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The real estate axiom “location, location, location”makes it apparent that the most important attribute for a piece of property is where it is located. For dashboards, think, “data, data, data.” An oftenoverlooked aspect, data is one of the most important things to consider in designing dashboards.
Even if a dashboard’s appearance looks professional, is aesthetically pleasing, and includes graphs and tables created according to accepted visual design standards, other issues come into play when assessing the true success of the application. Remember, appearances can be deceiving. It is also important to ask yourself: Is the data reliable? Is it timely? Is any data missing? Is it consistent across all dashboards?
Although visual design is important, sometimes the biggest challenge is getting the right data into the right dashboard in the most efficient way. This paper offers an overview of best practice business intelligence (BI) dashboard design principles and discusses data integration options for getting data into a dashboard.
First, let’s make sure we are using the same language with regards to dashboards. In 2004 Stephen Few, a data visualization expert, wrote an article for Intelligent Enterprise magazine that defined a dashboard as “a visual display of the most important information needed to achieve one or more objectives consolidated and arranged on a single screen so the information can be monitored at a glance.”1 In 2007 Gartner expanded the definition to: “…a reporting mechanism that aggregates and displays metrics and key performance indicators (KPIs), enabling them to be examined at a glance before further exploration via additional BI tools. Dashboards are useful KPI and metricreporting mechanisms that enable users to quickly monitor and track performance via an aesthetic user interface. They employ visualization components, such as gauges, thermometers, dials, and traffic lights.”
From these definitions we can make several agreed upon assumptions about dashboards: A user should be able to look at a dashboard and quickly make observations without scrolling, drilling, or clicking off the initial screen. Minimal user interaction can be included to enhance understanding and clarify observations, but too much interaction defeats the purpose of a dashboard and crosses over into the realm of analysis. And that dashboards also:
- Provide a way to monitor and track performance
- Should be able to convey what is going on rather quickly
- Typically contain key performance indicators and use several types of data visualization
A “Few”Words on Visual Design
Since dashboards serve as a way to monitor performance at a glance, graphs, icons, and tabular reports should not be put together in an uncoordinated, unplanned manner. Dashboards must be built methodically, strategically, and with attention to detail. The size, color, and style of a font – such as whether it’s bold or italics – matter more in a dashboard than anywhere else in a business intelligence solution.
“Two of the greatest challenges in dashboard design,” says Stephen Few in his book, Information Dashboard Design,“ are to make the most important data stand out from the rest, and to arrange what is often a great deal of disparate information in a way that makes sense, gives it meaning, and supports its efficient perception. An understanding of the preattentive attributes of visual perception and the Gestalt principles provides a useful conceptual foundation for facing these challenges.”
Achieving at-a-glance observations means making data pop. Designers must manipulate the graphs and tabular reports common to dashboards so the data reflects problems or opportunities – depending on which is important to the user – and stands apart from the rest of the information. This can be done through the use of icons, colors (hues), shapes, and sizes of objects and properties in a graph or tabular report.
Graphs, tabular reports, and text can be manipulated to make important information stand out. Figure 1 shows a dashboard created with Information Builders WebFOCUS business intelligence platform. Note that all the text is gray except for the problems, which are black and slightly larger. Even the axes values and borders are displayed in gray, which makes the text in black more apparent. Icons further draw the user’s eye to the data that needs attention so that observations can be made.
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