Data governance: an operational and strategic priority

Challenge

Lack of common rules

Without shared rules, each team applies its own conventions. The same information exists with differing definitions, inconsistent formats (dates, labels, identifiers), conflicting units, and varying naming conventions. This lack of standardisation makes data difficult to reuse, increases manual rework, and undermines consistency between your information systems and distribution channels.

Challenge

Unclear responsibilities

When governance is not formalised, essential questions remain unanswered: who owns the data, who updates it, who controls it, who validates it, and who makes the final call in case of disagreement. This ambiguity leads to bottlenecks, delayed decisions, and “ad hoc” adjustments, often at the expense of data quality and process continuity.

Challenge

Unmonitored data quality

Quality becomes a perception rather than a measurable framework. In the absence of shared criteria and control rules, errors take root: impossible values, inconsistencies between fields, incomplete products, duplicates, and obsolete data. Without a logic of validity, consistency, completeness, and uniqueness, correction is reactive and sporadic, instead of being structured and preventive.

Challenge

Unstructured validation processes

When workflows are undefined (or bypassed), validation depends on individual habits and emergencies. The stages of creation, enrichment, control, and publication overlap, leading to back-and-forth loops, premature or delayed go-lives, and a loss of confidence in the data. At scale, the organisation ends up with constant “exceptions” and deadlines that are increasingly difficult to meet.

Challenge

Lack of traceability

Without a reliable history, it becomes impossible to answer essential questions: who modified this information, when, on what basis, and which version was published. The lack of traceability complicates audits, incident management (publication errors, information withdrawal), and the ability to explain or justify data both internally and to partners.

Challenge

Uncontrolled master records

The uncontrolled evolution of classifications and metadata undermines the entire information system. On the MDM side, the “common foundation” (units, hierarchies) begins to crumble; on the PIM side, product structures become unmaintainable; and on the DAM side, poorly indexed media becomes invisible. The result: fragmented data that is impossible to consolidate.

Challenge

Inadequate access management

The lack of a clear separation of roles (editing, validation, publishing) creates an organisational risk. Excessive access leads to uncontrolled modifications, while insufficient access slows down execution. Without a permissions policy aligned with responsibilities, validation workflows are bypassed, errors spread faster, and data security becomes compromised.

Challenge

Compliance and risk management

In the face of legal obligations, a lack of governance leaves the company vulnerable. Integrity failures regarding third-party data (MDM), product inconsistencies (PIM), or copyright violations (DAM): without validation rules or traceability, it becomes impossible to guarantee reliable information and respond confidently to audits.

Challenge

Lack of data stewardship

Without a clear structure to address and prioritise corrections, the same issues recur, accumulate, and ultimately slow down teams, delay projects, and hinder the ability to scale up operations.