Why ROI Matters

Platform engineering earns trust when it shows measurable impact. Pair DORA metrics with platform-specific KPIs that resonate with engineering leaders and finance alike.

Core Metrics

  • Lead time for changes – From merge to prod on golden paths; target minutes or hours, not days.
  • Deployment frequency – How often teams ship on the paved road versus legacy paths.
  • Change failure rate – Incidents or rollbacks per deploy; expect improvements from guardrails.
  • MTTR – Time to restore service, helped by standardized observability and rollback patterns.

Platform-Specific KPIs

  • Adoption: % of production workloads on golden path modules; number of teams onboarded.
  • Time-to-environment: Minutes to provision a new service/project with pipelines, policies, and observability pre-wired.
  • Cost transparency: % of resources with required labels; accuracy of chargeback/showback reports; variance between forecast and actual.
  • Self-service vs. tickets: Requests satisfied via portal/API vs. manual ops; time saved per request.
  • Compliance-by-default: Policies enforced pre-deploy (CMEK, no public IPs, budget alerts) and reduction in exceptions.

Measurement Patterns on GCP

  • Pipelines: Instrument Cloud Build/Deploy to emit lead time and deploy frequency per service.
  • Infra drift: Config Controller/Policy Controller deny metrics to track prevented misconfigurations.
  • Cost and labels: Org Policy + required labels on projects/resources; BigQuery exports for showback.
  • Time-to-env: Log timestamps from self-service portal request to completed Terraform apply.
  • Reliability: Tie SLO burn alerts to incident records to measure MTTR and CFR.

Reporting That Lands with Executives

  • Monthly scorecards combining DORA + adoption + cost transparency, with trendlines.
  • Before/after case studies for pilot teams (lead time drop, fewer incidents, cost clarity).
  • A short narrative: what the platform guarantees, what teams own, and where the next efficiency gains are.

Actions to Prove Value

  1. Pick a pilot – Instrument one product team end-to-end to establish a baseline.
  2. Automate data collection – Emit metrics from pipelines, policy engines, and cost exports into a central warehouse.
  3. Publish a platform SLA – Define what the platform delivers (uptime of shared services, support model) and measure it.
  4. Close the loop – Use feedback sessions and ticket analytics to prioritize backlog items that cut the most toil.
  5. Show savings – Quantify hours saved from self-service and reduced incident load; translate to dollar impact where possible.

Closing Thought

ROI is the language that keeps platform investments funded. By pairing DORA with adoption, cost, and self-service metrics, you tell a story that connects developer experience to business outcomes.