When you share data – in a slideshow, a dashboard, or a written report – how can you give your message impact? (You know, so you persuade people that it’s a big deal, and so they act on your message.)
To help you do that, you’ll find 3 powerful steps in this post and my next:
Step 1’s the key (and the easiest)
Step 1’s the key (and the easiest), and step 3’s perhaps the most advanced – which is why I’ve put them in that order.
This post covers step 1, and my next post will cover steps 2 and 3.
You can add steps 2 and 3 to have more and more impact
If you’re relatively new to presenting data, you can use step 1 by itself to help get your message across. (And if you’re more experienced, you can add steps 2 and 3 to have more and more impact.)
Step 1: Simplify your content
You’ll see 3 tips (labelled A, B and C) for step 1 below
You’ll see 3 tips (labelled A, B and C) for step 1 below. I hope you find them helpful, and that they make the step easier to apply.
Here’s what you’ll find in this section:
Why this step?
They’ve so little time to absorb all your work
As you might’ve spent days working on your dataviz, it’s easy to forget that your audience is probably seeing it for the first time. As a result, it can easily go over their heads because they’ve so little time (and motivation!) to absorb all your work.
So unless you present it simply, you’ll severely limit your impact (even if you also do steps 2 and 3). That’s why the crucial step is to simplify what you share.
But, I hear you say:
“Stop – I don’t want to oversimplify all my work!”
“This is not about oversimplifying, but rather
not making things more complicated
than they need to be”
Cole Nussbaumer Knaflic
I’ve put this step’s 3 tips in decreasing order of “bang for your buck”, meaning tip A has most impact (from little effort), and arguably tip C has least impact…
1a: Reduce colours
Along with things like shape and size, colour’s known as a pre-attentive attribute. That means our brains process colour thousands of times faster than we can read numbers (or words).
If you use lots of colour, people won’t know where to look
Partly because of that, colour draws people’s attention very strongly. So, if you use lots of colour – like in the default charts typical of Excel and PowerPoint – people won’t know where to look.
On top of that, in any audience there are almost bound to be people with some form of colour blindness. That’s why it’s best to use colour sparingly, and with care.
Use one intense colour for where you want people to focus
An effective approach is to use:
- One intense colour for where you want people to focus
- Grey for the rest of your data
Want to see an example? Here’s dataviz expert Ann K Emery showing (in just 20 seconds) how that might look on a bar chart:
And here’s Cole Nussbaumer Knaflic explaining this approach (in a 30-second clip):
1b: Reduce text
Your listeners can’t properly do these 2 language-based tasks at once
Reducing text’s especially important if you’re sharing your data in a presentation (rather than a dashboard or written report). That’s because your listeners can’t properly do these 2 language-based tasks at once:
- Listen to you.
- Read text on your slides.
That’s why I recommend you use about 15 words (at most) per slide. (That might seem like a really low number. So to see why it applies, please follow that link.)
Here’s Nancy Duarte (author of Slide:ology) backing up that point in just 20 seconds:
Even if you’re sharing your data in a written report – where people have more time to absorb it than they do on a slide – reducing text and using short, simple words (whenever you can) still helps to get your message across better.
Think how a senior leader might say it
Worried that people will think you're being too informal? Think how a senior leader (or someone like Warren Buffett or Steve Jobs) might say it in a press briefing. His or her language would tend to be businesslike but conversational, not complex or formal.
1c: Reduce “chartjunk”
You might’ve heard of the concept of “chartjunk”, meaning elements like gradient fills, shadows and 3D effects, which don’t convey useful information. (The term was coined by Edward Tufte in his book, The Visual Display of Quantitative Information.)
Mind you, it’s debatable whether some parts of your chart (like gridlines and axis lines) are chartjunk and should be removed, or should just be faded so they stand out less. For instance, Steven Few (the well-known author of 3 books on data visualisation) argues against removing too much “non-data ink”.
Reducing chartjunk helps people focus on your findings
In any event, reducing chartjunk helps people focus on your findings, rather than being distracted by redundant parts of your chart. So I highly recommend you make your dataviz as clean and uncluttered as you can.
As an example, in the 1-minute video below, Leila Gharani (who’s a Microsoft MVP) cites specific measurements from an eye-tracking study to back up the point that you shouldn’t use 3D charts:
Over to you
As a reminder, here are the 3 tips I suggest you use to simplify your content – to give it more impact:
Thanks for reading, and look out for my next post for steps 2 and 3!
Also check out
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- Secret #5 of star presenters: @TEDchris on persuasion [Video]
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