AI Case Study
Aston Martin raises public first time availability target 2% to 97.5% and drives 18% reduction in safety stock value with machine learning engine
Aston Martin required a solution to be able to offer a high first time availability, having spare parts immediately available for customers, without increasing stock levels. The company implemented ToolsGroup's advanced machine learning engine to analyse historical data on consumer behaviour to better anticipate its customers' needs. The implementation of the technology has resulted in a reduction of inventory value of its safety stock by 18% and an improvement in FTA service levels of 97.1%, within only two months.
Consumer Goods And Services
Automobiles And Parts
"ToolsGroup's machine learning engine was able to dip into the vast array of historical data collected by Aston Martin over the years and pick out 8 completely new categories of behaviour.
ToolsGroup implemented an advanced machine learning engine. SO99+ is the first supply chain optimisation solution to embed advanced machine learning into daily demand and supply planning.
SO99+ uses these new categories to generate a more accurate forecast. Then, each day, SO99+ tunes the safety stock for all 80,000 SKUs, automatically reducing the inventory to take advantage of the improvement in forecast accuracy, before creating a replenishment plan to deliver the demanding new target service levels.
According to Wilson, the new focus on seasonality has been transformational: 'The great thing about the eight categories is that people can see them. This has not only educated the purchasing team in important new skills, but has also really given them confidence in the planning system'."
"In just two months of running the new machine learning system, Aston Martin reduced the inventory value of its safety stock on the clustered items by 18 percent while immediately improving FTA service levels to 97.1%, above its target. Outcomes are already trending towards significant further improvements in both service levels and reduced inventory value."
"ToolsGroup implemented an advanced machine learning engine. SO99+ is the first supply chain optimisation solution to embed advanced machine learning into daily demand and supply planning.
SO99+ was able to dip into the vast array of historical data collected by Aston Martin over the years and pick out 8 completely new categories of behaviour. Without any guidance from the humans."
"New demands posed by Aston Martin's international client base prompted its board to raise targets for first time availability (FTA) by 2 percent without increasing inventory, in 2015. For the first time, the board also wanted to achieve FTA parity across all three of its car categories: “Heritage (pre-1997),” “Recent Production (mid 90s forward, but no longer in production),” and “Current Production (today’s models)”."