Choosing the Right Chart Type for L&D Data: A Guide to Effective Visualization

Chart selection: Your secret weapon for L&D data storytelling

Choosing the right chart type is more than an aesthetic decision; it’s strategic. The appropriate visualization can showcase patterns, trends, and insights that might remain unseen in raw data. And conversely, using the wrong visualization can cause more confusion than clarity.

In other words, the right chart type can be the difference between a persuasive narrative and a confusing jumble of numbers.

Factors to consider when selecting a chart type

Before we get into specific chart types, it’s important to consider several key factors that should guide your selection:

1. Assess the nature of your data: Is it categorical, numerical, or time-based? Each type lends itself to different visualization methods.
2. Consider the variables you’re dealing with, as some charts handle multiple variables better than others. The purpose of your visualization is also crucial—are you making a comparison, showing distribution, illustrating relationships, or spotlighting a metric? Your goal should guide your chart choice.
3. Always keep your target audience in mind. Complex visualizations might impress data scientists but confuse executives who need quick, easy-to-digest insights.

Common chart types in L&D: Advantages and limitations

Let’s explore some chart types frequently used in L&D contexts and how they apply to specific scenarios.

Bar and column charts

Advantages: Bar and column charts are ideal for comparing categories or showing changes over time. For instance, they’re perfect for visualizing course completion rates across different programs.

Limitations: Bar and column charts can become cluttered with too many categories, so you should order bars by value for a more straightforward interpretation.

Scroll through the following images to see how the bar chart on the left uses multiple colors unnecessarily and presents data in a disorganized manner, making it difficult to compare course completion rates effectively. The simplified bar chart on the right clearly displays completions of popular curriculums, using a single color and sorting data in descending order for easy comparison and interpretation.

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Line charts

Advantages: Line charts display trends over time or compare multiple data series, making them ideal for tracking learner progress throughout a program.

Limitations: Line charts can be misleading if the y-axis doesn’t start at zero. Always use consistent intervals on the x-axis for accurate representation.

Scroll through the following images to see how the cluttered line chart on the left overwhelms viewers with weekly fluctuations in completion rates, making it nearly impossible to discern meaningful trends or patterns in the training data. The line chart on the right effectively displays average assessment scores over months, revealing an overall upward trend and a significant improvement in September, enabling easy interpretation of training program effectiveness.

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Pie and donut charts

Advantages: Pie and donut charts are often used to show the proportions of a whole, such as illustrating budget allocation among different L&D initiatives. However, you should use them sparingly and only when you have a small number of categories to compare.

Limitations: Pie and donut charts become difficult to interpret with many categories. It’s best to limit them to 5 to 7 categories max and consider alternatives for more complex data.

Scroll through the following images to see how the pie chart on the left overcomplicates compliance training data with too many categories, making it difficult to quickly grasp key information or compare proportions effectively. The chart on the right clearly shows the Global Risk & Compliance Certification status, using just three categories and providing an option to show percentages for easy interpretation.

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Scatter plots

Advantages: Scatter plots are excellent for showing relationships between two variables. They can be particularly useful in L&D for exploring correlations between factors, such as training hours and performance improvements.

Limitations: Scatter plots can be confusing for people who are unfamiliar with them. Include trend lines to help highlight correlations and make the data more accessible.

Scroll through the following images to see how the scatter plot on the left ineffectively uses dates on the y-axis and lacks clear correlation between variables, making it difficult to interpret meaningful patterns or relationships in the data. The one on the right effectively illustrates the relationship between supplier warranty defects and training completed, using clear quadrants and well-labeled axes to facilitate easy interpretation of trends and performance categories.

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Heat maps

Advantages: Heat maps visualize complex datasets with multiple variables. In L&D, they can effectively display performance metrics for multiple departments across various skills or competencies, making them ideal for comprehensive skill gap analyses.

Limitations: Heat maps may require some explanation for less data-savvy audiences. Using intuitive color scales (e.g., red for high, blue for low) can help make them more immediately understandable.

Scroll through the following images to see how the heatmap on the left has too many metrics across numerous departments, resulting in a cluttered, hard-to-interpret, and overwhelming visualization. The one on the right clearly presents final assessment scores for specific topics across individuals, using an effective color scheme and sorted data for easy comparison and spotting performance trends.

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Spider charts

Advantages: Spider charts (a.k.a. radar charts) compare multiple variables across various categories. For instance, you can use them to illustrate current skill levels versus desired levels across various competencies, providing a clear visual representation of skill gaps.

Limitations: Spider charts can be overwhelming with too many variables, so limit charts to 5 to 8 for the best clarity. You should also limit the number of series displayed to prevent them from being unreadable.

Scroll through the following images to see how the spider chart on the left displays too many skills across multiple departments, resulting in a cluttered visualization with overlapping labels and confusing color schemes. The chart on the right is clear, focused, and effectively compares priority skills against benchmarks, using a limited number of key metrics and a simple color scheme for easy interpretation and insights.

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Creating comprehensive L&D insights and ensuring accessibility

Sometimes you need several chart types to tell your whole data story. Creating dashboards that combine multiple chart types can provide a more comprehensive view and cohesive story, guiding the viewer through the data narrative.

For instance, the following dashboard shows the effectiveness of a customer service training program. It includes a line graph tracking customer satisfaction ratings over time for those who attended onboarding sessions versus those who didn't, a bar chart displaying individual CSAT assessment growth, and a scatter plot correlating CSAT scores with tickets resolved.

When creating charts, it’s essential to consider accessibility. Use high-contrast color palettes and avoid relying solely on color to convey information. Provide alternative text descriptions and, when possible, use more straightforward chart types that are easy to describe and digest.

Interactive elements can enhance data exploration, allowing users to drill down into details or toggle between different views. However, balance is key. Too much interactivity can overwhelm users and obscure the main message. In other words, use interactivity purposefully to support your data story.

Up Next: Bar charts & column charts—your new best friends in L&D

Selecting the right chart type is critical for effective L&D data visualization. You can create visualizations that inform and inspire action by considering your data type, audience, and storytelling goals. Remember, the best chart is one that makes your audience say, “Ah, now I see!”

As you continue your data visualization journey, experiment with different chart types. Practice creating visualizations with your L&D data, and focus on which ones resonate most with your stakeholders. With time and experience, you’ll develop an intuitive sense for choosing the right chart for every data story you need to tell.

Join us for the next post in this series, where we’ll cover bar and column charts, exploring their versatility in comparing data, tracking progress, and showcasing L&D achievements across various learning initiatives.