Designing resilient supply chains with a Digital Twin: Insights from BSH Home Appliances Group
Designing a global supply chain requires balancing cost, service levels, resilience and sustainability. For BSH Home Appliances Group (BSH), achieving this balance depends on the ability to simulate complex logistics scenarios before making structural decisions. By applying a Digital Twin to its supply chain network, BSH is strengthening decision-making across warehousing, transportation and long-term growth planning.
In an interview recorded at Realize LIVE Europe 2025, Bart Meers, Global Executive Head of Warehousing at BSH, explains how data-driven simulation has become a core capability for the company’s supply chain network design.
From warehouse networks to end-to-end supply chain decisions
BSH operates 188 warehouses worldwide, including both in-house and outsourced facilities. Within its Supply Chain Network Design (SCND) team, the company models the flow of finished goods from factories to warehouses and onward to customers. Using the Siemens Supply Chain Suite, BSH created a digital twin of its finished goods logistics network, initially focusing on the “deliver” phase of the supply chain.
This Digital Twin allows BSH to simulate different network configurations, including warehouse locations, sizes and service levels. Scenarios can be evaluated based on cost, operational performance and customer impact, supporting informed decisions before changes are implemented.
Improving resilience, cost efficiency and sustainability
Scenario simulation also supports supply chain resilience. As highlighted in the interview, recent global disruptions demonstrated that resilient networks can protect revenue while helping to control costs. By testing alternative setups, BSH can proactively design supply chains that perform reliably under changing conditions.
Cost optimization and sustainability are closely linked in this process. The Supply Chain Suite enables BSH to compare transportation options, including road, rail and overseas shipping, while accounting for cost structures and CO₂ emissions. This allows decision-makers to evaluate trade-offs between economic efficiency and environmental impact using consistent, data-based insights.
Data integration and collaboration as enablers
The Digital Twin is built on data from enterprise resource planning (ERP) systems, transportation management systems (TMS) and warehouse management systems (WMS). According to Meers, this integration provides a reliable foundation for fact-based decisions.
When BSH launched its Digital Twin program in 2021, Siemens supported the initiative as an extended workbench, providing consulting expertise to help establish standardized models and methodologies. As described in the BSH case study, this collaboration enabled faster implementation and reduced the time required to conduct network studies by approximately 50 percent.
Scaling the Digital Twin beyond logistics
Today, around 85 percent of BSH’s delivery network digital twin is defined. The next phase extends beyond warehousing to include manufacturing, sourcing, supplier hubs and aftermarket spare parts logistics. In each case, the objective remains the same: to evaluate scenarios, quantify impacts and support confident decision-making.
Learn more
- Further details on the BSH project can be found in the case study “Managing growth and anticipating market trends by optimizing logistics and supply chains”.
- Interested in attending Realize LIVE Europe 2026? Registration information is available here.
