The waterfall chart, also known as the Mario chart, is a simple data visualization comprised of a series of floating bars that look like a waterfall (or floating bricks for Nintendo’s Mario to jump on). The waterfall chart is an effective way to show the impact of a series of sequential drivers on a specific measurement.
In the example below, we use the waterfall chart to understand Microsoft’s income statement from revenue to net income for 3 months ending September 30, 2014 (source Microsoft earnings release). Throughout the waterfall we use “total bars” to provide an intermediary summation (e.g. gross margin, operating margin). We have also manually edited the labels to only show units for the total bars.
The waterfall chart is a standard Aploris offering on our Mac and PC compatible data visualization software. When editing the chart, simply drag the connectors between bars to adjust the flow of the waterfall.
Today we want to take a look at a real-life example of a chart. There may always be an alternative approach to display the same data and potentially make it easier to read and understand.
Here is a chart that we saw in a magazine which we reproduced using Aploris. It depicts the development of employee headcount in the German retail industry (March 2012 to March 2013, no source stated).
Is there a better way to display the data? First of all, we are seeing a composition of figures meaning that the total is the sum of the influencing factors. The chart does not help the viewer to understand this relationship. Next, one can see that the increase in part time jobs outweighs the reduction in full time headcount leading to a positive total change. However, it takes good vision and some deduction to develop this understanding.
In this case we would propose to utilize a waterfall chart that charting tools like Aploris support. Here is a how the same data can be used in a waterfall.
Now it should be very clear that a reduction of full time employees is more than compensated by increased part time workers leading to an increase in overall industry headcount.
Charting tools typical offer a number of different types of charts. You may see bar or columns charts, pie charts and Marimekkos. So which chart type would I use to display certain data?
As usual the answer is: it depends. In this case on the message that you would like the slide to tell. Imagine having sales data at hand. You might want to display how the sales revenue developed over time and is projected to grow. It may also be meaningful to analyze the distribution between multiple regions or division. Or you might want to know how the sales volume of multiple products relates to their profitability.
The outcome of your analyses usually falls in a certain category. For a certain category some chart types may be better suited than others. In this blog post and the next we are going to describe the categories comparison, composition, relationship/correlation and frequency/ranking.
Comparison, often a development over time
To see how numbers develop over time typically column and line charts are most powerful. You may add visual elements to highlight or summarize overall growth rates. Tabular data can be used to indicate growth rates for multiple lines or segments in stacked columns.
Stacked bar chart sample: US food consumption
For a comparison of multiple items along several criteria spider charts or line charts may be helpful. Use a rotated line chart with lines running top down to visualize a tabular comparison of multiple items.
Line chart template comparing items on multiple criteria
Composition, sometimes comparing between instances
Composite numbers may tell you how sales are distributed between several divisions. The simplest way to display a 100% composition is to use a pie chart. A single 100% stacked column carries the same information and provides a natural way to add the total number that equals 100%. Showing multiple columns adds a second dimension that allows to compare compositions over time or between several entities. If many periods are displayed it may make sense to use an area chart instead of many stacked columns.
A special chart explaining a composite value is a waterfall chart. Unlike the aforementioned chart types it is capable of showing positive as well as negative values incurring into a composite number. A waterfall chart is especially powerful to display how an input value (e.g. last year’s sales) transforms into a new value (current sales plan) taking into account multiple influencing values (delisted products, new products, additional sales channel).
For breaking down a number into two dimensions a Marimekko can be a good choice. Think about sales figures split across geographies and by product line within each geography.