This episode of Over the Edge features an interview between Matt Trifiro and Walker Reynolds, President and Solutions Architect of 4.0 Solutions. Walker’s mission is to save and create middle-class jobs by helping manufacturers become more efficient through successful digital transformation efforts. He dives into the fourth and fifth industrial revolutions, and how he approaches digital transformation within an industry where many companies have fallen behind.
This episode of Over the Edge features an interview between Matt Trifiro and Walker Reynolds, President and Solutions Architect of 4.0 Solutions. Walker’s mission is to save and create middle-class jobs by helping manufacturers become more efficient through successful digital transformation efforts.
Walker dives into the fourth and fifth industrial revolutions, and how he approaches digital transformation within an industry where many companies have fallen behind. He explains how 4.0 Solutions evaluates digital capabilities within their clients’ companies and what factors indicate that a company is capable of improving. This conversation gives insight into technology applications across the manufacturing plant floor and into the ways that Walker thinks the industry could solve its biggest problems.
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“It is the convergence of artificial and human intelligence. That's what the fifth industrial revolution is. And when we talk about industry 5.0 or the fifth industrial revolution, that's what we're talking about. We're talking about being able to take the best person you have in your organization and put them on the biggest problem, no matter where in the world that biggest problem is.”
“Do the people at the helm of your organization understand what digital transformation actually is?... Well, it's about unlocking potential on the plant floor to start. The smartest people in any manufacturing organization, they are the people who do the actual work on the plant floor.”
“And what I realized was, holy cow, if you could unlock that potential in all these operators, you could solve the manufacturing exodus problem in the United States overnight. If you could suddenly be able to figure out how to tap into the operator's knowledge and enable them to solve the business's problems, you would solve manufacturing in the United States overnight. And that's what digital transformation does.”
“If everyone in your organization can't recite from memory what the digital strategy is, you don't have one because every person in the organization is a node in an ecosystem. If they don't know how they're inter-operating in that ecosystem, well then you don't have a strategy. Or you didn't communicate it.”
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2:36 Walker’s start in tech
6:45 Understanding industry 4.0 and 5.0
10:10 How advanced are most manufacturers in the U.S.?
11:21 The top digital manufacturer
14:44 How does Walker determine whether an organization can improve?
17:00 Solving the manufacturing exodus problem
20: 35 How Walker gets leadership buy-in?
23:46 Intellic Integration and 4.0 Solutions
33:08 Factory floor examples / Kepware
39:12 Defining HMI, OPC, PLC
41:45 IoT and the Internet in the industrial world
44:40 The two steps of digital transformation
46:30 Example of how data supports consumables
48:30 Factories leveraging cloud
54:00 Digital and human advantages to using data to react in real time
57:22 What is Amazon doing right?
61:04 Data centers as factories
1:02:02 Speeding up the revlitalization of the manufacturing industry
[00:00:00]
Matt Trifiro: Walker, how you doing today?
Walker Reynolds: I'm blessed, man. How you doing?
I'm doing great. I'm doing
Walker Reynolds: Sorry, real quick, Matt. I do listen to your podcast, by the way.
Matt Trifiro: Is that. Very cool. Very cool.
Walker Reynolds: to a couple of different ones. I get 'em in my Apple podcast, but I do listen to your podcast. It's just whether I get to it in week, so I actually dig it though. I
Matt Trifiro: Wow, that's totally cool. Well, thank you. nice to have another fan and I'm definitely a fan of yours. you're sort of, in many ways the peak of your career. You're certainly somebody who people look up to from an IOT and a manufacturing automation perspective.
But how'd you get your start in technology?
Walker Reynolds: I mean, that, story's long. So I'm gonna try and do the, Cliff notes version. But, you know, I grew up in upstate New York in the 1980s. they call it the rust belt now, and it's when massive manufacturing exodus. probably the, manufacturing exodus that had the biggest impact on the area where I grew up was when IBM moved from Johnson City to Research Triangle Park in North Carolina.
So they moved from New York to North Carolina and there was this huge mass exodus of people who lived in the Southern tier, who moved to North [00:01:00] Carolina. I actually went to college, in upstate New York my freshman year, and then I transferred and I,went to college in Raleigh and so I, got a chance to see I, with my own eyes, the impact of the manufacturing exodus.
On communities. And conversely, I got to see the positive impact when manufacturing came to an area. So in 1993, Raleigh and Research Triangle Park was rated by Money Magazine, the best place in America to live. And part of the reason it was rated was because all these manufacturers had migrated from the Northeast into Raleigh.
Well, I, I started studying, sociology in college and I took a couple of courses in employment where I, I thought the reason that manufacturing left Upstate New York was because, manufacturers were greedy, corporations were greedy, and they were chasing cheap labor. I learned it was much more nuanced than that.
what it was was manufacturers had to chase cheap labor for a reason. And the reason they had to chase cheap [00:02:00] labor was because they made a strategic mistake. During the third industrial revolution, when automation came along in the 1960s, late 1960s and 1970s, the Japanese and the Germans adopted automation much faster than American companies did.
And because they didn't adopt automation so quickly, it put them at a strategic disadvantage. in key markets, specifically like the automotive industry. and a lot of suppliers that were based in upstate New York companies like Magna, they were forced to end up having to migrate to places where there was cheap labor because they didn't leverage automation either.
So that's my sociological background, like my experience that made me realize, wow. Manufacturing is really, really important to a vibrant middle class. I saw the middle class die in upstate New York, and I saw it grow in North Carolina with my own eyes. my education taught me the why. Right?
Well, I personally believe engineers are born, they're not taught. So I always thought like an engineer. I'm a kid who I tore apart my toys on Christmas morning. I've always been very [00:03:00] technical, right? I went back to school and got a degree in electrical engineering after I got my first job.
I got a degree in sociology. I was gonna teach, I was getting a master's in education and I got a job working in assault mine, and I was introduced to industrial automation. The only technical training I had up to that point was I got a certification in five volt DC systems when I worked in an arcade in college so that I could work on pinball machines and repair video games.
That's it. I could read i e c drawings. And I knew fivefold DC systems. I didn't know what three phase electricity was. I had no idea what three phase was. I knew none of that stuff. I get introduced to industrial automation in the late 1990s with my first job outta college, and I realized everything sort of converged.
Oh wow. this is how I can help revitalize the middle class. I can help use technology to make American manufacturers more competitive in a global market. And that started my journey.
Matt Trifiro: Yeah. You know, one, one of the things that I, really liked, learning about you online has been your passion for these, [00:04:00] small and medium sized manufacturers. and really focusing on helping them become competitive on a global basis. that's really pretty neat. now you're, the head of at least two companies I know of, one of them being, 4.0 solutions.
And actually before we go into 4.0 solutions, you mentioned, this sort of industrialization, right? And you talk often of Industry 4.0 and it's kind of a buzzword. And now you've even started talking about Industry 5.0. So you can just help us understand maybe not the full arc of all the industries.
Cause I think my audience has been through that before, but how you define Industry 4.0 and how you see us transitioning to what you're calling 5.0.
Walker Reynolds: So I'll start with this piece. here in the United States, specifically, when we say Industry 4.0 and Industry 5.0, what we really mean in most cases is the fourth industrial revolution. In the fifth industrial revolution, we converge the terms here in the us. In Europe, for example, if I say Industry 5.0 or Industry 4.0, what they're gonna talk about is a specification for the fourth industrial revolution or a specification for the fifth here in the United States.
We [00:05:00] really combine those two terms together. whenever you hear me say Industry 5.0 or Industry 4.0, I'm really saying fourth industrial revolution. Fifth industrial Revolution. And the reason why I use those terms is cuz if you talk to the average person in the United States and they say, Industry 4.0, they don't mean the EU specification for digitization of manufacturing.
They mean the fourth industrial revolution, right? It's just that the terms have become synonymous. most people I don't think understand as a sociologists, one of the things I learned was that industrialization is just a natural, progression of civilization. Like industrialization isn't something we did.
It's something that was self-evident. It was going to happen, right? You're going to create a printing press, so then you're gonna be able to communicate on mass, you're going to create a steam engine, you're gonna create some type of mechanical engine. You're gonna transfer physical properties in, nature, into mechanical energy.
To do work, you're gonna create an assembly line. Right. So industry 1.0 was the steam engine industry. 2.0 was the [00:06:00] assembly line. Industry 3.0 in 1969 was automation. It was the automation of industrial processes. Industry 4.0 fourth industrial revolution came right after TCP i p one, the Protocol Wars in the late 1990s.
And what we had was a standard protocol for digital communications across industry. And what ended up happening with that was we could start automating business processes. So Industry 4.0, the fourth industrial revolution is all about O T I T convergence, taking operational technology stuff on the plant floor, merging it together with informational technology, the stuff on the carpet side of the business.
And once we do that, we have that data merged. We can start automating business decisions, we can start automating. our schedule. For example, if I planned on producing good A, B, C, D, and e in order, I can, by converging my data together, I can use software to determine how I should actually schedule, right?
So that's the automation of business processes, automating the [00:07:00] triggers that tele,material handler to bring the raw materials from the warehouse to a certain location on the plant floor. That's the fourth industrial revolution. The fifth industrial revolution has started, okay? And it started in, November of 2022, with natural language processing.
That will definitely be the rising edge of the fifth industrial revolution. And it is the convergence of artificial and human intelligence. That's what the fifth industrial revolution is. and when we talk about industry 5.0 or the fifth industrial revolution, that's what we're talking about.
We're talking about being able to take the best. Person you have in your organization and put them on the biggest problem, no matter where in the world that biggest problem is. That's what Industry 5.0 is.
Matt Trifiro: Yeah. Very cool. Very cool. so when you look at, manufacturers in the us, most of 'em, on the spectrum of using large language models to improve their factory to on the other end, like walking around with a pencil and clipboard. where are most and medium sized manufacturing businesses.
Walker Reynolds: So you have two types of manufacturers. You have the manufacturers that'll make it, and those [00:08:00] who won't, I'm only gonna talk about those who are gonna make it. Okay. if what we do is we drop out the manufacturers that are just too far behind, and they're gonna either get gobbled up or they're gonna get, destroyed by, Let's talk about who's gonna remain. we have a digital transformation maturity assessment on a scale of zero. To 100. Okay, so basically we score organizations on a scale of one to five across 10, industry 4.0 pillars, and then we multiply by two, and that gives them a score on a scale of zero to 100.
The mean score right now is about 51 out of a hundred. Okay? So that means on the 10 pillars, the average company is less than a three okay? They're at about 2.6, 2.7, give or take the standard deviation's about 15. Okay? So if you look at Tesla, who is two standard deviations above the mean, Tesla is number one in the world when it comes to digital.
There is no more digital company on the planet. It's not even close, okay? Honestly, they're an 87 aggregate score. The next closest company is about an 82 and a [00:09:00] half, and that is a huge difference on the edges. I mean, that is a massive difference. Tesla is so far ahead of the game. the average company is right about on the mean.
And what does the mean mean? It means that they're strong in maybe three of the areas, and they're weak in seven of them. they have intelligence on the plant floor. They got intelligence on the IT side, but they don't have 'EM connected. That's the average business.
we talk about this. If you look at the automation stack, right? You've got plc, HMI on the edge, you've got supervisor control and data acquisition. You've got manufacturing execution layer. you have e r p, which is, most people are familiar with the E R P later, and you have cloud. The average organization, about 90% of manufacturers in our sample set, which is 1,380 something companies.
That middle layer is all paper. MES is where the sales order becomes manufacturing and in 90% of companies, that is.
Matt Trifiro: like literally
Walker Reynolds: It's
Matt Trifiro: pulped wood.
Walker Reynolds: right? it's literally paper on a clipboard. It's people carrying a traveler literally physically [00:10:00] taping it to a pallet that's the average company.
they have no insight into their operations in real time. at best, they may have like daily transactions. So that I'm running a transaction and I'm collating all that paper together to give me insight on where we actually stand. The most elite organization in the world.
Tesla, for example, doesn't even look at today, they're not even looking at right now. their operation is so, so digitally integrated all the way up through their supply chain. If you look at Saint Cobain, who supplies windows for Tesla vehicles, Tesla has insight into St.
Cobain's inventory in real time, and it is taken into account in their planning for manufacturing vehicles. They're not even looking at today. looking at next week and next quarter. That's what they're looking at when they're looking at real time. They're looking at predictions for next week, next month, next quarter.
In real time. That's why when I see these analysts on CNBC talking about Tesla, you know right away the analyst who has no idea what they're talking about. Because as an engineer, [00:11:00] when you walk into a gigafactory and you walk the plant floor, if you've worked in automotive at any time in your life and you walk into a gigafactory and you go from one end to the other, you come out on the other side.
If you work for Toyota or General Motors or Ford, you walk out on the other side going, we're out of business. You don't walk out on the other side going, I have an idea to improve our business. You walk out saying, I need a different job. That's how far ahead Tesla is.
Matt Trifiro: and they're only in 87, you said?
Walker Reynolds: at 87. Yeah,
87. Aggregate. Yeah.
Matt Trifiro: that's quite a delta. so you, mentioned the companies that aren't gonna make it and the companies are gonna make it. are you saying that, there's a bunch of companies at the median 50 ish on the score.
they're still mostly doing it on paper. and you think they can up their score on those other, pillars and,
Walker Reynolds: Yeah, absolutely No question. how do we determine whether they, ask us to evaluate? do they have a chance to change it? Yeah. The answer is really this, do you have transformative and disruptive leadership in your organization? We'll talk about the leadership piece.
Does the people at the,the helm of your [00:12:00] organization understand what, digital transformation actually is? Okay, number one, and what is it? Well, it's about unlocking potential on the plant floor to start. To start, it's about just unlocking potential. It's, you know, the smartest people in any manufacturing organization.
They are the people who do the actual work on the plant floor. I, if there's any, the greatest lesson my father ever gave me when I graduated from college, I was the first one to graduate from college in my family and before I went to go get a job working in the salt mine, and I only had a degree in sociology by the way, at that point, my father said to me, nothing you learned in school makes a bit of difference in the real world.
He said, I'm proud of you. I'm proud of you, but nothing you learned in college makes a bit of difference in the real world. And what he said is, your real education starts today. And he said, I'm gonna give you a piece of advice. He said, when you go to work in that salt mine, okay, you're gonna see two types of college educated people.
You're gonna see the college educated person who thinks they know everything, and you're gonna see the college educated person who's there to [00:13:00] get a new education. He said, you need to be the latter. And he said, so what you need to do is you need to find somebody who's got 20 or 30 years of experience.
You go in humble and you learn everything you can about what they know, and then you take what you learned in school and you put 'em together. He said, that's what your five year plan needs to be. And my father was so right about that. What I ended up learning was that the most valuable commodity in the American economy is the human worker.
It's the worker. It's the person who does the actual work on the plant floor. And I used to say this all the time when I was an electrician, early in my career, I was an electrician. I would literally go to the operators and I would say this, I would say, you know what my problem is if I get ever get called out here to fix something, you already know what's wrong.
You may not know how to say it in the technical terms, but you are the key to me getting this fixed in 10 minutes rather than three hours. I'm gonna do something for you, number one. If it's, if you're [00:14:00] ever at fault for the reason it's broken, that is you screwed up. I'm always gonna cover for you.
I will always come up with a different reason why it broke as long as you always tell me the truth about what the problem is. Okay? And that was one of the smartest things I ever did in my career because it opened up a line of communication between me and the operators that many of the other engineers, many of the other, company people just did not have.
And what I realized was, holy cow, if you could unlock that potential in all these operators, you could solve the manufacturing exodus problem in the United States overnight. If you could suddenly be able to figure out how to tap into the operator's knowledge and enable them to solve the business's problems, you would solve manufacturing in the United States overnight.
And that's what digital transformation does. I ask executives all the time, what is your plan for recruiting and retaining the employee of the future and who is the employee of the future? If you look at retention for Gen Z and millennials in [00:15:00] manufacturing today it's less than 50% at the 12 month mark.
So if I hire somebody who's a millennial to work in my manufacturing facility, there is a 51% chance or greater, they're gonna quit within the first 12 months. I'm a Gen X guy, that was a 10% number for my generation, right? there was a 10% chance that they were gonna leave. Now there's a 51% chance they're gonna leave.
Why? Because they don't wanna work at 50 years in the past. You have to the
Matt Trifiro: If they're making a video game.
Walker Reynolds: right? they are used to solving their own problems in their daily life. they're not used to the. Data on a need to know basis. You know, not being able to access their cell phone on the plant floor, which by the companies that don't have wifi for their employees.
That just seems so ridiculous to me. It's that kind of thing. Digital transformation is about enabling the frontline worker to solve your company's problems. That's how it starts. Okay. that's not their journey
Matt Trifiro: Well, I was gonna ask you how many humans are on the floor of the gigafactory?[00:16:00]
Walker Reynolds: There are, well, when we say floor, do we mean I'm standing on the concrete or sitting in chairs and control rooms?
Matt Trifiro: Fair enough. Yeah.
Walker Reynolds: If you look at the total number of employees that Tesla employs, they employ a lot of people. Okay. They employ a lot of people. Tesla plays a much bigger role in the survival of their suppliers than the average automotive auto manufacturer does.
Okay? Because There is a value proposition that Tesla provides that other manufacturers don't provide, and that is access to the data that Tesla collect. Tesla's not a car company. They're a data company who manufactures cars.
Giga wasn't designed to make cars. It was designed to make everything. What's the Future manufacturing. It's contract manufacturing. You're still gonna have vertically integrated businesses and specialized manufacturing, but the vast majority of our manufacturing is gonna be contract, certainly 70 to 80% in the life sciences industry.
For example, if you're a life sciences company who [00:17:00] is vertically integrated from research all the way out to, you know, your Salesforce selling the drugs to your drug, you're dead. I mean, you're, you bet you're not going to be manufacturing your own drugs, okay? you will not be manufacturing your own
Matt Trifiro: You'll be send, you'll be sending a, a digital file. That,
Walker Reynolds: right. You're gonna be sending a digital file to the people who have mastered the art of manufacturing drugs in bioreactors. Right.
Matt Trifiro: Yeah. that's really interesting. so let's talk about the leadership. You mentioned the leadership, right? So I imagine you can't get much done without leadership support. how do you get leadership on board?
Walker Reynolds: Well, okay. So number one, the first thing I do, what we do with leaders is we wanna find out what their values are. Okay. So look, you're gonna ask me about my companies and, we are a values based organization. and what I mean by values is our mission is to help save and create middle class jobs in the us.
To that end, one of the things that we did when we first started was we worked in with oil and gas customers. Who could afford to pay in a [00:18:00] premium for our services so that we could pass on that premium to mom and pop manufacturers who couldn't afford to pay what oil and gas customers did. So we used to say to our oil and gas clients, and we still do to this day, not just oil and gas, but life sciences as well, the industries that pay the premium because they're difficult to work with, right?
Or they want it done two weeks ago, so they're gonna pay a higher price to try and get it done as fast as possible. We tell them one of the values of working with us is that we are going to pass on the premium you're paying, and sometimes we're gonna do projects at a loss or at net zero for manufacturers who can't afford to do what you're doing.
We're passing that on. We're a values-based organization, right? So one of the first things we try to ascertain from leaders is what are their values? What are their core values? What do they believe in? Right? I mean, is are they purely capitalist? That is to the extreme where people are a commodity.
They're not a resource. Right. so assuming that the organization shares our values, then what we [00:19:00] wanna do is we wanna ask them three questions. Question number one is, how do you lead, what's your job as a leader? And if we don't get an answer, like it's our job to transform or disrupt or enable, if we don't hear those keywords, transform, disrupt, enable, then we know we're probably, they don't have the right leadership.
Okay? If they don't believe that they need to have a strategy for making products that get better after customers buy them, then we're probably working with the wrong leaders, right? If they don't think the right way, then we're probably not working with the right leaders. Now that doesn't mean we can't work with that company, but they have to understand, they need to bring in leadership who understands those things that are missing.
Okay? So the leadership piece is all about strategy and enablement. We have a strategy for becoming a digital company, and we're gonna make products that get better after people buy them. We have a strategy for recruiting and retaining the employee of the future by enabling to solve their own problems, which in turn solve the business problems.
That's what you're looking for in leadership. That's what you're looking for. Okay. the, [00:20:00] then what you're looking for beyond that is do you have the pieces within the organization to identify the problems in the business and enable their solutions? That's the next step. We have a process called the Digital Transformation Maturity Assessment that does all of that, and that's what we teach at 4.0 Solutions.
One of the things we teach other integrators is how to assess. here's the questions you need to be asking. Here's how you overcome these specific objections. Here's how you identify the caveman, the citizen against virtually everything. Here's how you overcome the immovable object within the organization.
Here's how you plot a course for success.
Matt Trifiro: Got it. Now, you mentioned 4.0 solutions, one of your companies. what is the purpose of 4.0 Solutions?
Walker Reynolds: All right. So, so I own, I have 49 companies altogether, but five of my companies are in the automation
Matt Trifiro: Okay, let's talk
about those.
Walker Reynolds: So I'm gonna talk about just the two most important, which are Intelli integration was my full service systems integrator, where when I worked for another, [00:21:00] I worked for a couple of like world-class integrators.
I was manager of Texas operations for this, big integrator based in California. And I came home one day and said to my wife, you know, I think I can do this better. I think I can create the type of place where I would wanna work. Because I think the biggest problem in our industry is the way that integrators are organized right now.
That is the vendor relationship. The vendor has too much say in the recommendations that an integrator makes to a client. the way that they structure the business. Applications engineer, senior engineer, Junior, the apps and the senior engineer are the ones who are selling everything.
You know, they're overselling and under-delivering, and then they're turning it over to a junior who doesn't have nearly the technical capabilities that those senior engineers have. So I was saying to my wife, I can create a place that I think does it better, and the goal will be mission-driven, values-based, and high retention.
So we want super, super low turnover. Intelli Integrion was always focused on digital transformation. We got famous by [00:22:00] building the world's largest standalone SCADA system in the world, actually at a fraction of the cost of the next nearest quote. It was one 50th, the next nearest quote, or one 25th. here's what happened.
I wanted low retention for three years. My engineers were, we were basically just coming behind other integrators
Matt Trifiro: In fixing.
Walker Reynolds: fixing, okay. And what we realized was all the same mistakes were being made. So it wasn't like this integrator made this mistake and that integrator made this other mistake.
It was the integrator working with their vendor and the end user were all making the exact same mistakes in the first try. Okay. and they basically boiled down to three things. They had the wrong strategy, they picked the wrong technology, they were using the wrong partners. That's it. If from a, if you're gonna distill it, it's one of those three.
So we started shooting YouTube videos in 2018. Initially, the YouTube stuff came from Zach's Scriven, who's, he's our media partner. Zach used to be an integrator. I've been friends with him for a very long time. He [00:23:00] starts a media company. He's like, do you wanna sponsor my podcast? Yes. I wanted to help him out.
So I'm like, why don't I just hire you to shoot content for us, The deal is, I will not be in front of the camera though, so you cannot ask me to get in front of the camera. He says,
Matt Trifiro: That didn't last very long.
Walker Reynolds: It lasted only six months.
That's it. Zach tricked me. he said, Hey, come out here and, you to shoot a whiteboard video.
I have a video editor in the Philippines who doesn't understand what we do. I want you to explain to that video editor what digital transformation is. And I started with the automation stack, and when he published those videos, that's why I'm not wearing a mic. He just tricked us and it, they all went viral.
So what we realized from that moment was education was what we could provide. So we started just educating on the mistakes people are making. Okay, here's the mistake the vendor's making. Here's the mistake the OEM is making. Here's the mistake that the end user's making.
What ended up happening was a couple years in. You know, we grow this huge following and we create a Discord server to bring everybody together. And [00:24:00] once we had everyone together and the people who were following us could communicate to us directly, easily, the first thing they asked for was more educational content.
And so we created a separate entity to manage that. So our goal at 4.0 Solutions, is education and outreach.
Because I think the best ideas have to win. And the best way to do that is to share all the ideas. So that's, that's our goal. We have. We have free content and we have commercial content. And the only commercial stuff we have helps us fund. I mean, this is very, I don't need to tell you guys this, this is very expensive to do.
I mean, um, I've spent millions of dollars since 2018. I think I'm over 2.1 million just on digital media, and I haven't made 2.1 million on digital media, but I indirectly, I think I've certainly gotten my money back. But our goal is to help educate the industry and, and keep people from making the same mistakes over and over and over again.
Matt Trifiro: so still does the system integration work.
Walker Reynolds: still does and, and the way we're, the way we're actually, um, structured, [00:25:00] it's 4.0 solutions has essentially seven products, right? So we have, we do vendor training. So vendors, instead of them having to develop their own training programs, the vendor can come to us and we can, we
Matt Trifiro: Build out a training program. Yeah,
Walker Reynolds: Program forum. We have enterprise training for really large manufacturers. So in, uh, if they want to do digital transformation and have every employee go through it, really, really big companies hire us to do their entire digital transformation program. then@iiot.university is where we do all of our core stuff, all of our workshops, like we're doing chat G P T on Wednesday, we're doing our second session chat, G P T, we did a MES bootcamp.
Uh, we have mentorship, which is a, where we teach engineers how to support digital transformation. That's a recurring program. So we meet once a month. This year we're doing a virtual factory. We're actually digitally transforming a virtual factory this year with the mentorship program and the mastermind program is where we're teaching the leaders how to guide, how to lead these programs, strategy, [00:26:00] architecture, minimal technical requirements, and what's amazing, this is the most amazing thing to me, Matt, my team just gave me all the, the metrics on our training programs, our churn rate.
So that we have people who have been in these programs for three years, and our turn rate is less than 10% year over year. It's like 8%,
Matt Trifiro: The peop the same people are signing up just to get the,
Walker Reynolds: They're recurring. They're they're recurring every year. Yeah. And, and at the end of the day, you know, there's a guy named Dave Schultz who made this joke, I think, you know, summarizes what it is we've been trying to do.
He said, you know, I learn more here by accident than I do in other places on purpose, you know, and, and so that at the end of the day, that's what we're trying to do. We're just trying to educate.
Matt Trifiro: Yeah. Yeah. and I love the Happy accident story, right? It's like, well, I set out to do system integration and I ended up starting a media company.
Walker Reynolds: Yeah. Yeah. and at the end, I never wanted to be in front of the camera. this, the whole camera thing and shooting the podcast and all of that's been pushed by our team.[00:27:00]
Matt Trifiro: I, and I think that's part of what makes it good, right? Like it's just like, oh, walker's here.
Walker Reynolds: I'm not known for being very diplomatic,
Matt Trifiro: Exactly, exactly.
So let's, do some educating. So, walk me through,a small manufacturer. So you, go to a small manufacturer, let's say they're at the 50% mark got a bunch on paper. what does the factory four look like? What's their technologically and where do we start?
How do we add things into this system?
Walker Reynolds: how about I give you an actual example? we are a Kepware partner. So, that is, PTCs Kepware. if you were to go to Kepler's website and look for an integrator who, does Kepware integration, our company will come up,
Matt Trifiro: What is Kepware? What do they build?
Walker Reynolds: So Kepware builds what is known as an O P C server. Basically it is a OT communications translator. What it does is it's a piece of software that runs like on a desktop, and it has drivers that lets it talk to any of the smart things you have on the plant floor. So it has a driver for Siemens PLCs and it has a driver for Alan [00:28:00] Bradley PLCs.
And so what you can do is you can take all of these various languages, you know, that Siemens and, Rockwell and do more PLCs talk, and you can put them in one place. You can pull the data and put it in one place, in one common language, known O as O P C U A. That's what Kepware does.
That's called an
Matt Trifiro: Got it. So it normalizes all these like bespoke languages that each manufacturer probably used to lock people in at some point.
Walker Reynolds: Oh, that's exactly the point. Yes. So, um, So, what happened was we were called to a local manufacturer here, a small organization that was doing say, 25 million a year in revenue. they're in the packaging industry, privately owned in fact, the guy who owned the facility, he used to be an executive for a really large packaging company in Europe.
He retired, he came here, he bought a small mom and pop organization and he wanted to hand it off to his kids. It was something to give to his kids when he was gone
Matt Trifiro: Okay, so let's describe packaging. what does a packaging factory make? like literally would [00:29:00] they, what did they
Walker Reynolds: So they, you know, in this case, they could make something like this, right? This is made by, this is made by a company called Tetra Pack, which is one of their competitors. Okay? But the packaging these guys were making is, imagine the bags that potato chips and pretzels come in. Okay? there's art that has to go, so they have a printing operation, they have a lamination operation, they have a, slitting operation, and they got a pouch operation and they do, you know, say 25 million a year in revenue.
You go to the store, go in the chip aisle, and they're supplying half the packaging in that aisle, right? So they brought us there and the goal was, we just want to connect to our equipment. we have millions and millions and millions of dollars of assets, but we just wanna be able to talk to the equipment.
We don't know if a machine's running or not running. And what we wanna do is we want you to put Kepware here and talk to this equipment.
they were asking us to solve a problem based on what they knew. Our job was to walk in on the plant floor, solve the immediate problem, but also identify the art of the possible.
What else could they do? [00:30:00] So what we did, we said we'll do what you asked, okay? But in exchange, what we want is we want you to give us access to this printing. Press this Italian printing press over here. Give us 12 weeks and let us do whatever we want to it. Let us show you what's possible and all you have to, and I'll pay for it.
Walker will pay for it. in 12 weeks, I'll show you what you should do with your whole organization. If you like it, you buy it and we do the rest of the facility. If you don't, we'll rip it out and you'll never hear from us ever again. Now the point is, is that that manufacturer they had already mastered the art of what they did.
Everything was on paper. But they had a, small industrial database where they were storing information about downtime and that kind of stuff.
They had state-of-the-art technology on their equipment, but they weren't connected to any of it. In fact, that printing press was running a state-of-the-art motion control package from Siemens, led by a DH 4 45 motion controller, like state-of-the-art stuff, [00:31:00] super, super high frequency data. There was also a database running on that press where every time the operator put in a work order number, the process data was being associated with that work order number for years, for like five or six years, and they didn't do anything.
They had no idea that that was there.
Matt Trifiro: We have five years of data from the database that's just sitting on a hard drive inside this
Walker Reynolds: They had no idea. Right? So what we did was, I and I led this initiative initially. So I did the first year of this, but for the first, the proof of concept, we said we're gonna do three things. What we're gonna do is we're going to look and see what's in that database on that machine, and see if we can provide some value from it.
Number two, we're going to analyze their operators. We're gonna tell 'em which of their operators, what the personalities of their operators are, okay? And number three, we're gonna show 'em the actual downtime that they have on that machine. Because what they had was the operators were keeping track of downtime in 15 minute increments on [00:32:00] paper.
They were, you know, writing down, oh, and they had to always put it in a 15 minute block. Well, I don't have to tell you. That means a one minute downtime, never got logged, a five minute downtime, never got logged. Uh, seven and a half minute downtime, never got logged unless it was close to 15 minutes. It didn't get logged at all.
Matt Trifiro: Right.
Walker Reynolds: So we took 12 weeks. We put in a digital system, single pane of glass. We connected to their database and we got lucky. We discovered that when the operators were typing in the work order number on their hmi, we were able to tie all the process parameters through that work order back to the A specific item number, A package that they were making, and we were able to show them over time, hundreds of work orders where they were running the exact same product and they were running the machine completely differently, different speeds, different tensions, different temperatures, that there was no consistency between operator A, B, C, D, and E, running the same product on the exact same process.
That was number one. Number two, we were about to [00:33:00] tell 'em their highest performing operator, we didn't talk to any of their operators. We said, this operator right here is your highest performer, this operator right here, number four, that's your rogue one. That's the one that doesn't listen to anything you say.
We didn't know who they were. And then the last thing was we showed them their actual downtime, and when they realized that they were only capturing about 40% of all the actual downtime they saw, wow. We don't really have any visibility into our process. So the average manufacturer has technology everywhere, but they're not unlocking the value of that technology.
Matt Trifiro: Interesting. Okay. So you mentioned a couple of acronyms, Is this the benefit of my audience that doesn't live in this world? Can you just quickly define what those are?
Walker Reynolds: PLC is a programmable logic controller.
So all it is is there's a little computer that you can connect sensors to, and it's got logic that runs and based on what the inputs say, we do things to the outputs.
That's a plc. every asset on a plant floor is controlled by a plc, HMI is human machine interface. That's a little touchscreen you see on all the machines. in opc in a nutshell. the acronym itself is not [00:34:00] important, You can go look at the OPC Foundation.
It is basically a standard for open interoperability. So if you see your OPC server, it's a server that's an extension of the O P C. Standard O P C foundation is the organization that controls the standard.
Matt Trifiro: Okay. So when I think of a, PLC program, logic controller, did I get that right? connecting to a device, I don't think of a network, I think of like serial cables. are these, PLCs networked together? Because you mentioned in ethernet, like the big unlock, are they connected together?
Walker Reynolds: they are now. so if we go with just like the PLCs that everyone knows, if you look at, say, Rockwell Slick 5 0 5 s, so right now we're in the control logics family. So before control Logics we had slicks. Before that you had PLC five. So the slick family is the nineties.
At the end of the nineties, there were. 5 0 5 versions that came out that had ethernet ports on them natively so you could plug them into an ethernet network. But the limitation was, is that they weren't [00:35:00] talking ethernet the way like our laptop does. They were talking primarily industrial protocol and ether ethernet IP Today, PLCs like I over my shoulder
I have a PLC next I have an Opto 22 Groove epic over there. They talk native ethernet as if it's a, standard device over T C P I P on your network. The vast majority of PLCs, actually all of them that you buy today, they're treated really like industrial edge devices. So, you know, imagine I took an industrial pc, I put it on the plant floor and I wrote a little program on it and I plugged in the network.
That's how PLCs are operating today
Matt Trifiro: That makes sense. Yeah. on a standard thing. Yeah. so now I've got a network in my factory, right? I've got all these machines generating this data, maybe in incompatible ways, but I have some software, some part of my software stack. The company you mentioned at the beginning has the way of normalizing across all these other devices.
Now I can see how now I've got some centralized, ability to collect data and to, enact based on that, that data. but we also talk about, well, two [00:36:00] things. Okay? So, one thing is when we talk about I I O T, industrial Internet of Things, there's an internet part in there. haven't heard you talk about the internet at all.
This is all like a private land, it sounds like in some cases it's an industrial land that doesn't even align with the regular land. tell me what percentage of the I I I O T is actually on the internet and how do you think about that?
Walker Reynolds: okay, so a very, very tiny percent. Is on the internet. it's a lot better to think in the industrial world, a very high percentage in a digitally transformed organization. All of the smart things in your business are on the intranet, which is the internal internet for your business.
Okay. But it doesn't have access to the internet, which is where all the bad guys are. Okay. or ostensibly the bad guys, a very, very tiny percentage of industrial hardware in the industrial internet of things are actually on the internet. And this is, we're talking single digits here. Okay.
Generally what it's gonna be is a data aggregator inside the internet [00:37:00] has a connection over the wide area network, which passes through the internet into the cloud, okay? Where I have another internet within the cloud in my own private. local area network in the cloud. So I'll have a data connector or you know, a data aggregator, and then I'm connected to some hub in the cloud, and then I go back into the private network on that side.
What's important is the technology you use in order to make those connections, right? So, edge driven report by exception, lightweight, edge driven means that I'm never requesting for data. Okay? in the old serial networks, you had to have
Matt Trifiro: Yeah. Poll it. Yeah. You're constantly
Walker Reynolds: Yep. Poll, poll response. Right? I, I have to check for a change. Most of the technology, by the way, is still designed that way. It still requires poll response, which by the way, you can't scale, you're not gonna be able to collect all data doing poll response, so you need the smart thing. Matt needs to tell me what changed and when, rather than me requesting a, Hey, Matt, [00:38:00] has anything changed?
Hey, Matt, has anything changed at set interval? Matt just connects to me and says, Hey, this value changed. Here's the new value, and here's when it changed. that's edge driven. Report by exception, is the piece you're only sending me the stuff that changed. And lightweight means is I'm using a protocol that doesn't have a huge header at the front end.
That to instantiate the connection, it's not very verbose. So every time we communicate, I'm not wasting a lot of information in setting up the communication.
Matt Trifiro: Right. Well, and it, it sounds like maybe we should call it the industrial intranet of things.
Walker Reynolds: today that would be much more appropriate a term,the industrial intranet of things. Now, what I will say is this, if you look at digital transformation for an organization, it looks the same for everybody, by the way. It happens in two giant steps.
The goal of the organization is to become a smart business. That's number one. A smart business is connected, okay? That is all the smart things are connected together. number two, we store every [00:39:00] data, every transition, and then we use software to find patterns in our data. Predict problems and mitigate those problems.
That's what a smart business is. Okay. The second step is plugging into a digital supply chain. So if you look at supply chain, supply chain is, you know, linear. generally in the old economy, I only talk to the links directly upstream for me and, the links directly downstream. And I only talk to the suppliers who I have relationships with.
And I only talk to the customers. I have relationships with. A digital supply chain is, I plug into a hub and spoke and I am able to make requests to all of the suppliers who could possibly supply me the ones I know and the ones I don't know. And I am plugged into all the customers I could. My total addressable market, that's a digital supply chain.
what is the journey for an organization look like? Well, number one, in that first phase where I'm becoming smart, my goal is to connect, collect, store, analyze, visualize. [00:40:00] Find patterns, report on those patterns and solve problems. and the first journey is connect, collect, store, analyze, visualize, get my data and information on a screen.
Okay? The second part where I plug into a digital supply chain is much more challenging because the way I plug into a digital supply chain and, and how I go to market is what my competitive advantage is. This is why organizations saying, what is my plan for making products to get better after the customer buys them is such an important question to ask because when I'm plugged to all customers, I wanna be able to collect data from the products that I've already sold to someone.
I wanna be able to improve those products, and I wanna be able to push the improvements to that customer. Now, people will say, well, what about consumables, bread? How are you gonna do that with bread? Well, okay. Let's say I'm a bread manufacturer. What's some data that would be really valuable to me? Okay.
Number one, the relative humidity and temperature of all. You know, as I'm transporting my [00:41:00] bread after it's left, my, my facility, if I were able to monitor relative humidity and temperature from the moment it leaves my distribution center to the moment it gets completely consumed, that would be incredibly valuable data for a bread manufacturer to have.
how long did it sit on the floor? In the back room of the grocery store where it's not climate controlled before it was put on the shelf in the grocery store where it is climate controlled. Right? All, all this data, even, even on the consumable side,there's events that organizations can benefit from, and that's what the digital supply chain's all about.
Matt Trifiro: Yeah, that's really smart. It's a very interesting way of thinking about it. Certainly, provokes me to think of new use cases, right? The bread example is really good. so most of these aren't on the internet, or not directly on the internet. There's an aggregator that's maybe pushing some data up to the cloud, but for a lot of the things we want to do on the factory floor, we may need cloud economics and cloud resources, right?
So let's say that we're doing, you know, computer vision, right? So we got,cameras. We're collecting a [00:42:00] lot of data, a lot more than a plus or a minus. And then we're running, you know, 4K video maybe through an AI inferencing algorithm that might be running on, a rack of servers within Nvidia GPUs.
And that seems very different from what the factory can support today.
Walker Reynolds: It's not that the factory can't support it today, it's that the factory chooses not to support it today,
Matt Trifiro: Okay. Talk to me about that. Yeah.
Walker Reynolds: Now we're not talking about Tesla here. if we talk about Tesla or we talk about, let's say Volkswagen in the United States, or we talk about, this company water fleet based in, you know, Southern Texas, or you talk about the companies who are all in the top 10 two standard deviations above the mean in their digital maturity.
they're all in on cloud. I mean, they are all in on cloud. It is not the industrial intranet of things. It is the industrial internet of things. the reason why is because they understand the risk and the reward of leveraging the technology. Right? But let's say that you're the risk averse organization.
Well, what you're gonna do is you're gonna come up with some [00:43:00] mitigation strategy where I can leverage cloud, but I don't have to be connected to cloud all the time. Right? So what I'm gonna do is I'm gonna collect data, I'm gonna buffer it, I'm gonna open a window. To the internet for some amount of time.
I'm gonna go ahead and pump that data up there. I'm gonna train a model and then what I'm gonna do is I'm gonna deploy that model back to the edge and close that connection. Right? So now that model's running on the edge. I'm using edge compute to look for the patterns that the model has looked for.
I'm looking at current state comparing for these patterns and then, you know, saying I'm 96% certain we've seen this, before, and this is gonna be the likely outcome here. All that's running on the edge. I don't need to be connected to the cloud to do that other than to take the raw events, get 'em up to the cloud so I can train the model.
that's a very, very common implementation right now. Do,is that what we recommend for our clients? Of course not. Should you be scared of putting your data on the internet? No. You should not be scared of putting your data on the internet. I openly challenge people. Are there risks out there?
Absolutely. do the risks outweigh [00:44:00] the reward of leveraging cloud compute? Absolutely not, not even close. It's not even remotely close. Okay. at the end of the day, you are either innovating or you're dying. Okay. and the companies who look at the horsepower, that pure horse horsepower that's available
most organizations, even if they wanted to put that kind of horsepower in their facility, the grid
Matt Trifiro: Right. They don't have the electricity. they don't have the staff. They don't wanna be in the data center
Walker Reynolds: That's right. That's right. and you know, it's funny, Dell sponsors your podcast, right? one of the things that I've talked about, I don't know if you know this, I've mentioned this in previous podcasts, you know, I've said to everyone, you watch out for Dell. Okay. based on who I talked to, you know, Dell's making a play on the industrial side, and it's not just edge compute. you know, at the end of the day, Michael and that group at Dell gets it. The group at a Amazon web services at aws, they get it. The group at AWS gets it. That, that the, what we're not cloud isn't the top layer in the stack. What [00:45:00] it is, the stack is getting compressed. It's becoming flat. Right? And what we're doing is we're using technology to protect it. So edge driven, report by exception, lightweight, right. Certification, that kind of stuff. So at the end of the day, cloud is the future. The good news is,the noise coming outta Hanover messy from last week is that with each year, companies are becoming much more amenable to cloud technology over on-prem.
Matt Trifiro: Yeah. Well, and there's a new category of, you know, it's not even hybrid, but a new category of, where to place the cloud or the cloud-like compute that we're starting to call near premises. And that is to say, look, there's a data center facility that you don't have to own, that you can put your own equipment in, or Dell's equipment or HP's equipment or Amazon's equipment potentially, that you could go kick if you wanted to.
So it is, near right and it, can be delivered over a private network, your own fiber at land speed. [00:46:00] So you can have that sort of real-time, but you don't have to be in the data center business. And then you have sort of like the, privacy,and performance of on-premises. But the, you're starting to get the cloud economics.
Walker Reynolds: and by the way, we haven't even touched containerization, docker, Kubernetes, or any of the safety elements that come from being able to leverage cloud with docker style, deployment of infrastructure. Right. So where what I'm doing is I'm scaling up and scaling down based on immediate need.
We are automating the process of scaling up, corporate infrastructure based on immediate demand and then immediately scaling it down within the next hour so that I can go from having enough horsepower to manage five users to having enough horsepower to manage 5,000 users within minutes.
And then, Literally decommissioning 4,995 of the connections so that I now only have the horsepower for five. And I'm doing that on demand and I'm doing that, being able to automate[00:47:00] the creation and deployment and then destruction of containers through cloud compute. And we didn't even get into any of those technical elements.
At the end of the day, when I do these podcasts, I generally don't get technical. I try to stay 10,000, 5,000 foot because if you look, the addressable audience generally is about 50% layperson, right? And then 50%, you know, are looking at the technology. at the end of the day, there is no reason for anyone to be scared of cloud.
like your point here. I say this all the time. when you hear cloud, you think some server, often the, and when I hear cloud, I think something at the top of the stack. And that thing at the top of the stack could be in the data center down the hall. it doesn't have to be, you know, out in the big, bad unknown.
Matt Trifiro: Yeah. Yeah. No, definitely. so let's talk about real time. You mentioned real time early on. as manufacturers move from this kind of like, you know, collect and react to on this, I don't know, human time almost, right. Which is a [00:48:00] little better than clipboards and spreadsheets, but it gets real time machine speed, you know, milliseconds and microseconds.
what happens, what does that bring me, in the factory,
Walker Reynolds: well, we'll talk about it in two points from a digital perspective and a human perspective. All right. So at the end of the day, from a digital perspective, the greatest advantage to connecting, collecting, and storing all data, so that is not just the stuff I think is important. All data is that we can use software to find patterns and data we can't see with the naked eye.
There are patterns in our data. that human beings will never see relationships, correlations. Um, you know, for every value X what's the likely outcome? Y it's really easy for me to write a linear regression that comes up with every value or every value y for every value X, likely value y for every value x, as long as I know what X and Y are.
I r
The real advantage in collecting all my data and using software to find those patterns is you can use machine learning algorithms to tell you what X and Y are not. I think there's a relationship [00:49:00] between this value and that value, but by collecting, and storing, and then analyzing that data, we can find patterns we can't see.
That's number one. So that's, the piece. You know, it's like when people talk about full self-driving with Tesla and how it's a pipe dream and all this stuff, and I think. You know, I use false self driving every single day. Literally, my car drove me to the office today. It does it every day.
I never intervene. I'm not sure what people are talking about. That's ai, that's machine learning and artificial intelligence, right? When it comes to the human piece of real time, human beings have always been very good at, I mean, we're great at troubleshooting. We're great at innovating. Human beings are outstanding at innovation, and we're great at troubleshooting.
You know what? We're really bad at collecting data. We're terrible at collecting data, by the way. in a world-class organization, like in Japanese organizations that are world-class with human data collection, if they get 60% fidelity, that means if the human being collected 60% of the data accurately, that's a worldclass number with human collection.[00:50:00]
That's world class. Okay, so what you want is you wanna collect data digitally and have human beings solve problems, troubleshoot and innovate with data from real-time compared to historical data. That's what you want. what the operator gets is I get insight into where I actually am right now.
How efficient am I is my waste high? Is it low? I think it might be high, it might think it might be low. Is my downtime high? Is it low? How am I operating relative to the way I should be operating? Right. I have immediate insights into state. Right. That's the biggest advantage of realtime data.
But the biggest value to the business is comparing realtime to
past performance. right. right.is the comparison, the comparative analysis to realtime against what we've done historically?
Matt Trifiro: yeah. That's really interesting. so one of the, one of the things you mentioned, you've talked about Tesla a lot, and clearly you're a fan, you're
an owner,
Walker Reynolds: and they let, they let us talk about Tesla, so.
Matt Trifiro: let you talk about
Walker Reynolds: It's one of the challenges is that most [00:51:00] organizations don't allow us to mention their name.
Matt Trifiro: And free speech. You can mention their names long as they're not a client. well, one of your other companies that you're very fond of is, Amazon. So what is Amazon doing right. That makes you so excited to talk about them and use them as a model?
Walker Reynolds: two things. Number one, I use Amazon, um, talk about how they collect all data points and they use technology to predict the future. Okay. So I use that example, but the big one I do is, I use Amazon as the example of transformative and disruptive leadership. Right?
So there's this famous email from Jeff Bezos, I think it was 2002. He wakes up at like two o'clock in the morning and he says, You know, we share entirely. This is on, by the way, this is only three years after T C P I P wins the protocol wars. Right. So you, we couldn't possibly have been more in the infant stages of Industry 4.0.
Right. of the fourth industrial revolution. The rising edge, by the way, of the fourth industrial revolution is 1999. When T C P I P won the Protocol Wars, he says we share entirely too much data and information manually. we send, we [00:52:00] share too much through email, we share too much, through spreadsheets.
We share too much manually. So Matt creates value out of data. He turns it into information, he emails it to Walker and. Then the guy who's sharing the cubicle right across from Matt does the exact same thing and shares it with somebody else. And we've repeated that work. What we really need to do is when Matt comes up with that great idea, we need to have an infrastructure where now everyone benefits from that value.
Matt created. So he writes this email and he says, effective tomorrow morning 8:00 AM you cannot share data manually anymore. You're gonna build services. Every group is gonna build services to serve data to the consumers. Okay? And you know, over the next 18 months, they turned over, I dunno, somewhere between 11 and 18% of their work, their workforce, they literally zero tolerance.
They literally, at the bottom of the email it said, you will be fired
Matt Trifiro: If you're not publishing data,
Walker Reynolds: if you're not publishing data, right? That became Amazon Web Services. So when you go to aws, you are literally in the exact same [00:53:00] infrastructure that Amazon runs its business in. Okay? The exact same infrastructure, no difference.
But here's what Amazon does. I ask people all the time, why is Amazon awesome? you look at how much money I spend at Amazon, they better be pretty damn awesome because I spent a lot of money in Amazon. How is it that they can get 98% of all the things they sell to 99% of all Americans in 48 hours or less?
do they
do that?
Matt Trifiro: I, know you can order something at six o'clock and it's there at three in the morning. You're like, How
Walker Reynolds: Well, the answer is they know what you're gonna buy 60 days before you buy it. They don't know Matt's gonna buy it. No. That's what they do. So, Michael Brown worked at Amazon and he's now with a, provider, Amazon, but he was an architect at Amazon. And you know, we, talked about what does Amazon actually do Well, what they do is they look at human, they look at lots of data points, all digital data points.
And what they're doing is they're predicting what you will buy 60 days before you buy it. Not what Matt's gonna buy, but what
Matt Trifiro: So they, they forward deploy inventory and then pull the supply chain based on what they [00:54:00] know somebody like me is gonna do in my neighborhood.
Walker Reynolds: And they do it to 98% accuracy. And the, only way that's possible, the only way you can train models like that, you know this already cuz you've already made references to artificial intelligence that only those in the know can make. The only way is that you have all the data points. They are all normalized, they are all high fidelity and they're all accessible for models to train on.
what they do is they use machine learning to predict the future 60 days out for their total addressable market in the United States. And that's how they get 98% of the things that they offer to 99% of Americans and 48 hours or less.
Matt Trifiro: Yeah, that's what I'm saying. You know, one of the things that might interest you, and you may or may not be aware of it, but people in my industry, the data center industry, networking data centers are actually starting to treat the data center and the operational technology as a factory, right? [00:55:00] Like those things spit off a ton of data too.
Humidity, pressure, temperature, you know, all these things. And they all affect the production of the ability to deliver bits around. and so it's interesting to see these worlds converging.
Walker Reynolds: Well,I was at Amron, so Amron built a new facility,center of Excellence here in Dallas. And it's right next to the airport. And they invited us over to tour the facility. It's basically where all of their sample operations are. And, we were walking around and they, we were in the Agv area, so they were showing us all their new agv technology.
And I was with the product engineer and as we're walking around, the AGV is going, you know, so they basically had a pick and place robot that was moving parts off and, plotting on a step, uh, pallet. And then they had AGVs going around, moving raw materials over to the end of the production line.
And I said to the operator, I said to the product engineer, I said, What is the value add that your agv can provide to your customers? Not the function that they're buying it for, but the value add. [00:56:00] I said, and he said, well, you know, honestly, I haven't thought about that, and I said that Agv is collecting data about the layout of their facility 24 hours a day, seven days a week.
It sees everything all day long over li they're using lidar. In this case, I said, you know what a value add you could provide. You could tell your client whether or not their floor layout is optimized, you could tell 'em whether or not their AGB paths are optimized and, you could see the light bulb go off, right?
It's the same thing in the data center component. one of the things I say, a Tesla car is not just a car, it is the most advanced and expensive iot sensor in the world. The most valuable thing. That Tesla gets from the Tesla vehicle is not what I paid for it when I bought it. It's all the data that car collects 24 hours a day, seven days a week, data that can be sold to municipalities on
Matt Trifiro: Where the potholes are.
Walker Reynolds: where the potholes are, which lights aren't running correctly.
human behavior and drive, you name it the whole knot. Right? It's the data is the most valuable commodity, [00:57:00] and at least you guys understand it,
Matt Trifiro: Yeah, let's look out to the, future a little bit. I can sense this kind of like, I don't know this energy that you have that you, you wish everybody would do stuff as fast as you do them.
Walker Reynolds: correct? Yeah.
Matt Trifiro: And so we look out at the American manufacturing,situation and, looking at becoming, re-energizing the
Walker Reynolds: Yep. Which, by the way, there is, there is a plethora of evidence that that is exactly what's happening.
Matt Trifiro: yeah, so, so I'd love to you to talk to you, have you talk about that, and then I'd like to answer, answer the question, which is, if you could, you know, be magic and push some of the dominoes down, if you could nudge a few of the dominoes to make this really go faster, what would those dominoes be?
Walker Reynolds: Number one, I would immediately overnight make manufacturing leaders. so the boards of directors who lead all the largest manufacturers, I would make them replace their CEOs with CEOs, with technology backgrounds. So overnight, Get rid of everybody, you know.[00:58:00] Jim Farley, who's the CEO at Ford, I'm sure he is an outstanding marketer, but he's a marketing guy.
He's not a technology guy. Elon Musk is a, he's an alien from the future. Okay? you know, he knows everyone's engineering job better than any engineer knows. Mary Barra is actually an engineer at General Motors, but Jim Farley is not all manufacturers need to be led by somebody with a technology background over.
So
Matt Trifiro: think you say that about politicians as well.
Walker Reynolds: overnight, it needs to be engineers and technologists. Okay? That doesn't mean there aren't places for MBAs, but it's certainly not as the chief executive. Okay? number two, I would have everybody focus on technology. Technology first and product second. So right now, the inclination of a manufacturer when we want to digitally transform is, Let's go to somebody who has all the products we think we need.
Let me go to Rockwell, let me go to Siemens. They have service groups and let's have them partner with us to solve our problem. No, what you wanna do is you wanna go to an agnostic architect who can help you [00:59:00] design a technology infrastructure first, then go find the products that meet
Matt Trifiro: D,
Walker Reynolds: technical request.
Matt Trifiro: of those?
Walker Reynolds: yeah, well that's us. And that's, but those, those are all of our partners as well. if you look at all the integrators who partner with us, if you're looking at galleries, industrial solutions outta Ireland, or you're looking at Skel automation, or you're looking at any, you know, G five consulting, any of these companies, they're all agnostic.
and the reason why is it's the same reason if I go to a doctor and I've got a brain issue and my doctor makes a recommendation to me about some new groundbreaking surgery, That I need, he's gonna cut my head open with some machine that Siemens developed, or arm run, for example, and I find out that he's getting a $10,000 kickback from making that resume recommendation.
That's gonna, I, that's not what I wanna know. What's best for me.
Matt Trifiro: Yeah.
Walker Reynolds: The agnostic architect who's focused on technology first, he's gonna tell you what's best. Then you make decisions. you do cost benefit analysis beyond best. Okay? So number two, I'd have people focus on technology. [01:00:00] Okay? Number three, first and foremost, what is the reason we want to be a digital company?
when I give keynote addresses, I'm doing one in at mass, m e p and the governor of Massachusetts is gonna be there. and I'm gonna literally address the governor directly. And I'm gonna say, I want, every time you go talk to a manufacturing leader here in your state, I want you to ask them this question.
What is your digital strategy? I want you to ask that question. And if they can't give you that answer in three sentences or less, I want you to say to them, you don't have a digital strategy. I'm gonna say that directly to the governor. I want organizations to start asking themselves, why do we wanna be a digital company?
And if you can't answer that question, then it means you don't have the technologist in the room to answer it for you.
Matt Trifiro: Yeah, I'm surprised that any manufacturer that went through Covid doesn't have an answer to that question. I would've thought it'd be obvious that
Walker Reynolds: You'd be stunned. You'd be stunned. Yeah. You would be absolutely stunned if they give you a 60 page PowerPoint. That's not a strategy. [01:01:00] here's our digital strategy. No, that's not a strategy. if everyone in your organization can't recite from memory what the digital strategy is, you don't have one because every person in the organization is a node in an ecosystem if they don't know how they're inter-operating in that ecosystem.
Well then you don't have a strategy. You or you didn't communicate it.
Matt Trifiro: Yeah, I think you're right. I think most, people wouldn't be able to answer that question,
Walker Reynolds: Yes. But you go ahead and ask. Ask anybody at
Matt Trifiro: I'm gonna start,
Walker Reynolds: you ask any,
Matt Trifiro: Oh, interesting. Okay.
Walker Reynolds: you ask anyone at Amazon? Anyone at Tesla? And they'll be able to answer it. Ask anyone at Volkswagen X in Volkswagen America. ask anyone at Plant of the Future at Toyota, ask anyone at Saint-Gobain who works in their ceramics business.
you ask the companies who are high on the digital maturity assessment, where they've got a score of four or five on their digital strategy and everyone can recite it.
Matt Trifiro: Ha
hey, Walker, I mean, this has been an amazing conversation. I really appreciate you coming on the [01:02:00] show. And if people want to get ahold of you, although you did admit you don't actually read your own messages, but if people wanna get ahold of,Intelli or, 4.0 solutions or you, what's the best, how do people find you online?
Walker Reynolds: so I do, if you DM me on Twitter, I do get that. So of all my social media, the only social media that I actually manage is my Twitter. So that's I Walker d Reynolds, my LinkedIn, my email, I just get too many messages. I have a team that goes through all that stuff. I do answer LinkedIn messages.
If the team says, Hey, Walker, you need to answer this one, and they send it to me, the best place to go to get ahold of me is to go either go to Twitter, message me on Twitter, on LinkedIn, go to iiot.university. That's where 4.0 solutions is. We have a contact link there that goes to the entire team.
If somebody emails contact, every person in our organization gets that email including me.
we have a Discord server. know, if people say, Hey, they wanna become part of the community, where should they go? The first thing they should do is sign up for our Discord server.
We have a Discord server with about 5,000, 6,000 members from in the [01:03:00] industry 4.0 channels. You know, basically any topic you can think of, machine learning, vision, whatever. We have channels on basically every single topic. It's a who's who, you know, Arlen Nipper, you know, you name it, you name any of the biggest names in the industry, they're in there.
and that's a great place to go and, get answers about digital transformation. you can go to our YouTube channel 4.0 solutions, which is where all of our public content is. But let me, lemme say this, Matt, I love your podcast. I listen to a lot of content. some of it I absolutely love.
I love all of your guys' stuff. one of the things that really frustrates me, and I say this all the time when it comes to digital media, there's a lot of people doing media. Who aren't asking the most important questions before they ever get on camera. And that is number one. Why should anyone listen to me?
Number two, what am I gonna say? Number three, what are they gonna hear? And number four, what will the audience say is the most valuable thing I said? So if anyone is listening to this podcast and you wanna get into media, please rewind that. Listen to those four questions. If you ask those four questions before you produce anything [01:04:00] that I guarantee you, you will provide value to your audience if you do those four things.
Matt Trifiro: awesome life advice and podcast advice.
Walker Reynolds: yes, it's clear that you and your team ask those questions. That's
Matt Trifiro: Awesome. Thank you Walker. we'll put all those links in the show notes, But again, Walker, it's been a pleasure.
Walker Reynolds: Pleasure, man. Thank you.