Define HR metrics, standard reports, and data access rules
One agreed definition for each HR metric, a standard report set by audience, and privacy rules for who sees what.
The prompt
Help me create an HR data reporting standard for my organization, including privacy and access rules.
Organization: [size, countries or regions, business units]
HR systems and data sources: [e.g. HRIS, payroll, applicant tracking, engagement survey tool]
Who receives HR reports: [e.g. executives, business unit leaders, managers, works councils, the board]
Current problems: [e.g. "each region counts turnover differently", "managers can see salaries they shouldn't"]
Privacy laws that apply: [e.g. GDPR, state privacy laws, local labor law]
Create:
1. Metric dictionary for core measures: headcount, FTE, hires, voluntary and involuntary turnover, retention, time to fill, absence rate, diversity representation, and pay ratios. For each: definition, formula, inclusions and exclusions (contractors, interns, leave), data source, owner, and refresh frequency.
2. Standard report set: which report goes to which audience, how often, and at what level of detail.
3. Access and privacy rules: access tiers by role, minimum group size before showing breakdowns (to prevent identifying individuals), which fields are sensitive (pay, health, diversity data), anonymization rules, retention periods, and how ad hoc data requests are approved.
4. Data quality checks to run before each reporting cycle.
5. Regional differences to handle, such as consent rules or limits on collecting certain data in some countries, marked [CONFIRM WITH LOCAL COUNSEL].
6. A rollout plan: pilot, training for report users, and a change log for metric definitions.
This is general guidance; have privacy and employment law requirements reviewed by legal or the data protection officer.
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
- size, countries or regions, business units
- e.g. GDPR, state privacy laws, local labor law
- CONFIRM WITH LOCAL COUNSEL
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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