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Metrics platform (spec)

The build specification for the platform the metrics framework feeds: one build, many views — not eleven dashboards. Every measure is auto-fed from systems of record; nothing is hand-reported. Baselined during StudyBuddy so "velocity compounds" is measured against a real denominator, not asserted. The build itself is pending; this spec is what it must satisfy.

One build, many views

The same underlying data, filtered per audience. If two audiences see different numbers for the same question, the platform has failed.

ViewAudienceAnswers
STOP progress & burn-downLeadership, DeliveryIs the remediation backlog shrinking on schedule? What's blocked?
Savings vs AI spendLeadership, FinanceIs the FinOps savings plan funding the token spend as promised?
Engineering / DORASquads, DeliveryThe four keys vs the legacy baseline — the compounding-velocity evidence.
QualityTest, SquadsEscaped-defect rate by root-cause category, mutation score, regression-pack growth, first-time gate pass rate.
Security & complianceSecurity, LeadershipGate pass rates, open findings by severity, waivers and risk acceptances approaching expiry.
AI cost & usageAI, SquadsToken cost per shipped change, agent first-pass acceptance rate, rework rate on agent PRs.
Toolkit adoptionAI, EngineeringWhich prompts/skills/playbooks are actually used; capital-deposit rate per loop (governance).
Commercial proof-pointsCommercialClient-safe evidence: release frequency, fix SLAs met, uptime — feeds the transparency pack.

Data sources — no manual reporting

SourceProvides
gitCommit/PR flow, provenance tags (human/agent/mixed), docs-updated-with-code compliance
CI/CD pipelineDORA four keys (emitted by the pipeline itself), gate pass/fail, coverage and mutation scores, scan findings
Registers (toolkit/registers/)Remediation and security-debt burn-down, waivers, risk acceptances and expiries, signal dispositions
Agent telemetryToken spend by project / phase / environment tag, first-pass acceptance, rework, capital deposits
Product telemetryAdoption and funnel events per the product telemetry standard

The rule: if a metric requires a human to fill in a spreadsheet, it is not on the platform. Either the source system emits it or the metric is redefined until one does. Manual reporting is the overhead RAPID removes, not a data source.

Baselined during StudyBuddy

The DORA legacy baseline is the denominator; StudyBuddy is instrumented from its first loop, so the velocity, quality and cost curves exist from day one. This ordering matters: a platform stood up after the first build has no before-picture, and the commercial case rests on the comparison.

Rules inherited from the framework

  • Metrics inform, never rank individuals — every view aggregates at squad or product level. This is enforced in the platform's data model, not left to dashboard etiquette.
  • Definitions live in the framework (metrics standard and toolkit/metrics/); the platform computes them. One source of truth for what "lead time" means.
Pending: platform tooling selection

Whether this is assembled (warehouse + BI tool) or bought (an engineering-intelligence product) is a tech selection decision not yet made — recorded as an ADR when taken. This spec is deliberately tool-agnostic so the selection can be scored against it.

Standards referenced: DORA, SPACE, DX Core 4.