Aston Martin raises public first time availability target 2% to 97.5% and drives 18% reduction in safety stock value with machine learning engine

"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)”."

"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''."

"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."