We provide executive data direction with the 4 Data Office roles coordinated: Data Governance Lead who implements, Metadata Manager who catalogues, Data Quality Manager who certifies and Data Office Manager when maturity arrives. An operational CDO with KPIs measurable from the first week.
It rarely shows up as «we need a CDO». It usually appears as projects that don't progress, initiatives that lose sponsorship and technology that doesn't connect with business. Four patterns where CDO as a Service activates the function from the first month.
When the CDO coordinates but does not formally decide, the role becomes ceremonial. CDO as a Service activates the function with real authority over domains, OKRs and corporate backlog from the first week.
When policies are written but metadata is not updated and traceability is rebuilt at every audit, the executive piece is missing. The service turns the DAMA framework into a living process with measurable KPIs.
When the Office coordinates and reports but does not have the 4 operational roles (Governance Lead, Metadata Manager, Data Quality Manager, Data Office Manager), governance does not hold. We activate the role the model needs at each phase.
When the Committee meets with cadence but does not close agreements on time, structured agenda and RACI are missing. The service includes a Committee that decides, with systematic impact analysis and traceability of every agreement.
It is activated with authority, agenda and operating model.
CDO as a Service is not an external consultant who advises nor an assessment that ends with a document. It is the executive data function instantiated with real authority from the first month: direction, committee, corporate backlog and measurable OKRs. We operate the role while the organization builds the definitive internal model.
The service covers the 4 canonical Data Office roles: Data Governance Lead who implements policies, Metadata Manager who catalogues, Data Quality Manager who certifies and Data Office Manager when maturity arrives. Each role activates when the model requires it — not as formal addition but as measurable operational capability.
The CDO must be able to prioritize, decide and arbitrate ownership conflicts with corporate mandate. Without formal authority, the function stays as recommendation.
Governance Lead, Metadata Manager, Data Quality Manager, Data Office Manager. The function is not an isolated role — it is a coordinated capability with clear responsibilities.
Active committee, corporate backlog, measurable OKRs, executive RACI. The function operates from the first week, not after an implementation project.
The governance model rests on DAMA-DMBOK. Standard, certifiable and recognized framework. Not improvised, not opinion-based.
Data objectives connect with business objectives. Each initiative has expected return, risk and dependency documented — defensible before CFO and CEO.
The model is designed to be assumed by an internal CDO when the organization is ready. The service accompanies, it does not generate dependency.
Five blocks of work activated according to maturity. The organization does not contract parts — it contracts a complete data function.
Leadership of the Data Committee, management of the corporate backlog, connection with general management and translation of data into business value.
Policies, standards, glossary, catalogue, lineage and quality rules. Operational implementation, not only documental.
Agenda design, decision model, RACI, operational sessions and structured follow-up of agreements until closure.
Inventory of initiatives, systematic impact analysis, prioritization by value·risk·cost·dependency and executive traceability.
Definition of corporate data OKRs, monthly dashboard with 5 operational KPIs from the Governance Lead and reporting to the management committee.
A short and operational methodology. We start with assessment of the current model and end with the client operating autonomously. The function is active from the first week.
We understand which roles are active, which are nominal, which KPIs are really measured and where the chain between governance and operation breaks. Inventory of domains and first corporate backlog. Weeks 1–3.
We activate the operational role that translates policies into processes. Adapted DAMA framework, Owners and Stewards assigned by domain, first Data Committee with structured agenda. Operational KPIs start being measured. Months 1–3.
We activate Metadata Manager and Data Quality Manager when the model requires them. The Committee closes agreements on time. The backlog advances with systematic impact analysis. The Data Office moves from project to functional unit. Months 3–12.
At 12–24 months, the Lead role evolves to Manager: annual planning, dedicated budget, executive reporting. Training and documented RACI so the client assumes the role autonomously.
It is the data function activated with authority from the first month.
Policies, standards and roles active. Not archived documentation — living process applied in daily work.
Operational sessions with structured agenda, signed minutes and follow-up of agreements until closure. Real decision mechanism.
Inventoried, prioritized and with impact analysis. Each initiative with documented owner, deadline and success criterion.
% domains with active Owner+Steward, % backlog prioritized, DQ scorecard, % critical assets catalogued, % Committee agreements closed on time.
With Owner, Steward and documented lineage. The organization knows what data it has, who owns it and how it transforms.
Rules, scorecards and remediation plans. Quality is measured systematically — not rebuilt at audit.
For data governance and Committee. Each decision has unique Accountable and Responsible executor without ambiguity.
So the client assumes the data function autonomously with the model, processes and team already implemented.
With agenda, committee, backlog and OKRs operating. A real executive function, not an archived strategy document.
Data initiatives have a champion with weight in the management committee. Priorities sustain when daily urgencies arrive.
Data translated into business value, expected return and mitigated risk. An argument finance can budget and management can defend.
When the time comes to hire a permanent CDO, they inherit a proven model, a trained team and an active backlog — not starting from scratch.
| Approximate duration | Monthly retainer with 12-month minimum commitment. The function operates from week 1 and handover is planned at 24 months. |
|---|---|
| Modality | Monthly retainer with active leadership, operational Committee sessions, backlog management and executive reporting. Not occasional advisory — instantiated executive function. |
| Billing | Fixed monthly fee. Hour volume scalable according to activation of the 4 Office roles (Governance Lead always active; rest according to maturity). |
| Natural continuity | DATUM implementation, operational data governance, data architecture, activation of Data Committee as a Service or integration with real Data Owners and Stewards. |
We activate Data Governance Lead, Metadata Manager, Data Quality Manager and Data Office Manager when the model requires it. Not an isolated CDO — an operational Data Office with coordinated roles.
Our team operates with the DAMA-DMBOK framework as a base. The governance model deployed is certifiable, not improvised. Banking, healthcare, retail and insurance as practice sectors.
% domains with active Owner+Steward, % backlog prioritized, DQ scorecard, % critical assets catalogued, % Committee agreements closed on time. Measured from day one.
We start as Data Governance Lead executing the model. At 12–24 months we evolve to Data Office Manager: planning, budget, roadmap. The service accompanies both phases and ends in handover to the client.
Data initiatives scattered, without executive sponsorship and without a common framework. Accumulated investment does not translate into value defensible before the management committee.
Strategic data direction at an international banking institution
No client names — results that speak for themselves.
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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
The CDO does not operate alone. These are the three next steps depending on where you are.
Start with a 30-minute conversation to evaluate the real fit of the service in your context. No pre-sales, no deck — executive diagnosis.