Case Study: SimPlan AG achieves cost-effective supply‑network optimization with anyLogistix

Planning the supply chain of a German building materials producer

SimPlan faced a challenge to redesign the German supply network for a building‑materials producer to find a more cost‑effective configuration and solve location problems (GFA/NO) while satisfying service‑level, capacity and shipping constraints. To support data transformation, geocoding, scenario building and model execution they used anyLogistix (v.2.14.x) together with Python.

Using anyLogistix and Python, SimPlan performed greenfield analyses and network optimizations on clustered input data to compare scenarios and evaluate transport, handling and inventory tradeoffs. anyLogistix models identified concrete, measurable impacts: establishing a CDC west of Berlin and a CDC in the Ruhr would save €3.3M/year and relieve two warehouses; a central structure with 2 existing warehouses + 5 CDCs would save ~€1.8M/year and reduce active shipping points to 7, while other scenarios showed increases (e.g., exclusive supply raised transport costs by ~€1.7M; one scenario increased costs by €3.8M).

SimPlan

Till Fechteler

Branch Manager