Case study: Stock optimization

COSMO CONSULT developed an automated optimization process to improve the demand and inventory management for a company specialized in occupational safety and fire protection. Today, the company benefits from decreasing safety stocks while maintaining a high level of service. In addition, it was possible to reduce out-of-stock situations to a minim

• Automated sales forecasts with machine learning procedures
• Optimizing safety stocks and reorder points
• Increasing the service level
• Avoiding out-of-stock situations

A company supplies customers throughout Europe in a B2B environment with products in areas such as occupational safety, hoses technology and fire protection. For a long time, managing demand and inventory was based on practical values and rigid specifications. Due to the high market dynamics and the growing variety of products, this strategy has proven inadequate. The result is a low level of service and high inventory costs.

The company therefore commissioned COSMO CONSULT to develop an automated calculation of the optimal inventory level to ensure both service levels and high storage capacity requirements.

Based on a comprehensive data analysis, the project team developed forecasting models to calculate the demand and supply replacement times. The system was implemented using R. To forecast demand and structural changes with sufficient accuracy, data from framework contracts were used. On the basis of the prediction, it was possible to estimate the current volatility of the product correctly and thus forecast the required safety stock.

The optimization process helped the company reduce its safety stocks. At the same time, it managed to maintain global service levels and avoid out-of-stock situations. Another important improvement for products with special properties: With an adapted optimization methodology, the service level could be increased by seven percent and the cost level could be decreased by 10 percen