Very different sectors. One shared way of looking.

If it runs short or changes in nature, the whole of production wobbles. For a player in this sector, we rethought the way it uses its supply information. AI now helps the teams spot the risk of disruption earlier and decide before production is affected. It also links the quality of incoming feedstock to the yield obtained: the company finally knows what each feedstock really produces, and runs its plants far more finely. Supply is more secure, production better controlled. And the daily pressure has changed in nature: the teams anticipate difficulties instead of suffering them.

Where its advisers used to see only a transaction history, they now have a real-time view of their clients’ needs, to the point of sometimes being able to meet them before they are even expressed. Out of this reading came several small, simple and targeted innovative services that did not exist before. Data that lay dormant has become a lever for growth, for the firm and for its clients alike.

Only then did we use AI to analyse locations and position the teams better in the field. The result: more relevant targeting of potential donors, and a significant increase in donations. AI does not replace the know-how of street teams. It shows them where it will count the most.

This showed that returns were concentrated on a handful of avoidable causes, which we were able to address at source. Then we went further. With the help of AI, we analysed the needs and expectations of its retailers’ customers, as well as the positioning of their competitors, who sell other brands. The brand no longer just delivers to its partners: it helps them understand their own market better. Its sales teams spend less time untangling problems and more time serving. Here, technology supports their expertise without replacing it.