The same reason that pie charts are not very effective - it's relatively hard to make comparisons between angles instead of lengths like in a bar chart. It's probably even harder with a doughnut.

Here is a PDF article by Stephen Few about pie charts: http://www.perceptualedge.com/articles/08-21-07.pdf

That's a compelling article and I think I'm going to be a lot more cautious about using pie charts in the future, but the thin-doughnut design they're using here looks OK to me.

When you're summarizing coarse relative size across arbitrary categories, bar charts and tables give your selection of categories too much weight: everyone looks at the biggest bar or the biggest number and it's really hard to measure a long tail distribution visually.

If the message you're trying to send is, "nothing but X and Y matter, everything else combined is tiny", I still can't imagine a better visualization than a pie (or a doughnut).

You're absolutely right. Everyone harps on pie charts for being awful for element-to-element comparisons. This mainly stems from Tufte's work and experiments from Cleveland and McGill.

However, in part-to-whole relationship tasks, pie charts can outperform bar charts, since in bar charts there is no true "whole".

(In addition to Few's post, Kosara has more on this: http://eagereyes.org/criticism/in-defense-of-pie-charts)

A composite bar chart is like a pie chart that has been unrolled. The length of the bar is the "whole".

http://www.ncsu.edu/labwrite/res/gh/gh-bargraph.html#composi...

I think the angle vs. length argument is precisely what makes doughnut charts better than pie charts.