I started this post to make a relative mundane point for UBC Management students about the importance of making their presentations easily understandable, particularly when they involve lots of numbers or spreadsheet data. But after mulling over the post for a few days, I realized that this is a much bigger story.
Further back in my career than I prefer to admit, I had the exceptional opportunity to work with the founders of Silicon Graphics, Jim Clark, (who later went on to start Netscape with Mark Andreeson), Mike Ramsay and Jim Barton (who later started TiVo, the original PVR company). The premise of SGI was making 3D visualization ubiquitous in engineering, complex simulation, and computer animation. As often happens with the convergence of technology and great ideas, SGI was well ahead of its time. Disney loved it but the big engineering customers were not over the moon. The concept of 3D visualization of complex data was compelling. Extraordinary examples of SGI visualization of tornados, molecular modelling and animation can still be found on YouTube. But the chip technology required to achieve it, MIPS RISC (reduced instruction set computing) microprocessors) at that time, was not ready for prime time. Both MIPS and SGI are now long gone, and only SGI’s graphics computing instruction set, known as OpenGL survives. But the era of Big Data and Visual Analytics is just beginning to emerge into the mainstream, as the technology has fully caught up. If you have not seen this TED Talk video by Hans Rosling, it is only 4 minutes long, but it explains where we are going with Big Data, and how interpreting Big Data visually is already making a major impact on our thinking. I have also included a reblogged post from the HBR Network which I think you will find is related to this much bigger concept.
Hans Rosling: 200 Countries, 200 Years, 4 Minutes
Reblogged from the HBR Blog Network
When Presenting Your Data, Get to the Point Fast
by Nancy Duarte | 9:00 AM March 28, 2013
Projecting your data on slides puts you at an immediate disadvantage: When you’re giving a presentation, people can’t pull the numbers in for a closer look or take as much time to examine them as they can with a report or a white paper. That’s why you need to direct their attention. What do you want people to get from your data? What’s the message you want them to take away.
Data slides aren’t really about the data. They’re about the meaning of the data. And it’s up to you to make that meaning clear before you click away. Otherwise, the audience won’t process — let alone buy — your argument.
Take this table, for instance:
It’s confusing — especially if you project it for five seconds and then move on. And even if you leave it up for five minutes while you talk, anyone who’s struggling to derive meaning from it won’t be paying much attention to what you have to say. They’ll be too busy squinting from their seats, trying to navigate all those heavy grid lines that give every single cell equal weight. It’s not at all clear where the eye should go. Your audience won’t know what direction to read — horizontally or vertically — or what conclusions to draw. Though the Grand Total line is emphasized, is that really the main point you want to convey?
Now let’s look at the data presented more simply. Say you’ve identified three business units with potential for sustained growth in Europe. By eliminating the dense matrix and connecting only key numbers to a pie with leader lines, you remove clutter that distracts from your message. And notice the clear hierarchy of information: You can highlight important pieces of the pie by rendering them in color and their corresponding annotations in large, blue type. Other sections recede to the background, where they belong, with their neutral shades and small, gray labels.
But pie charts can be tricky for an audience to process when segments are similar in size — it’s hard to distinguish between them at a glance. If you’re running into that problem, consider displaying the same data in a linear way. In this bar chart, for example, you draw attention to the poorest-performing unit, a point that got lost in the pie:
These few tricks will help audiences see what you want them to see in your data. By focusing their attention on the message behind the numbers, not on the numbers themselves, you can create presentations that resonate with them and compel them to act.