Efficient Product Group Optimization
SBB successfully implements the revised product group structure in SAP R3, S/4, and Ariba.
The Project in Summary
Initial Situation
SBB aimed to align its product group structure as an indispensable tool for managing procurement processes more effectively in line with market demands and to sustainably integrate it into SAP R3, S/4, and Ariba.
Approach
The procurement data was classified using machine learning into revised product group keys. A “Stay Clean” concept ensures sustainable data quality and greater bundling effects.
Results
The efficient approach avoided significant manual classification efforts. Sustainable and high data quality is ensured.
Strategic Realignment of Product Groups
To enhance strategic procurement management and streamline the entire procurement process, SBB introduced a new product group structure comprising 515 groups. Designed as a core element, this structure aims to make procurement operations more effective. The uniform product allocation allows category managers and their teams to navigate the market with greater precision. Implementing this structure in systems like SAP R3, S/4, and Ariba required a lean and sustainable approach for optimal integration.
Collaboration Between People, Systems, and “Machine Learning”
Staufen, in collaboration with the technology partner Shouldcosting, supported SBB over a period of one and a half years in implementing the new product group structure. Using a “Machine Learning” algorithm, most items were efficiently categorized. Data objects that could not be automatically assigned were manually classified through a dedicated classification platform. To ensure long-term data quality, a “Stay Clean” concept was developed. Adjusted processes, targeted tasks, and clearly defined roles and responsibilities provide valuable support to procurement teams. Continuous education ensures these standards can be seamlessly integrated into daily operations.
In working with Staufen.Inova, we especially appreciated not only their professionalism but also their support from the conceptual phase through to post-go-live. In addition to profound project management expertise, Staufen.Inova provided valuable guidance with a deep understanding of machine learning technology.
Simon roth
Head of Group Procurement, SBB AG
Resource-Saving Strategies for Enhanced Procurement Efficiency and Value
By consistently implementing the revised product group structure, SBB’s procurement organization has achieved significant improvements in both the strategic and operational management of procurement volumes. The systems were successfully adapted, with a “Machine Learning” algorithm greatly enhancing efficiency in the process. Complex cases were accurately resolved through manual post-processing. The “Stay Clean” concept ensures consistently high data quality in daily procurement activities. This has provided SBB with a solid foundation for future responsibilities, bundling effects, efficiency, and data integrity in procurement.
With the support of Staufen.Inova, we were able to efficiently and seamlessly implement the migration project on time and within budget, ensuring a solid foundation for the sustainable management of procurement performance across all divisions.
Dietmar Gessner
Head of Category Management Excellence, SBB AG
