A recent Deloitte survey showed that more than 80% of companies surveyed said that analytics are currently being used to support their corporate strategies. Other research by SAP showed that those using data visualizations estimated it would take more than nine hours longer to identify patterns, trends, and correlations in data without using visualizations.
There are many more research findings that point to the same thing: analytics and data visualizations are important tools that enhance decision making. But, how can we use them to make complex things easy to understand. There are a few things you can do to better use both tools to simplify the complex.
To paraphrase the concept of Occam's razor, simpler explanations are generally better than more complex explanations. In a sense, the answer is in the question, "How do we make the complex easier to understand?" Keep the explanations simple.
Start With the End in Mind
Start by focusing on the purpose for communicating whatever analytic data or visualization you want to use. Are you trying to illustrate a trend? Identify exceptions? Show relationships? What conclusion do you want your audience to draw from what you communicate? This is one of the most important things you can do to frame your communication properly. As we discussed in an earlier article about the value of developing insights from data, knowing what your end user wants and needs is a critical piece to making the complex simple.
Remember the 80/20 Rule
Clear out some of the mental clutter by focusing on the small number of things that make the biggest impact. Not all data is important and the inclusion of irrelevant data serves only to clutter and confuse things. Your role is not simply to report on data. Your experience and skills are necessary to narrow down what’s important.
Clarity of language
Be clear in the language you use when you communicate your analysis and visualizations. Use precise language and avoid vague or ambiguous terms whenever possible. Don't describe a trend as good when you can describe it as increasing by 20%. The first is subjective and the latter is concrete and not subject to interpretation.
Choose the right type of visualizations
There are many visualization types to choose from, so choose carefully. Not all visualizations fit your data best. Be wary of the pitfalls of pie charts, for example. These are a very overused type of visualization and are sometimes the wrong choice. Too many pie slices (i.e. categories) is a common and classic mistake in the use of pie charts. If you have more than 6 categories to display, don’t use a pie chart. Learn some basic rules of visualizations, like which types work best in different situations. Illustrating a trend? Consider a line graph. Bar charts work well for comparisons, especially illustrating changes from one period or category to another.
Be careful with the scale of your visualizations to you do not distort the perception of differences between data items. This is a common mistake often made in interpreting visualizations that have been created specifically to distort perception. There are many other rules and guidelines, but these are a good start.
More is not always better, especially when communicating with executives. Say as much as possible with as few words and images as possible. This takes extra time and effort, but it pays big dividends.
Break down complex concepts into small, easy to digest parts. Chunk your communications into small, bite-size portions that are easy to understand on their own and build the story your insights reveal as a larger canvas that tells a story about your insights.
There are so many things you can do to make complex things easier to understand, it’s hard to fit them into one article, but these are a good starting point to get you exploring additional ways to serve your audience more effectively. There is plenty you can read about this topic, but also let feedback be a teacher. Listening effectively to feedback from those who consume your analytics and visualizations will tell you much of what you need to know to simplify them and make them more effective.
The article was first published in Prevero Blog.