Data visualizations are useful because our brains process visual information hundreds of times faster than written or spoken words, and thousands or millions of times faster than raw data. We can show a summary of billions of data points in ways that create understanding in a couple of seconds.
For decades, data charting has existed as a specialty between information technology and business practices. Many people became experts – IT staff who understood business and business individuals who understood technology — but most have muddled along. If you doubt that, I encourage you to look at a few corporate annual reports or news sources.
Now, the “democratization of data” puts sophisticated data visualization tools in the hands of millions of non-experts. It might be time to agree on how we convey an understanding of complex data.
There is no universally accepted standard for business data visualizations, and we don’t expect to see one soon. Analytics technology providers use their visualization tools as differentiators. Intense competition can drive them to become enticingly clever, sometimes at the expense of clarity.
Although we can certainly find commonality among analytics technology providers and business practices, we don’t find agreed-upon standards. A Google search of “data visualization standards” returns 1,380,000 results, but no agreement. It seems everyone has their version of what makes a “good chart.”
One organization that is trying to change that is the non-profit International Business Communication Standards Association based in Kreuzlingen, Switzerland. The association strives to create an international standard for uniform contents and layouts of internal and external business reports. It publishes standards under the Creative Commons Attribution Share. You can get a copy of the rules from the association’s website by signing up as a member at no cost.
IBCS concepts are not new. They have been developed over decades in business and academia. You will find them in some form in best practices guides or training courses. Here are a synopsis and our recommendations.
Conceptual: an appropriate story line.
Focus on the concise message and organize the content so it leads to a user to a conclusion or decision.
Perceptual: appropriate visual design.
We recommend using the simplest presentation that will deliver the message. Remove any unnecessary notation. For example, we almost never use axis labels or values when we have data labels that show values clearly. Review every visualization and make sure it does not have any unnecessary distractions.
Semantic: Apply semantic notation (IBCS Notation).
Business does not have uniform standards of notation like architecture and engineering, but we recommend organizational standards and governance so people in one part of the organization can understand visualizations created by those in another.
We are not expecting an international standard to emerge right now, but we would do well to consider how standardization and a common language across organizations and academic disciplines could serve us.
We could see a change in the next few years. Analytics company SAS has started a blog series on IBCS, and where SAS goes, others follow.