Dashboards are more common than you may think. Each one of us frequently uses these, from complex stock trading applications to the front panel of a car. Dashboards are, in fact, all-pervasive.
More often than not, we think of dashboards as screens exhibiting visualizations of complex data. This notion may be inspired by sci-fi movies that flaunt animated dashboards with volumes of data. But in reality, that is not true for all types of dashboards. As far as the real world goes, dashboards are categorized as operational and analytical. While you can create dashboards which are a combination of analytical and operational, they are typically defined as either of these types.
Operational and Analytical Dashboards
Operational dashboards, to put it simply, aid users in carrying out actions. Financial trading apps are examples of operational dashboards. These not only show information about financial assets but also enable the users to perform operations like buying and selling stocks. Good trading apps are designed in a manner that allows users to track asset prices in almost real time and place their buy or sell orders quickly and with minimum effort.
Analytical dashboards are designed to display large volumes of data in a way that helps users to interpret the information. They are typically used in reporting, business intelligence, and analytics applications, where the purpose is to summarize these large volumes of complex data in a fashion as allows the user to make sense of it all.
Google Analytics, a tool used to analyses site traffic is a good example of an analytical dashboard.
Designing a good dashboard is something that can be a challenge for designers. Here are a few principals that designers can follow to design useful, usable, and delightful dashboards.
1. Anticipating the User’s Needs and Goals
All the core principles of good UX Design apply to the design of dashboards. Asking and answering questions like how a dashboard will be used and what information does the user need to be successful, helps identify the information that is meaningful for your dashboard.
2. Deciding which Type of Dashboard the User Needs
If your objective is to present information, you need to use analytical dashboards. If you also want the user to take some action(s) on the basis of information, an operational dashboard is more suitable.
However, irrespective of the type of dashboard, keep in mind that a well-designed dashboard will convey the right information without inducing cognitive overload.
3. Choosing Metrics that Matter
For analytical dashboards, deciding the right metrics, relevant to the dashboard’s purpose is the key. Decisions like what kinds of data to choose, and how to present it, should be grounded in a thorough understanding of user needs and context. Including metrics that are irrelevant, can make the dashboard look cluttered, and the user can quickly lose interest.
To determine which metrics earn a spot on your dashboard, consider how much detail does the user need. You should provide easy ways for the user to dig deeper into the data in case they need to.
4. Telling a story
Dashboards should provide a snapshot of what is going on, and prioritize the information for what the users really need to see at the moment. All the metrics you choose should combine to tell a holistic story to the user.
5. Using the Right Data Visualizations Tools
For analytical dashboards, choosing appropriate kind of data visualization is imperative. Data visualization tools help organize data in a manner that is easily understood. Cluttering your charts with superfluous data labels is only useless since the values plotted on the bar charts can be deciphered well without plotting the actual value.
Here are a few tips that should help you use data visualization in an effective manner.
Pie charts: Use these to show comparative information.
Bar charts: Use these for comparative information, but with more variables.
Graphs: Use these for measuring trends over time.
Tables: Use these for sorting various variables; for helping organize and communicate meaning.
The Gestalt Principles of Visual Perception
For perfecting the skill of creating exceptional dashboard design, it is very important to learn the basic Gestalt principles of visual perception apart from exploring how to vividly convey actionable information in a particular context.
Gaining a sound understanding of these principles can enable you to devise a better dashboard structure, besides making your charts simpler and easier to translate.
Proximity: It means the tendency to see multiple elements as groups when they are located close to one another. Implying by example, we can visually end up distinguishing visually, the clusters on a scatter diagram simply by grouping the dots that lie closely.
Similarity: It is our brain’s natural response to associate the elements that appear similar to one another (for e.g. in shape, orientation, size, or color). For example, when looking at a color-coded bar chart, readers can easily associate the bars that have been presented in the same color, even if there is no evident mention of their grouping.
Enclosure: If a series of elements or objects are surrounded by a border, they are perceived as a group. For example, if a scatter diagram exhibits reference lines that seem to be surrounding the objects, say, between 40 and 50 percent, our brain will tend to consider them a cluster.
Closure: If we see a figure that seems incomplete, we form a perception that it is a closed structure. Taking the example of borders again, even if we do away with the borders that enclose a bar chart, our brain will lead us to consider the axes as the lines that isolate the graph and eradicate the need for extra lines.
Continuity: We perceive a number of objects that are closely aligned, as a continuous body. For example, if the eye starts following an upward trend line of dots, it will continue to do so till it encounters another object that breaks this continuity.
Connection: When we see objects connected by any uniform visual property, we will perceive them as a group as opposed to other elements that are not connected in this fashion. For example, we consider the dots connected by a frame or a line on a scatter diagram as a group.
Creating dashboard design with these aims and principles in mind can be pivotal in arriving at dashboards that are simple, elegant, and easy for the user to decode. It’s about time you based your endeavor on it.