Delivery services Advisory & Strategy Data & Analytics Security & Cyber Customer & Growth Regulation & Risk Sustainability & ESG Finance Procurement
Delivery service
Data & Analytics
Data people trust, in the hands of people who’ll act on it.
Most data programmes start with ‘everything’ and finish with nothing. We fix data in the order the decisions need it: governance that works, platforms that get used, and analytics tied to real operational questions. AI readiness comes as a result, not a slogan.
The problems we hear
“Three teams, three numbers, one month-end argument.”
Finance, operations and commercial each with their own truth and no shared definitions.
“We built a data platform. Nobody uses it.”
Technology delivered, adoption forgotten, and the spreadsheets quietly came back.
“The board wants AI. Our data isn’t ready.”
Quality, lineage and access gaps that no model can paper over.
What we deliver
01
Data strategy and governance
Ownership, definitions and standards agreed with the business – and the forum that keeps them agreed.
02
Data platform delivery
Modern platforms built with your engineers, scoped to the first use cases and widened from there.
03
Data quality and readiness
The unglamorous part: quality, lineage, access – fixed in use-case order.
04
Analytics and reporting
Reports leaders read and act on, replacing the ones they don’t.
05
Data protection and privacy
Exposure mapped across jurisdictions, gaps prioritised, a DPO placed when you need one.
06
AI readiness
The data foundations the AI Value & Scale practice needs – delivered together.
07
Master data and integration
One version of customer, product and supplier data, and the APIs that keep systems agreeing.
08
Data operating model
Roles, forums and funding so data has an owner – and the standing to say no.
A way in, not a methodology.
Every delivery service starts small and earns the next step. Most begin with a short diagnostic that tells you what’s true before anyone commits to a programme.
Step 1
Diagnostic
Map how data is created, stored and used; where it breaks; what the first decisions need.
4–6 weeks
Step 2
Foundations
Governance, definitions and quality for the first use cases. Platform scoped and started.
8–16 weeks
Step 3
Scale
Use case by use case, with adoption measured – often alongside our AI practice.
Ongoing
Who delivers it with
Delivery services are staffed from the practices below and, where it fits, run through our as-a-service offices so governance and value tracking come built in.
Often paired with
Advisory & Strategy → Regulation, Risk & Compliance → Finance Transformation →
Seen in practice
Case study · Energy & Resources
Gas distribution network: From outsourced IT to an agile business in 18 months
A data management strategy, silos broken down through capability modelling, IT run costs down ~50%.
Read the case study →
Case study · Healthcare & Life Sciences
Health tech scale-up: Data governance readiness ahead of a funding round
Exposure mapped across 3 regulatory regimes and a prioritised action plan for investor scrutiny.
Read the case study →
Practitioners at a glance
Three of the people who lead Data & Analytics work. Drawn from a network of 5,000+ practitioners averaging 14 years in their field.
Amira
Amira maps sensitive health and genetic data across UK, US and Gulf regimes ahead of investor scrutiny.
Marcus
Marcus scopes platforms to the first use cases, builds with your engineers, and widens from there – no 'everything' programmes.
Leah
Leah replaces the reports nobody reads with the few leaders act on, and measures whether they do.