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Project examples
Automotive supplier
- Identification of a risk of stockouts for 35 A and B materials.
- Significant reduction potential for 356 A and B materials, reducing working capital by 39 M€.
- The planned delivery time is a significant dirver of DIO. Partially, it differs significantly from the actual delivery times. Adjustment to appropriate values for 137 A and B materials.
- Long lead times and strong fluctuations in lead time drive DIO. Especially 14 suppliers are unreliable.
- Seasonal demand fluctuations especially of customers from Spain and France result in large stock for some products. Demand forecast has been improved to take these fluctuations into account.
- Large order cancellations especially of two large customers from GB. Forecast has been improved here as well.
Delivery service, improve truck loading
Goal
- Optimize truck loading for more precise customer deliveries.
- Increase revenue by improving delivery efficiency.
Approach
- Cluster analysis for customers using machine learning.
- Precise forecast using robust statistics.
- Focus on accurate order fulfillment.
Results
- Loading efficiency improved by over 40% (measured by successful customer deliveries).
- Enhanced delivery precision and higher revenue.
Consumer products
- For 47 products there is a risk: Orders could partially not be fulfilled. Service level for those was adjusted. Customer demand has been underestimated. Appropriate forecasting methods have been implemented.
- For some materials, we see a correlation between not completely fulfilled orders and the bulk production. Improved production planning for the bulk reduces the need for a high safety stock for the product.
- 7 A materials have an increasing stock and a high DIO. These are new products where the company expected increasing sales in France. Marketing campaigns and discounts have been checked to generate the expected sales.
- For one very importnat material, there are high stock values for the two components. The materials have long transport times. Since the transport times do not fluctuate, a better planning reduced stock for the two components by 74%.
- For one material sold in the Italian market, we see small fluctuations in consumer demand but increasingly larger order variances, resulting in surplus stock at multiple stages. Forecast has been improved to avoid that situation.
Technology products
- Main challenge: 99.5% service level for perfect fulfillment.
- A total reduction potential of 17% of the total median stock value of all A and B materials was identified.
- We found 98 B materials with a risk of stockouts. For these and other materials we proposed accurate safety stock values.
- Various MRP parameters needed adjustments.
This project was based on a restricted data set, only stock values, material movements, and sales data, no data from purchasing.