· Creates new revenue lines (platforms/APIs/managed services) or protects margin (FinOps, cost‑to‑serve visibility).
· Shifts transformation from one‑off projects to productised, repeatable operating rhythms.
· Strengthens trust as a differentiator (governance, resilience, compliance‑by‑design).
What changes in the operating model:
· Clear RACI and escalation paths reduce decision delays during incidents
· Runbooks and recovery procedures are tested and continuously improved
· Trust is strengthened with customers through consistent communications and evidence readiness
· Improved MTTD/MTTR and reduced downtime impact
· Higher customer trust and renewal likelihood
· Reduced repeat incidents via root‑cause remediation
· [INSERT: data residency / regulatory considerations]
· [INSERT: Arabic/English support and content needs]
· [INSERT: procurement and vendor onboarding requirements]
· NIST Incident Handling Guide (SP 800-61): https://csrc.nist.gov/publications/detail/sp/800-61/rev-2/final
LINKS → Use Case: UC-10: Cyber Resilience & Incident Readiness Playbook | Services: SVC-02: GRC & Digital Resilience/SVC-06: Cloud & Platforms
A telco disrupts its traditional connectivity model by launching platform offers (network APIs, developer programmes, marketplaces) with ecosystem partners. A 90‑day GTM sprint validates segments, messaging, partner motions, and pricing—then scales based on adoption signals.
An ICT enterprise rolls out AI-assisted workflows across support, engineering, and commercial teams. It adopts an AI risk framework and role‑based certification so usage is safe, validated, and measurable.
An operator improves operational visibility across sites (data centres, depots, high‑footfall service locations). Computer vision detects safety and operational events while privacy controls (retention, access, de‑identification) are built in by design.