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What Warehouse Modeling Software Should You Use?

Logistics Bureau

Essential Steps to Using Warehouse Modeling Software for Design 1) Understand the Design Objectives and Constraints The first step in your review should be to determine and prioritise the objectives for your warehouse facility and operation.

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Google Cloud Supply Chain with Paula Natoli

The Logistics of Logistics

enables logistics and supply chain companies to build, deploy, and scale machine learning models faster, with pre-trained and custom tooling within a unified artificial intelligence platform. Document AI. Document.ai Learn More About Google Cloud Supply Chain. Paula’s LinkedIn. Supply Chain Twin and Pulse.

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Optimizing Supply Chain Transparency with Digital Product Passports

Logistics Viewpoints

These passports document all aspects of the life cycle – from the sourcing of raw materials to final disposal or recycling. AI and machine learning tools identify patterns, predict issues, and suggest ways to optimize operations. Having a well-documented DPP also makes it easier to report to regulators and stakeholders.

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Four Essential Supply Chain Management Tools

CLX Logistics

To meet these demands, shippers need the right supply chain management tools with the flexibility to grow and scale as needed. The right supply chain management tools help not only to enable shippers to provide better customer service and on-time deliveries but also to remain competitive with everyone else in the market.

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Executives Exploring AI Need to Understand Data Fabrics

Logistics Viewpoints

Mr. Masson of ARC points out, “Each AI use case requires specific datasets and may necessitate different tools and techniques.” Developing Models : Building and scaling AI models in a manner that ensures they are reliable and understandable. The agent selectively pushes data to the Aera data model.”

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Can Improving Forecast Accuracy Address Our Demand Planning Woes?

Logistics Viewpoints

In times that continue to defy our ability to predict them, the words of famous statistician George Box have never been more right: “All models are wrong, but some are useful.” So what can we do to make models more useful? Why bother with forecasting if the model is always wrong? Trusting the box.

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Building Moats in AI: Buy vs. Build (AI Popup #1)

Freightos

In the first issue of our AI popup newsletter series, Matt Motsick, CEO of Rippey AI and a long-time logistics technology leader, explores buying or building AI models. If a company can specialize in core competencies with AI tools, it creates a high barrier for another company to compete against.