How can we reinvent the acculturation of data governance projects?

Data governance has become a critical issue for organizations seeking to unlock the full potential of their data. Artefact brought together industry leaders to explore data democratization and the transformation strategies they are using in their organizations. The discussion focused on gamification, event management, and ways to reinvent acculturation through hackathons, bootcamps, and e-learning.

Participants:

Carrefour developed the innovative concept of the Data supermarket. Based on the notion of data mesh, it’s a decentralized, collaborative approach to data management. By combining varied, structured and granular data, Carrefour created a unique ecosystem that facilitates data management and access. The system fosters user autonomy and improves efficiency and decision-making processes.

“The Data supermarket approach aims to make data analysis as simple as a trip to the supermarket, with a focus on simplification, clarification, reuse and autonomy.”

Sébastien Rozanes, Global chief Data & Analytics Officer, Carrefour

Everything began when the data was organized into several levels of granularity: domains, families and products. In concrete terms, Carrefour’s data has been mapped and divided into 21 domains and over 100 data families, enabling users to find certified ways of consuming the underlying data according to the use they wish to make of it. As in a supermarket, all products – whether data, KPIs or reports – are visible on the shelf and labeled.

Next, an efficient operational model was implemented to manage the data store (role of internal data owners, definition of decision-making processes, establishment of best practices). A dedicated team for integrating and managing the data “shelves” was set up, comprising:

Next, the tool was developed. This data supermarket portal, supported by Google Dataplex, makes Carrefour’s data accessible and intelligible to all. Once users have found useful data, they can access it themselves by requesting access to the data from the steward.

Carrefour’s example inspires. Artefact is helping Carrefour organize a dozen hackathons in France and Spain, aimed at facilitating the adoption of this new Data Supermarket concept by teams, and acculturating managers to the autonomous use of data.

To ensure the success of such a strategy in all sectors, data governance must be based on user understanding of data. Users must be convinced of the benefits of data governance for their team. This is a process we have observed at Veolia Water, Kering and Les Mousquetaires.

To empower data and make it readable, engaging, and effective within a company, it’s important to adapt it to the specific organizational context.

For example, Les Mousquetaires wanted to actively involve users in choosing data governance tools. To achieve this, they began by simplifying the data governance lexicon, making its technical terms more understandable so that everyone could understand what was at stake.

Kering, on the other hand, approached things progressively, starting with the most critical and mature departments, such as Supply Chain and Sales. The goal was to build consensus around clear and essential business definitions. This ensured a coherent strategy and simplified strategic discussions, allowing the process to be initiated in specific areas before being extended to the entire group.

Veolia Water began by defining business objects to achieve consensus. The company also avoided technical jargon and focused on empowering operational staff with a data platform, engaging data owners, and training “data champions”.

“The recurring question of the time required for implementation was addressed openly. Despite a longer than expected lead time, some use cases were successfully completed. We adopted a top-down (strategic issues) / bottom-up (business team needs) approach, for example when selecting our data dictionary, to ensure team commitment.”

Rémi Rouet, Group Chief Data officer, Les Mousquetaires

To implement an effective data strategy in the context of a data mesh, the support of the company’s governing bodies is needed to change the corporate culture:

“With the support of our Group Managing Director as a personal sponsor and by adopting a pragmatic approach geared towards solving concrete problems, we gradually gained buy-in. Our strategy focused on humility, understanding the business, and working closely with the teams.”

Yannick Beltran, Data governance & Transformation office director, Kering

Adapted to the organization’s culture and applied with discretion, gamification is truly engaging for teams. However, it is no substitute for the assimilation of detailed procedures through training to ensure that all employees are well informed.

The creation of communities of “data champions” stimulated Veolia employees through training and acculturation initiatives. The subsequent use of gamification reinforced their commitment until the teams became more autonomous in data management.

“Gamification can generate an autonomous and sustainable dynamic. After an initial phase of intense animation, it contributed to the self-management of the community.”

Xavier Jeulin, Head of Data & AI, Veolia Eau

Kering also organized a successful hackathon for the group. Hackathons can be effective for exploring use cases in depth and for involving a large number of people from different departments. A hackathon is particularly beneficial for corporate culture. To get the most out of it and ensure it runs smoothly, cohesion between technical and marketing teams is essential to ensure the relevant data is available for the event.

Data governance strategies must focus on value creation and empowerment. Transformation must be built on a solid foundation. Xavier Jeulin, Head of Data & AI, Veolia Water, recommends keeping the “three U” rule in mind: data must be useful, usable and used. The strategies pursued by these companies highlight the need for a rigorous approach tailored to each organization.

There are four key points to keep in mind when considering the success of data governance projects: