How the Pellucid Book Club works: Each month two books are nominated. A vote is taken on which to read and a few weeks later we get together to discuss it. The objective is to learn more about each other's areas of expertise and then write a post inspired by the book. The books fit into one of four categories: Smarts, Charts, Pitch, or Win. This month The Design of Everyday Things by Don Norman (Charts) beat out Liar’s Poker by Michael Lewis (Smarts). Here’s what we found interesting.
Signifiers and affordances in chart design
Things should just work, right? If they don’t we either blame ourselves or get frustrated and walk away. This human-centered design concept, that we should know whether to push or to pull, where to tap, or what to click, is something we expect to be clear in any product or tech-based interaction we have. And the more it builds on knowledge already in our heads, the better.
Central to these communications are affordances and signifiers.
Affordances: The possible interactions between people and the environment.
Signifiers: Signals that indicate what actions are possible and how they should be done. These must be perceivable.
So a closed door would have the affordance that you could pull or push it, the signifier would be a handle suggesting “pull” or a panel indicating “push”. Pretty straightforward.
In the discussion, we got to talking about what this means for pitchbooks and specifically chart design.
Take your typical time series vs. comps multi-line chart:
The affordance can be interpreted as the possible discussions that could be had on the basis of this data set. What are the values today? How have they changed over time? Is that unusual? How is IBM comparing to Microsoft? For a broad-based discussion, all of these questions may be appropriate and needed, but when it comes to specific questions, using a signifier can be very helpful.
For instance, if the conversation should be about IBM’s performance compared to its industry, aggregating all its individual comps’ data into a composite index benchmark and plotting just that versus IBM reduces the clutter and distraction of the individual comp series lines signifying that IBM’s comparison to the set of companies is where the key message lies. Using red and green shaded differences as signifiers of “bad” and “good” also gives immediate cognitive recognition of the times that IBM either traded at a discount or at a premium to its peers.
Alternatively, if it’s important to keep the individual performance of each comp, appending a data table to the chart’s time axis acts as a second signifier that the individual performance of each company is still important and relevant to the conversation.
In the book club discussion, we liked the affordances and signifier design concepts as an allegory for curating pitchbooks and building the charts. If you keep a close eye on the affordances—what conversations could this lead to? And are the signifiers you're using sending the right signal? These two things can help keep a tight rein on the direction of the conversation, help build a strategic narrative, and ensure each chart is pointing toward the same data-driven conclusion.
Have you read the book? Anything else you found pertinent to pitchbooks? Email Pellucid at FixThePitch@pellucid.com.
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