GA 447 | Reality Fights Back with Trond Undheim

There is a limit to automation. And when you start approximating that limit, the rest of the innovation is what you can squeeze out of people and people working with technologies, because people and technology working in an optimal way is always going to be much more powerful than just technology.

Today, I'm excited to welcome Tron Enheim to the show. Now, Tron has recently written a book called Augmented Lean and Augmented Lean, A Human Centric Framework for Managing Frontline Operations. And so we had a really interesting conversation. So the whole idea of what Tron and his colleagues are calling Augmented Lean is to essentially reframe work to ensure that the human being is really at the center of what we're doing, whether it's in a factory or in an office or whatever it might be. And that things like technology, automation are there to really serve and help elevate the human being. And then obviously the, the process itself. And so, you know, what was confusing me early on was I thought, well, this is kind of what we all say anyhow. And I think in the end, most lean thinking organizations that are really genuinely get the whole concept of respect for people, they're really going to be in agreement. Now I think Tron's argument is that there are some organizations out there who are going so much into automation that they're actually forgetting about the people who might be involved in that process. And so that's sort of what I think where his perspective is really coming in. So really interesting. And towards the end of the, of the, the episode, he was so passionate about human beings and elevating human beings, which obviously we're all about in the Lean community. I throw a wild question at him. It has nothing really to do with Lean and it was, I wanted, I was curious on his take on social media and its impact on humanity. In fact, I have a lot of opinions and I share some later on about social media and how it might impact, say, teenage people, teenage girls and young boys and things like that, and even human grownups like me and you. And so it was, I was really genuinely curious to hear his take on that. And yeah, he shares a nice response. So really interesting episode. Again, I think the last few have been a little bit longer than normal, so maybe listen in a few different car rides, but I think you're going to enjoy this one. So show notes can be found over@gembapodcast.com this is episode 447 again, gembapodcast.com look for episode 447. Okay, enough from me. Let's get to the Show. Tron, welcome to the show. How are you?

I'm great. Thanks for having me, Ron.

All right. Hey, where are you calling in from?

I am currently in California.

Okay. Awesome. Awesome. All right. Well, Tron, as you know, we were chatting before we got going. We like to begin all of our episodes with our guests sharing a quote. So do you have one?

Yeah, you asked me for a quote. I don't walk around with all these quotes. But, you know, John Lennon said that life is what happens when you're busy making other plans. It. It has been my experience that whatever you plan for, it's never what happens. And I think that's interesting for life. It's interesting for work. And I also think it's interesting for what we're going to talk about in manufacturing. Because we may plan a lot of things, but what transpires isn't always what we're planning for. Yeah.

Very cool. Very cool. All right. Well, hey, Tron, tell us a little bit about yourself. Tell us about your background, how you got involved in your line of work, and then explain what is your line of work and what are you up to these days.

Yeah, sure. Thanks for that. Well, just to continue on the line of the quote. I mean, I think my current line of work started a little bit out of a coincidence. When I was back at the university, I wasn't even studying at the time. I had a. I think I was in the military or something. And I saw this poster with a scholarship for application to a PhD. And I just tore the thing down and walked over to the professor's office and said, I want to apply for this. And he said, well, you know, the deadline's now. And I applied, got it, cancelled all my other plans for the holidays actually wrote this PhD proposal with the scholarship. Got it. And I've been in kind of technology and futurist thinking ever since because this was, you know, completely different really, from the whole rest of my activities. I wanted to, you know, I wanted to write, I wanted to study history, I wanted to do a bunch of different things. But my engagement with kind of industrial concerns and technology development and even with manufacturing and industry happened because I happened to walk by a notice on a bulletin board at a university.

What were you studying, like undergraduate or had you studied?

Yeah, I had studied a bunch of different things, but mostly, you know, across social science and humanities. So technology had not really been a massive focus of mine up until that point. But obviously, like everybody else, I'd been watching and thinking a lot about what causes technologies to occur. And, and, and, you know, to innovations to occur. And I've been reflecting on it a lot, but sometimes you need that stimulation externally to say, well, actually this might be my next thing. And it didn't turn out to be three years of my life, right. It's turned out to be 25 years of my life, and maybe the next 25, I'm lucky enough to stay alive. So that's crazy.

So what, maybe you said, sorry, what was the PhD? What was your concentration? What were you focused on then?

I was studying what back then, a long time ago, Ron was called. It was actually is now called the Future of Work. So it was on Internet and web technology in the workplace. And to the extent, I mean, back in 1999 and 2000, this was the early heydays of the Internet in the middle of them. And people thought, like we think now, that the workplace not going to matter. We're all going to sit in our isolated islands, maybe recording podcasts like we are now, and never come into the workplace. So this was, you know, a long time ago. And I was studying how there was this mismatch between realities and visions, right, because people were selling technologies that were reporting to. To accomplish all those things. But even the executives of those companies and the investors investing in such companies weren't really practicing what they speak because, you know, as. As, you know, great as it is to work remotely, there are so many things that at least so far, are just still better accomplished in person. So. So that was what we were discussing then. Now, clearly technology is at a whole different place. And we have had this collective experience of being forced, obviously not to meet as much. So, you know, today is different. But there are a number of challenges, especially in manufacturing, that have to do with, you know, how are you going to keep innovating inside of these factories, things that I hope we can talk about in a second. And many of those ideas that people have, you know, you might be a visionary, you think and say, oh, the factory of the future is going to contain no people. It's going to be great. It's going to be very, very productive. Yeah, you might be right. From an automation perspective, 247 factories driven by robots and remotely monitored. That may be possible in some cases, but as we write about in, you know, in our recent book Augmented Lean, this is not really the whole point here. It is the interplay of humans and machines. That's where the music is. As my colleague at McKinsey usually says, the music is kind of when you interact, and that's Also where the innovation is. So, you know, you might be able to automate. And obviously the whole thrust of software innovation now nowadays is in order to kind of activate the information that is in all these machines. We call it machine monitoring. And there are so many exciting things you can do with machines in manufacturing. But you have to never, you know, forget the objective, which is you try to mobilize information so that you can do things better. And things change also very fast. Today's markets are, you know, consumer demands and industry demands change fast. So, you know, I think the most adaptive machine that we ever built, you know, is the human being. And this is really important to think about. As fast as technology is moving, there will be quite a some time until, you know, our digital technologies or our hardware really can, can surpass a human being or teams of human beings. So. Yeah, yeah. So those kinds of questions have stayed with me for more than 20 years after that coincidence in that one place. Isn't that fascinating?

Yeah, that's so cool. So you mentioned your book, most recent book, Augmented Lean, A Human Centric Framework for Managing Frontline Operations. So before I ask you, my first official question is gonna be what is Augmented Lean? But I'm curious to get before get there, like what is your background which is what we would call Lean thinking, just Lean manufacturing, whatever you want to call it. Like what's your background with, with the, just the foundational concept of, of Lean.

Yeah, it's interesting. I mean, for many, many years I wasn't really using the concept Lean at all. It's not something that, you know, I have spent 25 years doing. But incidentally, when I started working with my co author Nathan Linder, who has spent decades working on Lean technologies and Lean practices in the manufacturing industry, and we started co writing and doing research for this book, that's when I started to really think deeply about whether some of the work that I had already been doing, whether it was related to Lean. And in fact, of course it is because Lean is such a generic principle, principle of increasing the quality of your work that a lot of people luckily are already practicing parts of Lean. It's a, it's a very nice concept to structure your activity around if you are in the industrial workplace. But of course it has inspired others. And you know, Toyota, where it originated, has inspired people across industry and you know, so I would say the background that I have in Lean is recent to the last few years, but the concepts that others have been innovating on that have to do with, you know, doing work of Quality, essentially, also reducing waste and, you know, focusing on what matters. I've been doing that for a very long time. Quality has been, in fact, before this PhD work, I was concerned with quality work. I wrote a master's thesis on quality criteria in the publishing industry, no less. But, you know, quality is such an essence and it's something that matters whatever you do. And I think a lot of Lean practitioners have been able to create a nice career for themselves by extrapolating on what Lean might mean in very, very different contexts, certainly outside of the, of the factory. And that's the powerful part about the concept of lean, is that it is so, you know, it has the plasticity to it. It just can be adapted to a great many settings.

Yep. Okay, Augmented Lean, give us a rundown. What is it?

So we've talked briefly about Lean, you know, so Lean, if you just isolate it to reducing waste and increasing quality, something very, very simple like that. You know, one version of defining Lean, what augmented Lean is, it's a reaction to the idea that when digital technologies get used in connection with manufacturing and industry, the temptation is just say, oh, just to say, oh. It's just we have digital lean. We have digital on top of, of whatever we're doing, which is Lean. And what we have found is that what this leads to is essentially just more and more automation. So augmented Lean takes difference with the way that industry 4.0, this, you know, very hyped up term, has been practiced, which is essentially a deep extension of a very technology determinist perspective on innovation, where you're kind of saying technology in and of itself has all of these effects. And you have to, as a worker, as a workforce, you have to adapt to all these machines. And the whole idea is, how can we train more workers to understand these fantastically complicated machines? What we're saying is the opposite. We need to become a human centric workplace. Not because of a feel good factor. That's nice too. Workers should be happy because they produce better. Yes. But, you know, in order to innovate, in order to tackle the challenges that the contemporary workplace really demands of us and to get more productivity out of each worker, it behooves us to create a human centric workplace, meaning the humans is at the center and the machines are at the periphery. Meaning it is the machines that need to adapt to the humans, not the other way around. So that's kind of the overall perspective, and we study in this book in very practical ways how large companies and small companies have applied these perspectives with great success. And are avoiding, you know, what really tends to happen in manufacturing, which is you look at somebody else's shiny machine and you invest millions of dollars in this machine. And after a year, you know, you wrap this machine up and put it in the corner because you never really checked if you needed it, if it fit your context. You never checked if the workers were trained or wanted this machine. You never checked if this was the particular bottleneck that this machine was addressing. So all of this, I think, relates a lot to the topic of your podcast Agemba situation. The. The idea of the power of walking around and the power of asking the workforce, what is your problem? What is your challenge? And then adjusting based on what you're learning continuously.

Right.

And this is. This is how we think technology needs to be implemented.

Yeah. Subservient to the humans. Right. Basically. So, yeah.

And it doesn't sound so radical when we, you know, perhaps we agree about this, but the thing is, really isn't practiced this way. This is not how technology is purchased in today's manufacturing workplace. You know, you're sitting there looking at productivity numbers, you want to squeeze out an extra 5%, and you're saying, well, you know, we buy some machines here, we buy some robots there, we're going to get these effects because we've seen it at Amazon or we've seen it at some big company.

Yeah.

Well, that is a very, very typical but not a very wise approach to implementing technology. You have to start with being extremely certain that you're fixing a true bottleneck. And, you know, you technology needs to be used in an innovative sense where you're actually looking at what your next challenge might be. So you have to make it adaptive. Now, there are technologies that are adaptive, and we are studying some of those. Right. Notably, you know, these new no code interfaces where you're using technology that demands very little training from the operator to use, and where industrial engineers can tweak a process, perhaps put in place a digital app that actually helps the worker without intruding in their daily life, where you, yes, you are using sensors, you are perhaps using machine monitoring, and you're using maybe AI to derive data. So it's not that we're against using technology, but you don't start there. You start with what's the problem? And then you implement from there with as simple technology as possible and never more complicated than it needs to be.

Yeah. I'm curious to get your perspective on, like, a company like Toyota, for example, who is, you know, arguably, as you mentioned earlier, even, you know, Present day one of, if not the top, so called Lean. They don't call themselves Lean, but you know, so called lean thinking organization in the world. Like how, how, how do you think they're doing with their use of automation and their, their involvement of the human beings that are walking around their facilities. Are they doing okay or do you think they would do better if they did something different?

Look, it's hard to argue against Toyota. That's like betting against, you know, betting against the winner is, is never a good game. So I'm not going to, I'm not going to criticize Toyota. I think they generally have been weathering a lot of changes throughout the decades in a very impressive way. However, the, the relationship that Toyota has with their workforce is quite different than it is in most other companies. And this is of course why you can't necessarily copy Toyota. It is very difficult. Certainly Toyota in Japan, but also the factories that they have other places they have just, you know, worked up a culture and a set of things that they prioritize that you, you cannot, you know, you can't copy that overnight. Having said that, there are some challenges with the assumptions around Lean that I'm certainly not the first to have noticed. But you know, in the classic conception of Lean, you're assuming a very, very stable workforce. Now look at the US Workforce. The turnover in most industries and certainly in manufacturing is very, very high. So there's a challenge right there. Whether you're Toyota or you are any automotive or, or really, you know, any factory. The fact that you have to retrain people a lot and with quicker and quicker turnaround cycles and you know, also an aging workforce that ages out and a lot of new talent that you have to bring in very quickly and with no expectation that they're going to stay beyond two years. Well, that's a challenge that Toyota wasn't prepared for either and no other company really has truly figured out. So I would say over time Lean is going to become more and more challenging unless we address the, you know, these assumptions with some of the tweaks that we are talking about in augmented Lean. Because augmented Lean fixes some of those challenges that have to do with, you know, larger disruption, bigger disruption factors that are, you know, affecting the work place. You just have to approach everything with a different temporality in mind. You have to launch things that can be effective after a week or two weeks. You cannot, you know, have these massive technology implementation programs because by the time you have, you know, in a perfect way implemented a complex system, whether it's software or hardware, that system will need to change. If your customer wants, you know, will want different things, you're maybe producing, you know, different metal parts for a completely different region in the world. So by the time you have implemented this very complex system, you know, your robot may not be needed anymore or, or that particular machine that you bought. So. So in other words, whatever infrastructure you are investing in, you have to make sure that at least the systems that run on top of it are able to adapt and that you can tweak those systems really fast. So that goes for Toyota, and I think it goes for any company. But certainly the automotive industry is one that automated really quickly. Right. And it is perhaps the most automated of all industries. But even for them, there is a limit to automation. And when you start approximating that limit, the rest of the innovation is what you can squeeze out of people and people working with technologies, because people and technology working in an optimal way is always going to be much more powerful than just technology. This was actually one of the original insights of my PhD back in 2000.

Yeah. One, I think the majority of Lean thinkers, the ones that I've interacted with over the last 20 some years for sure, aren't disagreeing with anything that you're saying. I mean, respect for people is one of the pillars that we talk about within a lean thinking organization. Right. And continuous improvement in the other one. You know, we do talk about things like Jidoka, which is, you know, automation with a touch, which is perhaps inching our way towards, you know, automation or something like that, to assist, you know, in those two pillars. But. But it's not a pillar, you know, in and of itself like continuous improvement and respect for people. So. Yeah, so I think, I think you're among friends here.

Yeah. And that's why we're calling it Augmented Lead. We're not. There are a lot of people who are trying to say, well, you know, Lean's not relevant anymore, that that's not at all what we are saying. You know, augmented Lean. The only reason we're qualifying Lean with Augment 3D is not to react to Lean, which we really respect, but to react to Digital and Industry 4.0 that people slap on top of Lean, which we do not recommend.

Yeah.

So Lean in and of itself is a very, very sound principle. And as people have added things on top of it that have to do with technology, you just got to be very, very careful because, sure, some of those perspectives were actually changing Lean in not a good way and perhaps are impossible to practice. With Lean. So this is what we were saying, our critique, the whole book is not a critique of Lean. It is a critique of, critique of the over easy digital that has been applied especially in manufacturing and industrial technology.

So do you have any examples perhaps of organizations who have implemented what you're calling augmented lean and then perhaps what they've, how they've, how they've done?

Yeah, and you know, let me take a couple of examples. You know, there are different industries that you can do this. But we work with Stanley Black and Decker, for example. Right. There's an organ that's an organization a lot of people might, might know at least if you are into, you know, home improvement projects.

Oh yeah, everybody's got a Black and Decker drill, you know.

Exactly. So you've used their, their tools. Oh yeah, well, those industrial tools is one thing, but you know, the way that Black and Decker's organization has reorganized around their workforce and putting their workforce at the center using these app spaced approaches, they, you know, have really been amazing. We have been observing, for example, I, I went to a factory there last year up in Massachusetts and I discovered that you know, even very junior but very smart sort of quality managers, through talking to operators we're able to implement this very easy app solution that simplified the work of this person that I talked to who was bending metal. And he now has a digital app that governs his role, basically where a lot of what he's doing is being recorded automatically by a sensor so he doesn't have to type it in. And whatever else he's doing, he gets immediate feedback with digital work instruction straight onto his station. And all of these changes, they could have been implemented by kind of management decree from the top. Right. You know, headquarters in Connecticut says you have to use all these things. But no, this was a very lightweight digital app that this young quality manager, her name is Sophia Baran, implement it in a matter of months. And she did it first by walking around and checking, you know, what are, what are the issues we're having here. And once she figured out what she thought was, you know, a very fixable problem, she built this little app, tested it with the operators, made sure that they were comfortable with it and then implemented it. And guess what happened? Now it's a best practice that's being sort of flown around. And this particular app will now probably be implemented in many, many other factories. Not because management, you know, says everybody has to do it, but because, you know, it came as a bottom up initiative, obviously using the app platform that she had available to her. So it's a software based platform that she as a non programmer was able to use. Right. So she's not a trained software programmer at all. Yet she implemented something in software that changed the, the way that her own operators on that factory could register the data that they're working on, registers the actions that they were taking and makes them much more efficient and actually makes them much more empowered because they have a lot of insight and knowledge that, that she is feeding onto their stations, you know, onto monitors that they can see. This could be information on basically what the product is being used for or it's information that comes before, you know, this metal bender gets, gets his job going or it's information about, you know, somewhere later in the, you know, in the production process. So this is just one example of, of how they use an augmented lean technique. Both in the way that they approached it, the way they kind of let the individuals, you know, figure their thing out. And then in, in retrospect, of course they now use this and they standardize the approach so that these kinds of things can happen elsewhere. But they're not saying you have to use it. Yeah, but you, you, I just want to give you an example from a completely different industries. We are also working life science and I've been observing activity there with J and J. Right. Massive company. And they similarly you, you would think because it's a regulated industry that everything there, you know, all technology is, you know, dictated from above. But similarly to standard Black and Decker, JJ decided very early on that digital was going to be an exception to kind of the typical top down situation. They were aware that the life science industry historically has, you know, a lot of top down rules, but when that happens in the digital space, it's detrimental. So they issued basically decrees that you know, there is a certain amount of experimentation allowed, obviously less so than in a non regulated industry because you know, there are certain frameworks that they have to follow. But again, they were able to implement two types of digital solutions. One in the regulated domain, you know, some of the technologies that they have been able to put in place, you know, were, were started by management and they were following, you know, regulations that, that are mandated and other technologies they discovered, guess what, this is a gap in the regulation. We can use the exact same approach as any other industrial firm and we can implement this digital app because you know, work instructions, you know, in, in this particular domain is not, is not regulated. So they're actually doing something that's more than the government demands of them for you know pill production or whatever they're doing at the, at the particular moment, but they're making simultaneously their work more efficient. And being such an enormous organization though, they have to keep the rules of engagement very, very clear. So again, you know, even in a life science situation, all of, all of these lightweight software based sort of apps that sit on top of, of the machines and give information back to the production workers, you can use them both to standardize the process. So you know, kind of a concern of a manager and you can use it to liberate an operator at the bottom of the organization who is sitting there and previously had really no oversight of, you know, where, what is happening right before, what I'm doing right now. Right. Typically, you know, just in time, you get the product, you know exactly what you're going to do, but you have no idea how many units are going to come in and you have no idea what happens afterwards. The power of these techniques is to give you much more visibility without requiring this typical training time and the rigidity of other solutions. So in both organizations, the empowerment, especially of the frontline workforce is I think the most powerful effect of this. Of course, machine monitoring also gives information to managers. So leaders now have a bigger chance to, to have an early warning of something that's going wrong in their organization or to turn their sort of ships around or even when they're shifting to different production techniques, you know, when things are digitized, it's easier to do so.

But again, what I'm hearing, Tron, is, is what it sounds like and correct me if I'm wrong, is that you're, you're really passionate, as am I. And, and I would argue the majority of the folks listening of elevating human beings in our workforce to use their brains and their full, that they have to elevate the workforce, leveraging things like technology, equipment, automation, whatever it might be to, you know, make progress, if you will. So. Well, first of all, is that accurate? Do I have it right?

You have it right, Ron, because I think manufacturing workers overall, right. I mean, whether in some countries they're up to 20% of the workforce, in others, such as the U.S. it's almost down to 10 or 12%. But it's a big amount of workers, right? This is a lot of people. And the thing is, when you think of a worker in manufacturing, you don't necessarily think knowledge worker, right? Knowledge worker is this label that one started to attach to office workers, right. Since the 70s and 80s. Basically we were kind of assuming that if you work with, you know, theoretical knowledge essentially and books and things. You're a knowledge worker. Turns out that I think this is a great misconception. Everybody in the manufacturing industry who works with complex information and builds complex products is in some sense a knowledge worker. It's just that all of the invest investment went to the desk workers who sit in offices and got billions of dollars in IT productivity software that, you know, after a while actually became pretty good and pretty simple to use. Now this didn't benefit manufacturing at all. You know, again, like not to scream about these big machines. There's, there's a lot of good machines out there. But the point is we never finished the innovation path. The machine is one thing, the interface unfortunately is a whole another. And we are now slowly over the last decade developing the kind of productivity tools that workers at the front lines are going to need. And it will be proven out in very, very few years that knowledge work is not a category that's, you know, saved for office workers. You know, if you stand up and you're working, you could also be a knowledge worker. It's just that you never had the tools. So. And it's not just about doing things faster as I, I guess repeat to the annoying detail here. It's about doing things better, obviously. Right. It's about doing the right things. And when you have those digital tools to simplify the stuff that can be simplified, you then have the mental energy to think about the complicated things, to train your colleagues to think about changes, to identify errors and root causes of failure on the floor. All of the good things that we think of with Lean. The problem is if you don't have the mind space to do that because you're constantly stuck doing repetitive work or you don't have the data on the work that you are accomplishing, that's or, or even worse, you're using a machine that is interfering with your natural way, with the way that you would have accomplish that work task.

Yeah, yeah. What's interesting about some, somebody might listen to this conversation, not hear the whole thing to think that you're anti technology or you're anti automation.

No, that's really, really not the case.

Yeah, yeah, yeah. What you're proposing is that we need to, we need to allow all of our associates the full access to the technology into the information, if you will, affording them the opportunity then to use their brains to say that he. I would like to be able to do this or my friend Paul aker is at FastCap. I don't know if you're familiar with that company there in Washington and some smaller company, but they're, they're prolific and as far as practicing lean really, and, and they're not big into technology and so forth, but they're, they're, they're, they're, their mantra is fix what bugs you, right? So like everyone in their workforce is empowered on a daily basis to fix what bugs them, you know, and so more, many, many lean thinking companies are practicing this now. Some aren't as well and I wouldn't call them lean company. That's the other problem. When we use these labels or you're a lean company, you're not a lean company, you know, it's a, you know, you're a company, you know, and you might practice some, some concepts that somebody called lean back in the 80s when they traveled the world. Right. You know what I mean? So that's the, that's the danger of labels, even Industry 4.0, automation. These are all labels that put things in boxes, right? And then, and then you have to choose do I box or not? You know, and, and so I, I feel like I want to make sure people don't misinterpret your, your true meaning here by thinking that, that, that you are against all these things. But obviously things like these, the so called smart factory and you know, this industry 4.0. Am I correct to say that, you know, you're not a massive fan of this, that, that movement in and of itself.

So I know a lot of the people in that movement, there's a lot of good people that mean well when they use the term Industry 4.0. They want to make things better, they want to deploy more advanced technology. They are concerned that, you know, workers are not getting trained on these exciting and new technology innovations. And you know, by no means am I against that. And in this book we're not arguing against technology. What we are saying is there are many, many ways to implement technology. Augmented Lean even can be implemented in very, very different ways. It's not a staged model where you have five things you need to accomplish or 11.

Yeah, five steps to being odd and benched and lean.

No, no, no, it's not like that. It is a kind of a rich fountain of perspectives that starts with being human centric, defining what that means. It essentially just repositions the objects that you have to deal with and it puts the human literally visually and phys, and then reorganizes even the physical position of the other objects and resources, whether they are machines or just necessary constraints around the Workplace all or all along the supply chain. Of course there's going to be technology here. You know, the, the company where we did this field work is Tulip. It's a software company out of mit. There is so much technology there that, you know, they actually had to slow down their technology because the biggest problem, you know, in 2013 when Tulip got commercialized was pen and paper, you know, on the manufacturing workflow. So you were dealing then with. And I love pen and paper. It's fantastic technology. Right. I still use pen and paper. But the thing is, you know, in order to adapt your technology to what the problem is, you choose the simplest. So in many cases, you know, we might have a panoply of technologies available. You just have to use it sparingly. So in some cases that is sensors, because they're cheap and they give you data. But even if you're using sensors in the, in the workplace, don't install 5,000 sensors because you're not going to have the time to read what those sensors are saying, install 20, and then really understand what those 20 sensors are telling you. This is more the perspective that we're using. And then by all means, if you get enough data from those 20 sensors to use an AI software and some algorithms to, to interpret that data and feed it just in time to operators, you know, obviously with a, an interface and some results that they can digest without stopping what they're doing, all the better. Right?

Yeah.

And if you have an advanced CNC machine that you bought and you want to use machine monitoring tools on top of that, Tulip facilitates that. Right. So it is just. The point is it's the interplay of data and production practices and human thinking. That's what innovation is.

Hey, can I ask you a completely tangential question? Completely, completely in a different direction on a. Maybe it's related, but I don't think it is. What is your opinion of the impact social media? Facebook, Instagram, TikTok for the kids, these things that this social media movement that we find ourselves in, what impact has it had on humanity?

Well, let me first bring it back to. I think what we're talking about, social media has had an immense impact on the mentality of young workers. The workers that grew up with social media don't really understand when they go to work and they have to leave their iPhone or smartphone at home or on the desk or whatever, and they can't deploy it and use it as part of what they're doing at work. This is why this apps based approach that I'VE been talking about which Tulip represents is so refreshing, I think, to many, many young manufacturing workers, because here it's not that they necessarily use their own smartphone, but they might use a tablet and they do use apps and they literally are using the same approach that they would do in their private life at work. This is very important because if those two spheres, work and home, become too different, it really is just not understand. It's not comprehensible to young talent anymore. So this is why one might have a talent challenge in manufacturing. Luckily, this is going away because it's actually very possible to use these approaches. Social media in and of itself, though, I think it's been called the problem of the decade. And right now it looks pretty bleak in the sense that I think social media, the worst excesses of social media have really created a lot of problems. They have created some trust issues overall in society. The fabric of society has been challenged by the ease with which you can share information that doesn't necessarily have, have a clear provenance so that you cannot really assess it. And this leads people to say, well, there's now no judge anymore. There can be no assessment of what is good and what is bad. The challenge with that is now you're questioning all expertise. Now no authority is valid anymore because, you know, you just don't really care. That I think isn't a good thing, but I do not necessarily think that it's a lasting problem. Social media showed up pretty suddenly and I think it might evolve into something else pretty quickly as well. I think we are probably overthinking it at this very moment in the sense that it's morphing into something else. Yeah, yeah.

The reason that I asked is because you're obviously very passionate about the, the human being being the center of the, of the workplace in, in this example of the factory, even. And what I, my personal bias and I'm, I'm, I'm open to being wrong. I could be wrong, is that I have children, you know, I have teenagers and, and you know, and some of them are, we don't, we have different rules with social media and our kids. I won't get into all that. But, but, but looking at my, like my daughters and, and sometimes I'll sense anxiety in them, whether it's I don't look pretty enough for something like that, you know, because these, these, these females on the app are perfect and the filters are perfect and all this. And so there's, there's all kinds of challenges for not just females, but for for just human beings. And so I'm of the opinion that it can be very harmful, you know, if it's not leveraged correctly and very harmful to humanity. Like, I worry, like, I'm, I'm freaked out, honestly, on this whole metaverse thing that, you know, we're gonna wear, wearing goggles, glasses one day, sunglasses, and my wife's gonna be like, are you talking to me? Are you watching the game? You know, you know what I mean? And like, I, I feel like we lose connection. Like, you know what I mean? Like, we're not. That we're not connecting human to human anymore. And so that's why I was kind of where I was going with that.

All right, so to answer that, I think, yes, that there's two things to say, right. Number one, this would follow from what we've been talking about that I don't think that technology in and of itself should or could change human beings in the sense that there are technology scripts embedded in every technology, meaning the designer of that technology has an idea in mind. He has a. You, he or she has a use case in mind. They want you to use it in a certain way. And some of the social media, tick tock or other things, they have these kind of viral mechanisms in there. Highly addictive, highly addictive. They react to you, you react to them in a psychologically sort of induced state.

Yeah.

However, humans are humans and we overturn scripts that we don't like. And so there's a rescue mechanism. There's a protective factor in human beings. That's why I'm saying I think social media is going to change and will change. I don't think your teenager is in such danger. Right. Any balanced teenager, they will do this for a little while and then they will come back to who they are as a human being. And even if they were for a few years, like I was immersed in some sort of computer game, it happens. You come out of it and you realize, yeah, well, that was interesting. I'm going to be in that space for a little bit. But there's so many other things that count. And when you're talking about the metaverse, right, the industrial metaverse, which is kind of our conversation here, I think, is a far more interesting place than the commercially consumer metaverse. The consumer metaverse you're scared about. First of all, it hasn't shown up yet, right. So the technology interfaces would have to improve so much. It will show up because, you know, there's an economic incentive there. However, I think it'll show up In a very different way than certainly than Facebook thinks. Right. The thing is, we are physically tethered beings. Sounds kind of awkward, but, you know, augmented reality, for one, is so much more powerful than virtual reality, augmenting something that is projecting an extra dimension on top of what you already have. So we've been talking about augmented in a more simple sense, like, you know, software and apps that help workers become more efficient. But there's also a whole other augmented reality discussion that has to do with, with goggles and things that now are, you know, active both in the workplace and, and of course, you know, your, your kids might have access to these tools and play games or interact using these virtual or augmented reality headsets. Tulip actually implements the RealWear headset. It started to get some use cases now in industry in, in very, very special cases because, you know, it's still, these are wobbly. They're, they're still big, big glasses. You know, even Google Glass, right, didn't, didn't succeed in their initial mission, which was to kind of, to capture the imagination of everybody with, with, you know, the glasses form factor. But the, the point is, even if the interface becomes really very, very small, augmentation still is only a complement to the rest of reality. There's a complex compellingness in reality that I think we need to hold on to, and that I think is going to win in the end. I hope I'm just not so worried about this. I, I think reality fights back, Ron. Yeah, Reality fights back.

Okay, Maybe that's the name of this podcast. Reality Fights Back.

I love it.

That's fantastic. That's so good. That's so good. Reality fights back. Well, we're aligned on that, my friend. I, I, I, I, I, I want reality to keep fighting. It's almost like entropy, you know, it's always pulling disorder into the system, right. And it never stops, you know, and the only way to combat entropy is to continuously improve, you know, and, and never stop, so. Fantastic. Well, wow, this has been a really interesting conversation, Tron. I, I appreciate you taking the time to, to come onto the show and to share your thoughts. Hey, if folks wanted to connect with you or learn more about your book or your work or all that kind of stuff, what's the, the best way? Social media, perhaps, or, you know, website, something like that? What do you got?

Good. All Internet augmented lean.com. you know, it's been there since the 90s. It's true and tested. I, I also do respond to people occasionally on LinkedIn, unless it's just super commercial pitches. So straight on LinkedIn or, or you know, through the website on augmentedlean.com that's, that's the best.

Spell your name Trond. In case people are just listening.

Yeah, my name is Trondenheim. T R O N D U N D H E I M. It's a, it's a name hard to spell but impossible to forget it.

Yes. Yes. Fantastic. All right, well, thanks again for coming on Tron. This has been a.

Been a.

Been a really super interesting conversation and I appreciate you taking the time.

Thank you so much for having me.

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