Data & AI Consulting & Strategy
Scoping, roadmap, ROI
Data & AI strategy: from scoping to roadmap
Turn an ambition into prioritised use cases, a target architecture and a costed action plan. Our data and AI strategy consulting is pragmatic, vendor-agnostic and execution-focused.
What we do
Strategy is the first cross-cutting dimension of our offering: it feeds into all four pillars (governance, architecture, engineering, generative AI). We help with:
Data & AI vision and strategic scoping with executive sponsors.
Maturity assessment (organisation, processes, platform) and gap analysis.
Building and prioritising a use case backlog based on value and complexity.
Blueprint: target architecture, operating model and governance.
Transformation roadmap and business case, including change management.
Make-or-buy studies and solution selection support.
Our approach
The Explore & Design phase follows a proven four-step process: planning, interviews, co-design workshops and deliverables. We keep a brisk pace so stakeholders stay engaged, and the pilot phase can start before scoping is formally closed to avoid any loss of momentum.
Scoping concludes with three sets of deliverables:
- the blueprint (findings and recommendations across the dimensions of the 5P framework),
- the prioritised use case backlog,
- and the roadmap with business case.
What sets us apart
Actionable deliverables, not a report:
every recommendation is tied to a workstream, an owner and a budget estimate.
Technology agnosticism:
platform choices are driven by your needs, not by commercial partnerships.
Continuity into execution:
the teams who scope the work are the ones who support its delivery.
Openlane: data platform strategy approved by the executive committee
Client case study
Challenges
Support growth and protect margins in the European cross-border vehicle auction market.
Improve operational efficiency through automation and deliver on the “Have, use, trust data” vision.
Solution
Explore & Design phase of our methodology: 12 interviews, 7 workshops.
Two-stage organisational transformation (unified team, then hub-and-spoke model).
Modern data and AI platform on Azure and Snowflake, with raw, curated and semantic layers.
Benefits
Blueprint, three-year roadmap and business case approved by the executive committee.
95 use cases identified, 5 of them prioritised (AI pricing, buyer scoring, etc.).
€1.6M investment for a projected ROI of over €5M over five years, with break-even expected after six months.
FAQ
How long does a data and AI strategic scoping engagement take?
A full scoping engagement (interviews, workshops, blueprint, roadmap, business case) typically takes six to twelve weeks, depending on scope and stakeholder availability. A rapid audit can be completed in two to three weeks to identify priority workstreams.
What does a data and AI roadmap include?
It sets out the steps and milestones for implementing the strategy: platform workstreams, organisation and governance, use case sequencing, change management, budget and ROI indicators.
How do you prioritise use cases?
Each use case is assessed on two axes, business value and implementation complexity, then positioned in the backlog. The first use cases selected combine demonstrable short-term value with the ability to lay the foundations for what comes next.
Working on a data master plan or need to refresh your strategy?
Let’s talk about it in a no-commitment scoping session.