Gedimat accelerates its digital transformation by reconciling the 200 databases of its members and automating the categorization of product sheets for e-commerce.
The deployment of our GeSi point-of-sale ERP requires the reconciliation of the databases of the 200 independent members with the central database. For a long time, this tedious work was carried out on Excel with a fairly low success rate beyond the Gencod matches and a considerable amount of time spent.
Gedimat/Gedibois, the largest group of independent building materials dealers in France and Belgium, faced a significant challenge: converging 200 separate product databases into a single centralized system.
To strengthen its strategic position, Gedimat was rolling out a new ERP system (GeSi) across all sales outlets. This system aimed to unify article repositories and national pricing, enabling members to optimize purchasing and performance management. However, reconciling 200 independently managed databases was an extremely complex and time-consuming process.
Historically, this reconciliation work was handled manually in Excel, yielding low success rates beyond simple barcode (Gencod) matches. The time required for verification and corrections slowed down database consolidation and limited the efficiency of product updates at both store and e-commerce levels. Gedimat needed an automated solution to streamline data reconciliation and product categorization while improving accuracy.
The in-house development of a recovery portal coupled with the SDM solution allows each member to check the reconciliation proposals generated by SDM independently and to validate them or not. Invalidations are transmitted to the SDM engine to improve its learning process
To address these challenges, Gedimat implemented SDM, an AI-powered solution for automating data reconciliation and product categorization. SDM’s advanced matching algorithms allowed each member to verify and validate reconciliation proposals independently, significantly reducing manual effort.
By integrating SDM with Gedimat’s in-house recovery portal, members could review and approve matches, while invalidated entries were fed back into SDM’s system to continuously improve its accuracy. This self-learning capability ensured that over time, database synchronization became faster and more precise.
Beyond database reconciliation, Gedimat leveraged SDM to automate the classification of 10,000+ new products per month within its internal and web-based nomenclature. This automation eliminated the need for manual classification, significantly boosting productivity for database maintenance teams.
By implementing SDM, Gedimat achieved substantial improvements in efficiency, speed, and data accuracy:
By leveraging SDM, Gedimat successfully centralized its product data, improved efficiency, and accelerated time-to-market, providing a stronger foundation for its ERP deployment and e-commerce expansion.
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