Data & AI Strategy.

Three engagement types under one pillar.

• Diagnostic to target state. Current state across data, infrastructure, governance, and operating model. Target operating model designed across utility, data product, and data mesh planes. AI-ready foundation roadmap.
• Data product strategy and education. What a data product really is, and the disciplines to build, govern, and own one. Tailored for execs, product owners, and data leads.
• Advisory sessions. One-off confidential conversations for execs, boards, and data leaders. Future of data and AI, decision support, no pitch deck.

CDOs, CDAOs, COOs, CTOs, CIOs, and CEOs setting direction. Heads of Data, Heads of AI, Heads of Data Products who need to align a target state with execs above and platform teams below. Boards evaluating data investment.

Organisations that have invested in data but are not yet extracting value, or who are preparing to scale AI and realising the data foundation isn't ready.

Most strategy engagements are 6 to 8 weeks of intensive work with the leadership team and two or three working sessions per week. One-off advisory sessions are 45 to 90 minutes. Data product strategy programmes can be modular, run remotely or onsite, and tailored to executive, product-owner, or technical practitioner audiences.

Outputs your board signs off on. Outputs your teams can use.

• A target operating model the leadership team has agreed on, costed, and committed a sequence for
• A shared definition of what a "data product" means in your organisation
• An AI-readiness assessment with prioritised gap work
• A blueprint of the utility, data product, and data mesh planes specific to your context
• A change-management framing your platform team can execute against
• An advisory relationship you can return to when you hit the next decision