What are the most effective ways to use a waterfall chart for data analytics?

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Waterfall charts are a type of data visualization that show how a value changes over time or across categories. They are useful for data analytics because they can highlight the positive and negative contributions of different factors to a final outcome. In this article, you will learn what are the most effective ways to use a waterfall chart for data analytics, such as when to choose it, how to create it, and how to interpret it.

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1 When to choose a waterfall chart

A waterfall chart is a good choice for data analytics when you want to show the cumulative effect of sequential or hierarchical changes on a value. For example, you can use a waterfall chart to show how revenue, expenses, and profit change over a period of time, or how sales vary by region, product, and customer segment. A waterfall chart can also help you compare scenarios, such as actual versus budgeted performance, or before and after a policy change.

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Leandro Araque

Chief Data Officer at Datzure | Compartiendo conocimiento con Dawoork ?? | Profesor de Ciencia de Datos | Innovación en AI, Web3, FinTech & EdTech
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Waterfall charts are indeed valuable for showing cumulative effects, but they're not always the best choice for all types of data. For instance, they may not be suitable for data that doesn't have a clear sequence or hierarchy. Also, while waterfall charts are excellent for comparing scenarios like actual vs. budgeted performance, they can be misleading if not designed carefully. For example, if the scales are inconsistent, it can distort the perception of the data. Therefore, it's crucial to ensure that the scales are consistent and that the data used is appropriate for this type of visualization. Always consider the context and the message you want to convey before opting for a waterfall chart.

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2 How to create a waterfall chart

To create a waterfall chart, you need to have a data set that has a starting value, one or more intermediate values, and an ending value. You also need to label each value with a category or a time period. Depending on the tool you use, you may need to calculate the difference between each value and the previous one, and assign a positive or negative sign to it. Then, you can use a stacked bar chart or a custom chart type to plot the values as vertical bars. The starting and ending values should be shown as whole bars, while the intermediate values should be shown as floating bars that connect to the previous and next bars. The bars should be colored differently based on whether they increase or decrease the value.

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Leandro Araque

Chief Data Officer at Datzure | Compartiendo conocimiento con Dawoork ?? | Profesor de Ciencia de Datos | Innovación en AI, Web3, FinTech & EdTech
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One aspect that's often overlooked is the color scheme. While the article mentions that bars should be colored differently based on whether they increase or decrease the value, it's crucial to choose colors that are easily distinguishable and convey meaning. For example, using a gradient color scheme can help the audience quickly understand the magnitude of change. Also, labeling is key. Make sure to not only label the categories or time periods but also any significant increases or decreases. This aids in the interpretability of the chart. Lastly, consider using tools that allow for interactive waterfall charts, as they can provide deeper insights upon user interaction.

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3 How to interpret a waterfall chart

To interpret a waterfall chart, you need to pay attention to the size, direction, and color of the bars. The size of the bars indicates the magnitude of the change in the value, while the direction and color indicate whether the change is positive or negative. You can also look at the gaps between the bars to see how much each factor contributes to the final outcome. A waterfall chart can help you identify the main drivers and inhibitors of the value, as well as the trends and patterns over time or across categories.

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4 How to customize a waterfall chart

To customize a waterfall chart, you can adjust the layout, design, and formatting of the chart elements, such as the axes, labels, titles, legends, and gridlines. You can also add annotations, highlights, or markers to emphasize or explain certain points or segments. For example, you can add a horizontal line to show a target or a benchmark, or a vertical line to show a milestone or a break. You can also use different colors or shapes to distinguish different groups or subcategories within the data.

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5 How to avoid common pitfalls of a waterfall chart

A waterfall chart can be an effective way to use data analytics, but it also has some potential pitfalls that you should avoid. One pitfall is to use too many bars or categories, which can make the chart cluttered and confusing. Another pitfall is to use inconsistent or misleading scales or colors, which can distort the perception of the changes in the value. A third pitfall is to use a waterfall chart for data that is not sequential or hierarchical, which can make the chart irrelevant or inaccurate. To avoid these pitfalls, you should follow the best practices of data visualization, such as choosing the right level of detail, using clear and consistent labels, and ensuring the accuracy and validity of the data.

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6 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?

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Leandro Araque

Chief Data Officer at Datzure | Compartiendo conocimiento con Dawoork ?? | Profesor de Ciencia de Datos | Innovación en AI, Web3, FinTech & EdTech
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One additional consideration is the audience's data literacy level. Waterfall charts can be complex to interpret for those unfamiliar with them. Providing a brief explanation or legend can be invaluable. Also, it's worth noting that waterfall charts are not universally the best choice for all types of data. They excel in showing cumulative effects but may not be suitable for data that doesn't have a sequential or hierarchical relationship. Lastly, always validate your data before creating the chart. Even a small data error can significantly distort the insights you're trying to convey.

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What are the most effective ways to use a waterfall chart for data analytics?

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1 When to choose a waterfall chart

2 How to create a waterfall chart

3 How to interpret a waterfall chart

4 How to customize a waterfall chart

5 How to avoid common pitfalls of a waterfall chart

6 Here’s what else to consider

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