How to optimize your supply chain with AI?
In order to reduce its carbon footprint and improve its supply chain, Tereos called upon JEMS to implement a data platform and a machine learning algorithm. The result is clear.
Improving the supply chain, a priority for Tereos
Tereos is an international cooperative group, the 2nd largest sugar group in the world with more than 12,000 French cooperative farmers. The group is specialized in the transformation of sugar cane, sugar beet and cereals into sugar products, alcohol and ethanol, electricity and animal nutrition. As part of its vast digital transformation project “Ambitions 2022”, Tereos contacted JEMS to help build its data platform and among the needs identified, improving the supply chain, production, deadlines and task management became the priority. Indeed, during the sugar beet harvest, more than ten thousand trucks circulate every day from the fields to the factory. And if the waiting flows are not managed correctly, considerable time is lost during the harvest, with the systematic appearance of tailbacks on the roads.
The data solution implemented by JEMS
JEMS brings its expertise both on the implementation of the roadmap and on the execution of the project. We set up a remote solution on the Microsoft Azure cloud; we use Talend to transport and organize the data in the different layers of the platform, the Snowflake database, DataStax in the cloud, and Tableau to provide the data visualization. A machine learning AI algorithm was used to optimize the waiting times of more than 10,000 trucks per day.