Tracking test automation metrics manually often leads to outdated figures and missed engineering gaps.
To solve this, automated reporting directly from your test suites—such as Playwright and Cucumber—provides clear visibility into health, execution speed, and coverage.
Below is a breakdown of how to structure an Automation KPI Dashboard to streamline test metrics, track trends, and establish actionable engineering goals.
Executive Summary Dashboard KPI Metric Target Current Value Status Trend Total Test Cases 100% coverage 85% 🟡 Partial ↗️ Up Automated Test Coverage 90%+ 78% 🟡 Partial ↗️ Up Pass Rate (Last Run) 95%+ 92% 🟡 Partial ↔️ Stable Avg.
Execution Time < 30 min 28 min 🟢 Good ↘️ Down Flaky Test Rate < 2% 1.5% 🟢 Good ↔️ Stable Defects Detected — 3 🟡 Review ↔️ Stable CI/CD Pipeline Success 100% 98% 🟡 Partial ↗️ Up Key Metric Breakdowns
1.
Coverage & Execution Total Test Suite: 120 tests (94 Automated, 26 Manual).
Latest Run (2026-05-29): 94 executed — 87 passed, 7 failed, 0 skipped.
2.
Flakiness Tracking Flaky Tests (Last 10 Runs): 2 scenarios identified.
Top Offenders: Scenario A: UI timeout issues.
Scenario B: Data synchronization lag.
3.
Defect Detection & CI/CD Performance Defect Lifecycle: 3 opened, 1 closed (Avg. resolution time: 2 days).
Pipeline Health: 98% success rate, 12 min average build time.
Primary Cause of Pipeline Failure: Dependency resolution errors.
Execution & Pass Rate Trends (Last 6 Runs) Run Date Pass % Fail % Flaky % Duration (min) 2026-05-29 92% 8% 2% 28 2026-05-28 91% 9% 2% 29 2026-05-27 90% 10% 3% 30 2026-05-26 89% 11% 3% 31 2026-05-25 88% 12% 4% 32 2026-05-24 87% 13% 4% 33 Next Engineering Action Items Automation Expansion: Push total automated coverage past 90%.
Flakiness Mitigation: Refactor explicit waits and isolation for UI timeout and data sync scenarios.
Pipeline Stability: Resolve dependency caching errors to bring CI/CD success to 100%.
Optimization: Lower execution suite duration below 25 minutes using parallel run setups.
Implementation Note: This dashboard context can be auto-generated by parsing execution JSON outputs (from frameworks like Playwright or Cucumber BDD) directly into your CI/CD reporting artifacts after every major test cycle or sprint.