Self-service BI tools are a big hit and they permanently changed the business intelligence landscape. The ease of use, performance and agility towards ever changing data structures, while respecting data governance, are just overwhelmingly appreciated by users.
With the capabilities of the self-service tools to quickly create inherently advanced analyses and visualizations, our topic of the ‘art of visualizing visualizations’ is unveiled. This art is about the interaction between the developer and the tool to create visualizations and dashboards which are crystal clear, interpretable by consumers in a blink. Even more the art is about the ability to communicate essential messaging and data into actionable information.
Engaging with customers every single day on business intelligence, brings relentless questions from their part on whole variety of ‘Christmas trees’ and ‘colorful paintings’ that are intended to act as core dashboards to monitor business insight. No doubt these dashboards are often pieces of art (graphical capabilites of the tools are really impressive), though they are questionable when it comes communicating data into actionable information. It takes an awfull lot of time for the consumer to understand the dashboards and interprete them, if this can even be done. Is the developer to blaim? In a sense, yes. However current tools make it so easy to use any graph and chart in almost any situation, an unclarity is quickly created.
Time for guidelines on how to structure visualizations and dashboards:
- Agree on standards. Agreement on some principles of visual development within your organization, greatly accelerates adoption and recognition of your dashboards and reports.
- Avoid what can be avoided; less is more. The less graphs and charts needed to visualize your message, the better.
- Use multipage stories: tools like SAP Lumira use stories that are multipage, allowing to spread graphs over multiple pages. This is preferred over a single page loaded with info.
- Use color coding only to highlight or accentuate important data. Any other colorcoding only distracts attention from your messaging
- Use input controls. Inputs controls are a great way for end users to select and filter the data sections they are interested in. They take little space.
- Use hierarchies and drillable graphs but present at summarized level. Present your data and the highest presentable level possible, and allow the users to drill where applicable. This keeps tour dashboard clean and overseeable.
- Avoid legends where possible. Separate legends next to charts and graphs use a lot of space. Preferrable use charts with embedded legends (see below examples)
Less good example with seprate legend
Good example with embedded legend and datalabels
- No gauges. I am asked every single week after gauges. Avoid them, they take way to,much space. Bullet charts are a better alternative and offer more capabilites and better messaging
- Be carefull with 3D and pie charts. Though they might look good, these charts take more time to interprete and are often unclear.
- Tip: numeric point graphs are very specific, take little space and are crystal clear
- Tip: radar or polar charts are very good when comparing facts over multiple dimensions
- Tip: use heat maps for white space analyses
- Tip: use dynamic text. Dynamic text makes text on a dashboard dependant to its underlying data. Whenused correctly, it often saves an additional,chart of graph to be created
Luckily for us the ‘art of visualizing visualizations’ attracks some attention. The web offers definately guidance and information. Very interesting is the documentation of the Hichert IBCS group on notation standards in business communication, providing good ideas for standardization principles for visualization in your company. Happy reading !