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Presenting an Insight and Recommendation

Lesson 5: Presenting an Insight and Recommendation

What is an analytical story?

An analytical story connects:

  1. The question
  2. The evidence
  3. The interpretation
  4. The recommended action

It doesn't mean forcing data into a dramatic narrative. It means presenting the most relevant facts in an order that helps the audience understand what to consider next.

A simple structure

Section

Content

Example

QuestionWhat we set out to answer"Why did delivery complaints rise in the West?"
Main findingThe headline answer"Median delivery time rose from 28 to 36 minutes."
EvidenceCharts and numbers supporting itTrend chart, breakdown by time of day
Context & limitationsWhat else could explain it; data gaps"Route data is missing for 2 of 30 days."
RecommendationA specific next step"Review evening staffing before changing the delivery promise."

Lead with the key message. Put supporting detail after it so a busy reader gets the conclusion quickly (the "pyramid principle").

Example

Weak

Strong

"The chart shows delivery times.""Median delivery time increased from 28 to 36 minutes in the West region during the last month. The increase is concentrated in evening orders; review staffing and route data before changing the delivery promise."

The strong version gives the what, the where, the when, the pattern, and a next step.

Match detail to the audience

Audience

What they need

Format

ExecutivesDecision, business impact, risk1-page summary, 1–3 charts
Managers / operationsTime periods, locations, records to act onDashboard + drill-down tables
Technical peersMetric definitions, query logic, validation stepsNotebook, SQL, documentation

Key takeaways

  • Separate observation from explanation.
  • Be clear about:
    • What the data shows
    • What it suggests
    • What additional evidence would strengthen the recommendation
  • Use precise language: "is associated with", not "causes", unless you have causal evidence.

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