The Impact Of Onshoring On Wholesale Distributors

Foreign welcome to around the Horn in Wholesale Distribution with Kevin Brown and Tom Burton. Sponsored each week by LeadSmart Technologies. Tom, Kevin and their guests review the news of the week and dive deep into the topics impacting manufacturers, wholesale distribution, independent sales agents, and the global wholesale supply chain. Whether It's M&A SaaS and cloud computing, B2B, E commerce, or supply chain issues, we peel back the onion with our guests into the topics that impact your business the most.

How are you this morning, Tom?

Doing okay? Doing okay.

Very good. Cloudy day in Santa Barbara, I presume?

No. Sunny but cold.

Oh, sunny but cold, yeah.

All right.

Good Rain at the end of the weekend, I think.

Supposedly, yes. Supposedly.

Very good. Well, hey, good morning, everybody. Kevin Brown here with lifelong friend and business partner Tom Burton. We get together every Friday morning here live on LinkedIn live, Facebook live, and YouTube live. And we discuss kind of the news of the week, what's going on, and a little bit about the economy. Sometimes, like today, we're going to talk about regulations related to AI talk, talk about technology, mergers and acquisitions and so forth. But what we do is we try and unpack all of that data and bring that back to how that impacts wholesale distribution and manufacturing. And, you know, day in and day out, we see these changes. There's, there's things that go on in the news and we kind of bypass them pretty quickly. But they can have a significant or major impact on what's going on within the markets that we work with, which is, again, wholesale distribution and manufacturing. So our show each week is, is based around a newsletter that we send out on Friday mornings. It's called around the Horn in Wholesale Distribution. Shocking. And if you'd like to get that and you don't currently get that newsletter, please you can pop us a note in the comments here today if you're live with us. If you're listening on the podcast, it goes live later in the day. You can just pop us a note two different ways you can do that. One is at our website for the podcast, which is www.aroundthehornpod.com. you can see all of our previous episodes there as well as like, register to get the newsletter or simply just send us a simple email to helloadsmartech.com and we'll get you on that list right away. So as we go through the day today, we're going to be looking through some articles that we curated from throughout the week. We're going to talk about that. We'll look forward to comments from folks that may be joining us live. So if you're out there live with us today, I know we had, I think just from the small LinkedIn audience that that registered to come. We've got three or four countries represented there at least and historically we get five to seven countries and I don't know, three, 400 people on the live show each, each week. So we enjoy that. Share some comments, some thoughts, even if you just say hello and where you're from. So last part of this, Tom, I guess we should talk about who sponsors this, which is Lead Smart Technologies. It's the company that Tom and I co founded and work for. And Lead Smart puts the dollars behind this so we can produce this each week. When we get done with this, this live session this morning, an editor takes it and he costs money and so forth. So the good folks elite Smart do that. LeadSmart is a AI enabled CRM and Customer Intelligence solution. It's built solely for wholesale distribution and manufacturing. We don't work with companies outside of that arena and that scope. We bring my 35 years of experience in wholesale distribution and Tom's 30 plus years in technology together to bring a solution that works great to accelerate growth. So, Tom, I've spewed enough. You want to ready to get us rolling?

Let's get on with the news here.

All right, so for months, maybe, maybe close to a year, we've popped a little article in like we do. This particular one is from CNBC that we're posting here that is talking about Dow's rally up almost 100 points after a little bit of a Fed announcement. We've been talking about a simmering, kind of lethargic economy that we've had for quite some time. What are your thoughts on the, the Fed the other day?

Well, you know, I mean, they were definitely more accommodative in their, in their messaging. A little bit of a different.

Pardon I said a great term.

Yeah. And definitely a different tone. Obviously, you know, the market's been going crazy up even before that sort of expecting, I think a bit of this. I think they even exceeded expectations a little bit, which then drove the market up what, 600 points the first day and I think yesterday, so, so it's a little bit, I don't know, it's a little, it's, it's, it seems a little bit excessive, I guess. But the fact is is that, yeah, I think for sure we will have interest rates being cut next year at least two to three times, possibly even more depending upon what happens. But I think three is what everybody's expecting.

Well, that's what they hinted at. Right. And I found that particular point of it kind of interesting because I'd have to go back and look and research it, but I don't. I think they kind of forecast and had some ideas when they were looking to start raising interest rates and they accelerated that pretty quickly. And we'll see if they, if they do just that small, small number of three or if it's maybe a little bit more.

Yeah, I don't know. But anyway, they're, they're hinting at three and, and the market certainly seems to like that. I think it's more than just the, the number is that, okay, we, we've reached the summit now. We're on our way back down. I'll just share though real quickly. You know, we've talked a lot about over the last few weeks about just the economy and the consumer and all of that. We did a little exercise at home and we use Quicken to track all of our expenses and everything, you know, our household expenses. And so we went back to Q3 of 2019 right before COVID and we looked at all of our household expenses, groceries, you know, rent, whatever, all the different things that just day to day living, not, you know, trips or anything like that, and then compared it to 20, 23 Q3. So right now, and basically everything to, to live the way, basically the same way we were living in 2019 was about 28% more. So inflation in our, in the Burton House is 28 over three years or cost of living is increased 28 over three years. Eating out was by far the biggest one. It was up almost 40% of compared to where it was then. But, you know. Yeah. The fact is, is that even though we're now going to see interest rate cut, prices I think for the average person are obviously significantly higher for the cost of living. And unless you're a United Auto Worker employee that got a big raise. Right. Most people aren't getting those types of raises. So it'll be.

That's what I was saying when you were away. I was wondering if you got a raise that I'm not aware of.

I, I wish, I wish. Yeah, I didn't notice that. So.

And that's probably not tied to you switching from Central Coast Pinot Noir to French Bordeaux. No, that's 28, right?

No, no, we're still doing Charles Shaw. So everything's still the same.

Very good. I think that would be a very dangerous exercise to do in our house. But it is, it's intriguing, you know, but you live there in Santa Barbara by the Hollywood stars and so forth. So. But it's probably relative, right, because, you know, incomes are tied typically to where our zip codes are. So we probably see something similar across the board. But I think, you know, looking at this, right. Is there's a risk to all this, you know, frothiness that we're probably seeing. I think the market's up right now and things are, you know, doing well day after day. Interest rates or mortgage, mortgage rates were below 7% yesterday for the first time and certainly I think this year. Right. And we'll see if there's some easing on, on consumer credit and so forth coming. But here we talked a little bit before we got together today about the, I, I'll just call it the potential boomerang effect.

Right.

Because we could find ourselves in, in just another pickle again if we go back to, you know, very quickly. And I don't think we're going to see, you know, 2.8% mortgage rates or, or free money like we did in a lot of places. But, and I think it's interesting too, is kind of almost ties back to Covid times with, you know, government dollars that are available and people started spending and, you know, never saw the Amazon truck as much as they did during the, you know, heat of COVID through the neighborhood. And I think those spending things are interesting, but I think there's a risk right now, Right. That we go into a, into a little boomerang effect that we get rates start to drop, people start to buy, people start to spend too much again and we get hot and heavy and we've got to get some adjustments. So hopefully there's some cooler heads that prevail through this.

Yeah. And if, and again, if, if companies are forced to increase salaries, right. To keep up with our, with the fact that everything is 28% more expensive. That's also going to put. So, yeah, there is a lot of, I mean, first of all, I want to, it's, I think it's obviously good news that the, that the tightening process, I believe, has come to a close and we're going to get a bit towards normal. I think the key is, is looking at this more towards normal and not looking at it as, okay, party time.

Right.

But I do think that all said, I think we are going to see a lot of party time over the next 12 months. And because of this, you know, just, and there has been a lot of money on the sideline in the stock market. And as they start cutting more rates, I Think you're going to see more. More money going in and prices going up. So I think it's going to be interesting.

I think we need to kind of roll this back to, you know, the audience that we look to address here. And by the way, good morning, Mike from. Looks like it's snowing in Minnesota this morning, so be safe out there. And. But as we tie this back to wholesale distribution, what's going to be interesting to see? And I'm gonna. I've got some chats later in the day and early in the week with a few different distributors, and I'm gonna chat with them about this. You know, we've talked about this and we've had comments from distributors on the show recently about, you know, they had a glut of inventory coming out of COVID because they bought so much because. And often depending on what the commodity they sell is and products they sell. But, you know, it really ramped up inventories. And then we hit this spot where money got really expensive, but a lot of folks had plenty of inventory. So I'm wondering if what we'll see out of this is the high cost of money hasn't impacted wholesale distribution nearly as much as we might think it would or has in other sectors because of those high inventory rates. They've been bleeding those off. And I think we talked with Paul Kennedy about this a few weeks ago, you know, and getting inventories balanced a little bit better now and then, cost of money now should be balancing out here pretty quickly. That maybe, maybe we see some almost minimal impact out of all of this.

Yeah, could be. And then maybe that's a good way to bridge into this next article about the onshoring and the impact.

Yeah, Yeah, I think that's it. You know, we've talked about this quite a bit. I thought this was just. Again, if you're, if you're listening to the recorded podcast on Apple or Spotify or any of the other podcast formats later on. We have a newsletter that we have up on our screen on the live broadcast today that, that we're looking at. We show some articles that we post in our newsletter each week. But this is from more of an investor standpoint and this is from Seeking Alpha. And they talk about onshoring and its impact on US Centric companies. And they talked about this very quickly about the Fed's actions, raising interest rates and tightening lending, what that would do and putting pressure on economic growth, slowing capital spending and thus on shoring in the short term. Well, now I think we're Going to see this opportunity with easier to build if we've got more interest rates coming down and loan rates coming down, easier to build new facilities, easier to make investments and so forth. I think we're going to see the ramp of this going up.

Well, there was a graph in that article that showed the. I mean, literally, straight up. Yeah. The number of companies that are either considering, discussing or planning to do move things onshore.

Yep.

And. And that by itself, economically could have a. A major impact. Right. Because now look at the jobs. Look at the things that are granted, you know, you can talk about AI and other things optimizing it, but it's still things are happening here versus there. There is going to be a positive impact from that.

Well, I think you're absolutely right. You know, there's a jobs impact. There's all the things that go with that.

Right.

Whether we're in construction trades or you're working in a warehouse or whatever it might be. But what intrigued me is they talked a little bit about even this, you know, kind of starting pre Covid, but I think Covid was really that. I mean, it just. The world had to see it. Right.

It rubbed your nose. It rubbed your nose into the problem.

I think that's exactly right. Right. When all of a sudden you're realizing, you know, pre holiday times that you've got all these backlogs of ships in, in the ports and throughout China, you know, trying to get stuff. Ports are shut down, factories are.

Have.

They're shut down, goods aren't being produced. We'll talk as we look later in this article about, you know, some of the geopolitical stuff that goes with that. But just in general. Right. We saw what, what people that were watching it closely were seeing pre Covid and now are seeing that are watching things within, within, specifically China a little bit more Southeast Asia, but mostly China in the setting is, you know, to your point. Right. We got our nose rubbed in it. Right. When I could see tankers backed up or not takers, but container ships backed up. I live about 40 miles south of the L A Long Beach Harbors here in Southern California. And there were tankers backed up as far as in container ships backed up as far as where I live, waiting to get up there. So interesting pressure there. But you know, and then we. You mentioned earlier briefly, Tom, you know, insightfully from a standpoint of we have all these, whether it's AI or just general commercial tracking tools and so forth for manufacturers and suppliers and, and distributors to track JIT inventories and it's just so much easier to manage things at this stage of the game and it's just going to get better as we technology grows, AI grows and so forth. But I think the big thing people are really looking at is the geopolitical tension, you know, and it's, it's a whole lot easier to get goods out of Mexico if there's geopolitical issues in Mexico or somewhere else in Latin America than there is coming across the Pacific.

Yep. No, it's. So, yeah, I mean, it's. It that, that article to me was very literally the graph was like straight up. And so certainly this is not something that we've seen the last of.

Well, I mean, you just, you see there's, you know, whether it's, you know, G7 getting together and you know, you've got China flexing their muscles or potentially, you know, supporting Russia and some things that are counter to what the US is trying to accomplish. And I think if you were had an opportunity to sit into some boardrooms and listen to some of these discussions, you, you'd really hear what's going on with all of this. But it'll be interesting. The other part of it too is a, this article talk that I hadn't been thinking about is energy costs and energy costs here are so much lower than in a lot of parts of the world. I, it didn't speak to, to China, but it talked to Europe about Europe and about how high energy costs are. And we just, you know, what is a, you know, A thousand British BTUs, British thermal units cost in gas to run a plant? It was dramatically less here. So a lot of things going on with that.

All right, so should we move on?

Let's keep, yeah, let's keep talking about manufacturing because. But I'm going to, I'm going to bend this article, this next article about digital twins a little bit both for manufacturing and distribution. The articles from Facility Executive magazine and newsletter that talks about will digital twins revolutionize manufacturing. You know, we've talked about the industrial, you know, Revolution four. We've talked about Web four. We've talked about, we talk regularly about AI Tom, before we dive too far into this, why don't I ask you give us the Reader's Digest quick view of what is a digital twin for those that haven't been with us before when we've talked about that.

Well, I think obviously the term is used in a lot of different ways in a lot of different places, but as it relates to manufacturing, think of it as a clone, right? Or I'm cloning something that I can then test run through, do things with outside of, I guess, my production environment, right? So take my production, manufacturing processes, structure, facility, all of that stuff, clone it digitally, and then be able to look at how it's going to operate and so forth digitally before I put it into actual production physically. So I think that's the simple answer to it. And obviously with AI piece, right, the. It allows you to continually be. Get closer and closer to the scenarios and situations that you would have in a real physical operation, right, that are sometimes, you know, what if. What if five people don't show up for work one day? Or what happens if, you know, everybody gets Covid or whatever the case, right? All of these different scenarios that can be modeled and emulated digitally. That's essentially what we're. We're talking about here.

So we go back from kind of along with what you're saying, right? Is historically, we get a bunch of people sitting around my engineers, right? We're sitting, sitting around a room with spreadsheets and design drawings, whiteboards of all of the information we're trying to replicate. What should happen if we do A, B and C? Will it create X, Y and Z for us? And instead of making assumptions, we take large data sets from within the organization. We put all of those things together to create a digital twin of what happens in that setting and in this manufacturing line. If we do these things, we're actually visually replicating it through real data versus what we think might happen. Talking in a room.

And I'll give you. I mean, one of the things that we've been working on at Lead Smart and something that I've. I'm. I'm finding as we do our development, is that I'm seeing that we're in some ways being able to do a digital twin of a sales organization and look at how a sales, you know, sales organizations or revenue operations, whatever you want to call it, have a similar thing, right? You have processes, you have objectives, you have goals, you have people, you have all of those things. So, yeah, manufacturing, or the manufacturing floor is one piece of it, but the ability to take and clone digitally what's going on physically or in the analog world, and then run and analyze that and then optimize. I, you know, I've just been testing it more from the sales perspective, but, man, there's some interesting things that pop up and it's, and it's almost impossible for, you know, what you were saying to somebody to go on a whiteboard or a Spreadsheet or a bunch of people to, to do that all manually and figure out what can be done, you know, digitally and through AI and in seconds or minutes, you just never see it. Yep.

Well, you know, we're running real models against it versus plugging some data into, you know, you know, we've heard the, the term. Right. Forever, you know, space race and things like that of, you know, running models. Right. Well, this is just taking that from, you know, a whole exponentially different, different level. And what's intriguing about that, and you started to, you alluded to this earlier with what you're seeing from the product development side with our team at Lead Smart is, you know, where the, where else does this go? Because this article is about manufacturing.

Sure.

But you know, the other side of it is, hey, you know what, what, what if you could take a picture of your warehouse with your smartphone and the pallet racks that you have. Right. That will automatically. And this is I think maybe a good analogy that says it already knows. Right. It can figure out what the dimensions of the warehouse are, ceiling heights. Right. What, what's your racking look like? And look at the things that you have in inventory. Also look at models of what you should have in inventory or might want to take a picture of the big rack or stack of pipes that just got delivered. That's outside. Use AI from your smartphone camera to count that stack and let that data go in against all of your existing inventories, historical sales, every piece of data against that to say here's exactly what goes where in the warehouse and how much of it should we have. And it's doing that in moments. And we're going to talk about the speed of AI a little bit later today. But I mean, those are, you know, real world examples of where we're very, very close to.

Well, and, and again, if you just take a step back, right. Businesses, and especially in this world, manufacturing and distribution businesses are run by systems. Right. So whether it's a sales system, a marketing system, a manufacturing system, a distribution system, a financial system. Right. We're run, we're at least we attempt to run our business as best that we can through systems. Yep. And by taking a, whatever, whatever systems you have in your business, if you can create a digital twin of that system and then use AI and data and all that stuff to then optimize it, like they said here, your system inherently is going to run much, much, much better and much, much more efficiently. And I think that one of the things I've seen, just as I go through these sales systems is just the amount of lost opportunity that. Or I guess camouflaged opportunity, because they're just. It's. People don't know.

Right.

It's just we're too busy. We don't see all that. And I assume this is going to be true. And manufacturing is places where, like, you don't even know there's an opportunity. And then through the process, you're going to see, wow, we could do this. And this could accomplish these things just because we haven't been able to see the data.

Right.

So it's really intriguing. Yeah.

We look at so many of these things historically. Right. Is this is either one, this is the way we've done it, or, you know, Joe's been here forever and he's tried every different way that the warehouse can be configured. And, you know, there's no disrespect to Joe, but Joe doesn't have the computing power that we can use all of this data with. You brought this back, though, a couple of different times of the data that's available, you know, both to manufacturers and distributors. You know, we were talking with a gentleman yesterday on the phone. We were both on this Zoom call, and we were talking about, you know, what could a distributor do if they had a Digital Twin model that said I can. By using AI tools to look at my open quotes.

Right.

What. What does this do to my business if I, quote, closed 5% more of the open quotes that I have? Well, what is that? You know, what is the growth factor in the company? Okay, well, let's put that time and energy and use the right technology to manage that.

And quoting is a system. Right. There's a system. Most companies have to do quotes. The problem is the system's very. The system is quite inefficient, and there's a lot of camouflaged opportunity there along the way. But, yeah, quotes are easy to understand because clearly, if I close more quotes or if I get more out of the quotes that I do close, that can. Can definitely, obviously make a huge impact. So, yeah, it's really all about optimization at the end of the day.

Yeah. So before we jump ahead, I did a little something last night. I didn't tell you about this, but I was reading this all on my iPad and I clicked on the ChatGPT app and I went to. I just asked it and. And said, how will this. Will Digital Twins work well with sales and marketing? And it was great. I'll tell you. I want to share with you a little bit about what it said. It Said this was great. It says yes. Digital twins can be used to replicate and test sales models and methods. A digital twin virtual model designed to accurately reflect a physical object or system in the context of sales. Digital twins can simulate various aspects of sales processes to your point, including customer interactions, market dynamics and product performance. This allows businesses to experiment with different sales strategies, forecast outcomes and optimize their approaches without the risks and costs associated with real world testing. Well, historically that's what we're used to, right. Is well, let's give it a try with this division of the company or let's try it with these four people or that branch right now. We can do this with a digital twin scenario. And it talked about four key factors. Risk reduction. Right. Testing new sales models in a virtual environment reduces negative impacts on actual sales or customer relationships.

Right.

I mean, how often have we looked at something and we've said, hey, you know what, should we raise our prices or not? Well, let's see what the data says about those things. And it just talks about data driven invoice insights, cost of efficiency. Right. Virtual is less expensive than real world experiments. And then speed and flexibility. Because if we could start testing models on sales and marketing as an example. Right. How do we expect our, our customers will respond based upon historical data that we have to a new marketing effort by doing that with digital twins rather than going and giving it a try. It's game changing.

And the key to be able to do all this more or less in real time by the, the guy on the street. Right. Not having to all this have this all done in an ivory tower every day in a company. But how do I optimize just day to day by the things that I'm already doing?

Right, right.

And making that so no, it's. You're right on track. And I am amazed. We're gonna. I will talk a little bit about some AI tools here in a minute. But I'm amazed at the depth every day I'm more and more amazed at the depth of the insights that I'm getting back in this testing that there's just no way anybody looking at a spreadsheet or a, a dashboard or a bunch of spreadsheets and a bunch of dashboards would ever see or figure out, especially when you're dealing with large amounts of data. And you know, the, the one company we were dealing with yesterday in the last 10 years have done 1.2 million million quotes. Right. How are you ever going to know?

Say that again. 1.2 million quotes, not dollars, physical quotes.

Quotes, quotes. They issued 1.2 million quotes in the last 10 years. Right. Which on average is about 120,000 quotes a year or 10,000 quotes a month. How do you know? How do you keep up with that? There's no, there's no way you're going to keep up with that without having the right systems and the right pieces in place to analyze and then provide that guidance.

So anyway, no, that's it, that's, it's powerful. So, you know, the key thing is going to be how do we take advantage of these things? And it's going to be an exciting 2024 that, that goes along with all of this. Right. I mean, to see that the things are going to be. I'm just, it's not why we're here to talk about and promote what we're doing at Lead Smart, but the things that you and your team are building just astound me. And I get to see more of it just before lunchtime today, which I'm pretty darn excited about. So. Very good.

Should we move on to AI regulations?

Yeah, well, you know what? We were, as we were talking last week, they were taking a break from the, in the EU and trying to pull their, their, their guidance together. We saw earlier, I guess it was later in November when, late in November, that the Biden administration came out with some, I'd just say less than well thought out what they call it, a presidential order and with no, no real teeth to it. And it was pretty darn vague. And I, I just, I kind of wonder. You never know when looking inside these things, you know, was that trying to get out in front of what they were going to be doing in Europe. But here in Europe, they had the main players in the EU trying to all come together about EU standards, much like they did with gdpr. In fact, as we talk about this, you have more experience with what GDPR did for data security or data privacy than I do. But I think this is an interesting comparison as we start looking at what they're doing before we go further and talk about what they did. I, I just, I think I sent it to you last night after I kind of worked on our articles for Today. Yesterday the Pope came out looking for a global set of regulations to keep AI safe for human beings. Don't hear the Pope talk about technology too often.

I didn't see that, that I have to opt to check.

I thought I sent it to you. Maybe I didn't. I think it was in TechCrunch. But you know, obviously there's, you know, there's a worry about it. And I think about that, you know, when you start seeing not just political figures but, you know, religious leaders and so forth like that, getting involved in something, I think there's probably a concern that goes with that way beyond what we talk about day in and day out about, you know, the advantages of things is that there people get excited and ahead of themselves about the potential doom and gloom and we could have some, you know, furor over all of this that people are panicked over something they don't understand, you know.

So. Yeah, my two cents. First of all, we don't know all the details of this. So it's, we don't, we don't know exactly what the specifics are of everything yet. But the, well, they put some pretty.

Clear guidance into four different areas to start with that we can, we can talk about.

But, but they haven't released all of it. They haven't released everything with all the details of it. So we don't know the details of the, of the pieces that are there. I, I think it's still if in reading this, I think what they did on some of the things related to privacy was good. Like saying, you know, hey, these are some things privacy wise and how you can use the technology, you know, to kind of protect rights and things like that. I think that was good as far as the actual, you know, monitoring of models and all of that. It still to me seems a bit vague and a bit unenforceable. But again, we don't have all of the data. But I think it was, you know, something that they said. Was it definitely beyond the executive order that we had here in the U. S a few weeks ago?

Right.

But is it really going to do anything to really other than make maybe people feel like something's being done about it? I'm not, I'm not 100 sure. I'm actually more sure that it's not really going to do anything really practical other than make people feel like, hey, I feel better, something's being done about it.

Yeah.

But. Well, we got to talk about, I mean, I understand what you're saying and respect that, but there's a different factor. Right. And I'm going to, I want to talk about a few of these areas briefly, but that they, they have addressed. But here's the difference. There's sanctions for violations in place, right. So the bigger you are, the more you're at risk because it says depending on the infringement and the size of the company, fines will start at seven and a half. Start at seven and a half million euros or $8 million or 1.5% of your global annual turnover or revenues rising to up to 35 million euros or 7% of global turnover. So if you're a large organization a Microsoft and aw. Amazon, the big players in this and you get this wrong, you know, and these guys. Let's, let's stop this for just a second, Tom, and think about what's real. Apple, Google, Facebook, Amazon, Microsoft have all had challenges and lawsuits and major problems in Europe over the last five years that have cost them billions of dollars. So this is what I think is interesting is these big guys, you and I could poo poo this all we want. But they are going to have to take note of these things. Right. Because of the risk. The bigger you are, the higher the risk.

No, no, I, by no means do I say that they don't have to take note of it. In fact, the lawyers are the ones who are going to be probably the big winners on this. But is it really going to do anything to accomplish what the purpose of this was, which is to, and all that stuff? I. Is there certainly going to be violations or accusations of violations and all? Absolutely. Is there going to be lawyers trying to prove just no different than, you know, the stuff we talked about antitrust and some of the other stuff we've talked about before.

Good point.

I don't have any doubt about that. I just don't know if it's going to accomplish at all the purpose of why they did this in the first place.

Well, I think that's a very reasonable viewpoint. The other side of that is at some level how do they know until the cows left the barn is another side of that. So a couple of the things that they started with is they want to look at high risk systems. And what is a so called high risk systems they talk about deemed to have significant potential to harm health, safety, fundamental rights, the environment, democracy, elections and the rule of law. So if you're building a smaller business model that's focused on. Let's just, let's just use Lead Smart.

Right.

As an example. You know, we have customers using our products throughout Europe and, and being in a place where our focus is on helping wholesale distributors and manufacturers run their business better. Right. We don't have an impact on the environment or democracy or the rule of law, but there are these models that are being built. So they're looking at these different levels. Right. They talked about a lot of which I thought was interesting and kind of Intriguing. They talked about the use of AI in law enforcement. Right. Where it could be. And I thought it was interesting, right, because they said they could use AI against kidnapping, human trafficking, sexual exploitation and to prevent specific and present terrorist threats. So they're putting some guidelines, some guardrails around what you can call terrorism and they'll say they'll be permitted in efforts to track down people suspected of terrorism offenses. Trafficking, sexual exploitation, murder, kidnapping, raped, armed robbery and criminal organization and environmental crime. So you know what, rob the, rob the, the 711 down the street. And they can't use the AI cameras against you for that. It's weird that they, they put these parameters around that.

And that's what I mean. I think there was some things they tried to do to protect rights, if you want to call it that, and, and all that, which is good. I mean, again, I'm not against it. I just, I'm not sure is it really going to accomplish what the whole regulation, if you really take a step back, why are we regulating? Is to really protect against maybe a catastrophic event or a series of catastrophic events. I don't know the regulations are going to accomplish that anyway, but I don't know if they're gonna. This is what they. Anyway, it's just. We'll see. I'm interested to see more of the details, but you're right, it's definitely more comprehensive than anything we've had before.

Well, it's, it's absolutely the probably the best thing that exists globally today. Right in that, in that setting. So we can jump ahead a little bit. What's our next one there? We're talking about an AI tool that upends online product configuration. So we only talked a little bit about AI earlier today. We talk about it every week. I thought this was kind of an interesting piece though. And this article is about a company and a product called. It's an AI driven tool to help online ordering. And the reason I found this unique was, you know, we talk to a lot of people, you know, people talk about, you know, CPQ of, you know, configure price and quote. That is oftentimes, I certainly don't want to say all the time, but oftentimes that's reasonably straightforward because somebody's saying we have a manufacturing client that uses Lead Smart, that works a lot with us and it's like, hey, I have this item and you can configure it with these 17 other things. So use this CPQ piece tool to go to do that. They're fairly antiquated I know you and your team have worked with that particular customer and they're cumbersome. Right. There's a lot of off the shelf tools. The idea behind this one I think is really kind of neat from a standpoint is it allows using generative AI this whole process to take place. And I want to translate that over to another type of. It's not even CPQ is we talk to, we've got a, we've got a call next week with a distributor that does a lot of this and a division of their company. We talk regularly. In fact, one of our regular guests on this show's company does this. They take hose A from manufacturer A, hose type B for manufacturer ABC clamp component valve fitting from seven different companies. They put all that together to put that into one sku. Well now this is a kind of tool that makes those things happen so much quicker where customers can start saying this system can be configured to say all these items can work together and we can configure and build that for you in our shop. Right. That whole process through these tools, using generative AI just happens that much quicker.

Yeah. Even if it's not a, if, even if it's not an engineered solution though, it still could be used, right.

To come up with 50 to 7, 50 to 70% faster than conventional methods by moving that direction.

So what I liked about this, what I liked about this was, and this is again something that I'm, I'm learning, right, is they're using AI to configure AI. And what I mean by that is rather than saying, okay, we need to build an AI model and an AI solution and we're going to sit down and get programmers and figure out how to do all of this. They're using AI to help them then build what they need to build. Right. And I'm seeing that as well. Like I'm in the stuff I'm. We're working on, rather than writing code for everything, we're telling the AI what we want to do, essentially letting the AI write the code of what we need to do and then executing the code against AI, if that makes any sense.

Well, in this case, right. They talk about, you know, manufacturers having lots of different databases that they need to work from and people need to go build that databases to come out to this cpq, right, Potential system that always has flaws. And now what they're saying is they can use a natural language request and have the system generate the rules against the databases.

That's right.

And I think that's Your point? Right. It's a, it's, it's a circle, right. Or a loop of I need to do these things to do this. And it just keeps building on itself.

Well, and think about this. Right? You have an idea of what you want to accomplish traditionally, right? I have an idea, then I have to go do the analysis and I didn't have to go do the work and then I get the outcome of that idea. Now I can have the idea. Let the AI figure out the analysis of what needs to be done, then have it go do the work and produce the outcome.

Right, Right.

It's very different and the speed of that is very different than anything that even just in the last six months or so with AI, even if you had an idea of what you needed to do with AI, there was a lot of work and there still is, but there was a lot of work to actually implement that in the real world. Now you can just to some degree say, here's what I want to do, let the AI figure out what to do and then do it. That's a, that's a very monumental step.

I'm looking forward to when I finalize all of that of how to run. A tech CEO can do that for all of his day to day role and I can process that from being out sailing.

So, you know, as crazy as that sounds, I actually believe that to a large degree that will be a very possible situation here sooner than later.

Well, I think you're right and I said that tongue in cheek. But then I'm looking at a browser in front of me and my tabs on my browser are all tied to different pieces of technology that we use. One of them is I can get a quick image and view of what your development team is working on. I've got another piece here. That's all of our dashboards for what's going on within the company using our own software. Right. Leads, more channel, cloud. I've got another one right next to it. That's just a single click. That's Zendesk that says here's what's going on on the service and client success side of things. Now if all of that just says has prompts that say I want these alerts right. To come to my phone at these times of the day that are only within these parameters do I want to know about it can stay on top of a lot of things.

Yeah. And, and really the responsibility of executives now become really coming up with more clear and concise ideas that are then able to be implemented.

Yeah.

Versus you know, so again, the responsibility changes. It doesn't mean that there's not a responsibility, but a lot of the, I guess just sort of heavy lifting and a lot of the, the day to day just, you know, things that we have to deal with I think can be over time, can be improved.

Well, it's interesting, right? This is a discussion that I have with senior executives that use, use our technology. In fact, I got a text this morning from a gentleman that, you know, the CEO of a large customer of ours and, and was going to be joining us today in his comment, I should say his comment. I remember my conversation with him a couple years ago when they first implemented our software across their, their national footprint of their company. He was commenting on, well, maybe he doesn't need, you know, a login. And I said, you know, you, you do need a login, but here's what you need to do. You need to look in lead Smart Channel Cloud at your home page because it's going to show you any anomalies going on. Sales, marketing, right. Any operational functions that we have. Are the sales numbers off for what we were anticipating or are, is our margin off right now and so forth. And look at those dashboards. And if those dashboards don't have anomalies, go about your day, right. And with that how you're going about your day, be envisioning the future of your company, which what a CEO is supposed to do. So back to your model in my example, right. Is if I can be just checking on some things I could be working on the vision of the organization versus the mundane that most executives get wrapped up.

Yeah.

Which, which will tie into another one of our last articles of the day. So let's move ahead from a time standpoint. But I just thought that was kind of cool as we look at that. So we have a, a feature every week called Tech Talk. This one, this week we talk about Chat GPT is showing signs of showing laziness. Tom, I'm going to let you run with this because I know you got thoughts and so forth.

Yeah, we won't spend a lot of time on this, but I noticed this myself Monday. So I was in using Chat GPT, I was asking it actually to write an article that was about a thousand words. And it started off and wrote, started to write the article, got about 300 words into it and kind of just, I kind of laughed. I mean we've all probably done this. When we've written the paper or a presentation, we start off like with a bang and then we get about halfway through and we get tired of doing it and we kind of quickie the. The last part of it just to get it done. That's exactly what it did. It kind of like it, it just kind of just stopped it.

It.

It was doing full speed. And then it just kind of said summarize at the end, like it got halfway finish. And so I said, try it again. I asked it to try it again. And it came back and said, you know what? If you need this, you can do it yourself, basically.

Did it really?

Yeah, yeah. You know, I can't. I think it was a little nicer than that, but it was like, I don't have the capabilities to produce that, but here's how you could do it yourself.

Okay.

And I hadn't seen this before, and I just, I thought. And then the next day I started to see these things. So where others were obviously seeing the same situation. Yeah. And then OpenAI came out and said, well, we don't know why it's happening, but we'll. We agree that it is happening and we'll work on fixing it.

Well, then all the pundits started on Reddit and everywhere else that's saying that they're throttling the system to save money and doing all kinds of things. And I think to your point. Right. Is I don't think they know yet.

Right.

Finish up on this topic. I have a question for you related to this as well. As we kind of wind up on this particular article, I do believe that.

Somewhere someone tuned or trained the model to say optimize.

Right.

I mean, everything that these AI systems do requires energy.

Yep.

Right. Whether it's computing energy or whatever or. And we know that the systems right now are a bit overloaded. So I wouldn't be surprised at all if there was some optimizations that were added to the model to try and get it to optimize energy and to save energy. How it's manifesting I'm not sure people fully understood, but it's interesting to identify how it. It's no different than us as individuals. Right. It's like we run out of steam. We just, you know, start. Stop our workout and go home. Right. It's kind of like what it. What it did here, which was. I have seen it much better the last couple days. So I'm thinking that whatever came out of this, they've done some things to potentially address. But I really noticed this for like a day or two.

You. You work in other models besides chat GPT with what you have Going on behind the scenes for our company. Have you seen the same thing with other models or.

No, it was just with open AI. It was just the open AI model.

So it's interesting, right? So that, that just kind of just. And this literally just. I don't have it in my notes or anything. This just triggered for me is, you know, I think what's interesting, and we've been talking to quite a few people, most recently about our, as an organization, our company, about an AI roadmap and working very closely with that. And the idea behind where we are today is very different than where people are going to be very shortly. And I look at it as, you know, we talk to people quite regularly who, you know, there's AI products that have been in the market for a couple years for distribution and manufacturing that are using a different model than generative models. Generative models are kind of, correct me if I'm wrong here, but more of the where the future is lying in these settings and there's people kind of struggling with the model works, but I'm not getting the optimal results from it right now. Things are getting better every single day. But now I'm also seeing people that, you know, we would, I guess you'd say we might call competitors coming out with some pretty dramatic statements about what they have with some AI capabilities today. And if they're using as an example is to this article, perfectly, if they've rushed to the market with some things that are using OpenAI and the generative model of ChatGPT behind that, and they're betting the world on it, they're going through the same learning curve, the same hiccups and the same pieces, but that could impact their customers. I'm not trying to throw rocks or stones at anybody particular, but I think the caution that I think people need to have is if I were looking at a vendor, and I think you probably do this with our vendors that we use is look at their roadmap, where they're at today, what they're doing, but where is their roadmap versus all the main things they have today? Because if you've got a lot of things today, there may be some challenges that could go with that. As we see these types of hiccups.

It'S even more than the hiccups. The product roadmap is more important right now than the product itself. Because if you're not looking to the future of where this is going, you're going to engineer yourself to a corner. And there's never been a time I'VE seen in my engineering 30 years where a poor design engineering decision now can have a huge downstream ramification because you've engineered yourself into a corner not only from an engineering perspective, but from a customer perspective and from a product perspective. So you're roden up in your horizon right now and looking out on that horizon and the time you're spending on that and then backwards and how you architect that is the most important thing right now that in my opinion engineering or a product manager organization do. And that's true. A vendor or as an IT organization or anything. Anybody who's looking at a technology roadmap, we should probably do a whole thing on that because I think it's a real important issue and I do think a lot of companies have either internally or through products made quick decisions to go, hey, I got AI and then themselves a situation where they may have engineered themselves into a corner either from a product perspective or engineering perspective.

Had a new LinkedIn connection earlier this week that sent me a four paragraph note right after we connected on LinkedIn. He funny found us through through the podcast here and he wrote me four paragraphs about an AI tool that he bought that isn't giving him the results that he was looking for because it doesn't know how to work. I don't say it doesn't know how. It struggles to understand how to work at a SKU level in context of what somebody's trying to accomplish. Right. So things are gonna be changing quickly. I think the. And this might be a little bit self serving but I'm saying anyways, who you partner with, what their understanding of these things are and what the roadmap for AI was and then also the platform. Right. That they're using and working with on these things matters. And we're going to. Obviously we'll talk more about that.

Everything matters.

So yeah, yeah. So let's jump ahead. We have a feature every week before we jump into this as a quick reminder, if you're listening on the podcast on Apple Podcasts, Spotify, Odyssey, wherever it might be, those that were with us for the live broadcast, it's Friday, December 15th at 9:53am Pacific Time. Those with us live are looking at an email newsletter we send out every week. It's called around the Horn in Wholesale Distribution where we talk about M A AI technology, the economy, how it relates to manufacturing, wholesale distribution. If you don't get that you get a newsletter and you'd like to simple way go to our website for the podcast. It's www.roundthornpod.com and all the previous episodes are there as well as signing up newsletter or send us an email email that said at the address of hello we'll get that out to you. So part of what we each week is talking about but surprising to me this first grain sold to private equity firm here in Southern California E Industrial which we bought early 2000s. Friend of the show who's with us off and on here is Joe McCluskey. Joe's a former senior Granger executive that ran that company for quite some time and I pinged Joe yesterday asked him what's going on and why and he was sounded a little befuddled. I've I've texted this morning with a handful of other former Granger executives and nobody's got any clarity to why this this got sold to private equity but interesting move I'm sure there was a lot of money made and long since the family that owned ENR Industrial is back as with another company back in the same same marketplace. In fact we have a talk about in a moment Affiliated distributors they're back with another company that's part of the ad. So it's kind of interesting to watch the world spin here a little bit. So interesting thing with with Grainger Net plus Alliance they publish regularly the outlook, the sentiment from their members Jennifer Murphy and Dan Judge and his team. I think Dan was with us today optimistic outlook for 2024. This obviously came out even before we had some dovish words from the Fed earlier this week. So that kind of comes in in align with what we talked at the beginning of the show. Tom, did you have any thoughts on the the Net plus info that was there?

No, it was you know kind of aligns with what we've been hearing. So yeah.

And then another I I called it, you know you didn't use the term in here when you put the newsletter together. I I was messaging with a couple of large ad members yesterday about this and I used the phrase aqua merge because you know other than I think one of these over time just calling a spade a spade right is when a small group joins a large group it's an acquisition. But we use the term kind of merger in these things to to keep everybody happy and comfortable while the transition happens. I think aqua merge is the right right term here but adid another one in a really cool vertical ride, low voltage and Internet cabling type stuff connectors and kind of a new segment for them to bring this group in. So I think that one's exciting. So quick closing on the day we use a ad each week an article we call it Good Read. This was a kind of cool article from Inc. Magazine talked about 24 years ago. A Harvard researcher came up with some tools on productivity and you know, expanding productivity by 65% and people still aren't using it. Great Reef. You haven't read it. You can just look for it in ink as well if you don't get our newsletter. But you know the comment that they. One of the things that came out of that they were just a lot of it is just interruptions. Right. And whether it's you know, slack or zoom, email, phones, text messages, we have interruptions all day long.

And they called it time Confetti.

Exactly right.

I thought it was great. I thought this article was one of the better ones we've had on the Goodreads for a while. I think it's really got some very good practical things and some eye opening things.

You catch that on the. How many times the average person checks their email a day?

Was it 70 something or whatever?

77 times a day. And you know what all this stuff, I mean you and I are on teams, messaging all day. Others in the company, we've got their own text messages that are coming in and we look at these things. The core of it was unless we manage these things, we don't have the time to do the job we're paid to do.

Exactly. Nope. You end up basically interrupt mode all day long and nothing really gets done. And it's worth when this all happened. But yeah, it was a great article, highly recommended. It was really, really kind of thought provoking.

Well, that wraps kind of things up for us for this week. Any excitement for the weekend planned?

I got to do some Christmas shopping. So better than ever I expect you.

Will be at working on the next models for AI.

Get the models to do them for me. That's what I'm going to be working.

I would say get a model. So you're shopping.

That's what I mean. Yeah.

Very, very good. We appreciate everybody being with us. It was kind of a quiet day for comments which is kind of surprising. But some good articles. Neat things happening out there. You know if you're. If you're managing technology within your organization, we hope that we bring some value to you on the technology front. We try and come together each week and bring all of this information together for wholesale distribution, manufacturing. Again, if you don't get our newsletter and you'd like to get it, please let us know. We're here every Friday. We've got some downtime coming up because of holiday times. Last thing before we go today. Mark your calendars. January 12th, we'll do the announcement. Might not do it till the first week of January, but we have a blockbuster event. I think people will be very surprised to see the three people that are our guests in the same place at the same time. I'm, I'm gonna pat myself on the back that I got these guys together and it could be a block, actually. It has the, the capabilities of being our best show ever or the most.

The most outrageous confetti.

The most, the most outrageous ever as well. But mark your, mark your calendars for January 12th. We're closing. 9:59, 30 seconds on Friday morning the 15th. People, friends, been with us. Have a fantastic weekend. Be safe, be kind and do good things and we'll see you next time.

Have a good week.

We hope you enjoyed today's episode and our guests. Each week we try our best to dig into the topics that are impacting your business. So please reach out to us and let us know how you think we can make the show better or topics you'd like for us to tackle or talk about more often. And even guests you'd like to see join us. We're looking forward to bringing you next week's session and hope that until then you stay safe, stay focused, and do great things. If you haven't already, please subscribe to the podcast and leave a review to help others in wholesale distribution get access to the conversation. And finally, please check out our sponsor, Lead Smart Technologies and their manufacturing and wholesale wholesale distribution industry CRM customer intelligence and channel collaboration platform. That's LeadSmart Technologies at leadsmarttech.com.