A data strategy that aligns business, governance and architecture to produce decisions, not slides. A short, intensive, executive process: from diagnosis to roadmap in six to eight weeks, with a solid base to start the transformation the next day.
The signal does not always come from data. It comes from the executive committee, from reportings that don't match, or from investments nobody knows how to prioritize.
Scattered initiatives, KPIs inconsistent across areas, fragmented reporting and excessive dependence on IT to answer every business need.
Absence of a real data owner, ungoverned changes, proliferation of parallel solutions and growing compliance difficulties.
Platforms and tools that are bought but not adopted. Each new investment is justified, none builds on the previous one.
It is the piece that lets you decide with criteria.
Data Strategy aligns data with corporate objectives, the enterprise architecture and the operational evolution of the company. It decides why data should be managed, what value it should generate, what organizational and technological capabilities are needed, and how the change should be implemented.
It allows moving from a fragmented reality — silos, inconsistent definitions, low traceability, duplicated efforts — to a model where data is treated as a corporate asset with an owner, rules, priorities, risks and expected return. It is not a theoretical exercise: it translates into concrete decisions on governance, domains, capabilities, roadmap, investment, adoption and value metrics.
Not a tactical responsibility restricted to a single area. If it belongs to IT, it's not strategy, it's operations.
The model must be useful, proactive, non-invasive and value-oriented. Each policy exists to enable decisions, not to slow them down.
The organization must be able to absorb the change. A strategy that isn't adopted gets archived as a document. We design strategy that executes with the client's real resources.
Not everything must be implemented at once nor with the same level of ambition. Saying what will wait is as important as saying what starts first.
Goals, domains, policies, capabilities and roadmap must be connected. Without traceability, strategy is not defensible before the committee.
Six work blocks that produce an executive decision base, not a voluminous document.
Context analysis, pain points, maturity, AS IS situation, current operating model and main risks.
Definition of the data governance model, principles, domains, responsibilities, committees and decision framework.
Identification and classification of domains, initiatives, quick wins, dependencies and implementation sequence.
Phased plan with scope, milestones, preconditions, required capabilities and success criteria.
Investment rationale, rationalization of current cost and expected benefits in value, efficiency and risk.
Adoption plan, sponsors, key messages, organizational evolution and change management.
A short, intensive, executive process. It combines sessions with leadership, document analysis, structured interviews and joint definition of the target model. The methodology does not seek to produce a voluminous document: it seeks an executive decision base that becomes an implementation plan.
Kick-off, definition of objectives, sponsors, scope, stakeholders, hypotheses and success criteria.
Reading of the AS IS context, pain points, maturity, organization, capabilities, initiatives and current friction.
Design of governance, principles, domains, ownership, committees, functions and target capabilities.
Evaluation of initiatives and domains by value, risk, cost, dependency and adoption capacity.
Construction of the wave plan, quick wins, dependencies, milestones and implementation recommendations.
Final synthesis, recommended decision, risks, success conditions and message for the executive committee.
is deciding well what will not be done.
Vision, principles, objectives, domains, governance model and roadmap. The reference piece for the next twenty-four months.
Strategic backlog with explicit prioritization criteria. What gets done, in what order and with what capacity.
Roles, ownership, governance bodies. How the organization decides on its data from day one.
Message ready for the executive committee or sponsors. The strategy is told in fifteen minutes, not in a hundred-slide deck.
Identified quick wins and maturation phases. Something concrete that starts the following week.
Governance, architecture, platform, domains or transformation programme. The strategy opens the next conversation, it does not close it.
On what to do, why and in what order. The executive committee can defend the plan before any interlocutor.
Between business, technology, governance and security. Each area knows what is theirs and what is not.
Of investments and domains. Decisions are argued by value, risk, cost and adoption, not by political pressure.
On ownership, custodies and responsibilities. Data ceases to be no man's land.
To launch data architecture, Data Office or corporate platform. What follows starts from here.
| Indicative duration | 6 to 8 weeks, depending on the size of the organization, stakeholder availability and complexity of the environment. |
|---|---|
| Modality | Closed strategic consulting service, with calendar, executive sessions and defined deliverables. |
| Payment terms | 50% at start and 50% at delivery of the final document and executive closing session. |
| Natural continuity | Data Architecture, Data Governance, TOGAF, Data Office or platform implementation services. |
Strategy connected with real implementation, not with generic recommendations. Each documented decision is designed to be executable.
Business, governance, architecture, DataOps, security and exploitation thought of as one piece. The strategy does not fragment the problem, it articulates it.
Prioritization by impact, adoption and sustainability. Investments are justified by what they generate, not by what they look like.
DAMA and TOGAF as a structured base, applied with practical criteria. Structure without bureaucracy.
Possibility of evolving from strategy to architecture, governance and operations. Strategy opens doors, it does not close them.
Scattered initiatives, diffuse ownership, investment without clear direction or measurable return.
Multi-country federated data strategy
No client names — results that speak for themselves.
Design of the global data ecosystem architecture, legacy platform integration and analytical modernisation for a financial institution operating across multiple countries.
Definition of the corporate data strategy, implementation of a federated governance model and design of a modern architecture based on Databricks, Confluent Cloud and Snowflake to industrialise data exploitation and optimise platform costs.
Definition of the data strategy and a Data-Driven architecture to activate precision oncology analytics, clinical data governance under HL7 FHIR and mCODE standards, and interoperability between heterogeneous systems.
Representative · pending authorised publication
Data strategy without organizational transformation stays in slides. And without an operating framework, it stays as intent.
Start with a 30-minute conversation to understand the real scope of a strategic assessment tailored to your context.