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Chart of the day improved, needs better data

False promises of equality and structure

(Here's something especially for those like me who are stuck in their homes in the Northeast USA this weekend.)

A few readers weren't impressed by Nielsen's presentation of the smartphone marketplace:

Nielsen-smartphone-marketshare

This chart type is very popular, both among business consultants and statisticians. Consultants call them "marimekko charts" while statisticians call them "mosaic charts". It's got multiple names as it has been reinvented multiple times. I have nightmares from having to produce this sort of charts in Powerpoint by hand (deconstructing and reconstructing column charts), and I have written before about my dislike of them (see here, and here).

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Supporters point to two advantages of this type of chart:

  • Equality: it puts the two dimensions of the market place -- operating system/software, and producer/brand -- on equal footing. As an added bonus, the areas of the rectangles are meaningful: they correspond to the relative market shares.
  • Structure: the chart often reveals interesting aspects of the structure of the data. For instance, here it shows that certain smartphones have "closed" systems where the OS and producer forms a one-to-one relationship while some producers like HTC makes phones with different operating systems.

A little thought exposes these as false promises.

The two dimensions are, in fact, not equal. Look at the one contiguous column for Apple versus two separate sections for HTC. In order to know the market share of HTC, the reader needs to do additions... in his/her head. While this is not so hard when HTC appears only twice, your reader would not be amused if HTC appears seven times on the same mosaic. It is a limitation of this chart type that one cannot get the column sections to be of one piece without destroying the one-piece structure of the row sections.

In addition, I don't think it is easy to compare the areas of fat rectangles versus narrow rectangles, or squares versus long strips, etc. On consulting style charts, you almost always find the entire data set printed, which is to say, this chart is rendered not self-sufficient. On statistical charts, you typically find axis labels; this is not much better because of the difficulty in estimating relative areas.

The extent to which one can learn the structure of the data is restricted by our ability to estimate and sum areas.

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In the junkart version, I use a flow chart. Special attention is paid to expressing as clearly as possible the structure of the marketplace, thus the separate sections for the "open" versus "closed" systems, as well as the many-to-many relationships among the "open"-system players.

Redo_smartphone

The thickness of the flows is proportional to the market shares. I added a few data points to anchor the scale. The two dimensions of the data are treated symmetrically.

There is also no need to startle readers with a kaleidoscope of colors so typical of marimekkos.

 

 

 

 

 

Comments

Chrisbeeleyimh.wordpress.com

Hello- I do like the flowchart. How did you make it?

Kaiser

The vendors who are lurking might be able to give better answers.

The one I did was all Powerpoint so my answer is not useful if you have to mass-produce them. But this data has a clear structure, so you can, for example, write an R function to generalize it.

Tom

This "flow chart" is also known as a web plot, and is used to plot predator-prey and similar relationships. The bipartite package provides functions for creating such plots in R.

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