Module 3: Visualizing for Decisions
Choose the right chart and remove everything that doesn't help the decision.
1
Quick Intro
2
Guided Practice
3
Applied Task
4
Quick Refinement
1
Quick Intro
~2 min
WHAT
A visualization is a chart, map, or table designed so the reader can spot the pattern in under 5 seconds — clutter (3D, dual axes, rainbow palettes) is the enemy.
WHY
A chart that takes 30 seconds to understand has already lost the audience. The chart is what the audience LOOKS at — it must answer the question, not just show the data.
HOW IT FITS
Pillar 2 of four. A good chart makes pillar 1 (your data) legible; a bad chart hides it. Modules 4–6 then wrap the chart in audience-fit narration and interaction.
EXAMPLE
A bar chart with one annotation highlighting the year cycling overtook driving beats a 12-series stacked area chart of the same data.
1
Chart = answer machine
30 sec
A chart should answer ONE question in under 5 seconds. If it takes longer, simplify.
Too complex
12 data series, dual axes, 3D effects, rainbow colors
Decision-ready
1 key trend, clear title, annotation on the turning point
Your chart should make the decision obvious, not require explanation.
2
Pick the right chart type
30 sec
Trends over time = line chart. Comparison = bar chart. Parts of whole = stacked bar.
📈 Line
Ridership 2019→2023
📊 Bar
Modal split comparison
🗺️ Map
Regional differences
Match your chart type to what you want to show.
3
Remove chart junk
30 sec
Every pixel must earn its place. Remove: 3D effects, gridlines, unnecessary legends.
Chart junk = visual elements that do not help the decision, such as 3D effects, heavy gridlines, redundant legends, or decorative images.
Before: uniform grey — no emphasis on the recovery story.
Chart junk to remove
2
Guided Practice
~3 min
1
Choose the chart type
1 min
Match the question to the best chart type.
Question: "Has suburban rail ridership recovered since 2020?"
Which chart type fits best?
📈 Line chart
Shows trend over time
🥧 Pie chart
Shows parts of whole
🗺️ Map
Shows regional variation
2
Write an annotation
1 min
Annotations point directly at the insight. Don't make readers figure it out.
Chart shows: ridership crashed 56% in 2020, recovered to 96% by 2023
Annotation template
[Key number] — [what it means for the decision]
Write an annotation:
3
Write a takeaway title
30 sec
Title = takeaway, not description. "Ridership recovered" not "Ridership 2019-2023".
Descriptive (weak)
"PT ridership 2019-2023"
Takeaway (strong)
"Ridership recovered, but frequency didn't"
Write a takeaway title:
3
Applied Task
~3 min
1
Plan your visualization
1 min
Based on your M1 question and M2 data, choose your chart type.
Your previous work
(Loading...)
Select your chart type:
📈 Line
Trends over time
📊 Bar
Comparisons
📉 Area
Cumulative trends
🗺️ Map
Geographic data
2
Write your chart specification
1 min
Specify: chart type + axes + annotation + title.
Chart specification
Chart: [type]
X-axis: [time/categories]
Y-axis: [metric]
Annotation: [key insight]
Title: [takeaway]
X-axis: [time/categories]
Y-axis: [metric]
Annotation: [key insight]
Title: [takeaway]
Write your spec:
3
Simplicity check
30 sec
Does your chart...
4
Quick Refinement
~2 min
1
Review your design
30 sec
Would a decision-maker understand it in 5 seconds?
Your chart design
(Your spec will appear here)
2
Improve the annotation
30 sec
Make it more specific. Add a number if missing.
Refined annotation:
3
Commit your visualization
30 sec
Your visualization will guide your audience adaptation in Module 4.
Final visualization brief: