Avoid common chart design mistakes

The goal is the design

Imagine a client sends you a massive Excel file. You might head to Dribbble for inspiration and design something complex and beautiful.

But here is the reality: there are many ways to visualize data, but there's usually only one best way to communicate a specific message. The design magic isn't in the look; it's in the goal. What is your chart's job? To answer a question? To push an audience to act? Or just to highlight key insights?

As Nicholas P. Desbarats says: “If you don’t know why you’re creating a chart, your chart will communicate random insights.”

So forget "what looks cool." Ask: what job does this chart need to do?

The 3 most used charts: defining their job

There are countless chart types out there. Picking the right chart always comes down to effectiveness, how well it nails the job. Let’s focus on the three workhorses of data visualization.

1. Bar Charts (Since 1786: the comparison machine)

Invented by the Scottish economist William Playfair in 1786. The bar chart remains the best tool for comparison. Bar charts are accurate, super easy to read, and incredibly flexible Whether they are horizontal, vertical, or stacked, they just work. Use them for:

Use them for:

• Comparing values across different categories.
• Clearly showing ranking or differences in magnitude.
• Making precise comparisons between data points easy.

(Image description: When designing a bar chart)

2. Line Charts (The trend spotter)

Also introduced by Playfair, these are your best friend for showing change over time. They're intuitive for spotting trends and patterns, making them essential for monitoring metrics.

How to visualize trend and change over time with the Line Chart? While time traditionally flows left-to-right, if you're designing for a local right-to-left (RTL) audience, consider reversing the horizontal axis so time moves from right to left. This aligns the data's flow with the audience's natural reading direction.

‍(Image description: Line chart optimization: tips for clear trends)

3. Pie Charts (The problem child: 1801)

Playfair is responsible for this one too, though he might regret it. Simple and familiar to non-experts, they are the most criticized charts today, often overused and misused.

Here is why they are frequently misused:

1. Visual inaccuracy
   Humans are better at comparing length (bar charts) than angles or area (pie charts). Small differences between slices (e.g., 22% vs. 25%) are nearly impossible to detect visually without numerical labels.
2. Low scalability
   Clutter: More than 5 slices make the chart unreadable.
   Thin Slivers: Small categories become "slivers" that are hard to see and impossible to label directly.
3. Poor comparison
   Comparing two pie charts side-by-side is difficult. Tracking how a specific slice changes between two circles is far less intuitive than seeing a bar grow or shrink.

Therefore, if you need to show precise values, skip the pie and use a bar chart.

Use pie charts for:

• Showing parts of a whole (100%).
• If there are very few categories (ideally 2–5, max 6).
• If the goal is rough comparison, not precise values. Tip: If the segments are almost the same size, switch to a bar chart immediately—your user cannot accurately compare angles.

(Image description: Pie chart: tips for a good design)

A visual checklist: focus on the details

A smart chart is one that stays out of its own way. Use these suggestions to improve your data storytelling:‍

Color and palettes

• Avoid highly saturated, jarring colors.
• Avoid varying colors unnecessarily; use color to communicate meaning, not just decoration.
• With sequential categories (e.g., small to large), use a sequential palette.
• For communicating "good" or "bad" values, a red/green or indicator works best.
• Use black, gray, and white for supporting context: totals, missing values, "others," etc.

Typography and Context

• Pick a typeface that’s easy to read.
• When dealing with lots of numbers, choose a typeface with monospaced and lining numerals to ensure columns line up perfectly.
• Hide the final digits of large numbers (e.g., use 1.2M instead of 1,200,000) unless that high level of precision is absolutely required.
• When showing dates, favor formats with alphabetic months (Jan 2025) and four-digit years.

Stop creating charts that look good. Start creating charts that work. The better your chart does its job, the better your design is.

Level up your data Viz: considering accessibility

A sleek chart is useless if it’s not accessible. Our goal is to give everyone, including people using screen readers or those with color blindness, an instant understanding of the data.

Here is the lowdown on making your charts inclusive:

‍1. Ditch "Color-Only" coding

Color should never be the only way to tell data apart. If you flip your chart to black and white and it becomes a guessing game, it’s not accessible.

• Use texture: Add patterns, dots, or dashes to bars and lines.
• Direct labels: Skip the legend and label your data points directly. It reduces the cognitive load for everyone.

2. Respect the contrast

Those light-grey axis lines might look "minimalist," but they’re invisible to many.

• The rules: Aim for 3:1 contrast for graphics and 4.5:1 for text.
• The check: Use a contrast checker to ensure your markers and labels actually pop.

3. Write a "TL;DR"

Screen readers can't "see" your pixels. Give them a narrative alternative.

• Summarize: Add alt-text or a caption that explains the trend (e.g., "Sales peaked in July and dipped in December").
• Explain: For complex visuals, write a short paragraph nearby explaining the key takeaways.

4. Provide data tables

Always include a clean, well-structured data table below your chart. Screen reader users often prefer tables because they can explore the raw numbers at their own pace. If the chart is complex, break it into multiple simple tables rather than one giant, messy one.

Conclusion: intentional visualization

Ultimately, data visualization is more than just making things look pretty; it's a critical design skill. The main takeaway? Your intention must drive the design from the start. 

By defining the chart's goal, sticking to reliable chart types. Bar and line charts are your essentials for trends and comparisons.  And carefully polishing the look (think the right color, clean fonts, and clear context), you turn a raw data file into an undeniable, "I get it" insight. Always prioritize accessibility: high color contrast, clear information for screen readers, and keyboard navigation.

If you're ready to master this, you need to check out Nicholas P. Desbarats. His book, Practical Charts, gives you the complete guide for effective, ethical data communication.

Want to work with Hike One? 

Schedule a call with a designer to see how we can improve your charts. We build clear systems so your team can act on data without getting overwhelmed.