Engineering Team KPIs: DORA Metrics, Velocity, and Quality Dashboard,\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\n
Define engineering performance KPIs based on DORA metrics (Deployment Frequency, Lead Time, MTTR, Change Failure Rate) combined with quality and team health indicators.
Create an engineering metrics dashboard that measures delivery performance, code quality, and team health without incentivizing harmful behaviors like velocity inflation or quality shortcuts.
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Prompt objective
Create an engineering metrics dashboard that measures delivery performance, code quality, and team health without incentivizing harmful behaviors like velocity inflation or quality shortcuts.
Real use case
A 40-person engineering organization has no standardized way to measure team performance. Leadership only knows if projects are late. They want DORA metrics plus quality indicators to understand engineering effectiveness.
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Prompt
Design an engineering KPI dashboard for [COMPANY NAME] with [NUMBER] engineering teams and [NUMBER] developers.\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\n\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\n**DORA Metrics (Industry Standard):**\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\n\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\n1) Deployment Frequency:\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\n- How often does each team deploy to production?\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\n- Target: Elite = multiple/day, High = weekly, Medium = monthly\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\n- Data source: CI/CD pipeline logs\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\n\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\n2) Lead Time for Changes:\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\n- Time from code commit to production deployment\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\n- Target: Elite = <1 hour, High = <1 day\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\n- Data source: Git + deployment timestamps\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\n\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\n3) Mean Time to Recovery (MTTR):\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\n- How long to restore service after an incident?\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\n- Target: Elite = <1 hour, High = <1 day\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\n- Data source: Incident management tool\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\n\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\n4) Change Failure Rate:\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\n- % of deployments causing incidents or rollbacks\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\n- Target: Elite = 0-5%, High = 6-15%\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\n- Data source: Incident + deployment logs\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\n\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\n**Additional Engineering KPIs:**\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\n\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\n5) Code Quality:\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\n- Code review turnaround time\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\n- Test coverage %\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\n- Bug escape rate (bugs found in production vs. testing)\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\n- Technical debt ratio\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\n\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\n6) Team Health:\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\n- Sprint velocity trend (stable, not increasing)\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\n- Work-in-progress (WIP) limits adherence\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\n- On-call load per engineer\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\n- Team satisfaction survey\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\n\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\n**Dashboard Design:**\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\n- Per-team scorecard with DORA classification\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\n- Trend over 12 weeks\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\n- Cross-team comparison (not for ranking — for learning)\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\n- Alert thresholds for degradation\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\n\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\n**Anti-Patterns to Avoid:**\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\n- Never use velocity as a performance metric\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\n- Don't compare teams directly (different contexts)\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\n- Focus on trends, not absolute numbers\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\n\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\nInclude data collection SQL queries and dashboard mockup.
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