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Aligning Supply Chain Metrics to Improve Value

Supply Chain Shaman

In follow-up qualitative interviews, one of the largest issues with organizational alignment was metric definition and a clear definition of supply chain excellence. In my post Mea Culpa, I reference my work with the Gartner Supply Chain Hierarchy of Metrics. Error is error, but is it the most important metric?

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Modern TMS Solutions: Driving Sustainability in Supply Chain Operations

Logistics Viewpoints

However, as carbon taxes and emissions reporting requirements continue increasing, supply chain professionals face mounting pressures from inside and outside their organizations to measure and improve performance against new, nebulous sustainability metrics. References: 1.

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AI Agents in Procurement: The Ultimate Guide

ivalua

As supply chains become more interconnected and risks more dynamic, traditional procurement tools fall short. AI agents offer a smarter, faster way to manage sourcing, risk, and spend across the entire procurement lifecycle. This refers to AI systems that act with autonomy and are programmed to accomplish specific goals.

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AI Agents in Procurement: The Ultimate Guide

ivalua

As supply chains become more interconnected and risks more dynamic, traditional procurement tools fall short. AI agents offer a smarter, faster way to manage sourcing, risk, and spend across the entire procurement lifecycle. This refers to AI systems that act with autonomy and are programmed to accomplish specific goals.

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The Role of AI in Sourcing and Procurement: Benefits, Use Cases, and Roadmap

ivalua

In this type of environment, traditional procurement software and manual processes are insufficient – and many procurement teams are looking to artificial intelligence (AI) for answers. Key Takeaways Understand the potential impact of AI – including Generative AI & AI Agents – in procurement.

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How to Optimize Fulfillment with Unified Data

Logistics Viewpoints

The formula for OTIF is: Measuring a supply chain against OTIF metrics is a key strategy that helps decision makers attach a tangible value to the success of their fulfillment and allows them to determine key strategies. Organizations are ready to implement AI and ML-driven prediction and productivity gains.

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Pandemic Lessons For Supply Chain Leaders

Supply Chain Shaman

Next Steps: Start to model demand based on market data to align the organization on baseline demand. Resist the temptation to place deeper analytics on top of existing data models. Instead, rethink the model and the approach. Out of desperation, they turned to the use of descriptive analytics. Next Steps.