ThinkWithPrompt by SynotticThinkWithPrompt

Turn business insights into an action plan with owners and deadlines

Converts findings from an analysis, review, or workshop into a prioritized action plan with owners, deadlines, and success measures.

Projects & OperationsFew-ShotAdvancedAnalyzePlanFill-in Template

The prompt

Turn these business insights into an action plan. Insights or findings: [PASTE the analysis conclusions, review findings, workshop output, or survey takeaways] Goal these support: [e.g. "improve renewal rate from 82% to 88% this year"] Team and people available: [ROLES or names] Budget and time constraints: [DETAILS] Deadline or planning horizon: [e.g. next 90 days] Steps: 1. Restate each insight as a so-what: what it means for the goal. Drop or flag insights that are interesting but not actionable. 2. For each actionable insight, propose 1-3 specific actions. Each action starts with a verb and has a clear deliverable. 3. Score each action on impact (high / medium / low) and effort (high / medium / low). Sort into quick wins, major projects, fill-ins, and not now. 4. Sequence the actions: what must happen first, what depends on what. 5. Assign one owner per action (use [OWNER] where I haven't named someone) and a realistic deadline. 6. Give each action a success measure and a review date. Return: 1. An action plan table: # | Action | Insight it addresses | Impact | Effort | Owner | Start | Due | Success measure | Status. 2. The 3 actions to start this week. 3. Actions I'm choosing not to do now, and why. 4. Risks to delivery and how to reduce them. 5. A short message to share the plan with my team in email, Teams, or Slack. Don't add insights I didn't give you. Keep the plan small enough for my team to actually deliver alongside their normal work.

Highlighted [brackets] are blanks to replace with your own details.

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What to fill in

  • e.g. "improve renewal rate from 82% to 88% this year"
  • ROLES or names
  • DETAILS
  • e.g. next 90 days
  • OWNER

How this prompt is built

This prompt follows the Few-Shot structure (Few-shot prompting). A few-shot prompt includes one or more worked examples of the input and the output you want, so the model can copy the pattern instead of guessing it.

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