How AI Helps the Front-Line Manufacturing Supervisor

[Transcript]

[00:00:00] Jan Griffiths: This is the Auto Supply Chain Champions Podcast. We are on a mission to bring you real conversations with the leaders who are transforming supply chains in the automotive sector. These leaders are true champions of manufacturing, and we're here to share their stories. I'm Jan Griffiths, your host and producer, and I'm joined by my co-host, Tom Roberts, Vice President of Strategic Industry Development at QAD.

[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.

[00:00:45] Jan Griffiths: Let's get into it. This podcast is powered by QAD RedZone.

[00:00:53] Hello, and welcome to another episode of the Auto Supply Chain Champions podcast. Let's check in with my co-host, Tom Roberts.

[00:01:00] Hey, Tom, how are you doing?

[00:01:02] Tom Roberts: Hi, Jan. We're on the tail end of the election. Again, it's not about love, it's not about hate, it's about comply with what comes out of our legislative body and our administrative body, and it's an exciting time.

[00:01:12] There's a lot that's facing automotive and we'll have to see how everything pans out over the next months and couple years

[00:01:18] Jan Griffiths: Yeah it is exciting. Today I'm in Frankfurt, Germany, and you know how sometimes you have an idea, Tom, and you work it out on the computer and you think, "This is great," and then the reality is something different?

[00:01:28] Tom Roberts: Yes, I do. We

[00:01:31] Jan Griffiths: So I created, not me. I don't have the skill. I'm working with an incredibly talented graphics designer who's created new slides for me for PowerPoint, 'cause I'm upping my PowerPoint game. And these things are so me. They're very strong, you know, red, bold, bold font. I'm doing a keynote tomorrow, so this is the first time I've seen them live behind me. Oh my gosh, these things are massive. It's like a massive head. It's very powerful and very impactful, and it's exactly what I wanted, but the reality of seeing them like that behind the keynote was quite alarming, and that just happened, so I'm still reeling from that a little bit. But anyway, yes, exciting times ahead.

[00:02:17] Now today, Tom, we talk about AI, and we talk about all these different processes and transformation and process re-engineering and all these different things. But today, we're gonna focus in on the manufacturing frontline because I often feel like the production supervisor is torn. They've got the shop floor pulling on them. They've got to produce product, and then they've got corporate coming at them with all these ideas and, you know, AI is kind of floating out there.

[00:02:53] Today, I could think of nobody better to get into this subject because he cares passionately about it, and he's in it every single day.

[00:03:02] And that's why I'm thrilled today that we bring back on the show Zack Sosebee, who is the SVP of customer success for RedZone. Zack, welcome back

[00:03:14] Zack Sosebee: Thank you, Jan.

[00:03:15] It's a pleasure to be here. Excited to talk some more about the front line this morning.

[00:03:19] Jan Griffiths: Tell us, Zack, what a frontline production super's feeling right now. What are you seeing out there? Tell us.

[00:03:25] Zack Sosebee: So production supervisors are near and dear to my heart. I've been one. Almost everybody at RedZone has been one. We've worked for production supervisors. We've been production supervisors. We've managed and led and grown production supervisors. And the one thing, you talk about elections and change, and change is inevitable.

[00:03:43] The one thing that never changes in manufacturing is front-line supervisors are very busy. They will always be very busy because the environment's constantly changing around them.

[00:03:52] My concern with front-line supervisors, they're the brightest, they're the best, they care the most, they work the hardest, but they only have so much bandwidth.

[00:04:00] And I remember thinking about as an operator, and a team of operators, how do we ensure that the supervisor magnifies the efforts of the team, supports the team, rather than accidentally becoming the black hole where ideas and opportunities and requests go to die because they're too busy? And so the brightest side of AI for me is I see an opportunity on the horizon where we actively give supervisors a better experience.

[00:04:32] We can decrease some of the workload and the pain, and we can make sure that nothing gets lost with the help of AI. So that's where I think, it's painful for the supervisors, but AI can actually show us a very bright future.

[00:04:45] Tom Roberts: Zack, how do you explain AI to somebody who's very skeptical? 'Cause I know that everybody on the manufacturing line is from the Show Me State, right? Everybody's from Missouri so they wanna see, "Hey, how is this gonna help me? How is it gonna make my day better? How is it gonna make me get quality product out the door on time?"

[00:05:02] How do you overcome the potential skepticism out there?

[00:05:05] Zack Sosebee: It's a great question, and I would start with what AI is today, where it's been, where it came from. And I live in a world, most of us at RedZone live in a world where we straddle between the manufacturing front line and the shop floor and desk work. At the end of the day, we still have Outlook calendars we're tied to.

[00:05:24] We still have Google Chats and Zooms and things where we're attached to our computer. We still make PowerPoints. We do presentations and documents. And you think about where AI fits today, it's a tool to reduce complexity and simplify repetitive tasks so that a human, one of us, can get more done than we normally get done.

[00:05:46] As a desk worker, it's easy. All my notes are recorded. All my meetings are recorded. I've got notes everywhere. I've got action items that it tracks. My emails, I get prompted. If I have an email that gets buried I forget about, it comes back to the top. It reminds me. Claude can do the analysis for me, so instead of me spending hours somewhere, I can actually have an analysis done in minutes and spend my time on driving the behavior, driving the results.

[00:06:08] So as a leader at a desk, it's very easy to see. And the people that develop AI work around a desk, so naturally it makes sense that that's fixed first. Now, where I see skepticism in the front line is if you're not sitting at a computer doing computer things where AI can recreate your workflows, how's AI gonna put things in a box? How's AI gonna put things from this section of the production line and tool it and fit it in that section?

[00:06:35] I mean, there's a point, tom, where we'll have robots that can do some of that, but that's kind of off in the future. So I think, it's important that the front line and manufacturing leaders recognize that although there's a gap between AI making desk workers' life amazing today and AI robotics revolutionizing the front line in ten years, there's a lot between now and then.

[00:07:01] There's a very healthy bridge, and we do need to take advantage of it. My examples there would be AI does very well when there's context. If the AI has the contextual data and the maps of what's going on and can understand, number one, it never forgets. It can remember things forever. It's got all the history.

[00:07:21] It knows how people perform individually. It's got context from individuals and how they react and what their roles are in the factory. With the right context, things don't get forgotten, analysis can be done at your fingertips, and we can make people's jobs more effective so that the routine, mundane things don't have to be done over and over.

[00:07:41] So as I think about RedZone, for example. So one of the most powerful things for me that we've done in championing AI in RedZone is we help people do huddles and daily meetings to drive behaviors on the floor where the front line, the maintenance, the leadership, they look at what's happened on the production line, they look at what's coming up, and they make play calls to run the line more effectively, to get ready for a changeover, to handle a supplier issue, whatever it might be.

[00:08:07] And doing that on an iPad is kinda cool, 'cause better than not doing it all. But typing, really annoying.

[00:08:16] So how do we record the voice, transcribe the data? The AI actually recommends play calls and says, "Based on what's going on around you, here's something we think you can do better." And this is important to me because we're trying our best to get the operators to actually lead these huddles, and so when the operator leads the huddle, there are environments where they've not been empowered to drive actions.

[00:08:41] They might actually feel awkward to say, "I'm gonna give my maintenance supervisor an action. I'm gonna give my PC, my procurement guy, an action. Well, I'm just the hourly operator. Is that okay for me to-"

[00:08:55] Tom Roberts: Who am I? Who am I to be doing that kind of thing?

[00:08:57] Zack Sosebee: Yeah, I might get in trouble. Like, I'm not the boss. And so this idea of making a play call that's actionable sometimes is a little bit unnatural for the front lines.

[00:09:07] And so having the agent recommend something that will help so that someone doesn't have to push themselves to write something pre-typed out, you can make minor edits and go. It makes the meetings more effective, faster, and action-focused, which what we want to drive cultural change, behavioral change, and change the course of the shift real time in the shift so that we get better every day instead of looking back tomorrow and thinking, "Well, what could we have done differently had we known?"

[00:09:36] Well, now we know. And so that's where I can see AI starting to make a bigger impact. And so I'm starting to ask, how do we get more context? How do we get more context? For example, today in the RedZone line log, we capture a lot of information where, frontline workers and leaders within the shift share pictures of things happening on the shop floor, pictures of equipment set up and, vendor challenges, and they highlight their play calls, but they also recognize people when they do well.

[00:10:03] Well, this helps really nicely hand over to the second shift. So, your off shift comes in, and they've got all the history right there. And so, what we found for years is the people that make it a point to hand off and huddle between the two shifts, do a good job because the context is shared, or the people that make it a point to go and read what's there, they do a good job even if they don't huddle.

[00:10:26] But that doesn't represent a hundred percent of manufacturing. So now in a world where even if you don't have the time, even if you get busy, even if your environment doesn't allow for proper shift handover, the context is there, the recommendations are there, and the agent is acting proactively in the background to suggest things to the operator and help them be more effective, and that's where I get very excited.

[00:10:49] 'Cause now, at RedZone, we're big into coaching, right? We bring this coach to drive culture change and help people think differently and say, "Hey, if I've got two red hours in a row, what should we do? It's time to take a step back and look." But maybe my coach can't be there at four AM when they were already there from six AM to seven PM.

[00:11:09] Who's gonna coach at four AM? Well, we're building Champion AI, Tom and Jan, to have a built-in coach that is always driving, always improving, and my coaching team, they're the ones that are building this thing, and they're tuning it so that, it doesn't drive people crazy.

[00:11:27] I don't know if you guys remember Microsoft Clippy, one of the first agentic solutions. Was that not the most annoying thing ever built?

[00:11:37] And our goal in AI is to say, how do we coach this person without becoming the boy who cried wolf, without driving them absolutely batty, without Clippy being so annoying that people drag it off their screen and say never come back?

[00:11:52] And that's an important thing. So now, now we're in this world where we're balancing getting the context, driving action, but in a way that's sustainable and helpful and not, irritable for an operator.

[00:12:04] Tom Roberts: It's got to be perfectly distilled at the right level, so you're serving enough information but not too much to overwhelm. It's an incredible balance that has to be achieved.

[00:12:12] Jan Griffiths: I'm beyond excited right now listening to this conversation, and let me tell you why. So I'm going back to my days in manufacturing, right? And , we talk about, oh, empower your people, push decision-making to the front line. Uh-huh. Well, that's easier said than done. But if you think about it, just like you said, Zack, from an operator perspective, right?

[00:12:32] So let's say I'm an operator, I've been working there six months. I kinda know what I'm doing, but, you know, maybe I'm young. I certainly don't feel like I could challenge the purchasing manager in the plant, right? Or the buyer.

[00:12:44] Zack Sosebee: Sure

[00:12:44] Jan Griffiths: But in a way, and I haven't fully thought this out yet, so this is just gonna come out of my head, so bear with me. They can almost hide behind it, but I don't mean that in a negative sense. mean that the AI, just like you described, can take that awkwardness out of the conversation. So they have their huddle. AI suggests to them that you need to either contact the buyer and tell them to get more of this part or replace this component, or you need to get ahold of quality and do something, right? The operator, 'cause there's gotta be a human in the loop, the operator goes, "Yeah, I, quality, that's who needs to address this." They could press a button or just say something, and it automatically sends an alert to the supplier quality engineer.

[00:13:33] No human has to feel awkward or uncomfortable, and I don't wanna take that growth opportunity away from the operator. But if they do that a couple of times, and then all of a sudden in about 10 minutes or so, the supplier quality engineer shows up next to the operator and says, "Okay, what do you need? I got the message. Show me. Show me the part so that I I can do the thing and take the action." That has now sped up the process and is starting to build the relationship, and it's showing that the supplier quality engineer is actually a support function to the operator, and the operator really is calling the shots.

[00:14:08] I realize that that was a long explanation of what's in my head, but I can see that working on the shop floor and what a benefit that could be. And it's so simple, Zack. It is pure gold.

[00:14:22] Zack Sosebee: Well, it's funny that you say this. You remind me of something that Ron, our RedZone engineering leader says. He talks about RedZone being very unique at the edges and making decisions at the edge where the systems might not exist and how the decisions happen. And one of the things that I'm really passionate about was that we look at champion AI and AI for manufacturing, is there are always decisions at the edge, and they cross over from department to department, and it's actually an opportunity to do less siloing and more cross-functional communication, 'cause the AI can help bridge the gap so the departments don't get disconnected.

[00:15:00] And so that's something I'm very passionate about. You mentioned the frontline being empowered and, it's the right thing to do, and it's nice words, and we all say it, and we all believe in it, but it's so hard to make it happen. And I think as I think about the overloaded supervisor, back to the initial question, and I think about the under-empowered operator of today's manufacturing world, I mean, remember, these operators, they raise children. They fix their own cars.

[00:15:31] They're pretty talented individuals. These guys are important members of society. They're not low-priced labor, and we've got it wrong sometimes when we look at like, "Let's not let them make decisions." They should make all the decisions. And so in a world where the AI is bringing the data to them, bringing the context to them, and helping the decision be a very well-thought decision, not just through the close lens of the operator, but through the context across the production line, now we're actively giving operators more decision-making criteria and better context so they make better decisions.

[00:16:03] And watching the result, by the way, in case something goes wrong. The AI's always watching this and in the loop. Now, we're actively taking work off of the supervisor by doing this. This is real things that would normally bubble up to their level that opens them up. So now we've got a supervisor starting to lose a little bit of the minute responsibilities they probably shouldn't be handling in the first place.

[00:16:26] The next thing we do, we want the supervisors to drive improvement. They're business owners. As far as I'm concerned, that's a business unit leader, and their goal is to maximize the throughput while growing employees, growing technicality, and making sure the customer gets a perfect product every time.

[00:16:42] And so the way they do that is by challenging their process and improving their process, and you have to look at data, and you have to look at success rates and completion times and efficiencies. And what does that mean? Do we send our supervisors back to a cubicle to sit and analyze data? That's a terrible idea.

[00:17:00] We don't wanna do that. So what if AI for the supervisor now generates reports on command at their fingertips? They don't need to be Tableau or Power BI or whatever experts. They need to say, "Hey, Agent, can you show me the three things that are holding my line back and help me figure out how to solve them?"

[00:17:20] We actually just released this this month. We're calling it Generative Analytics, but we're debating what the term is. But the concept is at your fingertips, you ask for a report, and your data analyst within the Champion spits out the report, and you get work done.

[00:17:32] One of the things that bothers me about my team, Tom and Jan, is all the time the customers want analysis, and they're always tempted to go into analysis paralysis.

[00:17:43] And it's like, "Hey, can your coach, instead of driving behavioral change and coaching my team to do things differently, can they build me a report?" And I'm like, "What are you gonna do with the report?"

[00:17:53] So it drives me crazy. And we do it, and we help them because it's the right thing to do, but we try to balance this thing between, is the coach a report builder or is the coach a behavior change?

[00:18:03] And so I'm so excited to have data analysts built into Champion so it can build the reports, and humans can focus on driving cultural behavior and challenging the norms and getting processes stronger, which is really what we want out of those roles.

[00:18:19] So I think you have the bright opportunity.

[00:18:21] Tom Roberts: Absolutely. I think we have an example of a customer that did some sleuthing around some of the issues that they had.

[00:18:27] I think, Jan, we can probably attach that in the

[00:18:29] Jan Griffiths: Oh, that'd be great. Yeah, good, examples are always great. And you know what? I just had a thought, Tom. I think we should go visit, a company that's really, that's making this work, you and I, and let's do a live podcast, and let's see it. I mean, I realize I just threw this out on a podcast, but I think wouldn't that be more powerful?

[00:18:52] Don't you think so, Zack?

[00:18:55] Zack Sosebee: I think so. And I've got, I've got two real examples. I can help you. I've got three or four customers that would be just great. They'd love to host you, and, they're deep into this. Their AI is becoming one of their key strategies for the front line. But you remind me of a couple stories, Tom.

[00:19:07] This isn't just ideas. This is actually working. And the first story I'll tell you is actually from months ago. It's from one of our earliest releases of Champion AI. One of our customers was looking to find out the driver cause for downtime on one of their lines and how to fix it.

[00:19:26] And the AI did the analysis and spit out something about web failures. I don't know the-- you can see it on the video. But it actually crossed a few different things, cross-referenced, and came back with a solution that wasn't ever even mentioned. It's not even a downtime code. It doesn't exist. But it saw the communications and chats and saw the feedback underneath action items associated with that line, tied it together, and the recommendation actually helped their line and got them back running, which was incredible.

[00:19:53] The other example, again, this is a case where I feel very deterministic, and for those of you listening to podcasts and don't know probabilistic versus deterministic, the way we've coded for hundreds of years is very deterministic. You want a solution, you program a thing that if this happens, then that happens.

[00:20:11] Our programming, what we design builds the solution. And I'm trying to unwind myself these days to do a better job being probabilistic and help give an agentic capability, the ability to look and find solutions rather than assuming that I know everything, because the agent's got more knowledge and confidence than I have and more context.

[00:20:31] And so the big, the big thing that we've seen across customers, there's one specific one. One of the customers was running-- it was starting a changeover, and in the Game Ready, we have an agent that helps people game ready. The Game Ready said, "The last time you ran this product, you reversed the two parts on the line. Make sure you don't do that again."

[00:20:53] And they had already set up the line in reverse and were about to run it the wrong way. And it knew that from the line log chats. There was no downtime associated. It was nothing deterministic. It was just understanding the context and seeing the comments from the last time, like a week ago when the product had run.

[00:21:09] They had stopped the line and adjusted things and had to reset and put a massive quality hold on. And this kept them from making that same mistake again, which was really cool to see. And, it's not unique to that customer. The context, the comments are everywhere. And so, one of our big investments in the future of Champion is how do we get more context?

[00:21:29] How do we bring in more audio, more communication? How does video bring in context and give more capability so that the decisions and the recommendations are grounded and further and wider? So that's kind of where we're headed with this.

[00:21:43] Pretty exciting.

[00:21:44] Tom Roberts: I can tell you, after many years in IT, and supporting every level of employee, literally top to bottom. We were always looking for the dispassionate transfer of information about what the situation was.

[00:22:01] Let me give you an example. If somebody calls on the help desk and says, "The system's running slow," well, that doesn't necessarily give us a lot to

[00:22:09] to go on to figure out what's going on.

[00:22:12] Is it a specific report? Is it month-end and you're running some kind of consolidation at the end? Or is it backflush is slow because of something? It's that very specific dispassionate delivery of information that we're looking for with specifics, and I think that that is something that AI helps the certainly in the frontline, and others deliver that information in that context that you're talking about, in a manner that's distilled, in a manner that is factual and says, "Hey, here is what's going on. This is what happened the last time that you had this particular event. We suggest that you open a work order. Here's how you open the work order. Here's what it might look like and who you might assign it to." It's very specific on outcomes and, reacting to specific problems. And that's, I think it's a key about empowering people is giving them that avenue to deliver that message that way.

[00:23:02] Jan Griffiths: It absolutely is. And thank you, Zack. You know, we love having you on the show because you really keep it real.

[00:23:09] You're right out there at the front lines day in and day out, and we love that. And I know that you're extremely passionate about what you do, but that's not the only thing that you're passionate about, now is it?

[00:23:19] Let's go into your personal life and tell us what else are you passionate about?

[00:23:24] Zack Sosebee: Well, thank you, Jan. Just this morning before this show actually, I was with a group of high school students, and we were doing a financial literacy course. I'm a board member of the local bank that we started a few years ago, and we wanted to give back to the community, so we created a five-week-long course focused on financial literacy for high school students.

[00:23:41] All the things that I think we all wish we'd had, back in the day before we learned the hard way after graduating. And so we're teaching these guys about checking versus savings. We're teaching them how to open accounts. Credit cards, the dangers, the risks, the minimum payment risks of credit cards.

[00:23:57] We're teaching them about healthy loans. How to get loans, how it works? What they look at.? Mortgages, car payments. We teach them how to budget. And then we teach them about investments. And one of the last classes we have actually is how taxes work and when you get a paycheck, this is what payroll withholding looks like.

[00:24:14] When you do your taxes at the end of the year, here's why you, yeah, you might pay more or less. And so, I think some of the kids fall asleep because it is high school and eight AM. But many of them are very engaged, and they're trying to learn because they, they know they're just about to have to go figure out college and a car and start saving and budgets.

[00:24:32] And, we had a big day today where the local college president was there some of our local community folks were involved. The president of our bank was there. And they all spent a few minutes telling the kids how important their roles are in life, how they're the next generation and empowering them with driving the important change in our world.

[00:24:51] So it was a really cool thing and again, I'm happy to get involved and, spend my time where it makes a difference in the world.

[00:24:57] Jan Griffiths: There it is. Zack Sosby, not only are you keeping it real in the world of manufacturing, but you're making it real for those high school kids.

[00:25:06] Thank you so much for joining us.

[00:25:08] Tom Roberts: Absolutely.

[00:25:09] Zack Sosebee: Thank you, guys.

[00:25:10] Tom Roberts: Thank you.

[00:25:11] Jan Griffiths: We wanna hear from you, our listener. Tell us what are your challenges right now? What conversations do you want to hear across the airwaves on this podcast? Drop us a comment on our podcast website.

[00:25:27] The link is in the show notes.