15 Oral narrative, data graphics
Until now, our discussions of narrative, visualization, and interactivity assume that the communication must stand on its own to deliver our messages to our audience.
But sometimes we may want to combine our data-graphics with a verbal narrative. Doumont (2009a) motivates oral presentations as,
Oral presentations are about having something to say to one’s audience and being able to say it in an articulate way while looking them in the eye. They are about engaging the audience with mind and body, conveying well-structured messages with sincerity, confidence, and, yes, passion. They are about presence, about being seen and being heard, not about having the audience look at slides that are in fact written pages, while hoping not to be noticed.
Perhaps we present orally for those reasons. But let’s consider two more. First, we are all social, and can benefit from having a direct, human connection to the material we care about. Second, from a communication efficiency standpoint, we have a direct feedback loop in real time through each aspect of the narrative we present, if we’ve prepared to enable that loop. And having direct feedback at the time of the communication can be extremely valuable, leading to more rapid progression of the ideas presented.
In those circumstances, we should adjust how we provide our explanations and visuals, and we have multiple options. First, we should consider whether our audience would benefit from pre-presentation review of important material and, if so, how we should craft that material. Second, we should consider whether, if at all, we should adjust how we visualize and explain our information during the presentation. Here, we consider both issues, in turn.
15.1 (Pre-)meeting preparation
Edward Tufte has advocated for beginning meetings with a detailed written (paper or electronic) document with the expectation that our audience reads them before a discussion, so that the meeting itself can become a more productive dialogue with deeper understanding. Most recently, he provides a chapter-length treatment of the idea in Edward R. Tufte (2020). Here, he sketches out constraints: the document “should be 2 to 6 pages long, written in sentences, with appropriate images and data displays. Do not send out your stuff in advance, people won’t read it.” He explains why:
Audience members read 2 or 3 times faster than you can talk. The document is in hand, everyone in the audience reads with their own eyes, at their own pace, their own choice of what to read closely.
In contrast:
In sllide presentations, viewers have no control over pace and sequence as the presenter clicks through a deck — viewers must sit in the dark waiting for the diamonds in the swamp.
Then why are you there?
Your job is to provide intellectual leadership, which is why you are making the presentation.
Doumont (2009a), too, recommends companion documents to presentations. Along with Tufte’s above advice, he offers five thoughts. First, content and credibility: “your audience seeks to learn What is the substantive content? What are the reasons to believe the presenter?” Thus, our document and presentation should explain the problem, its relevance and the so what, and our next steps for resolving the problem. To be credible all content must not just be truthful, but it should also cite sources, including data, quote experts on the specific issue, and reveal any potential biases.
Second, and his next point has been front and center in many of the earlier sections, we should think about our audience. Along with what we’ve considered, do not underestimate our audience. Do not “dumb things down” but, instead, respect their intelligence. Third, when you present after the audience has read your document, “do not repeat”do not merely repeat what they read.” Instead, go more in-depth, and refer back to the document paragraphs where relevant to tie together the two channels of information.
Fourth, practice your presentation ahead of time! More than once! Consider writing it out word for word, then speaking it aloud to get a feel whether the written sentences feel like natural spoken language, and to have an estimate of how the time required for presenting it verbally. And part of aloud rehearsal is to include white space — silence — for your audience to process your messages.
Finally, respect your audience’s time: finishing early is better than finishing late!
All these ideas can be helpful in particular contexts. But consider a course I teach in Columbia’s graduate program — Storytelling with data — and the pre-lecture study of primary source material, guided in part by this text. This occurs by necessity before discussion, before class. Primary-source material, for the most part, does not fit within Tufte’s recommended six pages for that which we cover during a weekly session. Certainly, one aim of the text before your eyes is to provide summary of various source materials, as well as highlight important ideas. Yet students are expected to prepare ahead of time.
Let’s turn, now, to the post-study presentation and, specifically, how to incorporate verbal communication and data-graphics.
15.2 Verbal with the (data) visual
15.2.1 Limitations with multi-modal communication
To motivate the value of time working on design of presentations, consult Edward R. Tufte (2008). In fact, after considering Tufte here, we may be wondering whether slides are even a good idea:
PowerPoint, compared to other common presentation tools, reduces the analytical quality of serious presentations of evidence.
This is especially the case for the PowerPoint ready-made templates, which corrupt statistical reasoning, and often weaken verbal and spatial thinking.
To answer that question, we may consider how Tufte himself has conducted presentations, as at E. Tufte (2016). It’s worth watching, and in it, you’ll find he does use presentation visuals! Edward R. Tufte (2008) provides reasoning. First, PowerPoint (still, today) has poor default formatting for any slide you intend to create, and encourages things like excessive bullet points or the equivalent to what we considered with data visuals: let’s call it slide-junk. Secondly, slides as presented can be very low resolution compared to paper, most computer screens, and the immense visual capacities of the human eye-brain system (id). With little information per slide, many slides are needed. Third, information stacked in time makes it difficult to understand context and evaluate relationships (id). Visual reasoning usually works more effectively when the relevant evidence is shown adjacent in space within our eye span. This is especially true for statistical data, where the fundamental analytical task is to make comparisons (id).
When designing visuals for a verbal narrative, use the right tool for the information. As Tufte explains, Many true statements are too long to fit on a slide, but this does not mean we should abbreviate the truth to make the words fit. It means we should find a better tool to make presentations. Secondly, increase data-ink on slides too, within reason. Doumont echos this point (as do I):
A major noise source on slides is text, especially a lot of text, for the audience cannot read one text and listen to another at the same time. An effective slide gets the message across (the so what, not merely the what) globally, almost instantly. There lies the challenge: to express a message unambiguously with as little text as possible. Visual codings being in essence ambiguous, effective slides almost always include some text: the message itself, stated as a short but complete sentence. Besides this text statement, the message should be developed as visually as possible: this development shoiuld include only whatever words are necessary for the slide to stand on its own.
Beyond including no superfluous information in their design, slides should include no superfluous ink in their construction. Optimal slides get messages across clearly and accurately with as few graphical features as possible: they are noise-free (Doumont 2009b).
Along with Doumont (2009b), Schwabish (2016) provides helpful general advice for designing visuals for presenting. To be sure, the broad strokes all paint what we’ve canvased previously. Again, per Doumont: get our audience to pay attention to, understand, and (be able to) act upon a maximum of messages given constraints. Indeed, as Doumont correctly notes, most slide visuals contain too much text. Period. When asking ourselves whether we’ve over-texted, consider whether we have created the slide for our own understanding, perhaps in part as speaking notes? Don’t do that. You may have notes, but they do not belong on your visuals, and do not show them to your audience. Second, are the slides to be presented to double as a written report? Don’t do that, either. Instead, if dissemination is important, create the aforementioned document, with full sentences, paragraphs, and a coherent narrative. If you must, you may also key the document to the slides. Or, less ideal, when circulating the slides after the presentation, include a (perhaps lightly edited) transcript of your verbal narrative. For examples of transcripts with visuals, see Corum (2018) and Corum (2016)1. But well-created presentation slides would not, in most cases, adequately explain their context without our verbal narrative. Third, if we find ourselves copying from written documents onto presentation visuals, perhaps because we’re running low on time, consider that this approach is not better than nothing. If the words distract your audience from listening to you, if your words are competing with those on your visuals, those visuals are worse than none at all.
15.2.2 Strategies for verbally communicating data-graphics
If text on visuals compete for attention with our verbal narrative, and the general advice above is use as few words as possible, how should we think about the lengthy advice in data graphics to annotate and explain, in this context?
That advice still applies! But some of the annotations and explanations are now verbal. We have two helpful strategies in thinking about how much explanation we place on data graphics that support verbal communication. As an initial matter, we much understand what pace to provide material to our audience.
With pace in mind, we can, first, verbally explain what the data visual shows. In fact, a best practice is to verbally explain what the audience is about to see before you show them. And, second, we can layer information, chunk-by-chunk, onto and around the data graphic, so that the audience only needs to understand small bits at a time, and each subsequent portion is added as a new layer within the context of what the audience just learned.
Jonathan Corum’s presentations provide helpful guidance in their own right, too.↩︎