Our Services
Data Strategy Consultancy
A data strategy your board will fund and your delivery teams can use.
We produce costed, sequenced data strategies for UK public sector and financial services organisations: a clear current-state baseline, an agreed target, and a roadmap with owners and milestones that survives contact with an annual budget cycle.
Plenty of organisations have a data strategy. Far fewer are delivering one. The common failure is a strategy written as an aspiration rather than a plan: no baseline, no sequencing, no costs, no named owners, and no link to the outcomes the organisation is actually measured on. We write data strategies to be delivered. That means starting with an honest assessment of the current estate and capability, agreeing a target that is achievable within realistic funding, and sequencing the roadmap so that each phase produces something usable. We work with your finance and commercial colleagues from the outset, so the strategy arrives with a business case that can pass internal scrutiny rather than needing to be retrofitted six months later.
Key Capabilities
- ›Data maturity assessment and current-state baseline
- ›Target operating model and data organisation design
- ›Costed, sequenced multi-year data roadmap with named owners
- ›Target data architecture and platform option appraisal
- ›Business case support structured to the HM Treasury five case model
- ›AI and analytics readiness assessment
- ›Benefits framework, KPIs and measurement plan
- ›Alignment of the data strategy to departmental outcome delivery plans
Who We Work With
Our strategy work draws on delivery inside central government. For HMRC's Anti-Money Laundering Supervision service we provided DV cleared architecture and data analysis that built the case for a full system replacement over a costly incremental upgrade, the kind of options appraisal a data strategy has to stand on. Engagements range from a single directorate to an organisation-wide strategy.
Frameworks & Accreditations
Our Approach
How we work.
Baseline
We assess your data estate, capability and governance as they are today, and establish what the organisation is actually trying to achieve with data.
Define
We agree the target: the operating model, architecture direction and capabilities needed, tested against realistic funding and delivery capacity.
Sequence
We build a costed roadmap in phases, each one delivering usable capability, with dependencies, owners and decision points made explicit.
Mobilise
We support the business case, help shape the first delivery phase, and stay available through the early stages so the strategy is not handed over and forgotten.
Common Questions
Frequently asked questions.
What is the difference between a data strategy and a data roadmap?
The strategy answers why and what: the outcomes data needs to support, the target operating model, and the capabilities required. The roadmap answers when, how much and who: the phased plan, the costs, the dependencies and the owners. A strategy without a roadmap is an intention. A roadmap without a strategy is a list of projects. We deliver both as one piece of work.
How long does a data strategy engagement take?
Typically eight to fourteen weeks, depending on the size of the organisation and how many stakeholder groups need to be involved. A single directorate can be done in six to eight weeks. An enterprise-wide strategy across multiple business areas and legacy platforms usually takes three to four months to produce something that will genuinely be signed up to.
We already have a data strategy that is not being delivered. Can you help?
Yes, and this is a common starting point. We review the existing strategy rather than replacing it by default, identify why delivery has stalled, and rebuild what is missing. Usually the gaps are sequencing, costing, ownership and a credible first phase. Reworking an existing strategy is generally faster and better received internally than starting again.
Do you write the business case as well as the strategy?
We support the business case and structure our outputs so they feed it directly, including the strategic, economic and management cases. The case itself is normally owned and submitted by your finance and programme colleagues, and we work alongside them rather than in place of them.
How does a data strategy relate to AI adoption?
Directly. Most AI pilots that fail to reach production fail on data, not on models: unclear ownership, poor quality, no lineage, and no lawful basis for the intended use. We include an AI and analytics readiness assessment in the baseline so that the roadmap fixes those foundations in the right order, rather than after a pilot has already stalled.
Related case studies and reading.
- Case studyHMRC: Anti-Money Laundering Supervision modernisation
- Case studyCabinet Office: IBCA secure cloud-native data platform
- InsightAI data platforms for government: why clean data comes first
- InsightPublic sector AI implementation: moving pilots to production
See how our services come together for government in public sector consultancy.
Discuss your requirements
Speak with our team about how we can support your organisation's specific challenges. We respond within one working day.