[On-Demand Webinar] Getting started with artificial intelligence in supply chain planning

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Focus on a practical approach to implementing artificial intelligence (AI) and machine learning (ML) in your supply chain planning.

That’s the advice from industry-leading experts, as heard in our recent webinar, A pragmatic approach to getting started with artificial intelligence in supply chain planning, now available on-demand. Hosted by Robert Bowman from SupplyChainBrain, guest speakers Brian Tessier from Schneider Electric, Paul Cocuzzo from Merck and Trevor Miles from Kinaxis, discussed what you could do right now to take advantage of this trend. From finding a practical application that provides tangible value for your business, to ensuring you have the right organizational structure in place, Tessier and Cocuzzo provided real-world advice driven by their organization’s own quests to implement AI in supply chain planning. “Having AI take a world view based on best practices, and then applying it to your legacy data structures and business rules can give you insights into things you don’t even know are problems for you,” notes Tessier. “We found very quickly we had some very poor assumptions about lead times, both from suppliers and interplant shipments from within our supply chain. Given the number of transaction we do, the complexity of our product portfolio and the number of entities involved, there’s no way we would have found this any other way.” “You need to get out of the classroom and into the lab,” explains Cocuzzo. “You need to experiment as often as possible. Don’t be afraid to fail. You really need to get yourself out there practicing with these new capabilities, attempting some of these experiments with these new technologies. And you need to start to thinking about how you’re going to execute both on these experiments and for those experiments that are successful, how are you going to bring them forward?” Speaking on the required talent and organizational structure to implement AI, Miles added, “It’s about having the right combination of skills, because you do need to go and make those algorithms do stuff, but you must always know it in the context of the overall business objectives that you’re trying to achieve.” Interested in hearing more from these experts on how to implement AI and ML in your supply chain planning? Watch the complete on-demand webinar now.

 

Discussions

Ross George
- 2月 12, 2018 at 12:12午前
Artificial Intelligence in shipping and logistics has become a center-stage kind of focus within supply chain management over the years. Faster and more precise shipping reduces lead times & transportation expenses, adds elements of environmental friendly operations, lessens labour costs, & most important, widens the gap between competitors
Alexa Cheater
- 2月 12, 2018 at 10:39午前
Absolutely Ross! AI certainly has big implication on shipping, logistics and other aspects of supply chain execution. But I think it's important to note that while supply chain execution is getting most of the media attention these days (autonomous vehicles, drone delivery, warehousing robotics), there's still big benefits to be had by exploring AI and machine learning use cases in supply chain planning. There's some great work being done in that area.

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