Unit 4: Business storytelling and ethics
Computer Applications and Data Visualization for Managers notes · PTU syllabus (MBA 208-26)
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Unit summary
Insights matter only when they persuade people to act — honestly. This unit covers communicating analytical insights through narrative frameworks, designing impactful presentations, infographic development, data security and the ethical use of AI, misleading visualisations and interpretation bias, and applications across finance, marketing, HR and operations.
After this unit you can
- Communicate insights through data storytelling frameworks
- Design impactful presentations and infographics
- Explain data security and the ethical use of AI
- Recognise misleading visualisations and apply analytics across functions
PTU syllabus topics
- Communicating analytical insights through narrative frameworks
- designing impactful presentations
- infographic development
- data security and ethical use of AI
- misleading visualizations and interpretation bias
- applications across finance
- marketing
- HR and operations
- 1Context
Why this matters
- 2Insight
What the data shows
- 3Evidence
One clear chart per point
- 4Implication
What it means for the business
- 5Recommendation
What to do next
Topic 1
Data storytelling and narrative frameworks
Data storytelling combines data, visuals and narrative to explain what happened, why it matters and what to do.
- 1. Data: Accurate, relevant evidence
- 2. Visuals: Charts that reveal the insight
- 3. Narrative: Context, conflict and resolution
- 1Context
Where we are
- 2Complication
What changed or went wrong
- 3Insight
What the data reveal
- 4Recommendation
What we should do
- 5Impact
Expected result and next steps
- Other frameworks: Minto's pyramid principle (answer first, then supporting arguments), SCQA (situation, complication, question, answer), "What? So what? Now what?".
Topic 2
Designing impactful presentations
- One message per slide, written as an action title ("North region sales fell 12% after the price rise").
- Use the simplest chart that shows the point; highlight the key data in colour, grey the rest.
- Lead with the conclusion for senior audiences; keep details in the appendix.
- Rehearse the narrative and anticipate questions.
Topic 3
Infographic development
- Infographic: a visual summary combining charts, icons, short text and numbers for quick understanding.
- 1Define audience and message
- 2Collect and verify data
- 3Choose a layout
Timeline, comparison, process, statistical
- 4Design with icons and charts
- 5Add source and review
- Tools: Canva, Piktochart, PowerPoint, Adobe Express.
Topic 4
Data security and ethical use of AI
- Data security: access controls, encryption, strong passwords and multi-factor authentication, masking personal data, secure sharing, backups.
- Law: Digital Personal Data Protection Act 2023 — consent, purpose limitation, data minimisation, duties of data fiduciaries; IT Act 2000.
- Ethical AI principles: fairness (no discriminatory bias), transparency and explainability, accountability, privacy, human oversight, reliability.
- Risks: biased training data, hallucinated outputs from generative AI, leakage of confidential data into public tools, deepfakes.
Topic 5
Misleading visualisations and interpretation bias
Truncated axis
Bar chart not starting at zero exaggerates differences
Cherry-picked range
Only the favourable time period shown
Dual axes
Imply false correlation
3D and area distortion
Sizes misjudged
Cumulative charts
Hide declining recent figures
Missing context
No base, sample size or source
- Interpretation biases: confirmation bias, correlation mistaken for causation, survivorship bias, Simpson's paradox (trend reverses when groups are combined), anchoring on the first number seen.
Topic 6
Applications across functions
| Function | Analytics and visualisation applications |
|---|---|
| Finance | Budget vs actual dashboards, cash-flow forecasting, ratio trends, fraud detection |
| Marketing | Campaign ROI, customer segmentation, funnel and conversion analysis, sentiment from social media |
| HR | Headcount and attrition dashboards, diversity metrics, hiring funnel, training effectiveness |
| Operations | Inventory levels, on-time delivery, defect rates, capacity utilisation, supply chain maps |
Key terms
- Data storytelling
- Communicating insights with data, visuals and narrative
- Pyramid principle
- Presenting the answer first, then supporting points
- Infographic
- Visual summary of information and data
- DPDP Act
- India's 2023 law on digital personal data protection
- Simpson's paradox
- Trend that reverses when groups are combined
Quick revision
- Story = data + visuals + narrative; context → complication → insight → recommendation.
- Action titles; one message per slide.
- Infographic process and tools.
- Data security, DPDP Act, ethical AI principles.
- Misleading charts and biases; applications in finance, marketing, HR, operations.
Important exam questions
Practice questions written to the PTU exam pattern for this unit's syllabus: short answers (Section A style) and long answers (Sections B and C style).
Short-answer questions
- Q1.What is data storytelling?
- Q2.What is the SCQA framework?
- Q3.State two steps in developing an infographic.
- Q4.Name three principles of ethical AI.
- Q5.How does a truncated axis mislead?
- Q6.Give one HR application of dashboards.
Long-answer questions
- Q1.Explain narrative frameworks for communicating analytical insights.
- Q2.Discuss how to design impactful presentations and infographics.
- Q3.Discuss data security and the ethical use of AI in business analytics.
- Q4.Explain common misleading visualisations and interpretation biases with examples.
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