Each day, the Schweizerische Bundesbahnen AG (SBB) takes more than 1.3 million people and 750,000 tons of cargo to their destinations. Standing behind these XXL logistics are not just 35,000 employees, but also thousands of suppliers. To control this supply chain network more efficiently in the future, the SBB has realigned its product groups and worked with Staufen.Inova to migrate its data. An important ally here is Artificial Intelligence.
Staufen.Inova and technology partner Shouldcosting assisted the SBB with the introduction of a new product group structure. With machine learning, it was possible to categorize the majority of the items very efficiently. A “stay clean” concept was developed for long-term assurance of data quality. Modified processes, goal-oriented tasks, and clearly defined skills and responsibilities will help SBB’s purchasers for the long term.
Joint performance and digital expertise: the path to the new product group structure
When Simon Roth, Head of Group-wide Purchasing at SBB, looks back on that day at SBB headquarters in Bern, there is a lot of pride, but also a little humility. In his words: “We may be talking about a purchasing project here, but in the end it was a joint company effort, involving many departments, from Purchasing to Compliance, IT and Engineering, all making their contribution.” A project like this requires working together.”
Dietmar Gessner, Head of the Product Group Management Competence Center at SBB, was largely responsible for ensuring that this big project stayed on track in terms of time and budget. “This begins when you bring all stakeholders on board before the project starts.”
The project started almost two years ago. At that time, the old product group structure no longer reflected the market and current requirements. This made purchasing more difficult overall and in particular, it made bundling effects nearly impossible. The solution: A comprehensive reorientation of the product groups with the goal of increasing efficiency and transparency while strengthening the company’s position with regard to the suppliers. The experts from Staufen.Inova assisted us with the conversion and used their methods and specialized knowledge to reduce the manual work required for entering and processing purchasing data to a minimum.
“A project of this magnitude is something special even for consultants,” says Sebastian Perez Pena, Project Manager at Staufen.Inova. “We made use of our extensive expertise from previous digital projects here. That enabled us to efficiently integrate new technologies into traditional purchasing topics across disciplines. The result: From the development of the initial procedural concept to the processing of complex quantities of data, on through to the complete conversion of all data objects in all systems, every step went according to plan.”
Simon Roth Head of Group-wide Purchasing SBB AGDietmar Gessner Head of the Product Group Management Competence Center SBB AG
AI ensures the greatest possible efficiency
The complexity of this project was impressive. Approximately 650,000 items, 8,000 active supplier contracts, and approximately 80,000 open order items had to be transferred into the SBB’s new product structure. This would have been too much work without automation. Purchasing Manager Roth is convinced that “AI is the key to opening the treasure chest of company data and setting competitive advantages free.” Staufen.Inova and its technology partner Shouldcosting developed the appropriate applications with which most of the classification could be automated.
The tool uses algorithms and machine learning (ML) to make precise suggestions for reclassification based on a scoring model. This way, approximately 85% of the items could be assigned automatically, while the rest had to be reworked manually in places. This intelligent combination of automation and human control guarantees high data quality.
So that the measures will work in the long term, the group also introduced the “stay clean” concept. SBB expert Gessner said “In previous product group management, we worked according to the delegation principle, which meant that information was cleaned up during the procurement process. Strict adherence to the new product group classification should produce a cleaner data quality.”
For this, new processes and clear responsibilities were established to ensure correct and up-to-date maintenance of the product groups. To prepare the employees in the Purchasing department sufficiently for the requirements of the new structure, we conducted more than 25 trainings.
KPI reporting as a basis for the purchasing strategy
In addition, SBB is introducing a new KPI reporting system in category management that not only takes into account progress indicators in terms of maturity, but also factors such as contract duration or the allocation of business. The goal is to integrate both quantitative variables and qualitative assessments. For example, the topic of supplier qualifications were added to the scorecard in order to achieve greater transparency with regard to the whole procurement market and to better distribute responsibility for the product groups.
With the new KPI system, SBB’s nearly 70 Category Managers get a detailed overview each quarter. This allows them to detect optimization possibilities and potential for improvement and to make fact-based decisions. Finally, SBB is striving for more bundling of purchasing volumes and better control of the supplier markets. The newly gained transparency thanks to the KPI reporting also helps with the correct allocation and processing of goods and services in the connected systems, such as SAP Ariba.
In addition to the successful implementation of the AI-supported procurement processes, SBB employees – not just in Purchasing – are using a kind of “SBB ChatGPT,” that is, an isolated AI application, into which sensitive content can be uploaded. It is used in daily business to generate, summarize, or correct texts. “This is already the norm for us,” says Simon Roth.
About the SBB
In keeping with its motto “Connecting Switzerland,” SBB transports more than 1.32 million passengers and 175,000 tons of freight each day. Its 35,000 employees ensure that the more than 11,400 trains reach their destination on time. The purchasing volume of SBB was recently more than CHF 5.8 billion.
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Comparing quotations and analyzing contracts with large language models
In the future, SBB plans to use large language models (LLM) to assist Purchasing with quotation comparison and contract analysis. Furthermore, chatbots will lead key users through the procurement process in order to make it more efficient. In the past, uncertainty about product group allocation, with 515 possibilities, caused delays. Dietmar Gessner: “Machine learning and AI are no longer niche topics; they can achieve measurable efficiency and effectiveness gains in all areas of a company.”
The combination of state-of-the-art technology, clear processes, and cooperation across the company will make SBB fit for the future in product group management. This project shows on the one hand how digitalization releases potential and offers a blueprint for optimizing the entire organization for the long term.
Always keeping an eye on benefits for the entire company
On the other hand, a project of this magnitude highlights the importance of coordinated alignment and a clear structure of tasks and responsibilities. In this case, all relevant stakeholders were incorporated and informed through 57 communication events. This ensured intensive cooperation, communication, and a readiness to change.
For Jürg Hodel, Managing Director of Staufen.Inova, the high level of willingness to change and the joint creative drive were crucial. “The positive spirit was carried through the entire project by the early, close cooperation and mutual trust.” In addition, SBB has an impressive corporate culture that is open to new things.”
Group Purchasing Manager Roth also draws a positive conclusion. “We are pursuing the ‘One SBB’ approach. The goal is to draw everyone closer together and keep an eye on SBB as a whole. Even if in some cases this will take time. Our project underscores that we are well established here and can orient the cooperation so that in the end, the focus will be on benefits for the entire company rather than individual interests. With respect to new technologies, this project has also demonstrated in exemplary fashion where the journey will take us. We are not chasing trends, but intervening where we see a need and can detect clear benefits.”
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