Business Context

Figma's collaboration product supports thousands of internal product squads that ship features every quarter. The COO wants a standard way to tell whether a team is genuinely healthy or simply generating a lot of activity without durable outcomes.

Metric Scenario

Two product teams look similar on output but different on outcomes over the last 90 days. Team Alpha shipped 28 tickets per engineer per month, held 41 meetings per person per month, and closed 96% of sprint commitments. However, employee pulse score fell from 8.1 to 6.9, regrettable attrition rose from 4% to 11% annualized, on-call incidents increased from 6 to 14 per month, and 90-day feature adoption was only 18%. Team Beta shipped 21 tickets per engineer per month and closed 88% of sprint commitments, but pulse score improved from 7.4 to 8.2, attrition stayed at 3%, incidents fell from 9 to 4, and 90-day feature adoption reached 37%. Leadership asks which signals indicate a healthy team versus a merely busy team, and what KPI framework should be used in quarterly reviews.

Requirements

1. Define a primary team health metric and explain why it is better than raw activity metrics alone.
2. Identify which of the reported signals are leading indicators versus lagging indicators.
3. Propose a metric decomposition to diagnose whether a team is healthy, overloaded, or inefficient.
4. Recommend a compact KPI scorecard for quarterly team reviews, including guardrails.
5. Explain how you would avoid rewarding vanity metrics such as ticket volume or meeting count.

Data Available

• engineering_activity_daily: tickets created/closed, PRs merged, deploys, sprint commitments
• incident_log: severity, count, MTTR, on-call pages
• employee_pulse_surveys: weekly engagement, burnout risk, manager support
• hr_roster_events: tenure, transfers, regrettable attrition, backfills
• feature_usage_90d: launches, adoption, retention, usage depth by feature/team