Client stories

Evidence from assessments, clinics, and retainers — specific corrections to metrics, not generic praise.

  • “The pipeline assessment showed our deploy-success metric was counting retries as separate wins. We corrected the definition before our next planning cycle. The report was dense — we needed a second pass on the annotated diagram — but the corrections stuck.”
    Hyejin Park · Engineering manager, logistics SaaS · Delivery Pipeline Analytics Assessment
  • “Our metrics clinic forced an awkward but useful argument about which dashboards the risk committee actually reads. We retired two charts nobody could explain and kept the three that map to merge queue and rollback.”
    Marcus Ellison · Release lead, regional bank technology · Release Metrics Clinic
  • “Build Health Review found flaky browser tests that had been poisoning our change-failure number for months. They did not rewrite the suite for us; they showed exactly which jobs to quarantine first.”
    Sora Kim · Platform engineer · Build Health Review
  • “On the retainer, monthly reviews caught a silent gap when we added a second product line: production deploys were tracked, staging promotions were not. Mild reservation — scheduling across time zones took patience — but the signal quality improved.”
    Daniel Cho · Director of delivery · Quarterly Delivery Analytics Retainer

Case note: logistics release board

A Busan logistics product group asked for a Delivery Pipeline Analytics Assessment after their weekly board showed rising deployment frequency but longer customer-visible incidents. Read-only review of three pipelines showed deploy-success counting each retry after a partial canary, while rollbacks lived only in a chat channel.

We scored stage signal quality, rewrote the success definition with the release lead, and added a rollback tag exported from their incident form. Two planning cycles later, frequency looked slightly lower and recovery discussions finally matched what on-call had been living through. The team still owns the dashboards; we left after the walkthrough and a five-day clarification window.

Case note: metrics clinic for a bank release guild

Twelve participants spent a half day naming every chart on their shared wall. Three charts survived: merge-queue wait, production deploy outcome (with retries collapsed), and recovery by mechanism. Two vanity counters were archived the same afternoon. The reservation we heard afterward: “It felt slow compared with buying a dashboard pack” — and that was the point.