


Supply Chain Management in the Process Industry
We create the foundation for a resilient and efficient supply chain.
Optimizing the supply chain and managing complexity
Global supply chains have evolved over the years. New locations, additional products, and customized customer requirements. What made sense during periods of growth can quickly become a burden in day-to-day operations. For many COOs and supply chain managers, a key question arises today: How can complexity be managed without jeopardizing customers’ growing expectations? In practice, complex network structures that have evolved over the years are evident. Clear process rules and binding guidelines were largely absent, and inefficiencies persisted throughout the entire end-to-end order processing. Specifically, this manifested itself in critical performance metrics such as lead time, OTIF, or increased logistics costs. At the same time, the combination of long procurement cycles, a non-standardized inventory strategy, and production batch sizes that are not optimized leads to increased inventory levels. This situation can become highly critical for individual companies. Capital is tied up, on-time delivery is at risk, and flexibility toward customers in highly competitive markets is severely limited. Without structural changes, there is a risk of both negative impacts on earnings and significant liquidity pressures. Creating transparency is important, but it is not enough on its own. What matters most is the ability to systematically analyze and link relevant supply chain data and use it to identify specific areas for action. Flexible, customized data models and process mining quickly establish a foundation for a robust baseline, highlight deviations in KPIs, and support the quantification and prioritization of measures. At the same time, they serve as a control instrument for further implementation. The combination of data analysis and process understanding is a key success factor, to which we can contribute our extensive supply chain experience. Based on the analysis, the key value drivers of the supply chain were systematically identified. The focus was not on isolated individual measures, but rather on a consistent vision for the entire order processing workflow. One focus was on reducing lead times. It became clear that a lack of standardization and unclear interfaces between functions were the primary causes of delays. At the same time, measures to improve planning quality and forecast accuracy were identified. AI-based forecasting approaches help identify demand patterns more precisely and support data-driven planning decisions. We often see complicated, manual, and time-consuming order processing workflows that have only been optimized in certain stages of the process. Cross-functional challenges have not been fully addressed end-to-end, as competing objectives are often at play. Here, we work with the relevant functions to develop a clearly defined end-to-end order processing workflow that includes individual process steps, mandatory checkpoints, and a coordinated governance structure. Roles and responsibilities are transparently defined to enable consistent implementation. Another key driver is inventory management. By implementing a structured classification of inventory and identifying slow-moving and dead stock items, specific opportunities for optimization can be quantified. In particular, coordination between sales, planning, production, and order processing is often insufficiently synchronized. This results in inefficiencies throughout the entire value chain. A (non-)existent Sales & Operations Planning (S&OP) process often falls short or is not properly configured. There is frequently immense potential here if a supply chain can respond flexibly and in a timely manner to signals from demand forecasting. AI-based forecasting models help predict demand more accurately, identify fluctuations in demand earlier, and significantly better align planning, production, and inventory. The organizational dimension also plays a central role. It often becomes clear that sustainable improvements and transformation can only be achieved through adjustments to governance, roles, and responsibilities. Silo thinking is replaced by end-to-end accountability, while the pace of implementation is carefully aligned with the company’s culture. A key success factor is the close involvement of the organization. Rather than taking a purely conceptual approach, different functions are actively involved in developing the solutions. In particular, tensions between Sales and Production / Supply Chain need to be addressed from day one. This creates alignment early on and builds acceptance for the implementation phase. Would you like to explore these topics further? Discover how we can jointly optimize and strengthen the resilience of your supply chain sustainably. From transparency over the current maturity level to support during implementation and the internal change process.Identifying vulnerabilities in one's own supply chain
Transparency: What now?
What levers have been identified along the supply chain?
End-to-End Order Processing
Cash Generation Through Inventory Reduction
Planning: S&OP or IBP?
Adapted Supply Chain Organization
Shaping the Transformation Together
Key Takeaways for Practitioners
Contact us now
