the tools you do use. While many Excel users might be frustrated at the restricted number of built-in chart types, too few pursue what may be possible outside of the chart wizard; practitioner books still sit on too few desks.

We intend to launch our own FT Chart Doctor data visualisation workshops in the near future. They will focus on principles first and tools second. It is important to cover both topics but knowing why you are doing something must come before how. This is the same structure that Brinton used — and one of the reasons his books have stood the test of time. 

Meanwhile, how do you make a Sankey diagram? Much as I would like to say that you should painstakingly follow Brinton’s instructions, modern technology makes it ridiculously easy; visit, paste your data into the web browser and you can produce as complex a flow diagram as you like in just a few minutes. But where is the fun in that?

Twitter: @theboysmithy

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