Footwear Company Cuts SIOP Process Time by 50%

Red Wing Shoes deployed Logility and reduced inventory across the network, increased fill rates, shortened lead times, cut the SIOP process time in half and improved forecast accuracy.

Footwear Company Cuts SIOP Process Time by 50%


Footwear company Red Wing Shoes wanted to improve its sales inventory operations planning (SIOP) process. It needed better forecasting techniques to position its inventory more efficiently.

The retailer was finding it increasingly difficult to plan its business and work with suppliers across the world using spreadsheets alone. Red Wing Shoes needed a more sophisticated solution for its sales and operations planning.


Red Wing Shoes implemented the Logility platform to improve its end-to-end supply chain planning capabilities. Within just four months of introducing the system, Red Wing Shoes – along with its suppliers and retailers – was reaping the benefits of new levels of supply chain visibility, as well as better access to more detailed and more accurate insights than ever before.

The company can now provide suppliers with a synchronised demand and supply plan each month, allowing them to drill down to actual SKU-level demand in real-time, over a 12-month rolling horizon. While collaboration with global distributors via the Logility platform has helped planners understand order patterns across more than 110 international markets and create more accurate global consolidated demand plans.


Since going live with Logility, Red Wing Shoes has cut its SIOP process time by more than 50%. It has reduced inventory by 27% and decreased lead times by 30%. Fill rates have also increased by up to 10%.

With Logility in place, the company now has increased visibility across its supply chain and been able to improve forecast accuracy by 30%.

For Red Wing Shoes, deploying Logility has been transformational for its supply chain performance as improved supply chain visibility has meant the business has been able to significantly accelerate its SIOP processes.

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