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Effective data presentation: don’t let the medium be the message

Over the past couple of years I have been making presentations and delivering workshops on presenting data effectively. My approach has been on the side of clarity, and I’ll discuss why that is a “side” and what it is a “side” of.

During a recent post-presentation question-answer session, I was told that “younger people have shorter attention spans, so ‘traditional’ graphs don’t work for them”. I was taken aback a bit since what I had just been talking about was how to communicate quantitative ideas with maximum clarity and requiring as little effort as possible on the part of the viewer.(1)

There is clearly a tension in “data viz” between:

  • clarity and aesthetics – even among those who stress clearly communicating the meaning of data, there is a range. You could call that the Edward Tufte – Stephen Few continuum (2)
  • “informing” and “attention-getting”
  • graphical presentation of data and infographics

I think this tension can be a source of better understanding of what we, as data-communicators, are doing and should/can do in a given circumstance. Sometimes it’s critical to convey information as clearly and accurately as possible, and sometimes that is less important than drawing people in to take a closer look. That is going to depend on the circumstance. You want clarity and ease of comprehension in the boardroom. But you might want a certain “curb appeal” if you are communicating basic facts and ideas to a wide and general kind of audience that might otherwise ignore you in the daily competition for attention.

One way to harness this might be to look at choices as part of a set of continua, such as:

Data viz continua

OK, I just stuck the last one in as an admittedly rhetorical comment. I’m sorry. (3)

Another way to look at this would be to use two dimensions to set up target areas of information/attention and clarity/vagueness that might be appropriate for differing audiences and purposes.

Data viz space

I think that various mixes of clarity and intended purpose as between attention-getting and informing suit different purposes, and it’s worth being purposeful in this choice.

This is where effective data visualization practices like minimizing the data-ink ratio and using the attributes of pre-attentive processing come in, along with some sense of complementary and contrasting colour schemes and controlled use of fonts.

If you have effective practices in your toolbox, you can then decide purposefully whether or not to let clarity slide a bit in the interest of grabbing the attention of the casual reader, and by how much, in order to achieve your communications goals.

If you don’t, you’re probably just out there yelling.


(1) I’m not sure I accept this premise either. I’m pretty sure my kids can read a graph.

(2) Is this truly a distinction, or is clarity aesthetic in and of itself, too? Oh man, that’s deep.

(3) I don’t even want to talk about infographics that just use crazy shapes and colours without any relevance at all to the subject or its quantity. I’m interested more in the difference between what I’ll call “well-designed data graphics” and “well-designed infographics”.