Graphic design in data visualization has proliferated over the past few years. Flick through your weekend paper or go to your favourite news website and it will not take you long to find this week's exciting new visualization. But there are strong backlashes from traditional data visualization gurus arguing that a lot of the new graphics being created are unclear or even misleading. The general consensus seems to be that newly invented inverted double swirl plot would actually be better as a bog standard bar chart.
But do these critiques miss the point somewhat? These novel plots are not always about trying to make data easier to understand but more exciting to understand. Most are designed to capture attention, rather than inform quickly. Where they are difficult to interpret the reader feels challenged to make sense out of the numbers.
To be fair to the critics, there are numerous examples where it is nearly impossible to draw a logical conclusion, even after prolonged study, and others that lead to the wrong conclusions.
So what should businesses take from this? The first rule of presenting your data post-analysis is to know your target audience. Consider selecting simple, informative graphs for the intrinsically interested, but a more adventurous one for you marketing literature.
However, where so many of these new visualizations are let down is through a lack of labelling and explanation. Lack of rigour in the final presentation will inevitably call the analysis and data collection in to question.
Does the design fail if people do not get it immediately? Not always, but it certainly does fail if people can't get it at all.