Data Visualization Objectives and chart selection
What are objectives of visualization and what popularly known charts serve these visualization objectives?
Story telling frameworks
Storytelling frameworks help you structure information so it’s clear, persuasive, and action-oriented. Below is a comprehensive, structured list, grouped by use case, with simple explanations and examples (including data/business contexts like Superstore). Which One Should You Use? Since we work a lot with Tableau, dashboards, and Superstore-style datasets, the best combinations are: SCQA + Data → Insight → Action | What–So What–Now What for explaining charts | Pyramid Principle for leadership presentations.
A: Classic & Universal Storytelling Frameworks
1. Hero’s Journey (Joseph Campbell)
Structure: Ordinary world → Call to adventure → Challenges → Transformation → Return with solution
Use when: Long narratives, Case studies, Change management stories
Data example: A struggling retail business → discovers losses → analyzes data → optimizes pricing → returns profitable.
2. Freytag’s Pyramid
Structure: Exposition → Rising action → Climax → Falling action → Resolution
Use when: Explaining cause–effect, Process improvements, Incident analysis
Data example: Sales decline → discounts increase → profits collapse → correction → recovery.
B: Business & Executive Storytelling Frameworks
3. SCQA (Situation–Complication–Question–Answer)
Very popular in consulting
Structure : Situation – What we know → Complication – What’s wrong → Question – What must we decide → Answer – Insight + recommendation
Superstore example: Situation: Sales growing → Complication: Profit declining → Question: Why? → Answer: High discounts in Furniture → reduce discounts
4. Pyramid Principle (Barbara Minto)
Structure: Start with the answer → Support with grouped arguments → Back with data
Use when: Executive dashboards, Board presentations
Example: “Profits fell due to 3 reasons: discounts, shipping, product mix.”
5. Problem–Solution–Impact
Structure: Problem → Solution → Business impact
Use when: Action-oriented dashboards, Recommendations
C: Data & Analytics Storytelling Frameworks
6. Data Storytelling Flow (Most Common)
Structure: Motivation (business question) → Data → Metrics → Visuals → Insights → Actions
This matches our Superstore storytelling work very well.
7. DIKW Model
Data → Information → Knowledge → Wisdom
Data( Raw numbers) → Information (Organized data) → Knowledge (Patterns) → Wisdom (Decisions)
Example: Orders → Profit trends → Loss drivers → Stop discounting
8. Before–After–Bridge
Structure: Before: Current state → After: Desired state → Bridge: How data helps move us there
Great for: Transformation stories, KPI improvement narratives
D: Persuasive & Marketing Storytelling
9. AIDA
Attention → Interest → Desire → Action
Use when: Selling an idea, Pitch decks, Data-driven persuasion
10. PAS (Problem–Agitate–Solution)
Structure: State the problem → Show consequences → Present solution
Example: Losses → ignored will worsen → pricing fix
E: UX & Product Storytelling
11. Jobs-to-Be-Done (JTBD)
Structure: When ___ → I want ___ → So that ___
Data example: When profit drops, I want a dashboard so I can identify loss drivers.
12. User Journey Mapping
Structure: Awareness → Consideration → Decision → Outcome
Used heavily in product analytics and customer experience dashboards.
F: Teaching, Training & Explanation Frameworks
13. What – So What – Now What
Structure: What happened? → Why does it matter? → What should we do?
Excellent for explaining dashboards.
14. 5W1H
Who, What, When, Where, Why, How
Good for: Exploratory analysis, Root cause analysis
G: Strategy & Change Storytelling
15. OKR Storytelling
Objective (Why) → Key Results (How success is measured) → Initiatives (What we do)
16. Vision–Strategy–Execution
Structure : Where we want to go → How we’ll get there → What actions we’ll take
Summary (when to use what framework)
| Framework | Best For |
|---|---|
| Hero’s Journey | Long narratives, change stories, case studies |
| Freytag’s Pyramid | Cause–effect analysis, incident storytelling |
| SCQA (Situation–Complication–Question–Answer) | Executive communication, consulting-style data stories |
| Pyramid Principle | Decision-making, leadership presentations |
| Problem–Solution–Impact | Action-oriented recommendations |
| Data → Insight → Action | Analytics storytelling, dashboards |
| DIKW Model | Explaining data maturity and decision logic |
| Before–After–Bridge | Transformation stories, change initiatives |
| AIDA | Persuasive storytelling, pitches |
| PAS (Problem–Agitate–Solution) | Marketing and persuasive narratives |
| Jobs-to-Be-Done (JTBD) | User-centered product and data stories |
| User Journey Mapping | Customer experience and product analytics |
| What – So What – Now What | Dashboard explanation, insight communication |
| 5W1H | Exploratory analysis, root-cause analysis |
| OKR Storytelling | Strategy alignment, performance tracking |
| Vision–Strategy–Execution | Strategic planning and leadership narratives |
