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Order Visibility Is Critical Amid Low Inventories

Logistics Viewpoints

But shippers looking to avoid disruptions and ensure that tight inventory levels don’t lead to missed sales opportunities pulled their orders forward. As companies look ahead to the next three to six months, they’re weighing costs, risks, and demand as they plan and adapt their inventory strategies.

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Importance of Ensuring a Data Management and Supervisory Control Framework Spanning Supply Chain Execution Decision Making

Supply Chain Matters

In this commentary we focus specifically on the importance of a broader end-to-end data management framework while overcoming the fragmentation of data that is locked in separate, unconnected software applications.

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Five Reasons Why Are We Not Making Progress on Inventory Management

Supply Chain Shaman

At the session, we discussed why companies have not made more progress on inventory management. In the case of Apparel and Automotive industries there are slight improvements, but they have shifted inventories to suppliers. Days of Inventory Pre and Post-Recession. We share this data in Figure 3. There are many.

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Autonomous Business Planning Is Not Only Possible, It Has Already Been Achieved

Logistics Viewpoints

This metric measures the percentage of time the planners accept replenishment, transportation, or inventory plans as they are without any change in the timing of the delivery or the quantity to be delivered. You set a target inventory level. And that data has “to be internally consistent. That’s an action.

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Unlocking Supply Chain Potential with AI Agents and Multi-Agent Workflows

Logistics Viewpoints

user interface and data management agents) collaborating with specialized-skill and tool agents (e.g., data extractors or image interpreters). Here are some specific use cases: Demand Forecasting AI Agents can analyze historical sales data, market trends, and real-time demand signals to predict future demand accurately.

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

Logistics Viewpoints

We are no longer just forecasting demand but also when trucks and factory machinery are likely to break down ( predictive maintenance ), the optimal amount of inventory to hold and where it should be held ( inventory optimization) , and labor forecasting in the warehouse.

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Step Past AI Hype Drive Real Value

Supply Chain Shaman

Yawn and walk on if the answer is i mproving demand error or reducing inventory levels. The building of data listening platforms to enable teams to answer the questions that they did not know to ask. Data Management: Supply Chain leaders speak of dirty data as a barrier to improving supply chain outcomes.