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Tools that exploit the human visual system's ability to process information can help unlock workers’ untapped powers of analysis

It goes without saying that presenting information in a visual form helps people to understand it. One need look no further than the numerous graphs that fill presentations, financial results and performance reports to see that data visualisation is an established part of mainstream business culture. 

A crude explanation of the value of presenting data in graphical form is that the human visual system processes information in parallel; a series of numbers presented visually can be perceived simultaneously, and so trends can be spotted immediately. The alternative approach, to read each number in turn and try to build a mental image of the trend, is constrained by the limits of the mind's working memory. 

But while histograms, line charts and scatter plots are to be found everywhere in working life, the full potential of the visual system not only to understand but also to analyse information is still underused by business information systems, from desktop spreadsheet software to million-pound business intelligence architectures.

Stephen Few, founder and principal of Perceptual Edge, is an independent analyst and consultant whose work focuses on data visualisation. Few argues that the notoriously high rate of failure among business intelligence (BI) projects can be attributed, in part, to the failure of software vendors to design their tools to reflect the way human beings perceive information.

“Business intelligence is really just a new name for data warehousing,” he says. “The emphasis has always remained the same, and that is a focus on technologies for gathering and transforming data, supposedly making it ready for use but rarely taking that extra step to make data meaningful for people.”

Of course, top of the range BI software allows users to create all manner of charts and graphs with more effects and visual adornments than one could ever need. But this is not the same as designing a system that lets the user exploit the potential of their visual system to perform analyses they would be unable to do mathematically.

In fact, says Few, overdecorated graphs can have the opposite effect. “There has been this mad race among BI vendors to try to ‘out-sizzle’ one another with flashy visual effects without asking whether they are going to serve a purpose. And what happens is in most cases is that not only does it not help, but it actually gets in the way.”

However, there are a small number of software vendors whose technology is based on academic research into human computer interaction and data visualisation, supporting 'visual analytics' at its most powerful. Two leading examples of this, Few says, are Tableau Software and TIBCO Spotfire.

An algebra of graphs

During the 1980s, while working for a then little-known company called Pixar, Stanford University professor Pat Hanrahan was the chief architect of a system called RenderMan Interface, which defined an algebra for describing three dimensional visual objects. While that system went on to underpin Pixar's phenomenal success in computer animated films, Hanrahan developed another algebra, in this case for describing graphical representations of data.

Tableau Software, of which Hanrahan is now chief technology officer, is a data visualisation vendor whose tools are based on this very technology. The algebra developed by Hanrahan is used by the Tableau tool kit to query a given database, so that core concepts in data visualisation – such as the width or colour of a bar in a chart – are built into the operations of the system at the most granular level. 

According to Dr Jock Mackinlay, Tableau Software's director of visual analysis – who in the 1980s was part of a team at the Xerox PARC research facility that coined the term ‘information visualisation’ – this has two effects that greatly aid the user. 

The first is that it allows the system to analyse the data in order to decide which visualisation is most appropriate. “We've worked very hard on defaulting, so that you typically get the kind of view that a visualisation expert would recommend for you,” he says.

Secondly, it means that the user can change the visualisation as and when they please. Most visualisation systems use a wizard-style interface, says Mackinlay, “You have to know from the beginning what view you need. In Tableau, you just have to know something about your data, and then your visual system allows you to explore,” he adds.

According to Stephen Few, the ability to change the visualisation ‘on the fly’ is the key to data exploration. “The problem with a lot of software is that to get from one view to the next the mechanics end up being so cumbersome that we've forgotten what we're looking for by the time we get to the next view, so it doesn't support our analytical functions.”

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