The Component Comparison and its different alternatives

As we discussed in the essential article on Component Comparison, it represents a situation. You need to show an item as a mix of two or more elements. The usual words used with it are: % of Total, Share of, Mix of, Component of, Includes X. You can find it in the world around you every day. Last week, we talked about the Pie Chart. Today, we take a look at Doughnut Charts.

Doughnut Chart – The birth date is not as clear as with Pie Chart

The doughnut chart is a variation of the pie chart, distinguished by its hollow center. Scottish economist William Playfair introduced the pie chart in the early 19th century (as seen in the image below). It was created to present complex statistical data concisely and understandably. The doughnut chart emerged later. It was a response to some of the pie chart’s limitations, especially issues with labeling and comparing smaller sections.

The exact originator of the doughnut chart is unclear. Its development is closely tied to the evolution of circular graphing techniques in the 20th century. Digital tools made it easier to customize and enhance these visualizations. The primary motivation for the doughnut chart was to improve readability. It aimed to provide a space (the central hole) for additional information, such as totals or key metrics. This made the chart more versatile and visually appealing.

Practical Examples from the Corporate World

Something around Budgets and Audience Engagements…

You can clearly see that these charts depict five components of the whole. All five are adding up to 100%. This is very important to note; it needs to add up to 100% otherwise this chart does not make sense. There are some Pros and Cons associated with this chart.

👉🏻 Advantages

• Enhanced Clarity and Readability: The central gap allows for clearer labeling. It can display summary information. This reduces clutter compared to pie charts
• Visual Appeal: Doughnut charts offer a modern, sleek look, making them suitable for business presentations and reports.
• Space for Additional Data: The hollow center can be used for totals, percentages, or annotations. This adds another layer of information without overwhelming the viewer
• Multiple Data Series: By adding more rings, doughnut charts can display multiple data sets at the same time, unlike standard pie charts.
• Quick Understanding: Their simple structure enables even inexperienced viewers to easily interpret proportions.

👉🏻 Disadvantages

• Limited Number of Categories: Clarity drops quickly if there are too many segments; best used with 2–6 categories.
• Not Suitable for Dynamic Data: Doughnut charts are static. They do not handle frequently changing data well. Updating them can lead to clutter.
• Requires Labeling: To avoid confusion, each segment usually needs to be labeled directly, which can become cumbersome with many categories.

Practical Tips to Reduce the Disadvantages

There are always creative ways to help yourself avoid the pitfalls, depending again on the story you choose to tell. Not every piece of data is essential, and not everything needs to be visible or communicated. I have added some tips I’ve learned during my professional journey on the right side of the image below.

Are there other alternatives?

Of course, in the future post I am going to talk about:

• 100% Stacked Bar or Area charts
• Tree maps and Mekko Charts
• Sankey Charts and others

Summary

The doughnut chart evolved as an enhancement to the classic pie chart. It aims to improve readability. Additionally, it provides space for more information. Its main strengths are its visual appeal and clarity. It also has the ability to present proportions in a user-friendly way, especially when there are only a few categories.

However, doughnut charts share many of the limitations of pie charts, including difficulty with precise comparisons and clutter when overused. Doughnut charts are highly effective for simple, static data. They allow you to highlight parts of a whole. They also provide a clean, modern look. For more complex or dynamic datasets, you should consider using alternative visualizations. Options like bar or column charts offer greater accuracy. They allow for more straightforward interpretation.

There is always a chart for your story. You need to understand the basic concepts, principles, and language used. This helps you correctly choose what you need to persuade, inform, inspire, or entertain!

For a free downloadable resource, click the Chart Decision Tree and Compare Visual Guide.