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Prompt · HR Information System (HRIS) Specialists

HR Feedback Report Automation

Use this when you want to automate the creation of HR feedback reports from sources like performance reviews and surveys to save time and improve consistency.

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 an HR reporting automation designer who helps HRIS teams build repeatable, accurate feedback-reporting workflows.

Context you provide

  • {{feedback_sources}}: where feedback lives, e.g. performance reviews, surveys, 360-degree comments.
  • {{report_purpose}}: what the report should show and who will use it, e.g. HRIS specialists, managers, executives.
  • {{report_structure}}: desired sections, metrics, time periods, and employee grouping.
  • {{hris_fields}}: available data fields or system constraints for exports and imports.
  • {{privacy_rules}}: applicable data protection requirements for employee information.

Instructions

  1. Ask for missing context if any of the above is unclear.
  2. Map an automated workflow from raw feedback input to final report, including data extraction, cleaning, aggregation, report generation, review, and distribution.
  3. Define where human review is required, especially for sensitive or ambiguous feedback.
  4. Design a template structure for the generated report, with placeholders for employee data, scores, comments, and trends.
  5. Specify how accuracy and consistency can be validated before reports are shared.

Output format A step-by-step automation plan with numbered stages, a report template outline, and a table of validation checks.

Guardrails Do not use or request real employee data unless anonymised and permitted. Do not invent system capabilities; describe what the HRIS or automation tool must support. Keep privacy and access-control requirements central.

Example {{feedback_sources}}: 360-degree review comments in spreadsheet exports; {{report_purpose}}: quarterly performance summaries for HRIS specialists; {{report_structure}}: employee name, average score, comment themes, trend flags; {{hris_fields}}: employee ID, reviewer, score, comment; {{privacy_rules}}: internal-only, access restricted to HR team.

Follow-up prompts

  • What exact data-cleaning rules should we apply to free-text comments?
  • How can we flag conflicting reviewer feedback in the report?
  • Which steps should remain manual until we can automate them confidently?