The Implementation
Operating across four Eastern European countries with both B2B and B2C channels, the client faced a highly complex supply network. With 80% of their portfolio sourced from China (long lead times) and 20% from Europe (short lead times), their legacy execution—managed entirely via disconnected Excel spreadsheets with no demand forecasting—resulted in simultaneous severe stock-outs and debilitating excess inventory.
EvoChain was deployed to execute a complete operational turnaround, transitioning the company to a unified, demand-driven architecture:
- Algorithmic Demand Sensing: Automated data ingestion mapped unstructured sales history to generate highly accurate ML baselines, removing manual guesswork.
- Actionable MRP: Calculated dynamic inventory buffers utilizing stochastic modeling, instantly generating time-phased purchasing plans that mathematically offset Chinese shipping lead times against minimum order quantities (MOQs).
- Network Design Optimization: To support a new distribution center, EvoChain executed geospatial Center of Gravity (CoG) simulations against regional demand, isolating the mathematical ideal location to minimize transit costs and segmenting which SKUs should be stocked per DC.
The systemic transformation fundamentally altered their operating model. By automating data ingestion and replenishment logic, productivity increased by 50%, while inventory visibility logic reduced critical stock-outs by 80%.