Transformation
Change Management and Adoption
AI Operating Model & Governance
AI Operating Model & Governance
Turn strategy into sustained behavior change across teams.
- Deliverables: stakeholder maps & measurable goals, evergreen business case, risk/assumption log, comms plan, role-based training & enablement, adoption dashboards, feedback loops.
- How we work: co-create with your leaders, embed change champions, align incentives/RACI, instrument adoption from day one.
- Outcomes: faster time-to-value, higher utilization, reduced change fatigue, durable ways-of-working.
AI Operating Model & Governance
AI Operating Model & Governance
AI Operating Model & Governance
Make AI useful, safe, and measurable, company-wide.
- Foundations: data contracts, consent & preference management, content/prompt policy, model registry, evaluation & red-teaming, audit trails.
- LLMOps/MLOps: retrieval/RAG pipelines, human-in-the-loop, quality/bias/safety/drift monitoring, performance & cost controls.
- Risk & compliance: Responsible AI controls, IP/copyright governance, vendor due diligence, incident response.
- Enablement: CoE & community of practice, secure sandboxes, role-based training (exec/product/engineering/marketing/legal).
- Value realization: portfolio scoring, funding/chargeback, OKRs tied to revenue, cost, risk.
Cross-link: See “AI for Growth” on the Digital Services page for marketing & experience use cases.
Operational Excellence
Product Management & Value Realization
Product Management & Value Realization
Diagnose, redesign, and automate processes to remove waste and risk.
- Diagnostics: time-and-motion + system logs, benchmarking, service blueprints, gap & root-cause analysis.
- Improvements: automation candidates (RPA/AI), SOPs & controls, SLO/SLAs, FinOps/CostOps, quality & incident management.
- Outcomes: lower cost-to-serve, shorter cycle times, higher reliability and CX/EX.
Product Management & Value Realization
Product Management & Value Realization
Product Management & Value Realization
Build the right things, and prove the impact.
- Portfolio & product: strategy, prioritization (RICE/WSJF), stage gates, discovery→delivery loops, experimentation backlogs, pricing & packaging.
- Commercialization: ICP/segmentation, offers, launch playbooks, adoption & lifecycle programs.
- Measurement: LTV/CAC discipline, incrementality testing, MMM + MTA, adoption & quality scorecards, benefits tracking vs. baseline.
- Outcomes: faster product-market fit, higher retention/revenue, clearer ROI.