Depth vs. Breadth, Data Presentation vs. Absorption, Frank and Bernanke

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For anyone who knows me or follows this blog, it will be no surprise that I can get a bit…er…animated when it comes to data visualization. Partly, this may be from my background in Art and Design. I got out of that world as quickly as possible, when I realized that I lacked the underlying wiring to really do visual design well.

As a professional data practitioner, I also see effective data visualization as being a way to manage the paradox of business data: the world of business is increasingly complex, yet the human brain is only able to comprehend a finite level of complexity. And, while I love to bury myself up to my elbows in complex systems and processes, I’m the first person to admit that my eyes glaze over when I’m presented with a detailed balance sheet (sorry, Andy). A picture is worth a thousand words. A chart is worth a thousand data points. That’s how we interpret data most effectively — by aggregating and summarizing it in a picture.

So, it’s pretty important that the picture be “drawn” effectively. I had a boss for a year or two who flat-out was much closer to Stephen Hawking-ish than he was to Homer Simpson when it came to raw brainpower. He took over the management of a 50-person group, and promptly called the whole group together and presented slide after slide of data that “clearly showed”…something or other. The presentation has become semi-legendary for those of us who witnessed it. The fellow was facing a room of blank-confused-bored-bewildered gazes by the time he hit his third slide. Now, to his credit, he learned from the experience. He still looks at fairly raw data…but he’s careful as to how and where he shares it.

All that is a lengthy preamble to a Presentation Zen post I read this evening about Depth vs. Breadth of presentations. It’s a simple concept (meaning I can understand it), with some pretty good, rich examples to back it up. The fundamental point is that none of us spend very much time thinking about what to cut from our presentations. I would extend that to say we don’t spend very much time thinking about what data not to share or show. It’s easy to see this as a case for “make the data support what you want it to,” which it is not. At all! Really, it’s more about focussing on showing the data — and only the data — that directly relates to the objectives you are measuring or the hypotheses that you are testing.

Then, focus on presenting that data in a way that makes it clear as to what story it is telling. You do the hard work of interpreting the data. Then, highlight what is coming out of that intepretation. If there is ambiguity, highlight that, too. If there is a clear story, and your audience gets it, and you then introduce an anomaly, you’re much more likely to have a fruitful, engaging discussion about it. You will learn, and your audience will retain!

In the end, this is a riff on a bit of a tangent, I realize. Robert Frank presents some fairly alarming evidence of college professors aiming for broad and deep…and not gaining any better retention than the slide-happy, chart-crazy PowerPoint users provide in the business setting. He goes on to talk about how, in his teaching, he makes a point, repeats it, comes at it from a different angle, makes the students think about it, and then repeats it again. He goes for deep. His students, I’m sure, leave his introductory economics class with a thoroughly embedded (and accurate) understanding of “opportunity cost” (having seen the term mis-applied more than once in my day…and still having to struggle to get to the correct answer…and barely…and barely in time…in his presentation…I applaud that!).

I’m not arguing for simplicity for simplicity’s sake. I’m arguing for going deep, understanding the complexity, and then distilling it down to a narrative, cleanly presented, that leaves your audience with takeaways that are accurate and absorbed.

And…on that note, have any of you read The Economic Naturalist? It sounds like it would be right up my alley. It’s just a bonus that, if I ever actually attended something that could be labeled a “cocktail party,” I could talk about how I’d “read some of Bernanke’s work!”

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