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Breaking Boundaries: Exploring Generative AI’s Impact on Supply Chains

The Logistics & Supply Chain Management Society

With its ability to derive insights from vast amounts of data and derive insights, generative AI has emerged as a valuable tool to optimize supply chain operations. AI models have grown tenfold, representing a step-change in AI capabilities, creating new use cases across the supply chain. Generative AI is all about scale.

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Good-bye. I Will Go Forward by Going Forward.

Supply Chain Shaman

As a strong proponent of maturity models, many discussions centered on the movement from program-based to functional metrics and how to drive alignment. Our discussions, influenced the model shown in Figure 1 from the Book Metrics that Matter. Metrics That Matter Model Evolution. Roddy loved beer.

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Do You Really Understand What’s Driving Your Demand Planning Processes?

Logility

Descriptive, predictive and prescriptive analytics should be combined to optimize your demand planning processes. To really exploit your new data to gain an advantage, you need a clear analytical plan, specific metrics tailored to your situation, and an understanding of what analytics and reporting will help you the best.

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Automating Business Processes: Streamlining Efficiency and Profitability

Elementum

Monitoring and optimization : Continuous monitoring and improvement of automated processes allows for ongoing efficiency gains and adaptation to changing business needs. Metrics to Measure Success Once automation has been implemented, it’s crucial to track its success through Key Performance Indicators (KPIs) and other metrics.

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Better ESG Performance Will Unlock Fashion’s Supply Chain Resilience in 2022

Logility

The industry stands to gain too much to accept mediocre attempts, such as shifting to vertical production, embracing made-to-order business models, or creating new pieces from vintage garments or deadstock materials. But if the outcomes are inconsistent and do not produce tangible impacts, it means nothing. Supplier collaboration.

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How to Implement AI in Your Supply Chain: A Real-world Guide

ThroughPut

Instead, start by documenting current processes and identify issues. The quality of your AI model largely depends on the quality of your data input. Therefore, it is essential to perform an exhaustive audit and check for completeness and accuracy to fix data quality before commencing AI modeling. Or did it improve margins by 7%?

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How to Implement AI in Your Supply Chain: A Real-world Guide

ThroughPut

Instead, start by documenting current processes and identify issues. The quality of your AI model largely depends on the quality of your data input. Therefore, it is essential to perform an exhaustive audit and check for completeness and accuracy to fix data quality before commencing AI modeling. Or did it improve margins by 7%?