Thule has made several important changes in the last years going from a decentralized set-up based on demand planning to a more centralized process. Their positive results have been significant.
Prior to using Optilon’s Supply Chain Planning platform, Thule’s forecasting process had been based first on Excel, later on, decentralized demand planning. To obtain better forecasts the process was centralized but this brought too much manual work and a lack of connection between service and inventory.
The solution to these problems has been to implement ServiceOptimizer99+ (SO99+) from ToolsGroup as well as a new process implemented by Optilon. The new solution covers Thule’s biggest product segment Outdoor. The Outdoor segment has a global customer base consisting primarily of distributors within Cars and Sports, a significant portion of sales goes to OES customers in the automotive industry. There are six factories in Europe, one central warehouse, five regional distribution centers, and more than 4000 finished goods. Two of the major challenges are a distinct summer season and uneven demands.
Summing up we could say:
- Forecasting required too much manual work
- Seasonal demand spikes
- Slow movers with intermittent demand
Thule’s Outdoor segment called upon Optilon to implement an automated forecasting system that delivered a more efficient and accurate demand planning process. Thule’sDemand Planner, Michael Wolfsteiner, explained the uniqueness of the solution, based on ToolsGroup’s SO99+ software,
“Traditional demand planning considers demand history in terms of quantity only, ignoring customer order lines. ToolsGroup’s SO99+ on the other hand analyzes the demand history both in terms of quantity and customer order lines, in order to better model the shape of the demand. The close connection between desired service level and inventory level is very positive.”
The solution included inventory optimization. Thule‘s old safety stock routine was based on a seasonally dependent coverage rate (e.g., number of days’ average demand). The new optimization instead starts from an aggregated service level target and defined service levels for each SKU, taking advantage of a wide variety of variables, such as demand variation, average demand, order frequency, costs and lead time. It modifies service and coverage to maximize the overall use of the capital within a pre-defined “service group”. Minimum service levels are set for business-critical items. The system also included rough-cut planning to identify requirements to pre-build stock due to capacity limitations. The actual replenishment is still done in the ERP system.
The project has brought a common, more efficient, and accurate demand planning process within the Outdoor segment.
The new solution with SO99+ means forecasts and safety stock levels in the ERP are automatically updated every week based on optimizations in SO99+. Thule‘s old safety stock routine was based on a defined seasonal dependent coverage rate (setting number of days’ average demand).
SO99+ instead starts from an aggregated service level target; the optimizer defines service levels for each SKU to reach the aggregated service level target using an objective function. The optimization in SO99+ leads to distinct deviation in service and coverage within a service level group to maximize the overall use of the capital.
The project have helped Thule reach the following KPIs: –Service level increased by more than 20 points, from 75% to 95+% –Outdoor segment average inventory was reduced by more than $2 million–Workload reduced by 75%
Summing up results:
- Servicelevel increased by more than 20% points from 75 to 95%
- Workload reduced by 75%
- Managed to centralize and automate the forecasting process
- Reduced average inventory for the outdoor segment by more than 2 million USD