Steven Franconeri's Whole Brain Communication taught how to present ideas and solutions – and the data that motivates them – in a manner that is engaging, clear, and memorable. Presentations and explanations typically overwhelm an audience’s limited capacity for new information, by directing it to a limited part of the brain. We worked to communicate to the whole brain, by turning verbal messages to salient visuals, expressing abstract numbers as sensorimotor objects, leveraging existing association networks, and telling immersive stories. The techniques taught were grounded in cognitive science – why our brains are limited in perceiving, learning, and storing information – as well as research in data visualization, and principles of graphic design.
Flyer Redesign
Leveraging the graphic design principles of CARP (Contrast, Alignment, Repetition, Proximity), I redesigned a flyer I had seen around campus. Hey, it was a fine flyer, but a little nondescript, and I thought the bevy of information included could be presented a little more clearly. Additionally, I thought the rip-off tags were a little inelegant, and felt a QR code would provide the same function in a slicker manner (though I'll be honest, I've never used a QR code in my life).
Flyer Redesign
Leveraging the graphic design principles of CARP (Contrast, Alignment, Repetition, Proximity), I redesigned a flyer I had seen around campus. Hey, it was a fine flyer, but a little nondescript, and I thought the bevy of information included could be presented a little more clearly. Additionally, I thought the rip-off tags were a little inelegant, and felt a QR code would provide the same function in a slicker manner (though I'll be honest, I've never used a QR code in my life).
Data Visualizations
Cole Nussbaumer Knaflic's Storytelling with Data was our class bible, and I used lessons taught in her book to visually interpret the following prompts (packaged with accompanying datasets):
Prompt #1
You have been analyzing donation records at a non-profit that does not typically rely on data analytics. Your analysis shows that, from a fundraising perspective, this practice is deeply misguided. Of the 4570 donors in the last year, you found that the top 10% contributed 83% of all funds collected, and the bottom 50% only contributed 1% of all funds collected.
This fact isn't going to sit well with the organization's leadership, as it is part of their culture to spend a roughly equal amount of time courting donations from individuals capable of making potentially small and potentially large contributions. It's up to them whether to continue that practice, but your job is to put the facts in front of them clearly.
Create a single-page that puts the vast difference in donor impacts clear to them. You've shown them histograms before, and you suspect that they'll find that statement that "10% contribute 83%" confusing, so the visualization should make that point obvious.
Prompt #2
You're a product marketing manager for a company that manufactures and sells five distinct lines of software: Business Productivity, Educational, Games, Programming, and Utilities.
Over the past 5 years, the relative amount that each has contributed to overall revenue has shifted. 5 years ago, your programming products were on top, but today they are last, and games are on top. As you examine the relative sales of each product line for each of the 5 years, you notice a decline in the success of products that are more technical (i.e., programming and utilities) but an increase related to entertainment.
You are preparing recommendations for the company's 5-year plan. To set the stage for your recommendation that the programming and utilities lines be sold off and the games line expanded, you need to clearly present the shift that you've observed during the last 5 years. Create a single-page that presents the data pattern clearly, with annotation that explains how they should think about the relevant trend(s).
Prompt #3
You have been asked to consult on a visualization that will be presented to leaders at the Department of Education. Over four hundred educators were asked what types of research content areas they find most useful. Create new visualization in a single-page that that highlights four patterns in the data:
1. Most people could not pick a single content area.
2. Respondents in special education roles showed strong interest in research focused on special education, and race/ethnicity research areas.
3. Respondents in federal programs roles showed strong interest in research focused on English learners, race/ethnicity, and SES (socioeconomic status & poverty) research areas.
4. Respondents in the other roles typically named research that did not focus as strongly on a particular subgroup, showing more diverse interests.
