This article describes a ‘rethinking of AI’, looking at data first, establishing a hierarchy of data stores, ‘best fit’ capabilities, and reducing nervousness in supply chain decision making.
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We look at the use of AI for demand planning and forecasting, as well as inventory management and making MEIO (multi-echelon inventory optimization) work better.
This series explores the many supply chain-related use cases of AI, starting with pricing and promotion
We debunk myths about AI vs. human thinking, AI autonomy, the role of data, open source AI, the role of data scientists, and AI’s impact on jobs.
Previously intractable challenges that supply chain professionals have been grappling with for decades are now within reach using AI/ML. These include fixing new product introductions, stock-outs, optimizing inbound through outbound fulfillment, and improving profit margins.
AI and ML are not taking over your job. But they will change things. To avoid digital displacement, employees have to prepare themselves now to be the leaders of using these capabilities, and the advisers to their companies based on the new insights.
Systems and companies are evolving incrementally towards autonomous supply chain execution. Here we outline seven steps to autonomous supply chains.
Supply Chain Application Networks provide more than just multi-enterprise messaging and supply chain visibility. Multi-enterprise planning and execution functionality is built into these networks, in areas such as transportation, sourcing and procurement, demand collaboration, and outsourced production management.
Taking the longer view, companies can select a GIS platform that can serve as an enterprise-wide platform for many different applications. Here we discuss the characteristics to look for when selecting a platform.
Predictive maintenance can play a key role in a business’s transformation to servitization and an outcome-based business model.
Predictive maintenance can be highly valuable for asset-owning organizations to reduce downtime and maintenance costs. This includes large complex systems used in extractive industries (e.g. mining systems, oil platforms), manufacturing plants, warehouses, transportation fleets, and facilities.