Choose an appropriate visual display. When highlighting a number or two, simple text is best. Line charts are usually best for continuous data. Bar charts work great for categorical data and must have a zero baseline. Let the relationship you want to show guide the type of chart you choose. Avoid pies, donuts, 3D, and secondary y-axes due to difficulty of visual interpretation.
Eliminate clutter. Identify elements that don’t add informative value and remove them from your visuals. Leverage the Gestalt principles to understand how people see and identify candidates for elimination. Use contrast strategically. Employ alignment of elements and maintain white space to help make the interpretation of your visuals a comfortable experience for your audience.
Focus attention where you want it. Employ the power of preattentive attributes like color, size, and position to signal what’s important. Use these strategic attributes to draw attention to where you want your audience to look and guide your audience through your visual. Evaluate the effectiveness of preattentive attributes in your visual by applying the “where are your eyes drawn?” test.
Think like a designer. Offer your audience visual affordances as cues for how to interact with your communication: highlight the important stuff, eliminate distractions, and create a visual hierarchy of information. Make your designs accessible by not overcomplicating and leveraging text to label and explain. Increase your audience’s tolerance of design issues by making your visuals aesthetically pleasing. Work to gain audience acceptance of your visual designs.
Tell a story. Craft a story with clear beginning (plot), middle (twists), and end (call to action). Leverage conflict and tension to grab and maintain your audience’s attention. Consider the order and manner of your narrative. Utilize the power of repetition to help your stories stick. Employ tactics like vertical and horizontal logic, reverse storyboarding, and seeking a fresh perspective to ensure that your story comes across clearly in your communication.
Together, these lessons set you up for success when communicating with data.
In closing
When you opened this book, if you felt any sense of discomfort or lack of expertise when it comes to communicating with data, my hope is that those feelings have been mitigated. You now have a solid foundation, examples to emulate, and concrete steps to take to overcome the data visualization challenges you face. You have a new perspective. You will never look at data visualization the same. You are ready to assist me with my goal of ridding the world of ineffective graphs.
There is a story in your data. If you weren’t convinced of that before our journey together, I hope you are now. Use the lessons we’ve covered to make that story clear to your audience. Help drive better decision making and motivate your audience to act. Never again will you simply show data. Rather, you will create visualizations that are thoughtfully designed to impart information and incite action.
Go forth and tell your stories with data!
Bibliography
Arheim, Rudolf. Visual Thinking. Berkeley, CA: University of California Press, 2004.
Atkinson, Cliff. Beyond Bullet Points: Using Microsoft PowerPoint to Create Presentations that Inform, Motivate, and Inspire. Redmond, WA: Microsoft Press, 2011.
Bryant, Adam. “Google’s Quest to Build a Better Boss.” New York Times, March 13, 2011.
Cairo, Alberto. The Functional Art: An Introduction to Information Graphics and Visualization. Berkeley, CA: New Riders, 2013.
Cohn, D’Vera, Gretchen Livingston, and Wendy Wang. “After Decades of Decline, a Rise in Stay-at-Home Mothers.” Pew Research Center, April 8, 2014.
Cowan, Nelson. “The Magical Number Four in Short-Term Memory: A Reconsideration of Mental Storage Capacity.” Behavioral and Brain Sciences 24 (2001): 87–114.
Duarte, Nancy. Resonate: Present Visual Stories that Transform Audiences. Hoboken, NJ: John Wiley & Sons, 2010.
Duarte, Nancy. Slide:ology: The Art and Science of Creating Great Presentations. Sebastopol, CA: O’Reilly, 2008.
Few, Stephen. Show Me the Numbers: Designing Tables and Graphs to Enlighten. Oakland, CA: Analytics Press, 2004.
Few, Stephen. Now You See It: Simple Visualization Techniques for Quantitative Analysis. Oakland, CA: Analytics Press, 2009.
Fryer, Bronwyn. “Storytelling that Moves People.” Harvard Business Review, June 2003.
Garvin, David A., Alison Berkley Wagonfeld, and Liz Kind. “Google’s Project Oxygen: Do Managers Matter?” Case Study 9–313–110, Harvard Business Review, April 3, 2013.
Goodman, Andy. Storytelling as Best Practice, 6th edition. Los Angeles, CA: The Goodman Center, 2013.
Grimm, Jacob, and Wilhelm Grimm. Grimms’ Fairy Tales. New York, NY: Grosset & Dunlap, 1986.
Iliinsky, Noah, and Julie Steele. Designing Data Visualizations. Sebastopol, CA: O’Reilly, 2011.
Klanten, Robert, Sven Ehmann, and Floyd Schulze. Visual Storytelling: Inspiring a New Visual Language. Berlin, Germany: Gestalten, 2011.
Lidwell, William, Kritina Holden, and Jill Butler. Universal Principles of Design. Beverly, MA: Rockport Publishers, 2010.
McCandless, David. The Visual Miscellaneum: A Colorful Guide to the World’s Most Consequential Trivia. New York, NY: Harper Design, 2012.
Meirelles, Isabel. Design for Information. Beverly, MA: Rockport Publishers, 2013.
Miller, G. A. “The Magical Number Seven, Plus or Minus Two: Some Limits on Our Capacity for Processing Information.” The Psychological Review 63 (1956): 81–97.
Norman, Donald A. The Design of Everyday Things. New York, NY: Basic Books, 1988.
Reynolds, Garr. Presentation Zen: Simple Ideas on Presentation Design and Delivery. Berkeley, CA: New Riders, 2008.
Robbins, Naomi. Creating More Effective Graphs. Wayne, NJ: Chart House, 2013.
Saint-Exupery, Antoine de. The Airman’s Odyssey. New York, NY: Harcourt, 1943.
Simmons, Annette. The Story Factor: Inspiration, Influence, and Persuasion through the Art of Storytelling. Cambridge, MA: Basic Books, 2006.
Song, Hyunjin, and Norbert Schwarz. “If It’s Hard to Read, It’s Hard to Do: Processing Fluency Affects Effort Prediction and Motivation.” Psychological Science 19 (10) (2008): 986–998.
Steele, Julie, and Noah Iliinsky. Beautiful Visualization: Looking at Data Through the Eyes of Experts. Sebastopol, CA: O’Reilly, 2010.
Tufte, Edward. Beautiful Evidence. Cheshire, CT: Graphics Press, 2006.
Tufte, Edward. Envisioning Information. Cheshire, CT: Graphics Press, 1990.
Tufte, Edward. The Visual Display of Quantitative Information. Cheshire, CT: Graphics Press, 2001.
Tufte, Edward. Visual Explanations: Images and Quantities, Evidence and Narrative. Cheshire, CT: Graphics Press, 1997.
Vonnegut, Kurt. “How to Write with Style.” IEEE Transactions on Professional Communication PC-24 (2) (June 1985): 66–67.
Ware, Colin. Information Visualization: Perception for Design. San Francisco, CA: Morgan Kaufmann, 2004.
Ware, Colin. Visual Thinking for Design. Burlington, MA: Morgan Kaufmann, 2008.
Weinschenk, Susan. 100 Things Every Designer Needs to Know about People. Berkeley, CA: New Riders, 2011.
Wigdor, Daniel, and Ravin Balakrishnan. “Empirical Investigation into the Effect of Orientation on Text Readability in Tabletop Displays.” Department of Computer Science, University of Toronto, 2005.
Wong, Dona. The Wall Street Journal Guide to Information Graphics. New York, NY: W. W. Norton & Company, 2010.
Yau, Nathan. Data Points: Visualization that Means Something. Indianapolis, IN: John Wiley & Sons, 2013.
Yau, Nathan. Visualize This: The FlowingData Guide to Design, Visualization, and Statistics. Indianapolis, IN: John Wiley & Sons, 2011.
Index
A
Accessibility overcomplicating
poor design,
text, thoughtful use of action titles on slides
Action words
Adobe Illustrator
Aesthetic
s
Affordances creating a clear visual hierarchy of information
eliminating distractions
highlighting effects
Alignment diagonal components
presentation software tips for
Animation, leveraging in visuals
Annotated line graph with forecast
Area graphs
Atkinson, Cliff
Audience attention, focusing color brand colors
considering tone conveyed
designing with colorblind in mind
position on page
using consistently
using sparingly
memory iconic
long-term
short-term
preattentive attributes in graphs
in text
sight
size
B
Bar charts axis vs. data labels
bar width
categories, logical ordering of
ethical concerns
horizontal
simple
stacked horizontal
leveraging positive and negative
100%
vertical
vertical
waterfall chart
Beck, Harry
Beyond Bullet Points (Atkinson)
Big Idea
Bing, Bang, Bongo
C
Cairo, Alberto
Case studies alternatives to pie charts 100% stacked horizontal bar graph
showing numbers directly
simple bar graph
slopegraph
color considerations with a dark background
animation, leveraging in visuals
logic in order
spaghetti graphs, avoiding combined approach
emphasizing one line at a time
separating spatially
Closure principle
Clutter, avoiding cognitive load data-ink/signal-to-noise ratio
contrast, nonstrategic use of redundant details, use of
decluttering cleaning up axis labels
labeling data directly
leveraging consistent color
removing chart border
removing data markers
removing gridlines
Gestalt Principles of Visual Perception closure
connection
continuity
enclosure
proximity
similarity
presence of
visual order, lack of alignment
white space
Cognitive load data-ink/signal-to-noise ratio
Color considerations with a dark background
Color saturation
Communication mechanism continuum live presentation
slideument
written document or email
Connection principle
Context, importance of Big Idea
consulting for
exploratory vs. explanatory analysis
how
illustrated by example
supporting data
storyboarding
3-minute story
understanding
what action
mechanism
tone
who audience
you
Continuity principle
Contrast, nonstrategic use of redundant details, use of
D
Data-ink ratio
Data Points (Yau)
Distractions, eliminating
Donut charts
Duarte, Nancy
E
Eager Eyes (blog)
Effective visuals, choosing graphs area graphs
bar charts
lines
points
slopegraph
infographics
simple text
tables borders
heatmap
visuals to avoid 3D charts
donut charts
pie charts
secondary y-axis
Enclosure principle
Excel changing components of a graph in
slopegraph template
Exploratory vs. explanatory analysis
F
Few, Stephen
FiveThirtyEight’s Data Lab
Flowing Data (blog)
The Functional Art (blog)
Fung, Kaiser
G
Gestalt Principles of Visual Perception closure
connection
continuity
enclosure
proximity
similarity
Google People Analytics
Project Oxygen
spreadsheets
Graphs area graphs
bar charts axis vs. data labels
bar width
categories, logical ordering of
ethical concerns
horizontal
stacked horizontal
stacked vertical
vertical
waterfall chart
lines line graph
points scatterplots
slopegraphs modified
template
The Guardian Data Blog
H
Headlines, creating
Heatmap
HelpMeViz (blog)
Hierarchy of information super-categories
Highlighting effects
Horizontal logic
“How to Write with Style” (Vonnegut)
I
Iconic memory
Ineffective graphs, examples of
Infographics
Information Visualization: Perception for Design (Ware)
K
Kirk, Andy
Kriebel, Andy
L
Line graph annotated with forecast
Live presentation tables in
Logic in order
Long-term memory
M
Make a Powerful Point (blog)
McCandless, David
McKee, Robert
McMahon, Gavin
Model visuals, dissecting line graph annotated with forecast
stacked bars horizontal
leveraging positive and negative
100%
Moonville example
P
Perceptual Edge (blog)
Pie charts
Points scatterplots
PowerPoint
Preattentive attributes in graphs
in text
Proximity principle
R
Resonate (Duarte)
Reverse storyboarding
S
Scatterplots modified
Schwabish, Jon
Secondary y-axis
Short-term memory
Show Me the Numbers (Few)
Signal-to-noise ratio
Similarity principle
Simple text
Slideument
Slopegraphs modified
template
Spaghetti graphs, avoiding combined approach
emphasizing one line at a time
separating spatially
Spears, Libby
Stacked bars horizontal
leveraging positive and negative
100%
Storyboarding
Storytelling constructing the story beginning
end
middle
lessons in
magic of story in cinema
in plays
in written word
narrative structure narrative flow
spoken and written
repetition Bing, Bang, Bongo
tactics to ensure the story is clear horizontal logic
reverse storyboarding
vertical logic
storytelling with data (blog)
Storytelling with data process appropriate display, choosing
audience attention, focusing
building competency in team or organization combined approach
>
investing in internal experts
outsourcing
upskilling everyone
clutter, eliminating
context, understanding
telling a story
thinking like a designer
tips for success with devoting time to
having fun and finding your style
iterating and seeking feedback
seeking inspiration through good examples
tools, learning to use
Super-categories
Survey feedback
T
Tableau
Tables borders
heatmap
Storytelling with Data Page 19