Purpose
The purpose of this How-To is to provide QA teams at Memorres with a structured method for tracking QA metrics directly within project tools. Metrics like coverage, defect density, and closure rates lose meaning if they are scattered across spreadsheets or reported inconsistently. By tracking metrics in the same tools used for test management and bug tracking, QA ensures real-time visibility, transparency, and traceability for both internal teams and clients.
Scope
This document applies to all delivery projects using approved tools such as Jira (with Xray/Zephyr), TestRail, or ClickUp. It covers tracking of test execution, defect lifecycle, and trend metrics within these tools. It does not cover financial KPIs, client SLAs, or external analytics platforms.
Process
| Step | Activity | Detailed Description | Responsible Role | Output |
| 1 | Configure Metrics in Tool | QA Lead configures dashboards/widgets in the chosen project tool. Metrics such as execution % and defect breakdown must be visible by default. | QA Lead | Configured dashboard with key metrics |
| 2 | Track Execution Coverage | QA Engineers update case status (pass/fail/not-executed) directly in tool during execution. Coverage auto-calculates. | QA Engineer | Real-time execution % and coverage reports |
| 3 | Track Defect Lifecycle | Each defect’s status (New → Assigned → In Progress → Fixed → Retest → Closed) must be updated promptly in the tool. Defect counts and severity ratios update automatically. | QA Engineer + Dev | Transparent defect backlog with live metrics |
| 4 | Monitor Quality Trends | QA Leads configure trend charts: defect discovery vs closure, reopened ratio, regression failures. Trends should be reviewed weekly. | QA Lead | Trend dashboard (charts/graphs) |
| 5 | Validate Metric Accuracy | QA Lead reviews whether tool metrics match actual execution and defect logs. Discrepancies must be corrected before reports are shared. | QA Lead | Validated metric set |
| 6 | Export & Share Reports | Weekly snapshots are exported from the tool into client-facing QA reports. Dashboards are used internally; reports are used for formal updates. | QA Lead | Weekly QA report with traceable metrics |
Example – Tool-Based Metrics
| Metric | Tool | How It’s Tracked | Example Snapshot |
| Execution Coverage | TestRail / Jira-Xray | Case status updates (Pass/Fail/Not-Executed) | “92% execution complete, 8% pending” |
| Defect Distribution | Jira / ClickUp | Severity field in defect tickets | “10 open defects: 2 Critical, 5 Major, 3 Minor” |
| Closure Trend | Jira Dashboard | Chart: New vs Closed defects per sprint | “Closure rate exceeded discovery rate in last 2 sprints” |
| Reopened Defects | Jira Query | Filter defects reopened after closure | “3 reopened defects in payments module” |
| Regression Stability | TestRail Regression Suite | Compare pass/fail rates across builds | “Login test failed in 2 of last 5 builds” |
Closing Note & Cross-References
Tracking QA metrics inside project tools ensures accuracy, real-time visibility, and consistency across projects. Dashboards provide live progress, while exports form the basis of client-facing reports.
This How-To links directly with the Enablement Doc – How to Use Dashboards & Reports for QA Metrics, which explains reporting best practices, and the QA Summary Report Template, which provides a standardized reporting format.