Manage the data lifecycle with well-defined rules and roles to put that data to work for the company's growth. That's a summary of data governance. And in practice? How does data governance work in practice? At least in 4 ways. Here are some explanations.
Strategic data governance
It all starts here, with clear strategic directions. For what purpose does the company intend to invest in data? To deploy all-out acquisition? To work on customer loyalty? To improve products? All of the above at the same time?
Once these objectives have been set, there remains the question of resources and data culture. Is this subject reserved for a specialized division? Or are efforts planned to make data an everyday tool for everyone? These major strategic orientations therefore also define a cultural framework for data governance. And this framework is as important for employees as it is for customers.
An example? The RGPD and the application of the latest CNIL guidelines. By choosing how to interpret these guidelines through their consent interfaces, companies are not only making a legal-technical choice. They are also sending a message about their relationship with data and their respect for the privacy of their customers. Data governance has a direct influence on the perception of the brand.
Functional data governance
This aspect of governance refers directly to the subject of the organization around the data. A key issue is how to avoid counter-productive siloing. All too often, divisions still prevail: the acquisition team versus the loyalty team, offline versus online business, legal constraints versus the fundamentals of the user experience...
The idea is not to break down these silos - they also correspond to the specialized skills that the company needs - but to ensure their coordination. Governing data means providing a clear framework for collaboration and defining stable, complete rules of the game that are understood by all. Who has the rights to manage the storage of contacts? Their enrichment? Who monitors the quality of the data injected? Who regulates advertising pressure? How are user preferences managed in terms of personal data protection?
There are no universal, off-the-shelf answers. It is up to each company to define the roles, their interactions, their objectives and, above all, the overall objective to which each must contribute. An objective that is explicit and strong enough to transcend the famous silos.
Legal data governance
The implementation of the RGPD in 2018, followed by the implementation of the CNIL guidelines, has imposed personal data management as a central topic. With, at its core, a new discipline in its own right: the collection of consents. How to ensure legal compliance of this collection while optimizing it to meet business challenges? How to ensure that the use of personal data respects the wishes of prospects and customers?
To answer these questions, a new role has emerged - that of DPO, Data Protection Officer - and a new solution has found its place in the Martech stack: the Consent Management Platform (CMP). But the existence of a DPO and the implementation of a CMP are not enough to ensure the regulatory declination of data governance.
For a simple reason: the regulatory framework is changing, the products and services offered by the company are changing, as are its acquisition and customer relationship management channels. Maintaining an optimum balance between regulatory compliance and performance in the face of these changes requires continuous and effective collaboration with all other teams (acquisition, loyalty, UX, etc.).
Technical data governance
There remains the technical aspect of governance. Technique does not make strategy, but without it, strategy rarely goes beyond the status of a laudable intention. Data governance that relies on a new collaboration between stakeholders must be equipped accordingly. This is one of the reasons for the existence of Customer Data Platform (CDP): overcoming organizational and technical divides to federate data within a repository.
With such a CDP, there are many benefits: facilitating the reconciliation of data in an omnichannel universe, achieving more relevant segmentations, orchestrating activations in a more efficient way... This implies making reconciliations, for example between data acquired on the digital front and those stored in the CRM. A technical reconciliation that cannot succeed without clearly defined data governance.