Treating absolute and relative data simultaneously

A friend asked me to comment on the following chart:

Specifically, he points out the challenge of trying to convey both absolute and relative metrics for a given data series.

This chart presents projections of growth in the U.S. mobile display advertising market. It is specifically pointing out that the programmatic segment of this market is growing rapidly (visualized as the black columns).

The blue and red lines then make a mess of the situation. Even though both of these lines espress percentages, they report to different scales. The red line represents growth rates while the blue line represents share of market.

Both of these metrics are relative metrics useful for interpreting the trend. The growth rates (red) interpret the dollar values on the basis of past values while the market shares (blue) interpret the dollar values on the basis of the total market.

It is rarely a good idea to have many scales on the same canvas. Looking at the blue line for the moment, it is shocking to find that the values depicted almost doubled from one end to the other end. The blue line appears much too gentle.

***

In the makeover, I expressed everything in the same scale (billions of dollars). I used side-by-side charts (small multiples) to isolate each trend that is found in the data. I allow readers to look at each individual segment of the market, and then examine how the individual trends affect the total market.

One might argue that the stacked column chart by itself is sufficient. If there is a severe space limitation, I'd let go of the other two panels. However, having those panels makes the messages easier to obtain. This is particularly true of the steady growth assumption behind the programmatic spending trend (the orange columns).