You’re presenting the recommendation you’ve been working on for months. You’ve got the data to back it up. So much data. Overwhelming data.
Worried that the decision makers you need to influence won’t see its significance, you’ve used your favorite data visualization software to create graphics. You hope they’ll help your audience see the patterns, trends, and correlations that support your recommendation.
But your presentation isn’t going how you’d envisioned.
Despite all your hard work (and state-of-the-art data visualization software) your audience seems confused. Detached. Ambivalent.
What went wrong?
It’s Not Enough to Have Great Data
We know that data visualization is an effective way to share information with executives, to help them make smart and informed business decisions. Studies show that including graphical depications of information in your presentation increases your perceived credibility.
Impressive graphics are not enough.
What also matters is the method in which you share your data visualizations. How you present complex material makes a huge difference in whether or not your audience tracks with you, stays focused, or even understands what you’re trying to tell them.
While there are lots of great software options for creating data visualizations, there’s not a lot of science-based advice about how to use them in a presentation. Did you know, for example, that your audience can’t listen to what you’re saying AND process visual information at the same time? Neuroscience tells us it’s either one or the other.
What else can neuroscience tell us? A lot, it turns out.
If you find yourself struggling with how to use data visualizations effectively, I want to offer some science-backed tips to help you create a story for your data, keep your audience engaged, and know when to explain things or remain quiet.
Understanding How People Process Information
Have you ever been in a presentation or class where the information was so complex or dense that you couldn’t follow it? Or what about a presenter or instructor who went through the material so fast, you felt like you couldn’t keep up?
In both of these examples, your working memory was tapped out. Your brain’s ability to handle the cognitive load of information was overwhelmed.
Overloading Your Audience
When presenting data, people tend to do three things that overload their listener’s working memory:
- They keep talking while their audience is trying to process the graphics on a slide.
- They put way too much data and information on each slide.
- They simply read the slide aloud, exactly as it’s written.
To understand why this kind of data presentation is ineffective, you first need to understand how people process information.
Working Memory and Cognitive Load TheoryThe long-standing model of how humans assimilate information, developed by Atkinson and Shiffrin in 1968, describes the process as having three main parts:
- Sensory memory
- Working memory
- Long-term memory
Sensory memory is essentially how your brain takes in the world around you with all of its sights, sounds, smells and textures. Information from your sensory memory then passes into your working memory, which researchshows can only hold a limited amount of information at a time. Working memory is short-term memory.
With all of the information and input your working memory must handle while listening to a complex presentation, how does your brain decide what to keep and what to disregard?
Cognitive load theory is the idea that certain factors can make learning unnecessarily complex. These factors inhibit your working memory from being able to process all of the incoming information.
There are two main types of cognitive load, intrinsic and extraneous.
- Intrinsic load refers to the complexity of the subject matter or content itself. The more complex the information, the more things need to be processed in working memory.
- Extraneous load refers to how the information is presented. Too fast? Too much jargon? Too dense? This is where data visualizations can help lighten the cognitive load. But it’s also where presenters can become distracting or make things more complex than they need to be.
You may not have control over the intrinsic complexity of the data, but you have complete control over how you present it. Knowing how to use data visualizations effectively can keep you from overloading your audience.
Three Mistakes to Avoid When Presenting Data Visualizations
Mistake #1: Talking while your audience is trying to read your slide
It’s very tempting to continue talking when you first put up a slide filled with data. Why wouldn’t it be? You know the information inside and out. You know what your ultimate recommendations will be, and you might even be feeling pressed for time.
Here’s the problem — no one else in the room feels as comfortable as you do. So when you keep talking while your audience is trying to read, you’re increasing their extraneous load and creating what’s known as a split-attention effect.
Studies show that auditory data is processed separately from visual information. A “phonological loop,” or verbal pathway, handles speech and other sounds while a distinct “visuospatial sketchpad,” or image pathway, processes text and other visual stimuli.
Having to both listen and read at the same time makes the two pathways compete for attention, and the verbal track easily gets overloaded.
Solution #1: Say it, Show it, Talk it
Say it: Set up the story of the data.
Before displaying your information-rich slide, briefly preview what your audience is about to see, or explain how to interpret what they are about to see at its most basic level.
Show it: Pause and let them process it.
After showing your audience the slide, notice how their attention will turn back to you when they finish with it and are ready to hear more.
Talk it: Share important details.
At this point, share the important details of the data story. How much detail you give will depend upon the type of audience you have and how much detail they need.
Mistake #2: Putting too much data on a slide
No one wants to present an enormous slide deck — even fewer want to sit through it.
Data enthusiasts often want to cram as much information as they can onto a slide in order to make shorter decks. The problem is, more data on a slide doesn’t equal greater audience understanding. Just the opposite is true, since you’re taxing your listener’s extraneous cognitive load.
Solution #2: Be succinct and intuitive
Pare down the information on each slide.
Similar to the idea of information chunking, or the process of taking individual pieces of information and grouping them into a larger whole, think of presenting your data with intuitive headlines and succinct labels to avoid verbiage overload.
Highlight organization cues.
The first of Richard Mayer’s 12 Multimedia Learning Principles explains the “Coherence Principle.” Essentially, people learn better when extraneous words, pictures, and sounds are excluded rather than included.
A close second on his list is the “Signaling Principle,” describing how people learn better when clear cues are added that highlight the organization of the essential material.
Mistake #3: Reading the slide aloud, exactly as it’s written
If you’re uncomfortable presenting in front of an audience, it’s easy to fall into the habit of looking at your projected slide and reading out loud what your audience is already trying to read to themselves.
While it doesn’t seem like that would interfere with your audience’s ability to understand the material, it does.
In multimedia learning theory, the Principle of Redundancy shows that reading and hearing identical verbal information simultaneously can significantly reduce comprehension. This is particularly made worse if the information is intrinsically complex, or if the audience needs to split their visual attention between text and other elements on the screen.
Solution #3: Add color commentary
Think of the data visualization on your slide as the play-by-play commentary in a sporting event broadcast. It simply addresses the “what.”
As the presenter, your job is to add the color commentary that lets your audience know WHY it matters. To do this well, follow the advice in Solution #1 and pause to let your audience visually process a slide before adding your commentary.
Putting It All Together
Not all audiences require the same types of data visualizations. Because of that, they’ll likely require slightly different presentation approaches as well.
A highly technical audience may want more details from you in the moment, allowing you to get into the weeds to explain your thinking and recommendations in depth.
Senior leaders, on the other hand, may simply want to understand the significance of your concepts and data as a whole and steer clear of details entirely.
There are, however, three things that all successful presenters using data visualizations do well:
- Have a clear purpose for each graphic
- Ensure your content headers are succinct and intuitive
- Pause and give your audience time to process visual AND verbal elements
Remember that no matter who your audience is, their brains process information in the same way we all do. Never forget that the power to make your data readily understandable to any audience is in your hands.
Citations (in order of appearance)
Tal, A. and Wansink, B. (2014). Blinded by non-science: Trivial graphs and formulas increase ad persuasiveness and belief in product efficacy. Public Understanding of Science. Retrieved from https://www.sciencedaily.com/releases/2014/10/141017101224.htm
Explorable.com. (2011). Atkinson-Shiffrin Model. Retrieved from Explorable.com: https://explorable.com/atkinson-shiffrin-model
Mcleod, Saul. (2012). Working Memory. Simply Psychology. Retrieved from https://www.simplypsychology.org/working%20memory.html
Psychologist World. (n.d.). Cognitive Load Theory. Psychologist World.com. Retrieved fromhttps://www.psychologistworld.com/memory/cognitive-load-theory
Chandler, P., & Sweller, J. (1992). The split-attention effect as a factor in the design of instruction. British Journal of Educational Psychology, 62(2), 233-246. Retrieved from https://psycnet.apa.org/record/1992-41746-001
Garner, Joanna K., Alley, M. Gaudelli, A.F., and Zappe, S.E. (November 2009). Common use of PowerPoint versus the assertion-evidence structure: A cognitive psychology perspective. Technical Communication. Volume 56, number 4 Retrieved fromhttps://pdfs.semanticscholar.org/7998/a32337d0e19fada0dfa6aac9703efa0b36a7.pdf
Cherry, Kendra. (2019). How the chunking technique can help improve your memory. Very Well Mind. Retrieved fromhttps://www.verywellmind.com/chunking-how-can-this-technique-improve-your-memory-2794969
Walsh, Kelly. (2017). Mayer’s 12 Principles of Multimedia Learning are a powerful design resource. Emerging EdTech. Retrieved fromhttps://www.emergingedtech.com/2017/06/mayers-12-principles-of-multimedia-learning-are-a-powerful-design-resource/