Flag

We stand with Ukraine and our team members from Ukraine. Here are ways you can help

Get exclusive access to thought-provoking articles, bonus podcast content, and cutting-edge whitepapers. Become a member of the UX Magazine community today!

Home ›› Business Value and ROI ›› 6 Key Questions to Guide International UX Research ›› Four Cognitive Design Guidelines for Effective Information Dashboards

Four Cognitive Design Guidelines for Effective Information Dashboards

by Shilpi Choudhury
4 min read
Share this post on
Tweet
Share
Post
Share
Email
Print

Save

Following cues from cognitive science can help you create information dashboards that users can process reliably and quickly.

Effective data visualization supports cognition in many ways. It reduces cognitive load on the user, aids in problem solving, and facilitates discovery of insights. Poor visualizations, on the other hand, confuse and lead to wrong conclusions.

Since cognitive science has given us tremendous understanding of the mechanisms and processes by which we perceive things, comprehend them, and use them for decision-making, it’s reasonable to assume that such findings are very relevant to dashboard design issues. How users interpret data, what demands our designs place on their attention, what knowledge they need for making effective decisions―all these factors need to be considered while designing an information dashboard. Here are four guidelines derived from studies on human cognition that can be applied while designing information dashboards:

1. Put an Emphasis on Readability

To perform any kind of analysis using a dashboard, the user must be able to extract and process visual stimuli reliably and quickly. The interface should be such that it guides visual processing and doesn’t deter it.

Smashing Magazine image

Image source: Smashing Magazine

In the visualization above, the busy background image makes the chart cluttered and reduces its readability. To enhance readability, there should be proper contrast between the chart background and the data plots.

Using a dashboard, the user must be able to extract and process visual stimuli reliably and quickly

Also, prioritization of information helps make the dashboard more readable. As Amanda Cox, Head of The New York Times Graphic Department once noted, “Data isn’t like your kids. You don’t have to pretend to love them equally.” Know where to focus your user’s attention.

Dashboard Formatting

Image Source: Stephen Few, With Dashboards Formatting & Layout Definitely Matter

The layout of the dashboard can be roughly divided into four quadrants based on the importance it accords to its respective content. The top-left quadrant is the section that gains the maximum attention from the user so the most important metrics should occupy this section. The other metrics should then be distributed based on their order of importance.

2. Minimize Cognitive Load

Theoretical insights into cognitive architecture emphasize the memory constraints of humans. These lessons have been learned by the HCI community who argue that interaction sequences should be designed to minimize short term memory load. Since recognition memory is superior to absolute recall, the dashboard should provide all the information that the user needs for a specific analysis in front of his or her eyes. (The details of how a dashboard can reduce the dependence on short term memory are covered in my article “The Psychology Behind Information Dashboards”.)

3. Use Graphical Representation

We are wired for visualization. Whether it’s graphs putting raw data into a perspective or the use of icons, which helps to overcome issues of limited real estate, we do value a picture over a thousand words.

Sprout Social dashboard

To make dashboards easier to comprehend, couple icons with one-two word text labels (pop-up or otherwise) that explain the meaning to users who find the representations difficult to decipher.

4. Follow Gestalt Laws

Gestalt psychology offers a set of laws that explain how we perceive or intuit patterns and conclusions from the things we see. Applying these laws to charting and data visualization can help users easily identify patterns in their data. Some of these laws are:

Law of Prägnanz: This law states that the human brain tends to process simple patterns—patterns that are regular, even, and orderly—faster than patterns that are more complex. To understand this, consider the two charts below. If you were asked to find the top performer from these two charts, which chart would you find easier to get the data from?

It is easier to see that James is the top performer in the second chart because the data plots are ordered here. If the data is name or category-based, and not time-based, it is a good idea to arrange the data in descending/ascending order.

Law of Focal Point: This law states that in a visual presentation, distinctive objects create a focal point. For example, if you want to focus your user’s attention on a specific data point, you can create a focal point by using a different color.

In this chart, China is the focal point due to its difference in color from the other data plots.

Further reading: How to Make Data Visualization Better with Gestalt Laws

Conclusion

Information dashboards aim to augment human cognitive abilities and aid in decision-making. The challenges of designing an effective dashboard are many, but the potential benefits make this a challenge worth pursuing. The key is not in finding what’s most exciting or what’s most outside-the-box but in applying simple concepts which we know but still tend to overlook.

Image of colorful brain courtesy Shutterstock.

post authorShilpi Choudhury

Shilpi Choudhury

 

I am the Co-Founder & Chief Storyteller at Lemonade in Summer, a design and communications agency based out of Bangalore, India. I love to write about Content Marketing, Design and UX. I blog here.

Tweet
Share
Post
Share
Email
Print

Related Articles

AI is reshaping UX, and Figma may be sinking. As AI-driven systems minimize UI, traditional design roles must evolve — or risk becoming obsolete. Are you ready to adapt?

Article by Greg Nudelman
AI Is Flipping UX Upside Down: How to Keep Your UX Job, and Why Figma is a Titanic (It’s not for the Reasons You Think)
  • The article explores the fundamental shift in UX as AI-first systems minimize the role of UI, rendering traditional design tools like Figma increasingly obsolete.
  • It introduces the “Iceberg UX Model,” illustrating how modern AI-driven interfaces prioritize functionality and automation over visual design.
  • The piece argues that UX professionals must shift their focus from UI aesthetics to AI-driven user experience, emphasizing use case validation, AI model integration, and data-informed decision-making.
  • It warns that designers who remain fixated on pixel-perfect layouts risk becoming obsolete, urging them to adapt by engaging in AI-driven UX strategies.
Share:AI Is Flipping UX Upside Down: How to Keep Your UX Job, and Why Figma is a Titanic (It’s not for the Reasons You Think)
7 min read

Data visualization isn’t just about charts — it’s about telling a clear and compelling story. This article unpacks a wide spectrum of essential principles for making data easy to understand, honest, and engaging. Ready to transform complex numbers into meaningful insights?

Article by Jim Gulsen
The Ultimate Data Visualization Handbook for Designers
  • The article serves as a comprehensive guide for elevating visualization work, combining technical expertise with design principles to help designers transform raw data into meaningful insights.
  • It provides a point of reference for strategies, methods, and best practices to create more effective and impactful data visualizations.
  • The piece recommends tools and resources that design professionals can immediately implement to enhance the clarity and persuasiveness of their data storytelling.
Share:The Ultimate Data Visualization Handbook for Designers
23 min read

Discover how breaking down silos and embracing cross-functional collaboration can lead to smarter, more user-centered design — and better products for everyone.

Article by Rodolpho Henrique
Beyond the Design Silo: How Collaboration Elevates UX
  • The article explores how siloed UX design practices can hinder product success and argues for cross-functional collaboration as essential to creating meaningful user experiences.
  • It outlines the benefits of working closely with product managers, engineers, and stakeholders to align user needs with technical feasibility and business goals.
  • The piece provides real-world collaboration examples across research, prototyping, design systems, and accessibility to show how teamwork leads to more innovative and effective UX outcomes.
Share:Beyond the Design Silo: How Collaboration Elevates UX
4 min read

Join the UX Magazine community!

Stay informed with exclusive content on the intersection of UX, AI agents, and agentic automation—essential reading for future-focused professionals.

Hello!

You're officially a member of the UX Magazine Community.
We're excited to have you with us!

Thank you!

To begin viewing member content, please verify your email.

Tell us about you. Enroll in the course.

    This website uses cookies to ensure you get the best experience on our website. Check our privacy policy and