Dashboards: Basics and Best Practices

Explore the best practices for building dashboards to visualize critical data

Visual Design

12 exercises

Dashboards are tools that visually represent complex data in a simplified manner. They offer a complete overview of crucial information, allowing users to make quick, well-informed decisions. Used across industries like finance, marketing, healthcare, and project management, dashboards are indispensable for monitoring performance, identifying trends, and guiding data-driven strategies.

For designers, mastering dashboard design principles is crucial. It empowers you to create user-friendly interfaces that prioritize user needs and enhance overall usability.

Determine your audience’s needs

Dashboards can sometimes be confusing and overwhelming for users, which can lead to spending a lot of time trying to figure out how to use them. To avoid this, you can start by understanding what kind of information your users want to see on the dashboard.

User research is the best way to get accurate information about:

When and why users will look at and analyze the data
What brings users to the dashboard and what difficulties they might face
The specific information users need to see, compare, and analyze on the dashboard
The order of importance for different parts of the dashboard and how they should be arranged
Options for customization based on individual preferences
How familiar users are with the technical aspects of the system

Also, consider your business goals when designing a dashboard. Ask yourself what actions you want your users to take and how it can help your business.^[1]

Operational dashboards

Operational dashboards focus on displaying real-time critical data that constantly change their values and statuses. They're great for monitoring tasks that may require an immediate response, like patient vitals during surgery or flight traffic.

Operational dashboards provide frequent data updates and should be comprehensive enough at first glance. They must communicate information so clearly that users can quickly spot critical parameter deviations and take action.^[2]

Analytical dashboards

As the name implies, analytical dashboards provide information for analysis, investigation, research, and thoughtful decision-making. In contrast to operational dashboards, they aren't time-sensitive and don't require immediate action.

Sales dashboards are a common example of analytical dashboards. They provide thought information for sales managers about fluctuating sales data that may require thoughtful analysis rather than rapid intervention.

Use enough white space to simplify content scanning

The human brain has limitations when it comes to processing large amounts of information simultaneously. While this might seem counterintuitive for data-rich dashboards, there's a solution. The strategic use of white space can effectively segment related content, improving its overall legibility. Moreover, it serves to highlight crucial elements, providing them with breathing space for better comprehension.

Ensure that there's ample space between different data points, graphs, and textual elements. This not only prevents visual overload but also directs the user's attention to the most critical information.

Use labels for better navigation

When there's too much information, the human eye needs visual anchors that help scan the dashboard more effectively. Assign this work to labels, or section titles, as they group related content and guide users throughout the page.

Ensure that these labels and section titles are distinctive, using contrasting colors or typography to make them stand out. Additionally, they should be thoughtfully positioned to create a logical flow, aiding users in comprehending the content's organization.

Separate content groups

Just as kitchen containers organize spices, teabags, coffee, and sugar, dashboard containers help sort content. Accompany them with white spacing, titles, and visual dividers to distinguish content groups and organize the layout.

Remember that content within a boundary is perceived as a group. This is because according to the principle of the common region, users assume the information inside containers shares some common characteristics or functionality. Consequently, everything outside the container frames belongs to a different category.^[3]

Prioritize content to guide users' attention

When crafting a dashboard and thinking of where each container should go, start with prioritizing content. According to eye-tracking studies, people don't read the information on web pages word by word — they scan.

There are multiple scanning patterns, and which one users choose depends on:

Their task
Their prior experience of reading on the web
The page layout
The type of page content (text or images)^[4]

For example, the F pattern is people's default scanning pattern and is more typical for content-loaded pages, like news websites. The zigzag and lawn-mower patterns are more common for pages with distinct cells of content, like dashboards, or pages with small amounts of copy, like landings.

Regardless of the layout pattern, you should know how to lead users toward the desired destination. Use clear, evident headings and subheadings and place the information of core interest in the most scannable spots to direct users' attention.

Pro Tip! Avoid scrollable dashboards as they can cause users to expend extra effort. Instead, strive for less and prioritize essential content.

Use consistent structure

Ensure structural consistency in content containers on dashboards. Like a family, each member may have unique traits, but their appearances should share commonalities. Apply consistent left alignment, title sizes, and margins for each container. This approach makes dashboards more reliable for users and allows for greater flexibility and scalability in responsive design.

Allow users to compare content groups

When you have lots of information to show on one dashboard, interactive tools like tabs or pop-up boxes are really helpful. However, there's a catch. Don't use these for groups of content that users need to compare at the same time. And never hide information that should always be visible.

For example, if you're showing sales data for different regions, it's better to display it all at once instead of making users click on tabs to see each region separately. This way, they can easily compare the numbers. And remember, always keep important information visible without needing to click or hover.

Avoid overwhelming users with content

Sometimes, designers try to squeeze massive amounts of data into one dashboard, and bluntly speaking, it turns into a mess. When everything seems important, nothing is important. Thus, be respectful to your users and avoid overwhelming them with data they won't be able to process.

Let the project goals, user needs, and the nature of data guide you in choosing the most relevant widgets and graphs. Ask yourself: "What specific problem will this dashboard help users solve?" The answer will reveal which metrics, properties, values, visuals, and data are essential for completing a goal and which are useless and should be removed.

Allow users to customize dashboards

A personal touch can help your dashboard users feel comfortable. This means offering content and tools that suit different user roles. Customization is a big part of this because it lets users arrange content and tools to their liking.

In systems with many different roles, customization is crucial. It ensures that everyone, with their unique needs and tasks, can make the dashboard work just right for them. For example, a sales manager might want to see revenue figures first thing, while a customer service agent might prioritize support ticket updates. Customization makes these adjustments possible.

Select the right chart type

Charts are powerful tools for illustrating complex data effectively. However, choosing the right chart type is crucial, as it depends on the specific goals and needs of users.

Consider why users need graphs:

Use line charts or bar charts to track changes and trends over a period.
Opt for scatter plots when analyzing correlations or associations between different data sets.
Employ box plots to grasp the spread and distribution of data over a specific timeframe.
Utilize pie charts or stacked bar/area charts to represent components in relation to the whole.

According to Nielsen Norman Group, bar charts, line charts, and scatter plots are the easiest to understand.^[5] Selecting the wrong chart type can overload cognitive processing and hinder data comprehension. This may lead users to abandon the product if they struggle to interpret the charts efficiently.