There seems to be a strange disconnect with many dashboard designs. Most dashboard data is 1 dimensional (using gauges and pie charts) or 2 dimensional (line graphs and scatter plots) and yet many people seem to want widgets that look three dimensional (which I term faux 3D visualizations). Essentially, some people want an extra dimension that displays no information. Three dimensional visualizations may be justified when the data itself has an inherent 3D spatial meaning, as is the case for many anatomy and fluid dynamics visualizations. However, dashboard data is typically not spatial, and addition of a 3rd dimension can actually obscure the data.
So what benefit is there to using 3D charts? Some people argue there is an improved aesthetic appeal. Others say the faux 3D looks more professional. However, using faux 3D charts reduces the readability of the dashboard without most people knowing it. The presence of faux 3D charting widgets on a dashboard demonstrates a designer’s propensity for valuing marketing glitz over readability.
Why Faux 3d is poor visualization
Arguments against 3D charts are not new. In fact, I feel like I am simply parroting Stephen Few or Ben Shneiderman as I write this. Faux 3D charts and graphs have been demonstrated in the research literature to negatively affect the accuracy and speed at which one can interpret data. The image below demonstrates how the addition of a 3rd dimension can cause distortions in the perceived size, and thus the value, of the data.
3D pie charts tend to skew the size, and thus the perceived value, of the data.
Notice in the upper right image how the slices of the 3D pie representing 17 units are not the same size, whereas the 13 and 17 look equivalent? Even if we take a 2D pie chart and distort it to match the shape of the 3D pie chart (bottom), you’ll notice that the sections maintain the correct relative sizes. It is the perspective projection that is causing distortion. If you must use faux 3D charts, minimizing the 3D effect will reduce these interpretation errors.
In most cases, dashboards are used for monitoring and should be designed for rapid comprehension, particularly in business contexts. Dashboards are typically designed for repetitive, short duration use instead of long, in-depth analysis. Effective dashboards need to be clear, easy to read and accurate for this reason. So why sacrifice accuracy for aesthetic appeal? If some of your client base is aware of the faux 3D chart perceptual issues, how does a 3D chart look more professional? For a visualization researcher like me, faux 3D charts are essentially the black velvet paintings of the visualization world. You may still enjoy the look of a 3D pie chart, but others may not share your perspective.
For your consideration
I do not expect faux 3D charts to disappear any time soon. My hope is that some of you will begin to see that not all dashboards (particularly 3D dashboards) are designed for maximum performance. The flashiest kitchen gadgets are not necessarily the most effective tools for cooking. Similarly, faux 3D charts are not as effective as their 2D counterparts. Ultimately, identifying issues associated with different chart designs is a critical first step to creating effective dashboards.