Multi Tier Supply Chain Risk - Traditional vs. AI
When discussing multi-tier supply chain risk management
The traditional approach
A more effective approach is to leverage AI by incorporating thousands of external datasets, creating the "Battleship Effect." Think back to the board game Battleship. The more pegs you place, the clearer the "picture" becomes, helping you to locate your enemy's battleship. Similarly, by utilizing tens of thousands and even hundreds of thousands of datasets—from raw material prices, to geopolitical factors, to economic indicators—you gain a clearer, more precise picture of your multi-tier risk, all without having to directly obtain data from your suppliers. As the datasets are incorporated, AI fills in the gaps, locating your "battleship", or in the terms of supply chain, the AI will understand your multi-tiered supply chain and forecast the risk for better planning and procurement.
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No need for forms, constant data updates, or supplier information integration. AI takes care of the heavy lifting, providing a holistic forecast of multi-tier risk. While the traditional approach focuses on how major events like hurricanes, fires, and wars impact the supply chain, it often overlooks subtler elements that affect risk. To accurately forecast these subtle risks, a holistic approach is essential—one that considers a lot of factors and variables. This is where the cross section of AI and supply chain risk management becomes significant, carrying a lot of positive implications and much faster implementation times.
And this is exactly what we do. One of our ecosystem partners states it aptly: "Ceres represents a quantum leap forward in risk management." Do you want to manage your multi-tier risk? We promise we don't bite. Get in touch and learn more about our "quantum leap forward".