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Supply Chain Now

Utilizing AI/ML in your supply chain in 90 days - NO EXCUSES!

Nov 22, 2023
Jerry Collins and Todd Kovi discuss the importance of understanding and effectively utilizing AI in supply chains. They emphasize stakeholder involvement and the necessity of quality data, problem identification, and a dynamic approach for successful implementation. The speakers address challenges such as dirty data, unrealistic expectations, and the human-technology paradox in adopting AI solutions.
53:41

Podcast summary created with Snipd AI

Quick takeaways

  • Clear problem identification and measurable performance metrics are crucial for successful AI and ML implementation.
  • Realistic expectations and targeted use of AI and ML can maximize their potential benefits while mitigating risks.

Deep dives

Clear problem identification is crucial for successful implementation

One of the key benchmarks for successful AI and ML implementation is clear problem identification. It is important to understand what problem you are trying to solve and have measurable performance metrics in place. Quality data is also essential, as well as continually auditing the data to ensure accuracy. Additionally, it is important to remember that one size does not fit all, and solutions may need to be adjusted and improved over time.

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