Your question is Measure Engineering Delivery Success. Take a moment with it on the right.
Talk me through your thinking if you like. When you're confident, submit your answer and I'll grade it like a real screen (7/10 or better passes).
NovaCloud is a B2B SaaS company with 14 engineering squads shipping customer-facing features and platform improvements. The CTO says the team "feels busier than ever," but stakeholders disagree on whether delivery performance is actually improving.
In the last two quarters, story points completed increased from 4,800 to 5,900 (+23%), but on-time delivery of committed roadmap items fell from 82% to 68%. Median cycle time rose from 4.2 days to 6.1 days, Sev-1/Sev-2 incidents increased from 9 to 15, and 30-day post-release defect rate increased from 1.8 to 2.6 defects per 1,000 deploys. Deployment frequency improved from 210 to 290 production deploys per month, while engineering headcount stayed flat at 96.
The CTO wants a clear framework for measuring and reporting engineering delivery success to the executive team and product leadership. They do not want a single vanity metric; they want a balanced scorecard that captures speed, predictability, quality, and business impact.
jira_issues: issue_id, team_id, issue_type, story_points, status, created_at, started_at, completed_at, committed_sprint_idsprint_commitments: sprint_id, team_id, committed_items, completed_items, roadmap_flagdeployments: deploy_id, team_id, service_id, deployed_at, environment, rollback_flagincidents: incident_id, severity, service_id, opened_at, resolved_at, root_cause_categorydefects: defect_id, release_id, created_at, severity, source, customer_reported_flagroadmap_items: item_id, owner_team, planned_release_date, actual_release_date, revenue_flag, strategic_priority