Earlier in the blog, we covered the basics of the Mekko or Marimekko chart. In this entry, we discuss types of analyses that are best suited for visualization through the Mekko chart. Note that not all readers will be familiar with these charts and it is important that they are well designed and simply convey the information.
The Mekko is a two dimensional stacked bar chart where the width and height of segments carry information. Unlike the bar-mekko, the Marimekko chart has a 100% y-axis.
The Marimekko is great way of answering a variety of market overview questions. For example if we want to understand who the most valuable franchises are by sport the Mekko is a succinct way of showing it (see chart below). Each column in the Mekko represents a sport and each segment is a franchise. In this example no franchise can exist in two different columns/sports. This however does not have to be true for Mekko charts in general. Often the segments in a Mekko are repeated across the columns.
Mekko chart showing most valuable franchises by sport
Other types of questions you can answer with the Marimekko include:
- How many servers do Facebook, Amazon, and Google have across the world? Here we would make each continent a column in the Mekko and each company a horizontal segment
- Who are largest medical device companies by product line? Each product line could be a column in the Mekko and each company a horizontal segment. The value plotted would be company revenue
- Which countries grow the most coffee beans in the world? The columns of the Mekko would be continents. The segments would be the countries. The value plotted would be the amount of coffee grown.
The Mekko chart is a standard option with Aploris either on your Mac or PC. Simply select the Mariekko chart option and Aploris will provide you with sample chart and template data that you can quickly modify.
Stacked and clustered (or grouped) bar charts are standard data visualization tools used for business purposes on a regular basis. Stacked charts are typically used to investigate components in a category that aggregate while cluster charts are typically used to measure components across categories that do not aggregate.
In example 1 we use the stacked bar chart to examine the Economic Enhancer components for the US Global Competitive Index across three time periods (published by the World Economic Forum). Here the scores are aggregated (the World Economic Forum equally averages them) and the stacked bar chart is natural visualization option.
In example 2 we use the cluster or group bar chart to examine how the United States and Germany compare for each component used in the Economic Enhancer metric in a single time period. As the scores are not combined here, a cluster or group bar chart is more appropriate.
However, there are times where we would like to be able to combine the charts so that we can compactly examine two sets of data where each set is made up of components that aggregate. In example 3 we use a combination stack-cluster chart to achieve this and effective examine the Economic Enhancer components for both the US and Germany across the 3 time periods.
Most data visualization tools are unable to naturally create a stacked-cluster combination. Users are forced to develop workarounds that are time consuming and not easily editable. With Aploris, however, users are can use the stacking editor to quickly create a stacked-cluster combination starting from either a regular stacked or cluster bar chart. By right-clicking on the blank spot on the chart users can pull up the stacking editor and simply drag and drop elements to create the desired stacked-cluster combination chart.
As the name implies, the 100% stacked bar or column chart uses the percent unit for the y-axis. As a result, if you are comparing across multiple groups/bars, each would have the same height taking up the full range of the value axis. The chart is typically used when the author wants to highlight the portion of the total that each segment in a bar comprises. The chart is especially useful when comparing across groups of different sizes or along a timeline. In the example below, we use the 100% stacked bar chart to examine educational attainment in specific US geographies.
Relative to the rest of the US, a higher portion of Silicon Valley and San Francisco residents have a Bachelor, Graduate or Professional degree. The 100% stacked column helps the reader quickly arrive to this conclusion. If we had used a regular stacked chart the American population would have dwarfed Silicon Valley and San Francisco making the key message difficult to obtain. Still the sum displayed on top of each column gives insights into the absolute numbers behind the percentages in the 100% chart.
The 100% stacked bar chart is a standard Aploris offering. With Aploris, the user can switch between regular and 100% stacked bars with the just a few clicks allowing them to quickly test which graph best communicates the intended insight. In addition, Aploris labels can be automatically adjusted to show the absolute value, the percent of the total, or both.
The Marimekko (or Mekko) chart is a two dimensional chart that is especially useful when explaining market landscapes. The Marimekko, named after the colorful Scandinavian textile design is often used by management consultants. In the example below we use a Mekko chart to convey the types of grapes grown in California.
Market segments are arranged in columns along the x-axis with the width of the column denoting the size of the segment. In the example above, grapes are segmented into red and white. The height of the columns are typically equal (in our next entry we will discuss Marimekko charts with custom heights). Each column can then also be segmented with the height of the segment representing the share that segment occupies. In the example above, the segments within a column show grape type (e.g. Cabernet). Alternatively, we could have listed the grower (e.g. Robert Mondavi).
The Mekko chart enables the reader to easily grasp the overall landscape helping them quickly discern the largest and smallest segments along two dimensions. With Aploris users can quickly create Marimekko charts and also have great deal of control with how it looks and what information the labels carry. For example, labels can be modified to list the percent of the column the segment represents or the percent of the total chart that the segment represents.
Starting the value axis of a chart – usually the y-axis – at a non-zero value can visually exaggerate the initial insights that the reader draws. In example 1 below, the first instinct is to think that there is a >80% difference between 2010 and 2014. Once we extend the y-axis to 0, however, we see that the differences are quite minor (example 2).
Cropped vs. full value axis
That’s not to say that all charts should have a value axis that starts at 0. If, for example, we were looking at temperatures in the charts above starting at 0 Kelvin would make little sense. In general, the value axis range should include the reasonable range of the data and not deceive the reader. If, for example, we were looking sales data above it is reasonably plausible to have 0 sales and therefore the y-axis should likely extend to 0.
On the other hand, in a certain scenario a business analyst may have found out that a large share of sales is fixed. In that case she may want to focus on the fluctuations above a certain level like in example 1 above. So the right way of presenting the data always depends on the story it is supposed to tell and the insights the designer wants to share.
Advanced chart tools like Aploris have the ability to edit the format of an axis to ensure it appropriately depicts the chart data and supports the message to the reader. This includes editing the axis range and tick mark intervals, using 100% and logarithmic scales as well as inserting axis breaks.