How to make the most of your data? Recipes for large groups

In 2020, the government joined an initiative aimed at accelerating the digital transformation of French companies with the creation of the digital mission of large groups.

Since renamed French Tech Corporate Community (FTCC), the mission continues its concrete action, obsessed with impact, and focused on major themes such as artificial intelligence and data.

Deploy a relevant, interoperable and actionable device

The organization thus announces the launch of a Starter Kit on the enhancement and sharing of data. The purpose of this good practice guide led by Guiraude Lame (Chief Data Officer of Natixis) and Samir Amellal (DSI and CDO of Auchan Retail France): to help French companies.

More specifically, it is a question of providing keys to companies to enable them to “engage in a process of valorization and sharing of data”, whatever their sector of activity.

Even if “the exploitation of data is unavoidable today”, “numerous obstacles and difficulties” persist. The ambition of the FTCC is therefore to provide a “relevant, interoperable system that can be operated independently of the sector of activity”.

For the authors of this compendium of good practices, the recovery process therefore begins with data identification work. This step consists of a census and a classification.

Priority to data generating value

“This process will need to be guided by a value analysis,” recommends the FTCC. Priority must also be given to assets “generating value” or “containing a strong potential of value for future applications”.

To the identification will be added a data documentation phase. The objective is in particular to categorize the data (customers, products) and their sources. It is a question of “listing the data, detailing for each its main attributes: name, source, uses, definition, associated risks (…)”.

However, the real value of a piece of data depends on its uses. It is therefore appropriate to list the associated use cases and their typology (operational efficiency, study, advertising). Other parameters (rarity, history, quality, etc.) must be taken into account to assess the value of these assets.

The Starter Kit suggests several methods (such as cost or market valuation) to help companies define this value. It also advocates architecture and governance guidelines.

A Fairness charter to get started on sharing

Architecture and governance are necessary for data sharing, an area whose “legislative framework is partial”. Consequently, it is “recommended to deploy a contractual framework” which will be “generic” for recurring exchanges, in order to “respond to as many scenarios as possible”.

The main principles of data sharing can be formalized in a contract, or initially in a charter, such as a Fairness charter. To help build such a document, the Starter Kit lists its general principles.

This guide is not enough to raise a company to the rank of data company or data driven. Other achievements are necessary to “move fully towards data sharing”. The FTCC thus encourages in particular to launch and experiment with concrete initiatives and to involve the businesses in the documentation of the data.

This presupposes the emergence in the organization of a real culture of data, a project in its own right. “It’s a paradigm shift that everyone in the group must grasp”, reminded the chief data officer of Géodis, Pierre Lenclud.

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