DataStory

1. Data Storytelling: Transform Numbers into Compelling Narratives

"Data doesn't speak for itself; it needs a storyteller."

Storytelling power: The human brain is wired to process stories, making them a powerful tool for communicating data. By transforming data into vivid scenes and structuring delivery in the shape of a story, you make your audience care about what the data says.

Memory and emotion: Stories are more memorable than raw facts. In a study by Chip Heath, only 5% of students could recall specific statistics from speeches, while 63% remembered the stories. This is because stories activate emotions, making them stick in our minds.

Beyond raw numbers: Data storytelling isn't just about presenting numbers; it's about:

• Uncovering insights
• Providing context
• Inspiring action
• Creating meaning
• Driving decisions

2. Empathy is Key: Understand Your Audience and Decision-Makers

"The foundation of effective communication is empathy."

Know your audience: Tailor your message to those receiving it. What may seem clear to you could be perplexing to others. Understanding your audience's background, knowledge level, and preferences is crucial for effective communication.

Executive communication: When presenting to executives:

• Respect their time – they are incredibly busy
• Understand how they are measured (revenue growth, market share, etc.)
• Know their preferred communication style
• Be prepared for interruptions and questions
• Structure your message for quick consumption

Soft skills matter: Communication skills are in high demand. A LinkedIn study found that out of a 1.6 million soft skills gap:

• 993,000 required oral communication skills
• 140,000 required writing skills

3. Craft a Clear Data Point of View (DataPOV) to Drive Action

"Your DataPOV is the centerpiece of your entire recommendation, and all other material you present stands in support of it."

Structure of a DataPOV:

1. Your unique point of view requiring action
2. What is at stake (positive and negative)

Write it clearly: Express your DataPOV in a complete, well-constructed sentence with at least one noun and one verb. This becomes the title page of your recommendation.

Choose strong verbs: The action verb in your DataPOV is crucial. It should fall into one of three modalities:

• Change: We need to change who we are or what we're doing
• Continue: We need to keep going in the same direction
• Finish: We need to complete this

Examples of strong verbs:

• Performance verbs: accelerate, decrease, improve, scale
• Process verbs: implement, optimize, streamline, innovate

4. Structure Your Data Story for Maximum Impact

"Leveraging the structure of a story arc makes an executive summary engaging and memorable, and it actually reads much like a story."

Three-act structure: Organize your data story into three acts:

1. Beginning: Introduce the current situation, problem, or opportunity
2. Middle: Present the messy data that needs to change
3. End: Your DataPOV addressing the problem and creating a positive outcome

Recommendation Tree: Use a logical structure to support your DataPOV:

• Main point (DataPOV)
  • Supporting point 1
    • Evidence
    • Evidence
  • Supporting point 2
    • Evidence
    • Evidence
  • Supporting point 3
    • Evidence
    • Evidence

What-Why-How model: For each supporting point, answer:

• What needs to be done?
• Why is it important?
• How will we accomplish it?

5. Choose Simple, Effective Charts and Annotate Insights

"For gaining buy-in, clarity always outperforms cool."

Stick to basics: Use familiar chart types that everyone understands:

• Bar charts (for quantities)
• Pie charts (for parts of a whole)
• Line charts (for trends over time)

Write clear observations: Use descriptive language to highlight insights:

• For bar charts: Use adjectives to describe size differences (largest, smallest, higher, lower)
• For pie charts: Use adjectives to describe proportions (majority, minority, significant)
• For line charts: Use adverbs to describe trends (rapidly, steadily, sharply)

Annotate for impact: Use visual annotations to draw attention to key points:

• Highlight data points with contrasting colors
• Add large, graphical labels to important numbers
• Use brackets or boxes to show calculations
• Overlay benchmark lines
• Explode data to show subcategories

6. Make Data Relatable Through Comparison and Context

"To help your audience understand the magnitude of the data, compare it to things that are familiar to them."

Develop a sense of scale: Help others grasp large or small numbers by comparing them to relatable concepts:

• Size: "One million squares would fill almost 31 pages."
• Time: "One million seconds is 11.57 days."
• Distance: "A million millimeters is one kilometer (about 12 New York City blocks)."

Use familiar comparisons:

• Length: Your height, a credit card, the width of a car lane
• Area: Football field, city block
• Volume: Building, Olympic swimming pool
• Time: Work hours, flight duration, TV episode length
• Speed: Walking pace, speed limits

Add context: Provide additional information that gives your data new meaning or reveals unexpected results.

7. Humanize Data by Identifying Heroes and Adversaries

"Most organizational data wouldn't exist without humans generating it."

Find the human story: Look for the people behind the data points. Who are the customers, employees, or stakeholders affected?

Identify conflict types:

• Hero vs. Self: Internal struggles (fear, bias, values)
• Hero vs. Person: Conflicts with others (customers, regulators)
• Hero vs. Society: Challenges against institutions or norms
• Hero vs. Technology: Struggles with systems or processes
• Hero vs. Nature: Battles against external forces (diseases, disasters)

Speak with characters: To truly understand the story behind the data:

• Read forums and customer comments
• Conduct surveys
• Interview a sample of your "data heroes"
• Ask open-ended questions to uncover motivations and challenges

8. Use Storytelling Techniques to Reveal Data Dramatically

"Make your DataStory truly come alive by creating suspense and telling an intriguing story with some elements of mystery."

Create suspense: Strategically withhold key features of your findings to build anticipation.

Surprise techniques:

1. Add context: Reveal additional information that changes the meaning of data
2. Zoom in or out: Uncover hidden features by adjusting the scale or focus

Dramatic reveals: Use presentation software to:

• Reveal chart elements one at a time
• Use transitions to zoom in or out of data
• Hide additional screens or data for a shocking reveal

S.T.A.R. moments: Create "Something They'll Always Remember" by using unexpected visuals or props to emphasize key points.

9. Leverage Emotional Arcs in Data Presentation

"If you have a chart that ends in good fortune, you can reveal each bar (or line segment) one at a time."

Six basic emotional arcs:

1. Rags to Riches (steady rise)
2. Man in a Hole (fall then rise)
3. Cinderella (rise, fall, then rise)
4. Tragedy (steady fall)
5. Icarus (rise then fall)
6. Oedipus (fall, rise, then fall)

Apply to data presentation:

• For positive outcomes: Build suspense by revealing data points sequentially, ending with good fortune
• For negative outcomes: Clearly explain the cause and address it directly
• For reversible negative trends: Position the audience as heroes who can change the outcome

Create catharsis: When presenting data that ends in ill fortune, help the audience learn from mistakes and feel motivated to take action.

Last updated: April 1, 2025