Dramatic improvements in forecasting accuracy at Trelleborg

Trelleborg Sealing Solutions is a leading global supplier of polymer-based critical sealing solutions deployed in demanding general industry, light vehicle and aerospace environments. Trelleborg Sealing Solutions are part of the Trelleborg Group which is a world leader in engineered polymer solutions that seal, damp and protect critical applications in demanding environments. Its innovative engineered solutions accelerate performance for customers in a sustainable way.


“We were looking for a partner that could help us improve all our planning processes instead of looking at just one area and leaving out others. We decided to partner up with Optimity whose planning application covers statistical forecasting, demand planning, inventory optimization and supply planning which made us comfortable they could give us the end result we wanted. The most urgent area to tackle was forecasting and demand planning so that was where we started. We have now been live for 6 months and we are certain the new solution has led to dramatic improvements in Forecast Accuracy (30-40% improvement). This is thanks to a combination of smarter forecasting algorithms as well as an improved demand planning process.” comments Mattias Borén, Logistics Manager at Trelleborg.

Lars Gimbringer, Managing Director at Optimity says, “We are very proud to have Trelleborg Sealing Solutions as a customer. They have been very professional throughout this entire project and have managed to improve and change their internal demand planning process to harvest the benefits a modern demand planning application like Optimity can provide. This project presented some interesting challenges as the customer has a very large number of sales products produced to order while the stock is kept upstream in the supply chain for semi finished products. Together with the customer we modelled different approaches and the final decision was to run statistical forecasting on semi finished product level to achieve stable seasonality and trend patterns. The demand history is then used to break the statistical forecast down to the lowest level which includes market dimensions like sales product, country and customer. Changes can be applied on any level and this gives a very flexible while still robust solution.”