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Supply Chain AI: 25 Current Use Cases (and a Handful of Future Ones)

Logistics Viewpoints

Demand planning engines have natural feedback loops that allow the forecast engine to learn. The forecast can be compared to what actually shipped or sold. Since ML began being used in demand forecasting in the early 2000s, ML has helped greatly increase the breadth and depth of forecasting.

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Amazon and the Shift to AI-Driven Supply Chain Planning

Logistics Viewpoints

They integrate AI into demand forecasting, inventory optimization, and logistics operations to improve efficiency, reduce costs, and mitigate risks. Organizations examine past sales trends, apply seasonal adjustments, and make forecasts based on historical models. Amazon is a leader in AI-driven supply chain management.

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Causal Forecasting Brings Precision to your Forecasting

Logility

Causal f orecasting shines a light on , and isolates, actual demand signals from market “chatter,” thus improving forecast quality. You can be proactive and use c ausal f orecasting to leverage data you already own, model additional data sources that could help explain demand variability… or do nothing. .

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The Forecasting Accuracy Bugaboo

Logistics Viewpoints

When it comes to running a company, when things break down executives have traditionally said “we need to improve our forecasting!” Would better forecasting accuracy be a good thing? Unfortunately, most companies cannot, and will never be able to, consistently rely on highly accurate forecasts. Absolutely!

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Reinventing Supply Chains: Focus on Human Factors

Supply Chain Shaman

Supply chain was defined in 1982 as interoperability between source, make and deliver. Each organization has multiple demand streams with different characteristics–forecastability, demand latency, and bias. Most companies forecast a single stream with a focus on error. Why is a reinvention needed? The reason?

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Key Takeaways from SAP Spend Connect Live

Logistics Viewpoints

SAP is embedding its generative Joule across the SAP Ariba source-to-pay solution portfolio to make it easier for their customers to manage routine inquiries, such as status updates, summarization, and frequently asked questions. For example, a buyer might say, “You only shipped me 800 of the 1000 products I ordered.”

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How to Optimize Fulfillment with Unified Data

Logistics Viewpoints

Optimizing fulfillment requires a series of steps to get a shipment from its source to the end customer. These steps include sourcing and receiving inventory, storing inventory, order processing, picking and packing an order, shipping the order, and returns management.