Facing increased volatility in their supply chain, our customer wanted better demand and supply predictions—primarily to help them improve service levels in the North American market.
Also, our customer’s bias towards carrying too much inventory was impacting margins by driving up inventory holding costs, working capital and product obsolescence costs.
Athena Insights recommended that I reduce production for my product. I acted two weeks earlier than I would have with our traditional planning tool, which allowed me to eliminate planned production, and saved us $760K, all due to that single recommendation.
To improve fill rate, reduce inventory holding costs, and reduce obsolescence for our customer, Noodle.ai deployed two products from the Athena Supply Chain AI Suite: Athena Insights and Execution Control Towers.
In May 2020, Athena Insights went live to 45 planners covering approximately 2,000 high-profile SKUs in the North American market. Designed to help companies quickly get started with supply chain AI, Athena Insights provides weekly SKU-level predictions of both orders and weeks of supply, while recommending changes to the production schedule to better match inventory with demand.
In July 2020, we deployed Execution Control Towers, focused primarily on making shipment-level allocation and deployment recommendations. The application leverages the same AI-ready infrastructure that supports Athena Insights, while providing more robust, value-add functionality. Using sophisticated AI inference engines that have been trained on thousands of supply chain variables, the application predicts SKU/DC-level risks such as lost sales, product obsolescence, and unnecessary expedites.
Each of Noodle.ai's risk predictions is tied to a dollar value, what we call our Value at Risk (VAR) metric. Not only does VAR enable planners to prioritize their work, it also provides managers and executives with a clearer picture of the total financial risk facing a brand, region, or business unit.
Execution Control Towers provides planners with precise, action-ready recommendations to most efficiently mitigate the risks, such as how much (and when) to increase/decrease production, how much inventory to deploy across their DCs, and when (or when not to) expedite shipments.