Write an outcome-based scorecard for an executive hire
A scorecard defining mission, measurable outcomes, and competencies for a senior hire, used to align interviewers and recruiters.
The prompt
Help me write a scorecard for an executive role I'm hiring.
Role: [e.g. "first CFO", "VP Engineering"]
Why we're hiring now: [WHAT's broken or about to break without this person]
Company stage and next 2-3 years: [e.g. "raising Series B, expanding to Europe"]
What they'll inherit: [TEAM size, systems, known problems]
Reporting line and key peers: [WHO]
Must-haves and nice-to-haves I have in mind: [LIST]
Compensation range: [RANGE, or "not set"]
Build the scorecard:
1. Mission: one or two sentences on why the role exists.
2. Outcomes: 4-6 measurable results expected in the first 12-18 months, each with a target and time frame (e.g. "close books in 7 business days by month 6").
3. Competencies: 5-8 specific behaviors and skills tied to those outcomes, not generic traits like "strategic thinker".
4. Stage fit: experience at a similar scale and stage, and the risk of hiring someone who has only run much larger or much smaller teams.
5. Disqualifiers: what would rule someone out.
6. Interview plan: which interviewer assesses which competency, and one work-sample or case exercise.
Challenge my inputs: flag must-haves that are really preferences, credential requirements that narrow the pool without predicting success, and outcomes that are unrealistic for the timeline.
Keep the criteria job-related and consistent for every candidate, and check them against local hiring law.
Highlighted [brackets] are blanks to replace with your own details.
Fill in the blanks and use this promptMore HR & Hiring prompts
What to fill in
- e.g. "first CFO", "VP Engineering"
- WHAT's broken or about to break without this person
- e.g. "raising Series B, expanding to Europe"
- TEAM size, systems, known problems
- WHO
- LIST
- RANGE, or "not set"
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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