Many users believe that once you have the metrics in place and understand what data users want, the next step is to create the reports.
In reality, a lot of thought and a careful eye are required when making design considerations to create charts, grids and tables that convey the details in the simplest terms for user understanding. The right design choices enable users to see easily the trend, outliers, or items needing attention.
Many people think that the more data they can cram in, the better. However, studies have shown that the average person can only store 6 chunks of information at a time. Depending on how flashy and distracting your graphics and marketing logos are, you may have already used up half of your brain’s capacity, without getting to any reports or dashboards.
Graphic overload may make one consider removing all distracting graphics, highlights, bolds and visual clutter to show the data – novel concept right?
But this is not the solution. There has been lots of visualization studies and research done over the past century that have uncovered that eliminating graphics altogether is not the solution to this dilemma.
In fact, there are several leading experts on this topic, including three key people, who are leading the charge against clutter and visual distraction, cheering for more measured and thoughtful chart and dashboard visual design. These individuals are:
· Edward R. Tufte
· Colin Ware
· Stephen Few
All three have published several books explaining how we interpret visual data, including what makes our eyes drawn to color and form, and what aids understanding. It also explains “chart junk” – a term first coined by Tufte in 1983. Tufte defines “chart junk” as simply:
“Conventional graphic paraphernalia routinely added to every display that passes by: over-busy grid lines and excess ticks, redundant representations of the simplest data, the debris of computer plotting, and many of the devices generating design variation.”
The key concept of “chart junk” leads into another of Tufte’s mantras called the “Data Ink” ratio. The idea here is that by minimizing the non-data ink you are maximizing the data ink. In other words, that you can achieve the ideal balance of data and design by removing borders, underlines, shading and other ink elements which don’t convey any messages
There are a lot of available resources out there on this topic by these authors and others.
Stay tuned for my final blog post, in which I will demonstrate how to effectively put these concepts into practice when creating reports.