What is Chart Junk?

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By Brant Wilkerson-New
June 17, 2024


We’ve all seen them — charts and graphs that are so cluttered and overloaded with unnecessary elements that they actually cause confusion rather than providing clarity. 

This phenomenon is known as “chart junk” and it can seriously sabotage the effectiveness of your data visualizations.

We’ve all seen them – charts and graphs that are so cluttered and overloaded with unnecessary elements that it’s nearly impossible to decipher the actual data. This phenomenon is known as “chart junk” and it can seriously undermine the effectiveness of your data visualizations.

In this post, we’ll provide a few guidelines on recognizing chart junk and how you can avoid it.         

Why is chart junk bad?

The main problem with chart junk is that it distracts the reader from the actual data you’ve produced.

Instead of clearly driving home your key insights, the viewer’s eye is drawn to the shiny objects – superficial design elements that are far less significant than the substance of your hard work. This can lead to confusion and a misinterpretation of what your data actually proves.

Along with that, chart junk can give your work an unprofessional feel and cause the audience to doubt your credibility. 

Here are several elements to avoid when creating visuals:

3D effects

Unless your presentation is focused on poor design from the 90’s, avoid 3D effects in graphs, charts, or other data. It just doesn’t work. 

Excessive use of color

Stick to just using a few simple, neutral colors to avoid overwhelming the reader or distracting them from the data. Bright colors

Redundant labels

When making a graph, the labels belong along the axis or in a key. Placing them directly on a bar graph or pie slice creates clutter.

Decorative backgrounds

Simplicity is the best approach when it comes to backgrounds. Stick to muted, neutral colors and absolutely avoid using obvious patterns. 

Unnecessary gridlines

Eliminate gridlines where possible, and when they must be included, keep them thin. Bold lines can confuse readers and distract them from actual data.

Overuse of text

Adding lengthy explanations or annotations directly on the chart can obscure the data and make it challenging to focus on the key insights.

Inappropriately styled data markers

Keep markers simple, small, and consistent so as to not draw attention.

Misaligned or inconsistent scales

Be sure the X and Y axes use a similar scale and consistent increments to help readers draw the correct conclusions from the data. 

Gratuitous use of icons or images

Images and icons should be completely avoided in graphs and charts, except in very rare circumstances. If you find yourself with an urge to include one, consider what it adds for the reader.

Overcomplicating chart types

Bar charts, line graphs, and pie charts are so prevalent because they’re generally the best options for relaying data. Don’t overthink it and use a complex or unconventional chart when a simple option would suffice.

Best Practices for Creating Clear and Effective Visualizations

To create visualizations that effectively communicate your data and insights, follow these best practice to avoid chart junk:

Clear and concise title

Provide a title that accurately describes the content of the chart and helps the viewer understand the main takeaway.

Good labels

Ensure your axes and data points are labeled clearly and accurately – figuratively and literally. Along with using precise language, use a legible font size and style.

Consistent color scheme

When you’ve chosen a good neutral, muted color scheme, keep it consistent throughout your entire presentation. Those tiny details not only look great, but also add to your credibility with the audience. 

Highlight key data points

Used correctly, data labels and annotations can guide your readers to the most important data that will help them draw conclusions.

Provide context

Context always matters, so don’t be afraid to use brief explanations to introduce a chart or an annotation that will help with clarity.

Optimize for readability

As with any professional presentation, you won’t go wrong with a standard, easy-to-read font with good spacing. When in doubt, give your text room to breathe.

Continuously Improve 

Creating effective data visualizations is an iterative process.

Even if you’ve nailed every best practice in creating a chart or graph, it’s important to seek feedback from another source to identify areas for improvement. Share it with a trusted colleague, manager, or even your partner or roommate. Friends outside your field might even be able to offer a unique perspective.

When soliciting feedback, ask specific questions such as:

    • Is the main message of the visualization clear?
    • Are there any elements that are confusing or distracting?
    • Is the color scheme appropriate and easy to interpret?
    • Are the labels and annotations sufficient for understanding the data?

Actively listen to the feedback you receive and be open to constructive criticism. Consider each suggestion and evaluate whether incorporating the feedback would enhance the clarity and effectiveness of your visualization.

Once you’ve gathered feedback, prioritize the suggestions based on their potential impact and feasibility. Implement the changes that will most significantly improve your visualization while maintaining a clear and concise design.

Remember, the goal is to create visualizations that effectively communicate your data and insights to your audience. By continuously seeking feedback and refining your designs, you’ll develop a keen eye for creating compelling and impactful data visualizations that drive better decision-making and understanding.

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