Feb. 23, 2022

Manufacturing Excellence in Michigan

Manufacturing Excellence in Michigan

Today’s guest is Jon Sobel, CEO and Co-Founder of Sight Machine (@sightmachine), for episode 62 of Augmented Podcast (@augmentedpod). The topic is: Manufacturing Excellence in Michigan. Augmented reveals the stories behind the new era of industrial operations, where technology will restore the agility of frontline workers. Technology is changing rapidly. What’s next in the digital factory? Who is leading the change? What are the key skills to learn? How to stay up to date on manufacturing and industry 4.0? Augmented is a podcast for industrial leaders, process engineers and shop floor operators, hosted by futurist Trond Arne Undheim (@trondau), presented by Tulip, the frontline operations platform.

The Augmented podcast is created in association with Tulip, the connected frontline operations platform that connects the people, machines, devices, and the systems used in a production or logistics process in a physical location. Tulip is democratizing technology and empowering those closest to operations to solve problems. Tulip is also hiring. You can find Tulip at Tulip.co.

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Transcript

Augmented Season 2: Episode 62

Trond Undheim: [00:00:00] Welcome to another episode of the Augmented podcast. Augmented reveals the stories behind a new era of industrial operations, where technology will restore the agility of frontline workers. Technology is changing rapidly. What's next in the digital factory. Who's leading the change. What are the skills to learn?

How to stay up to date? The manufacturing and industry 4.0 in episode 62 of the podcast, the topic is manufacturing excellence in Michigan. Our guest is John Sobel, CEO, and co-founders cite machine in this conversation. We talk about the impact of digital platforms in manufacturing. How you have to create transforming processes in your company to take everyone with you on the journey.

We also discussed the fact that Michigan was the birthplace of the assembly line, but over the past 25 years, trouble hit and it seemed to manufacturing was headed for extinction. How's the manufacturing climate in Michigan now. And what accounts [00:01:00] for the change Augmented is a podcast for industrial leaders, process engineers and shocked.

Operators hosted by futurist thrown an ad presented by to the frontline operations, Augmented industrial conversations that matter. John, how are you today?

Jon Sobel: I'm doing great. Thanks. How are you? I

Trond Undheim: am doing well. I'm so excited and stoked to hear about how you got together with some buddies and basically are shaking up Michigan.

It's been a while since the assembly line was invented,

Jon Sobel: it has, it has we're due for some, uh, innovation in the whole area.

Trond Undheim: John, you're not really a manufacturer by trade. You've had a fairly illustrious sort of digital career. Yes. You've worked at Tesla motors, but you've also been at CBS and you have board memberships and you've even been around Yahoo.

I mean, what was it that kind of pull this thread? So

Jon Sobel: you're right. [00:02:00] I had done about 15 years in internet media, and then I started getting into energy and like a lot of folks early, a Tesla was very mission-driven about wanting to do something about climate and through working there. And at one other energy company, I personally got very interested in how.

Digital technology was starting to be applied to much larger older industries. So that part I kind of got, but I will tell you, I had never thought seriously about manufacturing until a good friend and former colleague Nate invited me to join our founding team. So we founded sign machine with five people.

We were all from the Midwest. The other guys were very accomplished, early internet software types, Nate and another founder, Kurt demise found it slash.in the mid nineties as college students. So these guys were just outstanding hackers, software developers. They were friendships between us and went back in some cases, 30 years.

And the final of us who [00:03:00] got together. There was another guy Anthony, who had been a robotics integrator for five years in Michigan, total opensource jock, and the other guy was Adam taste, a good friend of 20, some odd years. Now another internet media type. We had all gotten restless with ad tech and grab one dot O and two Dido.

And we were all feeling like this is good. Be applied to something else. What's the next thing going to be? The other four guys had all grown up with Manufacturing. I was the only one who hadn't really worked in the field. They came from manufacturing families and they incurred had worked at a tier one automotive plant in college.

And I had gone to school in Michigan. So we all had this feeling of wanting. Get into it and to try to help restore some of the competitiveness and leadership in geographies, where we were from. And so we just decided, Hey, let's take all this stuff that's going on with data technologies and see what we can do.

And first couple of years, that company was based in Southeast Michigan. I was the [00:04:00] only California for awhile. Then Adam joined out on the west coast and we just went to plants in Southeast Michigan and just started asking a bunch of factory leaders. Where's the paint. It was very cool. Experience, learned a ton.

It was tough. And I was very intimidated at the beginning, walking down the shop floors, you know, if you don't know what you're doing there, you immediately feel a little bit ilities and we just asked a lot of questions and spent two or three years studying the problem.

Trond Undheim: It's a fascinating journey because I guess you've now by now spent a bit of time in California with tech companies.

And there's a certain arrogance, which is also, I guess, a little bit deserved, right. When you've done. Several of these, you come in and you're sort of thinking, yeah, it's just another tech company. We're going to do a spin on this and it's going to be huge. And sometimes it actually is. Right. And you know, you've had track record on these digital companies and it's not that they're not complicated, but the shop floor is sort of a whole other level of physical complexity.

Oh,

Jon Sobel: yeah. You said that very well and very graciously. Um, I [00:05:00] think I've lived in California 30 years, you know, 27 years in Silicon valley. You know, I saw an energy in the early stages of kind of new fields. There is this we're really smart. We can fix things that nobody else knows how to fix belief in Silicon valley.

You need that to do anything hard, but you also are not well-served if you're not. And I think it's because we all kind of grew up in the geography and the other guys who had worked in the field, we certainly understood that this was a whole new ball game. We tried to be very humble and there was a guy from the Atlantic, a beautiful writer, Alexis Madrigal.

And he wrote a piece about us early on. And he said, you know, and the theme of it was this, company's probably not going to make it. It was a very positive. Supportive piece, but he, he had a line in there. He said, this is a company that is a little too Michigan for Silicon valley, a little to Silicon valley for Michigan.

And he beautifully captured the kind of in-between this that we were in at that time, Twitter was going public. I was a light loneliest [00:06:00] guy had Silicon valley parties. Nobody wanted to talk about manufacturing. And I just had this feeling like this is going to be really cool. We're going to pull it off.

But most people around us, aren't going to care or appreciate this for awhile. And if it works later, everyone will say it was a good idea. But at the time it was an incredibly lonely undertaking.

Trond Undheim: You know, it's really fascinating to hear you think about this and you guys were early because even this year or next year, it's not like everybody understands that industrial tech is the real new deal.

But I think. It's becoming increasingly obvious, at least to those of us who sort of are looking tiny bit in the tea leaves that not only is this like an area ripe for change. I mean, these, you know, different names of it, but foundational kind of industries or whatever you want to call it. The change has been fairly slow and it's almost a sin, right?

That we've been developing software for the white collar workers sitting comfortably at their desk. For like 25 years when an industry there's been, you know, two innovation, but [00:07:00] really no tools. So there have been tools, but the tools have been evolving at a very moderate pace. There's nothing wrong with the incumbent players, but the innovation has not followed pace.

You get the sense now that having listened to clients and factories over time, is there something that you're learning that will enable. Any kind of, sort of Moore's law or, you know, whatever you want to call it, a speedier path for industry going ahead, or, or do you see this more as like, it's an interesting area, we're doing good things.

We're going to make improvements, but it's going to be nowhere near a Twitter, nowhere near a Google, nowhere near any of these digital spin companies.

Jon Sobel: Oh, that's a great question. And you know, I think it's going to be much bigger over time, then the chapters we've seen, I don't think we're going to see a Netscape moment.

I've heard VCs in Silicon valley talking about the Netscape moment and everything just explodes, you know, and I remember that it's slower. Maybe the slope of the line is a little less [00:08:00] steep, but it's funny, you know, as an outsider to the industry, when I started, I could look at it with just very kind of clinical detached perspective.

And the first thing I realized there were a couple of things. You know, Manufacturing is the largest sector in the world. It's something like $16 trillion of value added work a year. So you just look at that compared to the size of the digital economy, when things really got going 15, 20 years ago, it's, it's unbelievably massive.

And then we think about things like sustainability, which we have to deal with as a society. There's just no getting around it. Now something like 30% of greenhouse gases. Are created directly and indirectly by Manufacturing. Oh, and then the other thing is there's more data in manufacturing than anywhere else.

So data is useful. It's necessary to innovate in this sector for all kinds of reasons. It's now a geopolitical thing. Everybody realized in the last 20 years, you got to have manufacturing based out of any sort of economic vitality. So all those kind of macro forces [00:09:00] seem inescapably directed at really making this an important field.

You know what the thing I came to appreciate is the stereotype of manufacturers among, among some people who don't know very much about it is that they, you know, they just liked not changing and that's how they are. And that's just because that's how they want to be. And that's a completely unfair portrait.

There's very good structural reasons. Manufacturing companies are conservative in some respects. You know, if you run into chemicals plan, you make a mistake, you blow up the plant and kill hundreds of people. You can't just be a cowboy about these things. On the other hand, it's constantly innovating as a feel.

These folks really believe in continuous improvement. That's where the whole metaphor comes from and kind of the competitive pressures to innovate and process. And then how you do things are going on all the time. So your question is what's going to be the. And I think I'm probably in good company with friends at Tulip.co and elsewhere.

Data's the unlock for this industry. Being able to use data. Once we get to a point where there's less think [00:10:00] of it as data interoperability and where you at your plant and me and my plant can talk to each other the same way we do on the internet. Now, as we say, where I grew up, we're cooking with gas.

That's what needs to happen. And the. Tower Babel problem in manufacturing is worse than anywhere else. The heterogeneity of the data is a nightmare. I think when we unlock that problem, there's going to be exponential acceleration in how people use data.

Trond Undheim: Uh, John, this is where my background and yours intersects a little bit.

I know early, early in your career, you got your degree in public policy at Princeton. Interoperability is not just a technical term, right. They sort of actually implies agreements and standards and collaboration, and a fair degree of if not public sector involvement, at least public sector mindset, or a sharing mindset among private collaborators in an industry.

What do you think. Is the path forward there because, you [00:11:00] know, if we were all to sit down and say, we are going to be part of this Cambrian moment in industry and like in health and other areas, interoperability, it just stops us from getting all of these benefits out of the data because we are in our separate data streams and.

You know, and then you add some privacy on top of that. So now you have some technical debt followed by some privacy laws that is not conducive to a Cambrian moment. What are we going to do about that? That's an

Jon Sobel: interesting question. And it is a policy question. That's a business question. I have a, a, a view that, you know, maybe to see.

We've thought about it a lot at sight machine. So, you know, let's make standards process, as you know, is cumbersome, laborious, and it's always kind of done with the appearance of neutrality, but there's intense jocking by big industry players to set standards. So personally, I don't see that leading to interoperability anytime faster, soon, there's tons of initiatives that have [00:12:00] been kind of hijacked or captured by somebody.

I think the best model for what is happening and we'll probably will have. Is what happens with open source software? What happened with the internet? There are certain technical protocols or methods that are just so elegant. Everybody ends up doing it. And I heard a word the other day that I never really heard before, but I know it's kind of trending now the metaverse to make the metaverse work, to kind of really represent the physical world in math and software.

All this stuff has got to be able to be standardized and talk to each other. So. And you hear companies starting to talk about common data models. The problem today with common data models is people say in one sentence, yeah. We have common data models. We have hundreds of them. Okay. That's not common at all.

What's really needed is a small set of building blocks. Almost like TCP IP has been for the internet at an elemental atomic. And I think we're starting to see that kind of thinking from a lot of good companies [00:13:00] out there. And so somebody is just going to get really good at it. It's going to happen.

Trond Undheim: Yeah.

John, I have to say, I am much more excited about the industrial metaverse than I am about the consumer. Metaverse right. So there are certain companies out there in the valley right now, talking about what I see as like a, well, honestly I'm early award because it's a premature. Commercialization of a space that could be not just billions, so dollar.

So I mean, forget that it actually could be a moment similar to the internet because you're talking about the physical internet in a certain way, but it's the industrial side of that that you and I, I guess, are engaged with. And, and that is a challenge. Communicating, you know, and sharing and hand stuff.

So anyway, go into site machine a little bit. So w where did you guys start? So you said, all right, we're going to get together a group of good friends, and we're going to do it in Michigan, because, because why, because you were sort of looking at the trends and, and thinking, you know, we, we think we can come back.

Yeah,

Jon Sobel: that's exactly what happened. Uh, [00:14:00] on a personal level, I was at a kind of a fork in the road I had at that point had about 15 to 20 years experience in Silicon valley. And I was burned out. I had been in a number of companies and I had been involved in some tough situations and turnarounds and fixes, and I was losing kind of lovely.

You know, losing the passion that made Silicon valley so exciting to me in the mid nineties when I went there. So I was thinking of doing something completely different and they called me and I had gone to school in Michigan and I went and visited him. He and our second founder, Anthony were in a one room office in the communal workspace.

And I started asking him, what, what are you guys doing? What are we going to do here? At that point, Detroit was on the ropes was about to go bankrupt. And I just had this feeling of. You know, it's funny. I was trying to decide what to do. And I read this article by David Brooks in the New York times. And he had asked a bunch of readers in their seventies and eighties.

What did they most regret in their life? And what were the happiest about? And [00:15:00] he wrote a column. I was trying, I was sitting there trying to figure out what to do next. And the column said the biggest single regret was that people didn't do something that was really. And whether or not it was risky. They were so glad they did it.

So I remember talking to my wife and basically saying, look, we've got this other path. It's very secure. And then there's Nate and Anthony. And this idea about me in factory Michigan, she says, do you got to do that? So we had no money. Nobody got paid for a couple of years and we just started going to plan.

And I remember driving to an automotive plant. We were starting to work in, in Detroit looking around what was going on and just feeling so sad about, of the state of the situation there, but meeting all these amazing people and just feeling like, okay, this'll be. Meaningful, you know, whether we do it or somebody else does it, this is what technology should be doing right now.

And that was a lot of fuel for us for a couple of years, you know? And we got a lot of crap from both sides. We got crap from Silicon valley and then we got crap from [00:16:00] manufacturing people saying, what are you guys doing? Everything's fine. So it was a really interesting soulful couple of years and learning about Manufacturing.

Totally cool experience. I'm still learning a ton.

Trond Undheim: So I have some data from 2020 from the national manufacturing association. They're saying that 19 point 38% of the total output of the state of Michigan is manufacturing. And it employs 14.2% of the workforce, which I believe is three, four percentage point above the national average, for sure.

It's still at shrunk, I guess it was much bigger before, but that's still a chunk of all the state economy and obviously very important to us manufacturing overall and certainly the signal effects. Are you getting the sense now that having listened to all these workers on the factory? Is there a. That things are turning around or what, what is the feeling now when you guys get out there and tell me maybe a little bit about what the path was with sight machine in terms of what you actually ended up doing [00:17:00] for these factories.

Jon Sobel: So with all this happened in the last couple of years with the pandemic and supply chains and just stresses in general in society, and there is an urgency in manufacturing. That is palpable a feeling of competitiveness and we got to change. We want to win that type of stuff. Whereas, you know, every five years technology companies may come along, tell them manufacturers for like 30 years.

Now this is going to happen, you know, digital's coming. So there's very, well-deserved skepticism always when you show up and say, I'm from Silicon valley, I'm here to help or from anywhere, but. We got to try stuff. We got to do stuff. We got to make some changes, but that, that feeling is much more focused than.

Trond Undheim: So Manufacturing in and of itself though, it is a discipline. And you pointed out before that operational improvement, you know, is like almost remarkably consistent. They have had their own version of, of [00:18:00] Moore's law, essentially in Manufacturing. Uh, you know, it has been physical and it hasn't been able to sort of digitize as fast.

It's been slower. But I think you wrote about this in an earlier piece that I saw the four levers of production, uh, you know, either way, you know, throughput, quality, cost, flexibility. It's fairly simple, but understanding and controlling those, I mean, already four, four is not that it's a complex machinery, even though there are only four main level.

What is it that you've been able to do with that insight machine now? Like which ones have you picked up?

Jon Sobel: So we really do believe that as you said, manufacturing as a discipline, so people will often say, is your company focused on automotive or are you focused on food and beverage pharmaceutical? And as you alluded to, we came to appreciate.

The art of making things repetitively in that scale, let's just say Manufacturing is about making stuff fast and a lot. There really are only four levers and it's a bit like finance. You know, our friends who [00:19:00] are listening, who have MBAs, they'll remember the DuPont levers. So you can kind of deconstruct any business without framework.

And there are frameworks and manufacturing around these four levels. What happened assigned machine is like a lot of good startups. We picked one type of data. The name side machine comes from the fact that we were doing image analysis in 2011. We were taking data from industrial cameras and doing machine learning on the data.

And like a lot of startups we got pulled. Once you get into a plant and you start solving problems. So we were looking at image data to improve quality. That's what that was our focus. The lever we picked at first was quality and we wanted to help companies do a better job of figuring out why they were having quality losses.

And quality is just a perennial challenge in manufacturing. Some people say companies directly and indirectly spend as much as 20% of their top line dealing with quality. And that doesn't surprise me at all. So we said, okay, that's a real high value, interesting area to get into. There's a lot of focus.

About two years into things. [00:20:00] The clients basically all said, it's cool that you're studying this one aspect, but what we really want to understand is our whole work as a system, can you analyze all the data? And that was a big move for us. There was a lot of good luck and kind of fortuity in how we chose to attack the problem with put us on a different path than most of the industry.

And we ended up developing a product that simultaneously studies. And so it's a big goal to try to understand everything going on in a plant. That's what we're going after.

Trond Undheim: I guess you're still a startup, but you're a grownup startup, I guess. Right?

Jon Sobel: I hope so. We're certainly growing up in, um, dog ears kind of, uh, in scale, as far as the.

It's funny, a lot of classical kind of Silicon valley companies will grow like a weed and then go back and have to fix their tech. Anyone who wants to do something in this environment has to really get the tech hardened and robust, or they won't use [00:21:00] it. So first five or six years was getting that nailed in the last couple of years, we've really started to make some commercial progress with.

Trond Undheim: What do you think the growth rate in industrial tech is actually going to be w when we go forward, is it very company dependent? Like these startups, like yours, are you going to, at some point, uh, hit kind of averages, that there are not the same as, you know, tech startups in other fields, but that start to at least approximate, you know, a hockey stick growth or.

Not even just the target here. You're just trying to, I mean, you'll grow in a scale, but you're not trying to do it. Hockey stick style. I may

Jon Sobel: back down from this in the future, but I think the hockey stick is there for the winners because the markets are so massive. And in contrast, you know, there were some great startups who just nailed.

For a couple of years, they get to 50 or a hundred million dollars. And that's the market. The great thing about this market is there are hundreds of multi-billion dollar manufacturers. Most people have never heard of. And [00:22:00] if you figure out how to serve a group of them, well, there's no firewall between that and doing it for hundreds of companies.

So I expect three, four X grows a year for the foreseeable.

Trond Undheim: Well, then the next question, and this is again, tea leaves and we don't have to relate it to cite machines, but the temptation for many companies in every industry, when you start growing is, you know, you become an acquisition target, and that's wonderful for these big companies to take you off the table and have, you know, have a field day that way, but it's not so good for building new powerhouses that are going to compete at that level.

Do you see a day when industrial tech is going to actually produce a new GM.

Jon Sobel: I think we're close. You know, if you go back and you look at the history of Google Facebook, there were moments where there were acquisition offers on the table for those companies that are laughably. My company, Yahoo tried to buy them both for numbers that are laughably small by today's standards.

And thankfully from a [00:23:00] kind of societal perspective, it's a good thing that there is patient capital and committed management teams that want to build great company. I think there are some really good industrial companies out there, industrial technology culminates. There could be those kinds of companies easily.

If they're investors in management teams stay focused on the big idea and hang in.

Trond Undheim: Absolutely. That's interesting. I want to go back to one thing you did say about sight machine though, which is counterintuitive insight that I thought you, you had there, like you started. Wanting to do super advanced specialized things envision, and then it's not like your clients said, you know, do something simpler.

It's actually probably more difficult to combine all data sources together. But in essence, they also told you lay off the tech for a bit and solve the real problem we have is kind of an interesting

Jon Sobel: message. Very well said, like a lot of good tech teams. I joined Nate. He and the other colleagues he incurred, you know, to, they [00:24:00] were among the best technology side men in 25 years.

And there was no question that we loved our technology and many technology teams start off with loving what they've thought of and what they can build. And to your point. I remember this vividly, Google was using image search to refine recognition of cats. And we were studying defects on cars. It was very sophisticated.

We had to get to 99.9% accuracy or the operators wouldn't use it. You know, tulip is great at this stuff. Right. You've got to nail this to get any sort of adoption. So. Grinding away on really hardcore image analysis. And the factories are saying, I would just like to know how much stuff I make and what I make, where I'm losing money or making money and, and, you know, all of those really basic important things.

So the tech to do that is actually harder, but it looks like a simpler product when you're. Was it very counterintuitive. Yeah.

Trond Undheim: And I think maybe that's common to companies [00:25:00] in our space. It's almost like a reeducation journey, not just for the management, but for our engineers as well. Right. So you didn't really go to school.

Most people certainly in software, didn't go to school to then end up on the shop floor or at least build software for the shop floor. It's a mind shift a little bit. It

Jon Sobel: really is. And it's interesting. We have kind of a great group of engineers. Many based in the bay area. And if you look at their resumes and you meet them, I mean, these are just classic cutting edge.

You know, Silicon valley engineers, a lot of them look really strong, open source background. And the thing that we, I think just naturally gravitated toward, and thank God we did is just focused on what the customer needs. You know, Steve Blank's books, everybody talks about this. It's it's so true. Let that be your north star.

Just listen really hard to what they did. And then, you know, what I noticed is our engineers are always asking, do people use this? That's what people care about. They want their work to be used and valued. And if you can make that connection and I made it sound like this [00:26:00] job for stuff is really simple questions.

They're not simple questions. They're really valuable and important. And there's a lot of people were really are in factories. It's been years of their life trying to make stuff well. And so when you help people do that, That's incredibly gratifying. And then of course, if you get that foundation, right, we were talking about interoperability and getting data to talk to other data.

If you get all that stuff, right, you can go crazy on the AI. We do all kinds of cool stuff. Now on top of that foundation, we. Complete the circle and go back to, you know, genetic algorithms and whatnot, but it's all because of the data's right. And in the end, I mean, we have this great chart. We show our clients where we say, look over here.

If you want to optimize and study multiple plans that wants a bunch of parameters, we can do AI. If you want to know what time it is in your factories, we can do visibility. It's all kind of driven by the same. So that's been a really cool journey. The key is just keep in mind what your customer needs.

That'll tell you what to build.

Trond Undheim: John, we've talked so much about sort of aspirations [00:27:00] also about, you know, what the future holds. I wanted to maybe end on a sort of weird note, but what are some of the biggest frustrations you have? Because, you know, you're a very enthusiastic person. This seems like, but what are some remaining frustrations in the, you know, in the business?

Yeah,

Jon Sobel: I will tell you for me personally, I don't know if I would use the word frustration, but, uh, I'll do my best to be as open and honest as I can about this. When you're doing something like what all these great industrial tech companies are doing, and you're bringing change, you got to just find a way to put gas in the tank every day.

Cause you're just getting challenges on all sides. Part of your customer's organization saying bring change and there's people in the organization that don't want it or concerned or threatened. And then everybody's coming. Basically a good place, but it can be exhausting sometimes, you know, and the journey has its ups and downs.

And so you're trying to keep the troops in the company fired up and then, you know, new customers going through a hard time, pandemic comes along. The whole world is genuinely suffering and [00:28:00] you know, it's true. All startups, all people who are trying to do new things and. That may have nothing to do with technology.

I just worked really hard on trying to keep perspective and figure out, like I said, how to put gas in the tank. Cause if you're not coming from a place of good intention and wanting to push the envelope a little bit, you're going to get exhausted. Uh, so I worked really hard on that. I have days where I go home and I just want to cry.

And then I wake up the next day and it's right back at

Trond Undheim: it. Well, I think you've just conceptualize the startup journey at any point. You know, whether it is the beginning when you have literally nothing or at some point when you again have, you know, compared to competitors, because by then your competitors, you know, are grown-up companies.

You, you literally still have nothing. So it's a grind and I'm glad you're doing it, John.

Jon Sobel: Thank you, you know, it's trite to say it, but you do have to enjoy the journey. I try to remind myself every day and I take real pleasure in how lucky we are. The people [00:29:00] we work with, the things we get to do. I've been all over the world.

Every time we go to a new company and learn about a new process, I'm amazed at the. Decades of learning that have gone into things. And so it's an incredibly stimulating opportunity and we all feel really fortunate to do it. It's a totally cool field to be in. And if anybody out there is listening to your podcast and they're thinking about it, Jump on it.

The water is

Trond Undheim: warm. I like that. I'd like to think that we have a role to play there, to get the right kinds of people in because otherwise all these wonderful innovations, you know, they, they will certainly happen slower. They might get there, but, uh, the good people have to be part of it, for sure. All right.

Well, thanks so much, John. I, uh, I'm very thankful for your contribution here

Jon Sobel: today. Thank you.

Trond Undheim: You have just listened to episode 62 of the Augmented podcast with host . The topic was manufacturing excellence in Michigan. Our guest is John Sobel, CEO and co-founder of cite machine. And this conversation, we talked about the [00:30:00] impact of digital platforms in manufacturing and how you have to create transforming processes in your company to take everyone with you on the journey.

And we also discuss the manufacturing. In Michigan. My takeaway is that Michigan has been at the heart of manufacturing, not only in the U S but worldwide, to what extent can the region revitalize itself that the world still need its engine of growth? What remains true is that an industrial legacy counts for something?

And if nothing else, it proves that building a cluster of competence. Michigan might surprise everyone. And again, emerge with innovations that stunned the industry don't count them out, especially in a landscape where augmenting workers to attain precision manufacturing with a batch of one becomes equally important as mindlessly automating production for mass production.

Thanks for listening. If you liked the show, subscribe at Augmented podcast.co [00:31:00] or your preferred podcast player, and rate us with five stars. If you like this episode, you might also like episode 17 smart manufacturing frog episode 50, the last mile of productivity or episode 52 unplanned downtime.

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Jon Sobel Profile Photo

Jon Sobel

CEO and Co-Founder of Sight Machine

Sight Machine Co-Founder Jon Sobel has led Sight Machine as CEO since 2012, driving all aspects of the company’s business and setting its strategic direction. A visionary in the digital transformation of manufacturing, he has built a company that the world’s top manufacturers turn to for solving their toughest production problems.

Jon has served on the management teams of companies in pioneering industries including Tesla Motors, SourceForge, and in its early years, Yahoo. At both Tesla and Yahoo he served as general counsel and secretary.

Jon holds an A.B. from Princeton, a J.D. from the University of Michigan, and an MBA from Wharton.