Best Practices for Dashboard Design: Four Essential Ideas
Gathering requirements, identifying KPIs, and developing a data model are typically steps in a thorough business intelligence process that culminates in building an effective dashboard in accordance with best practices for dashboard design.
Read More: Dashboard design
It is important to remember that a badly designed dashboard may not provide the necessary information and insights, or it may even make the data less understandable than it was before.
An outstanding design is one that
simplifies the complex: there is a wealth of data, a constant flow of information, and a variety of analytical requirements and queries. Our goal is to simplify all of this complexity.
Tells a clear story: We want to be able to respond to the viewer’s inquiries and make the connection between the data and its context in the company. This is where a dashboard’s visual design comes into play.
communicates the meaning of the data: The information you wish to extract from the data and the data itself must be accurately represented by the data visualizations you have selected.
Details are revealed as needed since we want every viewer to have access to the information they require, neither more nor less. While some users may want access to a more detailed perspective of the data, others may find that an overview is sufficient.
Although every data dashboard has its unique specifications, constraints, and objectives, there are certain general rules that apply to dashboard design practically all the time. We’ll go on to discuss four of these concepts and show you how to immediately implement them into your dashboards.
What bad design decisions stand out right away?
About thirty widgets is too numerous, and it clutters the screen.
Simple inquiries like “what is the total amount of sales” take a lot longer than five seconds to respond.
The visual layout lacks a clear organizing concept, with widgets seeming dispersed all over the place.
Little information is added by the tables at the bottom.
This dashboard might have been significantly enhanced by using the following best practices for dashboard design.
1. The Fifth Rule
Your dashboard ought to provide instantaneous answers to the business queries you ask most frequently. This implies that if you’re looking at the data for minutes, there may be an issue with the visual design of your dashboard.
Try to adhere to the five-second rule when creating a dashboard; this is the amount of time you or the pertinent stakeholder should need to spend searching through the dashboard to obtain the information you need. Ad hoc research will, of course, take longer, but the most crucial metrics—those that the dashboard user needs most frequently during her workday—should be readily apparent on the screen.
2. Inverted Pyramid as the Logical Arrangement
Sort the dashboard by displaying the most important insights at the top, trends in the center, and more information at the bottom.
It’s crucial to adhere to an organizational concept while creating a dashboard. The inverted pyramid is among the most practical (see illustration). This idea, which came from the world of journalism, essentially divides a news report’s contents into three sections in decreasing order of importance: general and background information, which will contain much more detail and allow the reader or viewer to delve deeper, is at the bottom; this is where you’ll find the most important and substantial information, followed by the significant details that help you understand the overview above them.
In what way does dashboard design connect to a journalistic technique? As with news stories, the main purpose of business intelligence dashboards is to convey a story. With the most important and high-level insights at the top, followed by the trends that provide context for these insights below, and the greater granularity information at the bottom that you can dig down into and examine deeper, your dashboard’s narrative should make sense internally.
3. Less Is More with Minimalism
There shouldn’t be more than five to nine visualizations on each dashboard.
In an attempt to provide a more comprehensive image, some dashboard designers feel compelled to jam as much facts as they can onto their dashboard. Although this seems reasonable in principle, cognitive science informs us that the human brain can only process around 7+-2 pictures at a time; hence, you should only have this many things on your dashboard. Any more beyond that merely serves to obstruct and obscure the dashboard’s primary function with visual noise and clutter.
Using filters and hierarchies—for example, allowing the user to apply a filter that changes the same indicator between North American and South American sales amounts—as well as splitting your dashboard into two or more distinct dashboards—are effective ways to reduce visual clutter.
4. Selecting an Appropriate Data Visualization
Depending on the goal of the data visualization, choose the right kind.
I won’t go into too much depth here because we’ve already discussed about data visualization techniques in previous posts, but let me just state that the goal of data visualization is to do more than just look good; it should accomplish a specific goal and communicate particular information more successfully than a simple tabular format.
Prior to selecting a visualization, think about the kind of information you want to convey:
Relationship: the association of two or more factors
Comparison: side-by-side comparison of two or more variables
Composition: dividing data into distinct parts
Distribution: a data set’s range and grouping of values
Dashboard Design: Additional Considerations
Making ensuring your end users comprehend what they’re looking at requires careful consideration of other factors in addition to selecting the appropriate depiction. One important consideration in dashboard design is identifying the first end-user of the dashboard.
For instance, you should definitely concentrate your widget design on data that can boost conversion rates while creating a dashboard for a user that is primarily concerned with ad platform optimization. Examining more specific metrics, such cost per mille (CPM), makes sense because your end user is directly involved in every ad’s daily operations. A vice president of marketing, however, is likely only interested in the broad details of how lead generation is affected by ad success at first sight.
To that end, as we previously discussed, meet down with your end users to gather needs and establish KPIs before jumping straight into dashboard design. If you don’t do it, even with the most exquisite dashboard design in the world, consumers’ decision-making process won’t be altered over time.