Case Studies

Hypothetical scenarios written in STAR format to show how the operating model is applied. They describe no real employer, client or person, and all figures are illustrative.

Hypothetical scenario

Application intake governance

Situation: A large financial institution was onboarding new applications into production support with no consistent entry criteria. Teams inherited services without runbooks, monitoring or named owners.
Task: Create a single intake path so that no service entered support without meeting agreed readiness criteria.
Action: Designed a weighted production readiness gate covering observability, runbooks, resilience, security and supplier dependencies. Agreed critical items with architecture and risk partners, added it to the change enablement process, and published gap reports with owners and due dates.
Result: Within two quarters, every new tier 1 service passed the gate before go-live, post-launch P1/P2 incidents for new services fell by an illustrative 40%, and handover time shortened because gaps were found earlier.

Hypothetical scenario

Major incident turnaround

Situation: Major incidents were averaging long restoration times, with confused communications and repeated escalations to executives.
Task: Reduce time to restore and make major incident communication predictable for leadership and regulators.
Action: Introduced a standard major incident role model (incident commander, communications lead, technical lead), fixed update cadences, a regulatory notification clock, and blameless post-incident reviews with tracked actions.
Result: Illustrative MTTR for P1 incidents improved by around 35% over six months, executive escalations dropped, and post-incident actions closed on time moved above 85%.

Hypothetical scenario

AI-assisted knowledge capture

Situation: Resolution knowledge sat in engineers' heads and chat threads. Runbooks were stale, and new staff took months to become effective.
Task: Turn everyday resolution notes into reviewed, reusable runbooks without adding heavy documentation effort.
Action: Piloted talking to AI to draft structured runbooks from sanitised resolution notes, with a mandatory human review step, quality scoring, and clear rules on what data could never be shared.
Result: Illustratively, runbook coverage of top recurring incidents rose from about 30% to 75% in a quarter, review effort per runbook was under 15 minutes, and onboarding time for new analysts fell.