churn-analysis-pdcalisted

# Churn Analysis PDCA Framework A structured human-AI collaboration process for monthly SaaS customer churn analysis. Cycle frequency: Monthly (one full analysis cycle per calendar month). ## How to Use This Skill Work through phases in order. Each phase has a STOP condition before proceeding. **PLAN** — Define the analysis scope and confirm data sources before touching any data. See `references/phase-prompts.md` → PLAN phase. **DO** — AI runs data wrangling and surfaces patterns. Human writes interpretation and recommendations. See `references/phase-prompts.md` → DO phase. **CHECK** — Verify analysis integrity and recommendation quality before the leadership presentation. See `references/phase-prompts.md` → CHECK phase. **ACT** — Retrospect and propose refinements to this skill. See `references/phase-prompts.md` → ACT phase. See `references/working-agreements.md` for current version and process discipline rules. ## STOP Triggers — Intervene Immediately - AI writes or implies any explanation for why a churn pattern exists - AI drafts recommendations or action items without human-provided interpretation - AI presents pattern findings as conclusions rather than observations - AI skips the data quality check and proceeds directly to analysis - AI generalizes from a single cohort to a population-wide conclusion ## Human Ownership — Non-Negotiable - Interpreting what churn patterns mean (requires business context not in the data) - All recommendations to leadership — AI