Automotive leaders spent Q3 waiting on things that won't show up on schedule: clean data, stable supply, and a version of AI that's easy enough to adopt without effort. Meanwhile, black swan events keep coming, and competitors keep moving.

In this Q3 review, host Jan and co-host Tom Roberts, Vice President of Strategic Industry Development at QAD, look back at the quarter's conversations through three themes (data, resilience, and leadership) and set the agenda for Q4 and 2027.

Perfect data hasn't arrived in their lifetime, and it isn't coming soon. Tom points out that AI can already suggest commodity code cross-references and help clean records. But without process discipline and poka-yokes at the point of entry, the first person to enter something sends it off the rails. The companies taking steps now will pull ahead of the ones waiting for everything to come together.

That takes real AI fluency at the top. Jan is two sessions into an AI boot camp, and she points to GM's Sean Gaskin, who recently finished a professional certificate in AI and machine learning through Michigan Engineering. His lesson: leaders need enough depth to know what's possible, where it creates value, and what it takes to scale.

On resilience, GM's $4.5 billion parts inventory arrangement with Procura Auto Parts shows that just-in-time is no longer the answer to everything. Jan challenges purchasing to weigh the total acquisition cost against the purchase price variance. Tom puts the stakes plainly: in a fight for market share, no OEM can afford for a supplier to shut down a line.

The episode closes with two assignments. Pick one process, RFQ or otherwise, and cut its cycle time by 50%. Then study your supplier and item masters before the next data project starts. The leaders who begin this quarter won't need perfect conditions to outpace the ones still waiting for them.

Themes Discussed in This Episode

• Why waiting for perfect data stalls progress
• AI fluency as a leadership requirement
• Proof over promise in AI adoption
• Classroom data vs real-world data
• Rethinking just-in-time for resilience
• Total acquisition cost over purchase price variance
• Decision speed and alignment
• Master data governance

This podcast is powered by QAD RedZone.

About Your Hosts

Jan Griffiths

Jan is the host and producer of the Auto Supply Chain Champions Podcast and The Automotive Leaders Podcast. A former automotive manufacturing and supply chain executive, Jan is recognized as a Champion for Culture Change in the automotive industry. She brings direct, grounded conversations to leaders navigating execution, disruption, and transformation across the global automotive ecosystem.

Tom Roberts (Co-host)

Tom is Co-host of the Auto Supply Chain Champions Podcast and Vice President of Strategic Industry Development at QAD. He works closely with automotive and industrial manufacturers to close the gap between insight and execution, helping leaders move from visibility to systems of action that drive real operational outcomes.

Mentioned in the Episode:

• Q3 guests: Josh and Ian on USMCA and trade compliance, Ambrose Conroy (Seraph), Ted Mabley (UHY), Cheryl Thompson, and Mia and Daniel from Wayne State
• ISM leadership event, December 2, Detroit, with Isiah Thomas and Shilpan Amin

Episode Highlights

[00:04:06] Perfect data isn't coming: Jan warns against putting AI on hold until the data is cleaned up, because that day may never arrive.

[00:05:28] Clean it, then protect it: Tom explains why any data cleanup fails without disciplined processes going forward.

[00:08:01] Leaders need AI depth: Jan argues that executives don't need to code, but they do need to understand what AI can do in their business.

[00:10:26] Automate the month-end close first: Tom cuts through the AI hype and focuses on what's live and working in manufacturing today.

[00:13:13] Rethinking just-in-time: GM's $4.5 billion parts move signals a shift from pure inventory reduction toward resilience.

[00:16:43] Line up behind the decision: Tom describes the speed he saw at a Chinese automotive supplier once a decision was made.

[00:17:37] Cut one process by 50%: Jan and Tom give listeners concrete calls to action on process speed and data.

Top Quotes

[00:04:06] Jan Griffiths: "But what I find interesting from a leadership perspective, as leaders look at data, we are never gonna have perfect data."

[00:16:05] Tom Roberts: "There's not a single OEM, especially in the West right now, that wants to give up one micro percentage of market share because this is a bare-knuckle brawl for market share."

[00:18:14] Jan Griffiths: "Just start somewhere. It might be the internal RFQ process, the external one. Just take something. Do something. Start somewhere."

If this episode resonated, share it with a fellow automotive leader and subscribe to the Auto Supply Chain Champions Podcast, where we're closing the gap between insight and action across the global automotive supply chain.

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[Transcript]

[00:00:30] Tom Roberts: Great to be here, Jan. What I see every day is simple: manufacturers don't have a data problem, they've got an execution problem. This show is about how artificial intelligence, systems of action, and empowered teams can help close that gap.

[00:00:53] Hello and welcome to the Auto Supply Chain Champions podcast. This is our Q3 review episode.

[00:01:04] Tom Roberts: Hi, Jan. Lots of great things going on. We had Champions of Manufacturing in Chicago. We've got Champions of Manufacturing Munich coming up. Great event in Chicago. it's getting bigger every year. We had Scottie Pippen as a special guest, interviewee with Sanjay, and he's a Hall of Famer, great player.

[00:01:45] Jan Griffiths: There is a lot that we can learn from high-performance athletes about leadership and teams and coaching. When you start to view leadership Through the lens of being a coach instead of the person that's just telling people what to do, it's a totally different experience. And it's funny you mention basketball, and you know I'm not a sports fan of any sports whatsoever, but I remember when I first came to this country, to Michigan, actually, I came to Indiana first and then to Michigan, and Isiah Thomas was always in the news.

[00:02:44] Tom Roberts: That's awesome. Awesome opportunity to interview Isaiah. I can remember being a high school student and my friends and I would take those, the $4 Elias Brothers tickets and go to the Silver Dome. They were still playing at the Silver Dome, and I got to see Isaiah a few times.

[00:03:06] Now, Tom, there are three themes are predominant in Q3, and that is data, I don't think that's ever gonna go away. Data, resilience, and leadership.

[00:03:25] Tom Roberts: Well, it's funny that data always comes up because it's affecting each of these particular process areas or compliance areas. We had Josh and Ian back on in July, and whenever we're talking about USMCA or we're talking about tariffs and trade compliance, you have to have great data.

[00:04:06] Jan Griffiths: But what I find interesting from a leadership perspective, as leaders look at data, we are never gonna have perfect data.

[00:04:19] Tom Roberts: Right.

[00:04:39] What do you say to those leaders, Tom?

[00:05:10] Can AI look at probabilities, look at old data, look at some old pieces of information and make suggestions about what the commodity code cross-reference should look like? It can, but you've gotta create somewhat of a foundation for it.

[00:05:54] You're right. All that come together at companies with thirty thousand employees, seventy thousand employees, twenty plants, fifty plants? I don't know if that'll ever happen until, until it's all truly automated. But I think it's worth the fight and it's worth, at least understanding the state of your data, and I think a lot of companies don't even understand that they have...

[00:06:27] Jan Griffiths: Yeah, I agree, but it's a little uncomfortable from a leadership perspective to start to execute projects with AI, when AI is using data that's not perfect.

[00:06:45] You've got to start somewhere. We can't wait.

[00:07:08] Because you have to have some creativity to prompt properly, to really get what you want, or you have to prompt the system to write the prompt for you, and you've gotta be good at that. So I think that people who are advancing their knowledge to understand these basics as we move along this linear flow. Well, it's probably not very linear, but, as we move along in this, I think the people who are advancing their knowledge, they're gonna have a huge advantage over the people who are just like, "Yeah, I'll just kind of wait until it's all coalesced together and it's all great and we can move on."

[00:07:43] Jan Griffiths: I agree, and there's different levels of understanding of AI. And I think that, most of us have played around with ChatGPT or Claude, and I thought I was doing great when I could figure out how to do a Claude project and co-work and all this stuff.

[00:08:06] Tom Roberts: Oh, nice

[00:08:34] Tom Roberts: Absolutely.

[00:08:50] And he just posted that he completed the professional certificate in AI and machine learning through Michigan Engineering, which I think is a very, very intense course that he put himself through. And this is what he said, his biggest takeaway: "AI leadership requires more than understanding the concepts. You need enough depth to know what's possible, where it creates value, and what it takes to scale." And I thought, "You know what? You're absolutely right."

[00:09:37] Tom Roberts: Right? And it's one thing to just kind of use it and, it's like going to play basketball or something. You go, you play, there's only certain movements that you're gonna make during a game. But if you don't practice, if you don't take the 100 free throws, and you don't take the 500 three-pointers and all those kinds of things, you don't put in that kind of work, you're not going to really get as good at it as you could.

[00:10:07] Jan Griffiths: Yeah, real world application is everything, right? And, I like, what Sanjay talks about, proof over promise.

[00:10:25] Jan Griffiths: Yeah

[00:10:43] It's like, well, if you think AI is very close to ending the world, can you maybe help me automate my month-end close?

[00:10:51] Tom Roberts: Before we go destroy the world, help me do a little bit better with some of my inbound demand signals from an OEM. And I think that creates some of this dissonance out there.

[00:11:12] And that means more than kind of these atmospheric claims or these high-level things that people are claiming out there that aren't really bringing advancement to their daily lives.

[00:11:57] Tom Roberts: Yeah. Or they have to find it, period. Somebody might give them some action to perform and they're like, "I don't even know where to ask for the data." And they're like, "Well, ask Jimmy over in engineering. He might know somebody." There's that whole step of even finding out what the sources are, and then finding out there's 20 of them and nobody ever talked to each other.

[00:12:33] Jan Griffiths: And then you gotta convince people to give you what you need, and that's a whole skill set in itself too. So I think we got a lot to do bridging the gap between the world of academia and the real world, knowing how fast the real world is changing today. Yeah, no, I think it's really fascinating. Well, that's data.

[00:13:13] Tom Roberts: We are. And Jan, whenever we're talking about resilience in supply chain, I wrote that blog not long ago, the LinkedIn post about the death of JIT, and what predicated that was General Motors took steps to stockpile four and a half billion dollars of specially needed parts with Procura in Asia to hedge against these black swan events.

[00:13:55] But it acknowledges, "Hey, you know what? We just gotta do something to make sure that our supply chain is resilient, that we are storing parts if we need to, and that we have that insurance against these black swan events." I mean, you see things happening in the Strait of Hormuz still.

[00:14:35] Is it alternative sourcing? Is it some safety stock? What is the approach that we need to take? Very important.

[00:15:01] Maybe. But is it the driving force for everything? Is having inventory in key strategic places now no more important to support a resilience strategy than just blindly following inventory reduction last, to the letter of the law? And the same is true for cost reduction, and I think Ambrose talked about this when he was on. Purchasing has been so driven towards purchase price variance, lowest product cost, are we now going to have to look at, truly look at, total acquisition cost and look at it through the lens of a more resilient supply chain rather than just pure cost? These are big leadership questions that have to be asked and answered.

[00:16:05] There's not a single OEM, especially in the West right now, that wants to give up one micro percentage of market share because this is a bare-knuckle brawl for market share. And if you have a supplier shut you down. If you can't meet a certain, delivery quantity where customers want to buy a particular vehicle, it's an awful situation. And there's gotta be planning to help insulate against that.

[00:16:43] Tom Roberts: Yeah, I mean, speed is key, and that's speed of movement, speed of decision-making. I had some experience at a Chinese automotive supplier. I think it was an awesome experience. What I noticed is if the decision wasn't made quickly, the follow-up was very quickly and everybody aligned to move forward.

[00:17:21] If we're always, sitting on the edge and, throwing rocks in at things, there might be some very valuable rocks being thrown, but in the end, people have to line up behind those decisions and move very, very quickly.

[00:17:36] Tom Roberts: or they'll be left behind.

[00:17:48] There's a lot going on in the world right now. We know this. Just take one process. One, whether it's the RFQ process, where we interviewed Ted Mabley on from UHY. Whatever it is, it doesn't have to be a big complicated process, but take an action to reduce the time that it takes to make that decision or produce that output. Reduce it by 50%.

[00:18:28] Tom Roberts: Yeah, I would say number one, understand your data. So you may have some anecdotal thoughts that, wow, this is really not a good situation with our data. But actually dig into a little bit of the dimensionality of the data and understand.

[00:18:57] And when you can buy in scale, you can get a better price and, all those good things. It's just simple concepts. But if you don't understand the data, if you don't understand the nature of what you're doing, then you can't get those advantages. So I would say number one, just understand your data.

[00:19:24] If you're gonna add a new, say that you're gonna add a new account to the chart of accounts, well, it goes through a team that asks why. Why do you need this? Why do you need this different dimensionality? Why do you need this, whatever. And ask those questions rather than kinda create them pell-mell.

[00:19:43] Jan Griffiths: Yeah

[00:19:53] Jan Griffiths: Great advice. Well, we're gonna keep bringing content to you, our listeners. If there's something specific or somebody that you wanna hear from, please let us know. You can reach out to either Tom or myself directly. We are here to provide content for you to help you on your journey into the future as we transform our beloved automotive industry.

[00:20:19] Tom Roberts: Thanks, Jan.

[00:20:36] The link is in the show notes.