Welcome And Returning Guests

Intro & Outro 0:00

Welcome to Tennessee on Supply Chain Management, where we unpack the drivers shaping today's global supply chains. From innovative ideas to real-world solutions, each episode brings you insights from the leaders charting the course for our discipline. Now here are your hosts.

Ted Stank 0:19

Welcome everyone to the next episode of Tennessee on Supply Chain Management. I'm Ted Stank here with my co-host and great friend Thomas Goldsby. This is season four, episode nine of Tennessee on Supply Chain Management. Hardly seems like we've been doing it that long, Tom. How are you doing?

Tom Goldsby 0:38

I'm doing well, Ted. You know, I and I think by episode count, I think we're about like 60 episodes in. Can you believe that? No, I can't. I haven't been pulled off the air yet. And you see me kind of looking out my window, Ted. It feels like we are reporting, or I am anyway, from Rocky Top, Tennessee, which uh is in the tropics. I mean, we just had a downpour, which is pretty routine around here these days. So a hot, steamy, rainy day here in Knoxville, Tennessee, but doing well.

Ted Stank 1:07

Yeah, no, I've been over on the coast all summer in North Carolina, and I keep getting these updates on my phone from Knoxville saying like heavy thunderstorms and flood watch and everything. So I don't know if I'm coming back, man.

Tom Goldsby 1:20

Not until you finish that arc, anyway, to get that thing going. But it does mean that summer's coming to a fast close here. We're about four weeks out from go time when we welcome all those students back to Rocky Top, getting very excited about that, of course. But hey, we're not quite there yet. Still time to get things together before they arrive.

Ted Stank 1:40

Yeah. Well, Tom, we have a couple of great guests here with us. Actually, returning guests, didn't you say March of 2025? They were with us. We've got Jason Murray, co-founder and CEO of Shippiem, and Thomas Deakins, who's VP of Industry Growth with Shipium, but he looks and sounds an awful lot like a guy named Thomas Deacons that was previously our executive director of the Global Supply Chain Institute and continues to be an adjunct faculty member of UTSCM. Jason and Thomas, welcome back. Great to have you both.

Tom Goldsby 2:14

Yeah, thanks for having us. Yeah, so return guests, and yeah, that Deacons guy does look familiar. This is my third time on the podcast, so I'm so excited.

Ted Stank 2:24

Well, you've hosted once before, too, haven't you?

Thomas Deakins 2:26

No, but I was on with Alex Scott one time. So we were talking about the initiative that we were working on. So great to be back. Thank you.

Ted Stank 2:33

Great to have you both. And you know, March of 2025, the topic was AI. That topic has largely gone away. And so we're gonna have to create some new topics to talk to you guys about, right?

Tom Goldsby 2:45

Well, I'm excited to hear what's happening in that world and what Shipium's been up to in the almost year and a half since we last had Jason and Thomas on the program. But hey, there's a lot of action in the supply chain world these days, and so why don't we kind of pick up on some of those news items and welcome Thomas and Jason to comment as well. Apparently,

Tariffs Return Ahead Of USMCA

Tom Goldsby 3:07

we're uh going to uh be uh revisiting tariffs again. This was supposed to be the summer of the USMCA renegotiation, and we knew that there were gonna be some daggers thrown, some posturing before any real news of those renegotiations. And it seems as though just a few days ago, the administration said, Canada, you're up first, 50% tariffs on select items, including hockey sticks. Ooh, that's a shot.

Ted Stank 3:37

You're gonna throw daggers, you know those bars that are out now, the axe throwing bars. This was an axe throwing at Canada 50. The 10% across the board tariffs expire on Friday as well. And we are promised a whole new tariff regime again, starting, as you said, Tom, with uh 50% on several products coming out of Canada.

Tom Goldsby 3:58

Yeah, as I understand, it's really only about 5% of the merchandise that flows southbound from Canada into U.S. But, you know, like I said, the hockey gear is is kind of a pointed one. You know, I guess we're not gonna touch some of the precious raw materials and energy that we rely on to come out of there. But, you know, again, I think this is you know some posturing heading into USMCA negotiations. What do you think?

Ted Stank 4:23

Yeah, uh yeah, I definitely think that there's gonna be a lot of axes thrown in the next few weeks. I know Mexico has thrown some of their own at us recently about some geopolitical issues, and I think that's probably some posturing as well heading into this negotiation.

Oil Prices And Energy Volatility

Ted Stank 4:38

Of course, Tom, you bring up energy. Energy is top of mind for everyone. Uh recently, barrel of crude went back above $90. The whole Iran-U.S. ceasefire uh didn't last very long. And while there was some oil flowing out of the Gulf, it's no longer flowing. Not really any uh clear insight on what's gonna happen with that whole situation. And so we're gonna look for some fluctuations in priced oil and energy. And by the way, we're almost to August. A couple of months from now, places like Northern Europe start getting cold and start thinking about heating energy for the winter, and so it's gonna become more acute, I think, as as we go into the next several weeks.

Tom Goldsby 5:21

Yeah, you know, I've called it out on many occasions before on this podcast as an economist in training. You know, I go back to supply and demand, and as far as I can tell, you know, we continue to consume about as much oil and gas as we ever have, maybe even more. But meanwhile, supply is challenged, right? I mean, when you basically take 20% of the world's supply off the table, I just don't know how, aside from draining down those strategic reserves, which are happening stateside and and around the world, but it it seems like that final variable price has to come into play eventually. And I know there's a lot of speculation between supply and demand and and what we pay at the gas pump, but I'm not at all surprised that we're back above $4 a gallon, $5 a gallon for diesel. Again, as you point out, until that flow resumes to normal levels, which that's not really foreseeable given the current circumstance. I don't know how we go below $4 a gallon.

Ted Stank 6:23

Well, unless you forget, you said price hasn't been impacted, but I I seem to remember before this all started, gas was in the $2.75 range. So we haven't been there. So it certainly has been impacted. I don't think it's been impacted as much as some of the more dire predictions called for. China has cut back on demand, which has really impacted the demand for oil from the Gulf, which is largely where that oil goes to. But we were able to kind of withstand a lot of the more dramatic shocks. But now, as this continues longer, I think that we're thinking again, China's done something kind of unique.

Tom Goldsby 7:00

They've diversified their energy sources, which uh seems like it would be really helpful right about now, not to be so dependent on a commodity, even if, you know, we're largely self-sufficient from an energy and oil standpoint. But still, as we are keen to point out to our students, hey, oil is a global commodity. And if uh US producers can find a fetching price overseas, you know, they owe it to their shareholders to go seek that out. So, hey, you know, we're kind of waxing philosophic. I'm curious about uh what these guys that are maybe a little closer to the action, a little closer to the data might see. Jason, Thomas, what's your read on the current situation?

Jason Murray 7:37

I mean, I think it obviously fuel goes up, shipping goes up, we do shipping pretty simple, right? Obviously, it's a big factor on the margins of all the customers we work with, et cetera, which is tough, or they have to raise prices, right? But, you know, and then I think the other thing's interesting is just we're right in the middle right now of this huge AI ramp up. We'll obviously

AI Data Centers And Local Pushback

Jason Murray 7:56

be talking about that. And that that requires a lot of energy too, right? That's very unique to kind of the previous generation of this technology. So kind of getting it on all sides, honestly. It's crazy.

Tom Goldsby 8:05

Yeah, and then that front, you know, as we talk about the AI build-out and the energy, a whole lot of growing interest around, I guess, moratoria. Didn't New York just pass a moratorium on data center build-out. And I'm hearing the same from some other states. You know, it's sometimes labeled not in my backyard, and a lot of concerns, energy consumption being one, the water usage being another. But I'd be curious about your perspectives on the very bullish outlooks we've had. And a lot of the growth we've experienced in our economy in total is pegged to AI and data center build-out. Do you see any cautionary tales here?

Jason Murray 8:44

I think we have to find some way. The demand is just ripping on this stuff, right? And we're gonna about to spend, we're gonna talk more about, you know, all the uses and the ROI and everything else. We'll get into that in a minute, but we have to find some way to keep increasing compute, you know, especially the kind of inference stuff, which has to be relatively close to people to be snappy, right? I mean, the the distance matters. So we gotta find some way to incent the people that are benefiting from this. The companies have to find some way to incent the towns that are going to be impacted by this, right? Like I'm not a public policy person, though I'm I'm not sure what the exact right answer is, but there has to be some way that if you're gonna have a data center in your town, the the folks have to benefit from that, right? You can't just have your electric bills go up and expect people to be thrilled about that, right? The other thing kind of going on is I think the data centers become this effectively representation of AI in general, and obviously the fear of job loss and everything else.

Ted Stank 9:40

So AI and technology dominates the headlines. I mean, it's crazy to say because we've got, you know, all the things that we've been talking about for years. We've got climate change, we've got geopolitical stuff going on, we've got the tariffs, but still, I think the the drumbeat of AI and technology kind of beats everything else going on in the news today. So it's really timely to have you guys on with us.

From Machine Learning To Agentic AI

Ted Stank 10:06

So let's make that shift then, because I really do think almost everything in the headlines, supply chain related, are influenced in some way or another by AI. Jason, one of the things you did for us last time, and I think it's worth doing again, is walking us through kind of the different evolutions of AI and telling us what the different things were and kind of sharing your thoughts on where we are in terms of AI moving into a real usage phase from experimentation to really being implemented for use within the supply chain.

Jason Murray 10:38

You know, I think obviously the roots of it all kind of go all the way back, right? I mean, when I was getting out of school in the 90s, there was like operations research and you know, mathematical optimization and all that stuff, statistics, right? It's all kind of based on the same fundamentals. But, you know, around 2010 or so, the machine learning took off, right? And obviously the companies like Facebook and Google were using that heavily for advertising predictions. They made a ton of progress on, you know, how do you predict what advertisers show someone, or you know, what are your search results, et cetera. That was kind of what I would call first generation or machine learning. People refer to that a lot of the time. At Amazon, we were able to make use of that for huge wins in the supply chain, just in terms of both predictability on the front end and, you know, kind of optimization on the back end. This next wave is the moment that kind of Chat GPT came out and tweeted, hey, try this out, right? I mean, the world has been in this frenzy over what you'd kind of refer to as generative AI. The first interface to that, that's these what they'll call large language models, where you've got this massive prediction of kind of how do the words fit together from training this thing against the whole internet, right? And whether that be coding or natural English language or other languages or whatever else, right? And so the first interface to that was the chatbots, which kind of happened the first couple of years. And obviously it's just kind of magical to use them for the first time. You know, we went through that, and then I think the stuff that was starting to emerge in 2024 and getting into 2025 is this concept of agents, right? And and really what agentic AI is about is more stuff that's running on its own. So things that are are more or less autonomous. The most interesting thing that's kind of happened between then when I was talking about this and probably now is just we have a much better idea now of kind of what this stuff works with, right? What are the kinds of tasks and kinds of things that it's it's really good at, stuff that it struggles with, you know, and and where there kind of becomes this almost ceiling on how much intelligence is available right now. So the way I've I'm kind of looking at it now is it's it's just a ton of opportunity in the supply chain space, specifically around all of these things that we're gonna be able to remove the drudgery work around that is what I would describe as kind of the the parts of people's jobs they probably don't enjoy very much, which then opens up, presumably, time for a lot of like strategic work, right? And so I think it's a very exciting time in terms of where we're heading.

Tom Goldsby 13:01

That's really helpful. And and I'm just curious if we could go a little bit deeper in terms of those areas where the technology seems to be thriving and maybe where it's a little more challenged. Can you kind of help to discern where uh we see more success versus those circumstances where it's maybe challenged?

Ted Stank 13:17

A news article that came out today about open AI having an uh exploratory model break out and hack a startup company. I need you to explain to me what that all means.

Jason Murray 13:31

Don't you notice how those kinds of articles always seem to come out when like Apple files lawsuits against OpenAI? I don't know. Just not to go too deep down that thing, but this is fantastic marketing, right, from both of these companies is one way to look at it.

Ted Stank 13:47

You know, for those of us who were kind of you know not deeply into the the industry, it's great. It's that's an interesting insight.

Jason Murray 13:54

Yeah, I mean, the high-level, you know, these things are um incredibly good at exploring code bases and vulnerabilities. And, you know, we went through this a couple months ago with, I don't know if you guys heard about like mythos with Anthropic, and they kind of had to tone it down a bit before they released Fable. Obviously, they're using it, I believe, kind of as a marketing stunt, right? I mean, it's it's overstated to some degree. But on the other hand, there's truth in these predictions because I just think the ability of these things to look at code bases and try a bazillion things and find these vulnerabilities is there. I think in the end of the day, what we're gonna end up with is a much better code around the internet. If you coded, you're a human in the past, you make mistakes. There's like, I can tell you, whatever company you're at, you're sitting on a code base with lots of bugs, lots of vulnerabilities. That's all very true. And so these things are extremely good at finding stuff. Kind of the like the whole world's gonna end part is probably the exaggeration, right? So

Where AI Works In Supply Chains

Jason Murray 14:50

yeah, but back to your question, Tom, I think what is it really good at, right? And I I think, you know, what's been so interesting is just that if you start kind of looking at these as what kinds of problems can it solve. I think the first one is kind of basic human labor. I think this is like most easily categorized by things like customer service. And if you look, that's one of the first categories that it's having a lot of success in. You know, you this is stuff that you would typically in the past have offshored to another country, right? Or found some mechanism to do this. And I think if you've got fairly boxed-in results you're trying to get out, like pretty standard answers that would be like kind of tier one CS, they're working really well. I think once the thing starts snowballing, that's when you've got to bring a human in to kind of once it gets out of bounds and they're doing something that's not in the standard playbook. But, you know, just as a frontline, as a first-level thought process, you imagine the amount of time that was spent by humans answering all these calls, and can this be directly replaced by AI? I think the answer is yes. But there's going to be a kind of a ceiling to what it can reach in terms of that, right? And then I think the second thing really relates to what I would describe as like human in the loop processes, where they in this stuff ends up being these massive productivity improvers. And the first case that has worked in the industry, hands down, is coding, right? Even today, I think if you watch what developers are doing and you play with these tools, if you're working in a complicated code base, there needs to be someone kind of steering the thing in the right direction. But it does handle all of the kind of drudgery work that you used to have to do as a programmer, where you need to understand every detail of the language, understand what the API calls are going to be, kind of go through this process. And that whole thing is obviously just blown up, right? These companies are growing faster than any company in the history of mankind, right? As a result of how effective that makes people. But as a mental model, this is another example where I think you can look at our space and start to think like, okay, what could this help with? You know, and and we have some examples we can we can talk about how we're applying this kind of thought process. Um, and then I think the third thing that's really interesting is around effectively taking unstructured data into the system and using it in new ways. You know, the the simple example would be like, when I was at Amazon, if we wanted to forecast based on what was happening in social media feeds, we just could not hire enough people to go through that data and bring it in and use it as an input into what's happening with decisioning, right? It's totally possible now, given this technology, that I can build a machine that's going to basically be reading these feeds in, summarize the data, and then apply that to some of the problems that a lot of us work on in the space. So that's that's very exciting. Those would be kind of the big three areas that I've seen really working. But, you know, the totally replacement of a complex job is not there yet. It's clearly, I mean, we have not seen massive job losses, that those numbers aren't there yet.

Tom Goldsby 17:46

So that's really helpful. Thanks. And, you know, it's been interesting as we talk about preparing students for that near future, midterm future, and you know, what jobs are gonna exist. And we we still feel very convinced that supply chain is capability, a knowledge base that students are gonna need to have. Computer science, I again, the coding work maybe is is fading away, but in terms of those folks that can apply the technology and make better, more informed decisions. And so it conversely to the flip side of that, and maybe we could kind of say the inverse of where AI is finding success might be where it's challenged, but kind of more pointedly, where would you say that we're having some growth pains or challenges with regard to applying the technology right now?

Why ROI Requires Process Redesign

Jason Murray 18:33

I mean, I just think that there was kind of this expectation that I'm gonna just I'm trying not to be too flippant, but basically I think the first passes of some of these pilots where you just say, like, I have some problem in my organization, I'm just gonna type a prompt and and now I'm gonna be able to just poof replace a human. That's kind of the ROI argument from this. The reality is that people, when they do jobs, the the more complicated their job is, the more kind of interactions they have, the more things that they do in any given day. And a lot of their tasks are not these mundane tasks, right? And so I think that kind of magical ROI has been a real challenge in terms of you need to kind of rethink your processes, you need to rethink how the type of people you hire, you need to rethink kind of your approach to solving problems. And so all that's gonna happen. And I mean, we've seen that with every economic revolution. You saw it with like the transition from the steam engine to the electric engine, you know, electric motors, right? It your factories had to be retooled to basically support those new processes. And I think that's gonna be the process that we go over the next 10 years or five years or whatever it is to start to kind of see those ROI things. But I don't think that without being thoughtful and kind of having a more holistic approach to the thing, you don't see the benefits immediately, right?

Tom Goldsby 19:51

Yeah, no, that's really insightful. And I think that many people look to the technology as if it was gonna generate all these hard savings as we used to refer to them, right? Headcount reductions and very direct connections to cost savings and revenue generation. But it really seems like we're back to where we've been for decades with regard to these soft savings, right? Improving processes, improving service, and then having to calculate some kind of pro forma yield out of all of it.

Ted Stank 20:19

You talked about economic revolutions, Jason. To me, it's the promise of the next jump to curve improvement in productivity.

Jason Murray 20:27

I think that's what it is. I think it's gonna open up more opportunities. The interesting thing is you mentioned the software developer, you know, kind of use case, right? And there's no drop in actually the the number of hired software developers has gone up, right? And I think it's kind of this classic people talk about Javon's paradox a lot, right? Which is if you make something cheaper, people are gonna want more of it effectively. So you think about it, if software is cheaper to make, people want more software. It's not the other way around. And that's the pattern that you kind of see continuously in these revolutions. I think what you're gonna see is basically a lot of these things that we couldn't get to or even imagine automating in this world that we live in. Now we can do it because we can we have so much more productivity out of these software development teams than we had five years ago, right? And so it's pretty amazing.

Ted Stank 21:14

Let's

How Shipium Builds Shipping Intelligence

Ted Stank 21:15

do a pivot. Jason, you are the co-founder and CEO of a company called Shippium. You want to talk about Shippium and how you guys plug into this whole AI revolution in supply chain?

Jason Murray 21:27

Yeah, yeah. You know, this is something we've been thinking about a lot. And I think if you're in the um the software space like we are, you know, when this technology came online, you kind of have to think the first question is hey, software's a lot easier to write. Where are your defensibilities? What are you now in this new world? Right. And so when we started Shipium in 2019, we really thought of it as kind of this almost the rails that are managing the shipping process end to end, right? So everything from promise through routing, manifesting to kind of the final closing out of the shipment or the payment, right? That was the vision that we laid out, because this is what I saw at Amazon and I saw how. Powerful it was for this particular space, right? And so more and more we think about that now as our core business, right? Where we've got this infrastructure layer that we make it really easy to ship anything from anywhere to anywhere and kind of handle all the muck that's down there, whether it's hazmat or international stuff or whatever, whatever you're trying to do in that layer. But now the the new kind of push as a result of AI being on the scene is building the intelligence on top of that, right? And so as a company, we're going really hard now into the audit and freight pay space, the kind of advisory services, and kind of later this year starting to touch on what I would describe as kind of exception management, right? And that's where we're kind of using this core layer of software and infrastructure that we built to now use this newer technology to solve these things that were traditionally done by humans, right? To fit with my narrative from earlier.

Ted Stank 22:51

You

Always On Audit And Freight Pay

Ted Stank 22:52

said that the next generation for you guys is the always on audit. You want to kind of enlighten us on that?

Jason Murray 22:59

Yeah, I love this because this is a great example of kind of when you rework a process and think about it differently, you kind of end up with new results that just you wouldn't have gotten with the old process, right? And so because the fact that we feel like with agents, we're going to be able to automate 99% of the audit process and errors that we do find, the system will be able to learn and adjust and get better and better and better. The audit process itself almost becomes like a monitoring system, right? Where it's it's dealing with is there an upstream problem? Is there truly a reconciliation issue between the carrier and you? This is something that, unlike a traditional audit firm, is running 24 hours a day, always looking, always trying to figure out where it can make adjustments, right? And that creates all of this opportunity for kind of upstream fixes to happen faster, right? Because I I think at the end of the day, if you really look at it, UPS doesn't really want to be going through this process either. We want the two things to be in sync. And so we're really positioning this as more of a monitoring system where we're just trying to make sure that everything is copacetic between everything. And so I think it fits with a lot of those core supply chain principles that I'm sure you guys spend a lot of time on with your students around fixing the root cause and you know, doing things in line, toy to manage manufacturing systems, et cetera. So it's pretty exciting.

Ted Stank 24:18

Let me give you an anecdote. 1995, I'm a young professor at Iowa State University working with a senior faculty member named Mike Crum. And Mike had a contract with a local manufacturing company to do freight audit, and we would get paid a percentage of you know of the overages that we found. In his garage, we had boxes, literally like case-sized boxes of microfuge that we hired undergrads to look through eight hours a day to find and compare to the contract. You know, there was no way that we could track where the problems were or what carriers were causing the overages or do any kind of root cause analysis. It was, well, you want to talk about just blunt block and tackling and grunting through to hear what you're talking about today in 2026. So what was that 30 years ago? Yeah. Quite a change. Quite a change.

Jason Murray 25:13

And that's an example of just like it's the we we're going hard after this because it's such a perfect fit for this new technology, that reconciliation process. And you can also get out of the sampling and just audit everything, right? So it's it's amazing.

Thomas Deakins 25:26

I think the other thing too it does here is Jason's being a little modest, but I think the other thing here is it allows Shippium to truly manage the entire life cycle of a parcel process or a parcel shipment, right? Because audit's always been that thing you think about after the fact. And if you do that earlier up in the process, as you said, you can catch the error earlier and potentially even save money. But having all that within that same platform, you don't need a third party, you don't need another piece of software. So again, the ROI is there, and there's a reason that Shippium is going down this path because there are a lot of very large customers, large logos that have asked Shipium to do that. Jason's very modest. I appreciate it, Thomas. Thank you.

Lightning Round AI Myths And Skills

Ted Stank 26:14

Hey guys, we came up with these questions that we're calling lightning round. I would love to throw these at you because I know both you guys. I know that you're really quick on your feet and have really interesting insights. All right. Here's the first one. What do you all think is the biggest AI myth?

Jason Murray 26:32

I think it's well, I'll say like both directions. I think people overshoot it. I think people uh, like I said earlier, believe that they're just gonna be able to plug this thing in and it's gonna work without changing, significantly changing process and staffing and culture and everything else.

Thomas Deakins 26:45

I think it's everything that you type into Chat GPT or any of the gen AIs that everything comes back is true. Yeah.

Tom Goldsby 26:54

Let's throw another question at you. Thomas will lead off with you. One technology every supply chain leader should learn more about.

Thomas Deakins 27:02

Definitely AI and just the way that AI would be used in their organization, whether it's gonna be generative AI or agentic.

Jason Murray 27:09

Yeah, I second that. I think just you got to start experimenting, you know, get get in there and and figure it out. Because I think you're gonna be surprised what you can do with it, and you're also gonna be surprised with what you can't do with it. The pattern is not clear when you try to kind of intellectualize it.

Guardrails Change Management And Vaporware

Ted Stank 27:26

You know, one of the things I think is really interesting that you said, Jason, is beware of the media that you read because there might be agendas behind it. I read something not too long ago that, you know, companies have invested so much money in AI. And some companies I think required their people to spend 10 hours a week, you know, playing with AI. And then I read something saying, no, we're not getting the ROI out of it, so we're backing out of it. And it just makes me wonder how much of any of that is true and how much of it is just media feed to, you know, to get us to get us going.

Thomas Deakins 28:00

I could tell you firsthand that change management is huge in this equation. And my daughter works for a company where she runs change management, and you know, they're getting their hands around how they're going to use AI, and they have to set up processes and they have to have a way that you're gonna use it in the organization. Because if you don't have guardrails, you literally can have people putting information into Chat GPT or other gen AI tools that shouldn't be there, right? So you've got to have rules.

Jason Murray 28:32

There's a pretty large gap between what people are talking about as far as their book goes and what is actually possible. And I I think you have to be very careful about incentives, who's who's telling you what and why.

Thomas Deakins 28:43

So I also think this makes in software, you've heard the term vaporware. Uh, I think it also allows companies to be able to say they have functionality maybe that they don't have because they think it's going to come faster. So I would just say buyer beware at times. Good call in. Yeah, that's a good one.

Ted Stank 29:01

Thomas,

Writing A Thriller With ChatGPT

Ted Stank 29:02

personal question for you. I understand you have a third career, I guess, coming up as a literary giant.

Thomas Deakins 29:08

I wouldn't call it a literary giant, but yes, and my wife and I have battled on this because on a weekend I was bored one day and I said, you know, I want to create this book. I've got this idea, I want to write a book. And I used one of the GPTs from ChatGPT and uh wrote a book. Over a weekend, it turned from one book to a trilogy. And so it's a thriller. It's about uh Chinese operatives and narco cartel and all kinds of things descending in on my hometown.

Ted Stank 29:38

So yeah. This might be media hype, but I heard that HBO picked it up.

Thomas Deakins 29:44

Uh Ted, I think I signed you on as my agent one night, and you've done something that I'm not aware of. I I'm looking for something to binge watch. So uh I need to get that in production.

Tom Goldsby 29:53

Hey, Tom, Tom, don't don't sit by your TV and wait on this. Can't wait to hear the uh the supply chain storyline because it's got everything's supply chain these days, right?

Thomas Deakins 30:02

I'm gonna make a quote from an esteemed professor that I knew, and he once said, supply chain is life. Hmm, Dr. Stank.

Ted Stank 30:10

Do you guys remember way back when CLM contracted with an author to write the CLM fiction book?

Tom Goldsby 30:17

Yeah, yeah, I do. Was it the precipice? Was that what it was called? That's what it was. Yeah. Not the best spent money that I recall. They were flush with cash at the time.

Thomas Deakins 30:29

I will say, and I'm gonna double back to Tom's question. Tom, you asked me that question, and you were like, hey, what's one technology everybody should, you know, in supply chain should know? That's a setup question because you know I teach how to implement a transportation management system, and I should have said a TMS. But thanks to Jason and team at Shipium, I'll be adding Shipium into my curriculum, you know, into the classroom. Fantastic. Because I think it's important for students to be able to get their hands around that as well. Yeah, and our students will benefit from that.

Ted Stank 30:56

Guys, I think it's important that we check in with you every year or so because things are moving so fast and you've just got great, great, great insights. Jason, you've been at the heart of this with Amazon and now with Shippium that it's it's just great to have you guys on board. Thank you so much.

Jason Murray 31:12

Right now, for sure. It's all that's awesome, and thank you so much.

Tom Goldsby 31:15

And Thomas, good to have you back in the mix, man. We we miss you in the shop, but uh appreciate that you still plug in in a multitude of ways with us.

Thomas Deakins 31:23

Of course. I can't wait to the what'd you say, just a couple of weeks, and we'll be back in the classroom. So I'm looking for it.

Ted Stank 31:28

Yep. Um, Goldsby, you want to take us home?

Tom Goldsby 31:31

Yeah,

Partner Events And How To Connect

Tom Goldsby 31:32

let's go ahead and close out uh in our uh late summer edition of the Tennessee on Supply Chain Management Podcast. Again, thanks to to Jason and and Thomas for joining us. And Ted, it's great to spend a little time with you as well, my friend. Uh, we'll be back at it very soon. We're gonna be hosting our supply chain advisory board, GSCI Advisory Board. And I know that uh we're gonna be recording live session there. I think. Ted, do you know who that guest is gonna be?

Ted Stank 31:57

Yeah, I do. Uh Heather Kettelhone is gonna be our guest there, and it'll be a live session with Heather from the Advisory Board. Fantastic. Josh asks us to remind our GSCI partners that early access networking night for student recruiting is coming up September 21st, and partners and non-partners can attend the Fall SCM Career Fair on September 22nd. Sign up on Handshake.

Tom Goldsby 32:22

Fantastic. And as always, all our listeners can reach us at gsti at utk.edu. With that, we'll sign out for now and uh be safe, be well. We'll see you soon.

Closing Thoughts And Subscribe

Intro & Outro 32:34

Thanks for listening to Tennessee on supply chain management. Be sure to subscribe on your favorite podcast platform for more conversations with the leaders framing the path for practitioners, scholars, and students. Have a question or idea? We'd love to hear from you at gsdi at utk.edu. Till next time, listeners.