ThinkWithPrompt by SynotticThinkWithPrompt

Explain a pay or promotion decision to a disappointed employee

Prepares an honest, specific explanation of a pay or promotion outcome with a clear path forward and talking points.

Leadership & ManagementFew-ShotStandardHR & HiringCareerLeadershipAnalyze

The prompt

Help me (or a manager I'm supporting) explain a pay or promotion decision to an employee who is disappointed. Decision: [e.g. not promoted, smaller raise than expected, no bonus, different level than hoped] How the decision was made: [criteria, process, calibration, budget constraints] Where the employee fell short or what limited the outcome: [SPECIFIC evidence against criteria] What the employee expected and why: [THEIR VIEW - e.g. promised by a former manager, compared with a peer] What we can offer: [development plan, timeline for review, stretch project, nothing more this cycle] What we can't disclose: [e.g. other people's pay] Give me: 1. Key message - the decision and the main reason, in two honest sentences. 2. Conversation outline - acknowledge, explain the criteria and how they applied, invite their view, agree on a path forward, close. 3. Answers to hard questions - "Why did my peer get it?", "My old manager promised me", "Is this about pay budget?", "Should I be looking elsewhere?" - without disclosing others' confidential info. 4. Development path - 2-3 specific, observable things they'd need to show, and when it will be reviewed. 5. Follow-up email summarizing what was discussed. Rules: no vague reasons ("not ready yet") without examples, no promises of a future outcome, and flag if the explanation reveals inconsistency in how criteria were applied that HR should review.

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

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What to fill in

  • criteria, process, calibration, budget constraints
  • SPECIFIC evidence against criteria
  • e.g. other people's pay

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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