Your question is Measure AVIA Engineering 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).
AVIA’s engineering organization supports the AVIA consumer app, booking flows, partner integrations, and internal platform services. Over the last two quarters, leadership sees mixed signals: feature throughput increased, but incident volume and customer-reported bugs also rose, and product teams say delivery feels less predictable.
You are the Engineering Manager for a 42-engineer org across 5 teams. In Q1, the org shipped 96 production releases, completed 118 roadmap tickets, and delivered 3 major features in the AVIA app. However, Sev-1/Sev-2 incidents increased from 6 to 11, mean time to recovery rose from 42 to 68 minutes, escaped defects increased from 21 to 34, and sprint commitment reliability fell from 84% to 71%. Meanwhile, AVIA app checkout conversion improved from 4.8% to 5.1%, but 30-day retention stayed flat at 28%.
The VP of Engineering asks: “How should we measure whether an engineering team is actually successful, not just busy?” Product leadership wants a metric framework that balances speed, quality, reliability, and business impact. Your answer should define a primary success metric or scorecard, explain trade-offs, and show how you would diagnose conflicting movements.
deployments: service_name, team_id, deploy_time, rollback_flag, change_size, environmentincidents: incident_id, severity, service_name, start_time, resolved_time, root_causejira_issues: issue_id, team_id, type, story_points, status, committed_sprint, completed_datebug_reports: bug_id, source, severity, created_date, linked_releaseavia_app_events: user_id, session_id, feature_name, booking_started, booking_completed, retention_day_30