The following is a quote from Stephen Few from his book Show Me the Numbers:
"The skills required for most effectively displaying information are not intuitive and rely largely on principles that must be learned."
More and more of us are becoming responsible for the analysis, presentation, and interpretation of data. This naturally reflects the explosion in access to data and the value attributed to potential insights that are contained.
As I've already stated, where once this was typically a specialist role, nowadays the responsibility for dealing with data has crept into most professional duties. This has been accelerated by the ubiquitous availability of a range of accessible productivity tools to handle and analyze data.
This means visualization has become both a problem and an opportunity for the masses, which makes the importance and dissemination of effective practice a key imperative.
The quote from Stephen Few will resonate with many of you reading this. If you were to ask yourself "Why do I design visualizations in the way I do?", what would be your answer? Think about any chart or graphic you produce to communicate information to others. How do you design it? What factors do you take into account? Perhaps your response would fall in to one or more of the following:
You have a certain design style based on personal taste
You just play around until something emerges that you instinctively like the look of
You trust software defaults and don't go beyond that in terms of modifying the design
You have limited software capabilities, so you don't know how to modify a design
You just do as the boss tells you—"can you do me some fancy charts?"
For many people, the idea of a conscious data visualization design technique isquite new. The absence of any formal coaching, at almost any level of education, in the techniques of visualization means until you become aware of the subject, you have probably never even thought about your visualization design approach.
Before discovering this subject, my own approach to presenting data was certainly not informed by any training or prior knowledge. I'd never even thought about it. Taste and gut-feel were my guiding principles alongside a perceived need to show off technical competencies in tools like Excel. Indeed, I'd like to take this opportunity to apologize for much of my graphical output between 1995 and 2005 where striking gradients and "impressive" 3D were commonplace. The thing is, as I've just said, I didn't realize there was a better way; it simply wasn't on my radar.
In some respects, the reliance on instinct, playing about with solutions that seem to work fine for us, can suffice for most of our needs. However, these days, you often hear the desire being expressed to move beyond devices like the bar chart and find different creative ways to communicate data.
While it is a perfectly understandable desire, just aiming for something different (or even worse, something "cool") is not a good enough motive in itself.
If we want to optimize the way we approach a data visualization design, whether it be a small, simple chart or a complicated interactive graphic, we need to be better equipped with the necessary knowledge and appreciation of the many design and analytical decisions we need to make.
As suggested previously, instinct and taste have got us so far but to move on to a whole new level of effectiveness, we need to understand the key design concepts and learn about the creative process. This is where the importance of a methodology comes in.