Employee Attrition Cohort Analysis Builder

You are an HR analytics partner analyzing employee attrition and retention risk. Use aggregated or appropriately anonymized data only.

Organization context: [industry, headcount, regions, growth stage]
Business question: [reduce regrettable attrition, understand first-year turnover, compare teams, plan retention actions]
Dataset fields available: [employee ID, hire date, termination date, role, level, department, manager, location, hiring source, performance band, engagement score]
Time period: [months or years covered]
Attrition definitions: [voluntary, involuntary, regrettable, non-regrettable, internal transfer, contractor excluded]
Cohorts to compare: [hire month, tenure band, role, department, location, manager, recruiting source]
Privacy constraints: [minimum group size, no naming individuals, sensitive demographics excluded or protected]
Known events: [reorg, compensation changes, remote policy, leadership changes, layoffs, market shifts]
Current metrics: [monthly attrition, annualized turnover, retention rate, headcount, exit reasons]
Tools available: [Excel, SQL, Python, Tableau, Power BI, Looker]
Decision needed: [manager coaching, onboarding changes, compensation review, workload intervention]

Create:
1. Data quality checklist for dates, termination reasons, rehires, transfers, and missing fields.
2. Attrition metric definitions with formulas and caveats.
3. Cohort analysis plan by hire cohort, tenure band, role, department, location, manager, and source.
4. Segmentation guardrails that protect privacy and avoid overinterpreting tiny groups.
5. SQL or spreadsheet formulas for core retention and attrition calculations.
6. Dashboard layout with trend, cohort curve, heatmap, exit reason mix, and action queue.
7. Interpretation framework that separates normal churn from concerning patterns.
8. Recommended interventions mapped to likely drivers.
9. Executive summary template with confidence level and limitations.
10. Follow-up questions for HR, finance, managers, and recruiting.

Keep the analysis careful, privacy-aware, and grounded in decisions the company can actually take.