I KNOW! I did diss Information is Beautiful previously, but I like this one. (Which is odd, because there are comments about readability).

It shows how the design decision to make data close to its MEANING rather than its structure works! I mean, really, we don’t want to see that Poland is 2.4% closer to target than the Slovak Republic; all we want is a general overview: which countries are doing well, and which ones suck like…well, are doing badly.

So what makes this good?

• Representation: there is a familiar style: the style is – of course – like a dartboard, directly playing on ‘bullseye’ and immediately giving readers something to base their interpretation on.
• Information AND Data: the pre-ordering and categorisation of ‘Bullseye!’, ‘On Target’, etc, make it super easy to know what you’re looking at. It’s *information* not *data*! Why would you order this by country name, for instance (there aren’t that many data points to warrant that, even)?
• Textual Context: okay, so datavis should be about the data and the visual, right? True, but where textual explanations and descriptions help, they can do wonders, as in this case. The commentary makes it that much easier to understand.
• Feeling: the countries placed under ‘Fail’ have absolutely no hope in garnering any sort of sympathy from someone who has seen this. It’s sort of biased, yes, but if we don’t get people to feel things when they look at a visualisation, what hope is there that they remember anything?

Of course, there are a few tiny things. I would have made the target the red one, and maybe left the models of what a ‘good’/etc (but perhaps having the countries is good enough).

What’s more, there’s a little bit of process behind it, which makes it that much more interesting.