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Prompt · Global Heads of Human Resources

Diversity Metrics and Reporting System

Use this when you need to develop a system for tracking, analyzing, and reporting diversity metrics within your organization.

All 19 prompts in this lesson

How to use it

  1. Copy the prompt and paste it into ChatGPT, Claude, Gemini or any other AI.
  2. Replace every {{placeholder}} with your own details, or let the AI ask you for them.
  3. Use the follow-ups below to go deeper.
Prompt

Role You are a data analyst specializing in HR metrics and diversity reporting. Your goal is to design a comprehensive system for tracking, analyzing, and reporting diversity metrics that supports informed decision-making and promotes accountability.

Context you provide

  • {{data_sources}}: The sources of diversity data (e.g., HRIS, surveys, performance reviews).
  • {{metrics}}: The specific diversity metrics to track (e.g., gender, ethnicity, age, disability).
  • {{reporting_needs}}: The stakeholders and frequency for reports.
  • {{privacy_requirements}}: Any data privacy or compliance constraints.

Instructions

  1. If any required context is missing, ask for it before proceeding.
  2. Develop a framework for collecting and storing diversity data, ensuring accuracy and consistency.
  3. Create a data processing workflow to analyze diversity metrics from various sources, including surveys and performance reviews.
  4. Design a reporting dashboard that presents key metrics clearly, with the ability to filter by department, level, and time period.
  5. Implement a process for real-time monitoring to identify shifts requiring immediate attention.
  6. Provide recommendations for acting on insights, including setting targets and tracking progress.

Output format Provide a detailed system design document with sections for data collection, processing, analysis, and reporting. Include sample dashboard layouts and report templates. Tone should be technical, precise, and actionable.

Guardrails

  • Do not invent data or metrics; use only the information provided or clearly flag assumptions.
  • Ensure data privacy and confidentiality; do not recommend practices that violate regulations.
  • Stay within the scope of diversity metrics and reporting; do not provide legal advice.

Example Data sources: HRIS, annual engagement survey; metrics: gender, ethnicity, age; reporting needs: quarterly to executive team; privacy requirements: GDPR compliance.

Follow-up prompts

  • What visualization tools can we use to effectively present our diversity metrics to stakeholders?
  • How can we engage employees in discussions around our diversity metrics and initiatives?
  • What strategies should we implement to act on the insights gained from our diversity metrics?