How data-driven inventory optimization helps Cordstrap to reduce days of inventory and stockouts

About Cordstrap

Cordstrap develops, produces, and sells solutions to secure and protect cargo loads during movement and transportation. Cordstrap has three production sites and a divergent distribution network where products are shipped to end-customers through global and local DCs, with in general long lead times for raw materials.  


The challenge

In 2022, William van den Bremer started as Director Planning & Logistics at Cordstrap and in his first year, he and his team realized an inventory value reduction of 20%. This was achieved by reducing overstock which was the result of forecast bias. There was a desire to further reduce, but also to set a direction and validate future working capital ambitions. Cordstrap asked EyeOn to assess their inventory health and to identify the best yet realistic way to reduce days of inventory (e.g., change network structure, planning parameters, etc.), without impacting customer service levels.


The project

In the first phase of the project, we started with mapping the “as is”-situation, by means of a Value Stream Map and an assessment of the current inventory health by assigning the actual stock to different stock type buckets (safety, cycle, transit, under- and overstock). From these insights, we concluded that safety stock is the main stock driver and that there was potential to improve the quality of the safety stock parameters.  

The second phase of the project focused on optimizing these safety stock parameters. This journey started with data collection & validation, defining and implementing business rules (assumptions) to map goods flows (i.e. demand) that have been rerouted over the last years, mapping demand from old products that have been replaced by new ones, and for identifying and excluding demand peaks and shifts that are not representative for the future. Next, we defined scenarios to differentiate policies (e.g. MTO/MTS) and target service levels across different product groups and segments (ABC/XYZ) 

We leveraged our Honeycomb (data science) platform to calculate the optimal safety stock parameters, and our toolkit of PowerBI-dashboards to visualize and support the transition towards the right-sized safety stock parameters and insights in (the root-causes of) overstock. Via workshops and trainings the applied methodology was explained and embedded in the global organization.



This project has helped Cordstrap to make the next step in their inventory management maturity and towards a data-driven approach to set target safety stocks. The quantitative analysis revealed the following insights: 

  • Implementation of service level differentiation will result in 10% safety stock value reduction and, at the same time, a service level increase from 91% to 95% on (semi-) finished products and from 97% to 99% on raw materials. 
  • Quantifying an informed further safety stock reduction requires a more sophisticated modelling approach (i.e. multi-echelon inventory optimization). The projected savings from applying some simple rules to leverage “multi-echelon effects” are small and don’t outweigh the complexity of their implementation. 

An action plan was developed for Cordstrap to structurally improve their inventory health, in terms of process, people, tools and data, in order for Cordstrap to make the next steps in professionalizing their inventory management and realizing the projected savings. 



Interested in how EyeOn can help you reduce your days of inventory and stockouts? 

Get in touch with us to learn how EyeOn can help you assess and improve your inventory health by identifying opportunities and putting them into action directly. If you want further insights into the Cordstrap case, contact Maarten Driessen, our team lead Inventory Optimization & Network Design.     



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