Data Maturity Assessment
Find out if your data can actually carry AI — before you build on sand.
Most AI stalls not on the model but on the data underneath it — scattered, undocumented, unowned, and not fit to be trusted by a system that will act on it. The Data Maturity Assessment finds that out before you build on sand: it checks whether your data is ready to carry AI safely and hands back a ranked list of what to fix first, not a maturity wheel.
CDOs, CDAOs and data leaders — and the CIOs who own the estate the AI will run on.
Illustrative. Every assessment scores your own six dimensions on real evidence and orders them worst-first, so the conversation starts with the two or three foundations to fix before you build.
What it checks — six dimensions
Built from conversations and document analysis, the assessment scores you across the six things that actually decide whether AI works in production: strategy, value and operating model; governance, ownership and policy; data quality and lifecycle; architecture, integration and technology; metadata, security and compliance; and people, culture and AI-readiness — around thirty probing questions in all.
A ranked list, not a wheel
Readiness is scored across the six dimensions and ordered worst-first, so the conversation starts with the two or three foundations that will give way — not a pretty circle with no priorities. You leave knowing exactly where to spend first.
Explore it, then act on it
The output isn't a static report. It runs on the same engine as the AI Opportunity and AI Maturity assessments: a scored picture you can interrogate in plain language, with generative BI that answers in charts. And the part clients act on is a ranked set of next best actions — name owners and stewards, stand up a catalogue and glossary, define data-quality rules and monitoring — cheapest, highest-impact first, each tied to the gap it closes.
- Readiness scored across six dimensions, ordered worst-first
- The two or three foundations to fix before you build anything
- A ranked set of next best actions, each tied to the gap it closes
- A living, interrogable picture — not a report on a shelf
Delivered for Nuffield Health and Anthony Nolan — data foundations assessed for automation before anything is built.
Read the Anthony Nolan case study →Data Maturity Assessment, answered
The AI Opportunity Assessment finds and scores the use cases worth building. The Data Maturity Assessment checks whether your data foundations can carry them. They work well together — and often the opportunity assessment surfaces a foundational data track this then details.
