This is the second episode of a two-part series on how AI is transforming best practices in supply chain risk management.
In the first episode of this series, we learned how AI and Generative AI turns the traditional cylinder-shaped data stream of supply chain risk issues into the shape of an hourglass, where AI-driven practices can create a pinch point in the middle that makes supply chain details far more manageable.
Craig Moss, Executive Vice President, Measurement at Ethisphere, and noted AI researcher Dave Ferrucci discuss how to use all of that data to inform and empower better supply chain analysis and decision-making by extrapolating data subsets across your entire supply chain.
3:57: Building trust & transparency into AI results7:27: Quality in, quality out14:16: Extrapolating residual risk subsets across the entire supply chain18:42: Communicating AI-driven updatesPREVIOUS EPISODE
How AI Helps Key Partners Manage Supply Chain Risk: https://youtu.be/Tf658Bc1tno?si=DUELjRmUKlMxUCDa
RELATED EPISODES
How to Prioritize Your Supply Chain Risk: https://www.youtube.com/watch?v=Suo7a_382mM
Understanding New Supply Chain Regulations: https://www.youtube.com/watch?v=crBWj6LaEIw&t=1s
Managing Due Diligence and Supply Chain Relationships: https://www.youtube.com/watch?v=jwlHBHuBLWw
Supply Chain Risk Management Solution: https://ethisphere.com/solutions/supply-chain-due-diligence/
Making Supply Chain Due Diligence Practical: https://ethisphere.com/making-supply-chain-due-diligence-practical/
Digital Supply Chain Institute: https://tinyurl.com/2nuskhms
Supply chain due diligence resources: https://ethisphere.com/resource-search/