Industries
The data problem is rarely generic.
Every organisation has its own history, systems and internal politics. What differs by sector is the constraint: who has to approve a data use, how a decision gets funded, and what a regulator, funder or customer expects to see.
Each sector page leads with work we have delivered, from company wide data strategy at DC Thomson to product direction at Games Jobs Live and indicator reporting for Flexible Childcare Services Scotland.
Book a Free 30-Minute Strategy CallChoose your sector
Four sectors where we go deepest.
Our experience in these sectors helps us understand the context faster, ask better questions and focus on the Data and AI work that will make a difference.
Financial Services
Trusted reporting, AI governance, risk and fraud, cloud platforms
For banks, insurers, lenders, wealth managers and fintech firms where every data decision eventually has to be explained to a regulator, an auditor or a board.
Explore Financial ServicesHealth
Clinical and operational analytics, information governance, AI readiness
For NHS organisations, healthcare providers and health technology companies balancing statutory reporting with the operational questions services need answered.
Explore HealthMedia & Publishing
Audience intelligence, subscription growth, commercial analytics
For publishers connecting audience behaviour, subscription value and commercial performance into decisions editorial and commercial teams share.
Explore Media & PublishingDigital Products & SaaS
Product analytics, customer behaviour, AI enabled products, data products
For product led businesses where activation, retention and expansion decisions depend on definitions and instrumentation that have to hold as the platform scales.
Explore Digital Products & SaaSWhat changes by sector
The architecture repeats. The constraints do not.
Sector context decides the order of the work: what counts as acceptable evidence, who signs off a data use, and how quickly a decision can move from analysis to action.
Financial Services
- Every figure has to be explainable to a regulator, an auditor or a board, and the lineage behind it has to hold up months later.
- Definitions, ownership and access control are agreed before reporting is built, and AI use cases are scoped against what can be evidenced rather than what is technically possible.
- Reporting that different teams calculate differently, or an AI ambition with no agreed governance position behind it.
Health
- Statutory reporting takes priority over the operational questions services actually need answered, and information governance shapes what can be joined together.
- Indicator definitions come first, then reporting designed for the people running services, with governance handled as part of delivery rather than after it.
- Manual returns absorbing skilled time, or operational teams working from numbers they cannot interrogate.
Media & Publishing
- Audience, subscription and commercial data sit in separate systems owned by separate teams, each with its own working definitions.
- A shared set of measures across editorial and commercial, supported by platform work and internal capability building so the reporting stays trusted.
- Executive reporting that takes days to assemble, or editorial and commercial teams disagreeing about the same audience.
Digital Products & SaaS
- Instrumentation and definitions written for an early product rarely survive scale, and product decisions move faster than governance.
- Event design and metric definitions treated as product assets, with analytics built around activation, retention and expansion decisions.
- Product and revenue teams reporting different numbers, or a roadmap decision that current data cannot support.
Also relevant
Other sectors we work in.
The same disciplines apply, with different constraints and different language.
Capability
Proof
Buying questions
Working with a sector specialist: questions we are asked.
For anyone deciding whether sector experience matters as much as data capability.
Let's talk about your Data & AI priorities.
Whether you're developing a data strategy, modernising your data platform, preparing for AI or tackling a specific business challenge, start with a 30-minute conversation with Inez.