Supply Chain Intelligence and AI for Manufacturers

“AI is not going to make the decisions for you. You’ve got to use all that help, model it out and really understand what’s going on.” — Mike Sibley, CPA, James Moore & Company

In this James Moore Live episode, Mike Sibley joins the conversation to break down what supply chain intelligence actually means for manufacturers, why traditional models are falling short and how AI fits into a responsible, structured approach to staying ahead.

Mike has spent significant time helping manufacturers build AI frameworks from the ground up. In this discussion he shares where most companies go wrong, why security and governance come before any tool and how AI can reduce costs without replacing the people who run your business.

Resources

• Manufacturing Industry | James Moore & Company
• Moore on Manufacturing Video Series
• Watch This Episode on YouTube

Full Transcript

[00:02] Host: Hi everyone and welcome to the James Moore channel. Today we are here with Mike Sibley. Hi Mike. How are you?

[00:07] Mike Sibley: Good. How are you?

[00:08] Host: Good. So today we’re talking about supply chain intelligence and how AI helps manufacturers stay ahead. The first question is, in your opinion, why are traditional supply chain models no longer enough in today’s market?

[00:20] Mike Sibley: I think information is moving really fast. Changes are happening really quickly, whether it’s because of geopolitical reasons or other costing issues. The easiest example is the conflict going on over in Iran and what’s happening to resin prices. Things are changing really fast. That means customer data is changing really fast, which means you have to be very nimble in your supply chain forecasting and analysis. That’s why it’s just not enough to do the same old same old with supply chain anymore.

[00:58] Host: Absolutely. What does supply chain intelligence actually mean in practice, not just as a buzzword?

[01:05] Mike Sibley: Intelligence, like anything, is having information and being able to act on that information. Supply chain intelligence is really understanding the downstream and upstream of what is happening. It’s using that information to plan properly for what you’re going to do. Manufacturers and distributors have all sorts of data and the biggest problem with data is it can be overwhelming. You get to the point of analysis paralysis. So what do you do with it? Maybe you don’t do anything with it, which can be very detrimental.

[01:53] Host: Absolutely. It can be very overwhelming for sure. Where is AI making the biggest impact right now? Is it forecasting, logistics, cost management?

[02:13] Mike Sibley: Manufacturers are still trying to figure that out. It’s one of the things we’re helping them do. I look at AI as having the biggest impact when you can insert it into your workflows. There are AI supply chain software options emerging. There are also tools like Claude and ChatGPT where you can build some of your own basic systems. But AI needs to be built into the workflows, which means you actually need to understand what your workflows are. Manufacturers are really good about having flowcharts for production, but what about the administrative side? Supply chain, finance, HR — understanding those workflows and inserting AI into them is where the real opportunity is.

[03:06] Host: Absolutely. How are leading manufacturers using AI to predict disruptions before they happen?

[03:13] Mike Sibley: It’s really about modeling. It’s important to understand what your customers are doing, what your market is doing, where it’s headed and why it’s headed that direction. Then use that information in your modeling, in your understanding of where the risks are, especially if you’re overseas or dealing with geopolitical factors. You can use AI to help take all this information and put it into something digestible, but AI is not going to make the decisions for you. People sometimes think, “AI did it, so it’s got to be right.” That’s not how it works right now. You’ve got to use all that help, model it out and really understand what’s going on to forecast your business.

[04:24] Host: Absolutely. What’s the biggest mistake companies make when trying to implement AI in their supply chain?

[04:33] Mike Sibley: I’ve built a framework for AI that I think about. You really have to start first and foremost with security and making sure your data is secure. Then you need a governance policy. How are you going to govern the use? Where can AI be used, where can it not be used? There’s a big risk that employees are throwing data into an unsecure version or connecting straight to data sources, which you may or may not want. A big mistake is not learning how to use it correctly and not putting it into your workflows. But an even bigger mistake is not looking at the overall infrastructure. Look at your AI framework first and then go from there down in.

[05:30] Host: Do you come across clients who are resistant to learning AI, who would rather keep doing things the traditional way?

[05:40] Mike Sibley: I think at first there was a sense of “I don’t understand it, so we’re not using it.” What you’re seeing now is a slow adoption. There’s really a lack of understanding, which is why we’re spending a lot of time training clients and companies on using it and where it can be used. But we always start with the framework side. The thing I want to caution more than anything else: don’t just sign up for an AI account on any platform and start throwing all your data into it. That’s not a good way to go. You can really open yourself up to releasing information that you don’t want released.

[06:16] Host: How do you balance AI-driven automation with human decision-making and expertise?

[06:30] Mike Sibley: Right now you have to look at AI as a tool. Think about Excel. We build all sorts of automations and models in Excel, but we check it. We make sure the information coming out of the model makes sense, because if you have a formula that’s wrong it can lead you to a wrong decision. The same thing applies to AI. It’s about learning how to put the right information in, how to prompt and then reading the output to make sure it makes sense. AI can help take a lot of information and boil it down really quickly. But at the end of the day, you have to use your experience and other data sources combined with that to make a decision. It’s a tool. Don’t use it as your sole advisor on how you’re going to manage and run your business.

[07:42] Host: Can AI actually help reduce costs in a meaningful way or is that just an overhyped notion?

[07:50] Mike Sibley: I think it can, and we’re really at the starting point of how it can help. Inserting AI into your workflows can be a huge source of opportunity cost savings. I’m a big fan of taking employees and upskilling them. For manufacturers who are trying to grow, you can possibly grow without adding employees, at least for a little longer. What AI can do is help reduce the amount of time spent on repeatable tasks. That means opening up more time for people to learn new skills and take on other tasks that are better suited to their abilities. Through attrition, some of the technology can reduce the need to hire new people. But I’m not saying go lay off a bunch of people and replace them with AI. It’s really about reducing manual repeatable tasks that will allow you to save costs over time.

[09:40] Host: If a manufacturer hasn’t started using AI yet, what’s the first step they should take today?

[09:50] Mike Sibley: Call us and we’ll help them. But in all reality, the first step is understanding. Go back to the framework: make sure you’ve got security and governance in place, and then training is a big part of that. You can dive in and start playing around with it, but training on the right utilization in the right ways matters a lot. It’s pretty easy to throw something into ChatGPT and assume the output is right, and then realize it has nothing to do with your business. I’ve seen people at manufacturers start taking data and throwing it into a personal ChatGPT account. You’ve just put private data into an open LLM. That’s why it’s important that companies get control of it, do the proper training and put security and governance around it first, then build from there.

[10:53] Host: Well, this was a great conversation today and I think it’s a really important one. People sometimes feel lost or overwhelmed and don’t know where to start. Mike, you’re a great resource for anyone looking to learn more or expand their business in these ways. Great talking to you today.

[11:08] Mike Sibley: Thank you. Thanks. Bye.

Start the Conversation With James Moore

If your manufacturing business is ready to think seriously about AI adoption, Mike Sibley and the team at James Moore & Company can help you build the right framework from the ground up. Contact a James Moore professional to get started.

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