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Case Study: Logistics, Warehousing and Inventory Optimization - Frozen Foods

Optimizing Logistics Strategy#

Finding the optimal logistics and warehousing footprint to decrease total cost, minimizing inventory while meeting service level requirements


  • Up to 5% logistics cost savings, despite an increased demand forecast
  • Overall order cycle time improvement up to 30% by optimizing the warehousing and distribution footprint
  • 40% reduction in required weeks of supply, realized up to 3% extra cost savings by decreasing the inventory constraint due to greater service flexibility achieved

FrozenFoods* is a leading speciality foods company producing and distributing frozen foods delicacies and high-end fresh foods to industrial and retail customers. FrozenFoods has production, storage and distribution facilities in more than 15 countries. Industrial and retail sales channels require different service levels and have different product mix demands.


Retail customers have increasingly high service requirements and both retail and industrial customers project higher demand than FrozenFoods' existing warehousing and distribution network can meet. A cost-optimal solution must be found that meets future storage and customer service requirements.


SimFlex identified the optimal future distribution flow by reconfiguring the distribution network. In order to meet the increased warehousing capacity needs, SimFlex performed sensitivity analyses and suggested reduced inventory levels, so that storage capacity constraint were respected, and avoiding the need for additional capacity investment.


SimFlex identified that shifting end customer distribution flow towards certain DCs would significantly improve service levels for retail customers without compromising cost, or service to the industrial customers. As a result, overall order cycle time improvement achieved was 30%. At the same time, up to 5% cost savings in logistics cost were realized. In managing the capacity-constraint problem, SimFlex identified that with current weeks of supply level there would be insufficient storage capacity. However, the better responsiveness achieved by optimizing distribution flow allowed the weeks of supply to be decreased by almost 40%, reducing storage space requirements and realizing an additional 3% cost savings.

Geo-based snapshot of actual service level distribution
Current Scenario Optimized Scenario

Green: service level requirements are met

Yellow: service level requirements are under risk if forecast increases further

Red: service level requirements are not met

Dynamic inventory behaviour for the selected warehouse

*Company name disguised to retain confidentiality