Jim explains how digital manufacturing in pharma has evolved over his nearly 3 decades in the industry, from basic automation and data collection to advanced predictive modeling and integrated digital ecosystems—and why having humans in-the-loop continues to be critical despite these advancements in autonomy.

He also shares his perspective on building trust in emerging technology, the continued importance of lean principles, and the tension between regulation and speed to market.

Augmented Ops is a podcast for industrial leaders, citizen developers, shop floor operators, and anyone else that cares about what the future of frontline operations will look like across industries. This show is presented by Tulip, the Frontline Operations Platform. You can find more from us at Tulip.co/podcast or by following the show on LinkedIn.

Special Guest: Jim Fox.

In order to successfully transform their business, Jörg calls on manufacturers to take a systemic approach to technology adoption by enabling interdisciplinary collaboration, and focusing on use cases that drive value for the business. He draws on his extensive experience with real-world implementation examples, sharing his lessons learned and best practices from successfully implementing the blueprint he describes in our conversation.

Augmented Ops is a podcast for industrial leaders, shop floor operators, citizen developers, and anyone else that cares about what the future of frontline operations will look like across industries. This show is presented by Tulip, the Frontline Operations Platform. You can find more from us at Tulip.co/podcast or by following the show on LinkedIn.

Special Guest: Jörg Gnamm.

Jim Huntzinger, President of Lean Frontiers, joins us in this episode for a deep dive into the lean business model and all things lean accounting. We explore value stream versus product costing, the importance of lean coaching, the principles of Toyota Kata, and how these strategies can drive processes improvement and product development simultaneously. Throughout the conversation, we examine the value of transforming traditional business practices and the potential impact on organizational decision-making and growth.

If you like this show, subscribe at AugmentedPodcast.co. If you liked this episode, you might also like Episode 108: Lean Operations with John Carrier, or Episode 84: The Evolution of Lean with Torbjørn Netland. Augmented is a podcast for industry leaders, process engineers, and shop floor operators, hosted by futurist Trond Arne Undheim and presented by Tulip.

Follow the podcast on Twitter or LinkedIn.

Trond’s Takeaway:
The lean business model is attractive to many manufacturing firms and still elusive to some of them, despite many examples of the principles in action popping up constantly. The business community should still spend more time on the interface between tech, logistics, and IT, and how all of that might interface with lean accounting. Strikingly, what we might think of as lean companies don't necessarily use lean practices across their business.

Special Guest: Jim Huntzinger.

In this episode of the podcast, the topic is "Lean Operations." Our guest is John Carrier, Senior Lecturer of Systems Dynamics at MIT. In this conversation, we talk about the people dynamics that block efficiency in industrial organizations.

If you like this show, subscribe at augmentedpodcast.co. Augmented is a podcast for industry leaders, process engineers, and shop floor operators, hosted by futurist Trond Arne Undheim and presented by Tulip.

Follow the podcast on Twitter or LinkedIn.

Trond's Takeaway:

The core innovative potential in most organizations remains its people. The people dynamics that block efficiency can be addressed once you know what they are. But there is a hidden factory underneath the factory, which you cannot observe unless you spend time on the floor. And only with this understanding will tech investment and implementation really work. Stabilizing a factory is about simplifying things. That's not always what technology does, although it has the potential if implemented the right way.

Transcript:

TROND: Welcome to another episode of the Augmented Podcast. Augmented brings industrial conversations that matter, serving up the most relevant conversations on industrial tech. And our vision is a world where technology will restore the agility of frontline workers.

In this episode of the podcast, the topic is Lean Operations. Our guest is John Carrier, Senior Lecturer of Systems Dynamics at MIT. In this conversation, we talk about the people dynamics that block efficiency in industrial organizations.

Augmented is a podcast for industrial leaders, process engineers, and shop floor operators, hosted by futurist Trond Arne Undheim and presented by Tulip.

John, welcome to the show. How are you?

JOHN: Trond, I'm great. And thank you for having me today.

TROND: So we're going to talk about lean operations, which is very different from a lot of things that people imagine around factories. John, you're an engineer, right?

JOHN: I am an engineer, a control engineer by training.

TROND: I saw Michigan in there, your way to MIT and chemical engineering, especially focused on systems dynamics and control. And you also got yourself an MBA. So you have a dual, if not a three-part, perspective on this problem. But tell me a little bit about your background. I've encountered several people here on this podcast, and they talk about growing up in Michigan. I don't think that's a coincidence.

JOHN: Okay, it's not. So I was born and raised in the city of Detroit. We moved out of the city, the deal of oil embargo in 1973. I've had a lot of relatives who grow up and work in the auto industry. So if you grew up in that area, you're just immersed in that culture. And you're also aware of the massive quote, unquote, "business cycles" that companies go through.

What I learned after coming to MIT and having the chance to meet the great Jay Forrester a lot of those business cycles are self-inflicted. What I do is I see a lot of the things that went right and went wrong for the auto industry, and I can help bring that perspective to other companies. [laughs]

TROND: And people have a bunch of assumptions about, I guess, assembly lines in factories. One thing is if you grew up in Michigan, it would seem to me, from previous guests, that you actually have a pretty clear idea of what did go on when you grew up in assembly lines because a lot of people, their parents, were working in manufacturing. They had this conception. Could we start just there? What's going on at assembly lines?

JOHN: I'm going to actually go back to 1975 to a Carrier family picnic. My cousin, who's ten years older than I, his summer job he worked at basically Ford Wayne, one of the assembly plants. He was making $12 an hour in 1975, so he paid his whole college tuition in like a month. But the interesting point was he was talking about his job when all the adults were around, and he goes, "Do you know that when they scratch the paint on the car, they let it go all the way to the end, and they don't fix it till it gets to the parking lot?"

And I'll never forget this. All the adults jumped on him. They're like, "Are you an idiot? Do you know how much it costs to shut the line down?" And if you use finance, that's actually the right answer. You don't stop the line because of a scratch; you fix it later. Keep the line running. It's $10,000 a minute. But actually, in the short term, that's the right decision. In the long term, if you keep doing that, you're building a system that simply makes defects at the same rate it makes product. And it's that type of logic and culture that actually was deeply ingrained in the thinking. And it's something that the Japanese car companies got away from.

It's funny how deeply ingrained that concept of don't stop the line is. And if you do that, you'll make defects at the same rate that you make product. And then, if you look at the Detroit newspapers even today, you'll see billion-dollar recalls every three months. And that's a cycle you've got to get yourself out of.

TROND: You know, it's interesting that we went straight there because it's, I guess, such a truism that the manufacturing assembly line kind of began in Detroit, or at least that's where the lore is. And then you're saying there was something kind of wrong with it from the beginning. What is it that caused this particular fix on keeping everything humming as opposed to, I guess, what we're going to talk about, which is fixing the system around it?

JOHN: There's a lot of work on this. There's my own perspective. There's what I've read. I've talked to people. The best I can come up with is it's the metrics that you pick for your company. So if you think about...the American auto industry basically grew up in a boom time, so every car you made, you made profit on. And their competitive metric was for General Motors to be the number one car company in the world.

And so what that means is you never miss a sale, so we don't have time to stop to fix the problem. We're just going to keep cranking out cars, and we'll fix it later. If you look at the Japanese auto industry, when it arose after World War II, they were under extreme parts shortages. So if one thing were broken or missing, they had to stop. So part of what was built into their culture is make it right the first time. Make a profit on every vehicle versus dominant market share.

TROND: Got it. So this, I guess, obsession with system that you have and that you got, I guess, through your education at MIT and other places, what is it that that does to your perspective on the assembly line? But there were obviously reasons why the Ford or the Detroit assembly lines, like you said, looked like they did, and they prioritized perhaps sales over other things.

When you study systems like this, manufacturing systems, to be very specific, how did you even get to your first grasp of that topic? Because a system, you know, by its very nature, you're talking about complexity. How do you even study a system in the abstract? Because that's very different, I guess, from going into an assembly and trying to fix a system.

JOHN: So it's a great question. And just one thing I want to note for the audience is although we talk about assembly lines, most manufacturing work is actually problem-solving and not simply repetitive. So we need to start changing that mindset about what operations really is in the U.S. We can come to that in the end.

TROND: Yeah.

JOHN: I'll tell you, I'm a chemical engineer. Three pieces of advice from a chemical engineer, the first one is never let things stop flowing. And the reason why that's the case in a chemical plant is because if something stops flowing for a minute or two, you'll start to drop things out of solution, and it will gum everything up. You'll reduce the capacity of that system till your next turnaround at least. And what happens you start getting sludge and gunk.

And for every class I was ever in, in chemical engineering, you take classes in heat transfer, thermodynamics, kinetics. I never took a class in sludge, [laughs] or sticky solids, or leftover inventory and blending. And then, when I first went to a real factory after doing my graduate work, I spent four to six years studying Laplace transforms and dynamics. All I saw were people running around. I'm like, that's not in the Laplace table.

And, again, to understand a chemical plant or a refinery, it takes you three to five years. So the question is, how can you actually start making improvement in a week when these systems are so complex? And it's watch the people running around. So that's why I focus a lot on maintenance teams. And I also work with operations when these things called workarounds that grow into hidden factories. So the magic of what I've learned through system dynamics is 80% to 90% of the time, the system's working okay, 10% or 20% it's in this abnormal condition, which is unplanned, unscheduled. I can help with that right away.

TROND: So you mentioned the term hidden factories. Can you enlighten me on how that term came about, what it really means? And in your practical work and consulting work helping people at factories, and operations teams, and maintenance teams, as you said, why is that term relevant, and what does it really do?

JOHN: Great. So I'm going to bring up the origin. So many people on this call recognize the name Armand Feigenbaum because when he was a graduate student at the Sloan School back in the '50s, he was working on a book which has now become like the bible, Total Quality Management or TQM. He's well known for that. He's not as well known for the second concept, which he should be better known for. Right after he graduated, he took a job in Pittsfield, Massachusetts, for one of the GE plastic plants.

Here he comes out of MIT. I'm going to apply linear equations. I'm going to do solving, all these mathematics, operation constraints, all these things. When he gets into that system, he realizes 30% of everything going on is unplanned, unscheduled, chaotic, not repeated. He's like, my mathematical tools just break down here.

So he did something...as important as marketing was as an operational objective, he named these things called hidden factories. And he said, 30% of all that work is in these hidden factories. And it's just dealing with small, little defects that we never ever solve. But over time, they actually erode our productivity of systems that can eat up 10% to 20% of productivity. And then, finally, it's work that I'm doing. It's the precursor to a major accident or disaster. And the good side is if you leave the way the system works alone, the 80%, and just focus on understanding and reducing these hidden factories, you can see a dramatic improvement quickly and only focus on what you need to fix.

TROND: So, for you, you focus on when the system falls apart. So you have the risk angle to this problem.

JOHN: Exactly. And so just two things, I'm like a doctor, and I do diagnosis. So when you go to the doctor, I'm not there to look at your whole system and fix everything. I'm like, here are first three things we got to work at, and, by the way, I use data to do that. And what I realized is if everyone just steps back after this call and thinks about today, right? When you get to the end of the day, what percent of everything in that factory or system happened that was in your schedule?

And you'll start to realize that 30% of the people are chasing symptoms. So you need data to get to that root cause, and that will tell you what data to collect. And second, look for time because what you're doing is these hidden factories are trying to keep the system running because you have a customer. You have your takt time, and so people are scrambling. And if you put that time back into the system, that's going to turn into product.

TROND: John, I'm just curious; when you say data, I mean, there's so much talk of data and big data and all kinds of data. But in manufacturing, apart from the parts that you're producing, I mean, some of this data is hard to come by. When you say data, what data will you even get access to?

JOHN: I come from the Albert Einstein School is. I need a ruler, and I need a stopwatch. Go into any system that you work in, whether it be your factory or your house, and ask the last time someone measured how long something took, and you will find a dearth of that data. And the reason why I love time data is it never lies. Most data I see in databases was collected under some context; I can't use it. So I go right in the floor and start watching 5 or 10 observations and looking at all the variation.

The second point I ask is, what's a minute worth in your system or a second? So if we're in an auto assembly plant, in a chemical plant, if we're in a hospital, in an operating room, those minutes and seconds are hundreds of thousands of dollars. So within about 20 minutes, not only have I measured where there's opportunity, we're already on the way to solving it.

TROND: So, so far, you haven't talked much about the technology aspects. So you work at a business school, but that business school is at MIT. There's a lot of technology there. It strikes me that a lot of times when we talk about improvements, certainly when we talk about efficiencies in factories, people bring up automation machines as the solution to that tool. And I'm sure you're not against machines, but you seem to focus a lot more on time, on organizational factors. How should people think about the technology factor inside of their operations?

JOHN: So, first, you brought up...my nickname is Dr. Don't. And the reason they call me Dr. Don't [laughs] is because they'll go, "Should we invest in this? Can we buy these robots?" I say, "No, you can't do that." And I'm going to tell you why. First is, I was quote, unquote, "fortunate enough" to work in a lot of small and mid-sized machine shops during the 2009 downturn. And I was brought in by the banks because they were in financial trouble.

And the one thing I noticed there was always a million-dollar automation or robot wrapped in plastic. And large companies can get away with overspending on technology, small and mid-sized companies can't. And so what you really want to do is go and watch and see what the problem is, buy just as much technology as you need, and then scale that.

First is, like I just said, I was just in a plant a few weeks ago, and they just implemented several hundred sensors to basically listen to their system. That's all good. It's data we need. Two problems, why'd you put in several hundred and not put in 20? And second, when we inspected it, about 15% were either not plugged in or weren't reading. So what happened was if we would have started with 20 and put the resource in analyzing that data, then when we scaled to the several hundred, we'd have had our systems in place. Instead, we overwhelmed everyone with data, so it really didn't change the way they work. Now we fixed that.

But your question was, why am I skeptical or slow to invest in technology? Technology costs money, and it takes time. If you don't look at the system first and apply the technology to solve the system problem, you're going to end up with a million-dollar piece of equipment wrapped in plastic. If you go the other direction, you will scale successfully. And no one's better at this than Toyota. They only invest in the technology they need. Yet you can argue they're at least as technologically sophisticated as all the rest. And they've never lost money except in 2009 so that is a proof point.

TROND: What are some examples of places you've been in lately, I don't know, individual names of companies? But you said you're working kind of mid-sized companies. Those are...[laughs] the manufacturing sector is mid-sized companies, so that sounds very relevant. But what are some examples in some industries where you have gone in and done this kind of work?

JOHN: I work for large companies and small and mid-sized. And I'm a chemical engineer, but I love machine shops. So I sit on the board of a $25 million machine shop. They make parts for a diesel truck and some military applications. They make flywheels. So one of their big challenges is in the United States and in the world, we're suffering with a problem with castings. We received our castings. Interesting thing is there are void fractions.

One of the things I do want to share is as a systems guy, I'm not an expert in mechanical engineering or any of that, but I can add value by helping look for defects. Let me tell you what their challenge is. So, first of all, more of their castings are bad. Then this surprised me...I learned from asking questions. If you've ever been in a machine shop, one thing I learned about when you're making casting is that there are always bubbles in it. You can't avoid it.

The art of it is can you put the bubbles in the places where they don't hurt? You minimize the bubbles, and you move them to the center. So one is we're getting bad castings, but the second part was when we made some of these castings, and they had a void problem in the center. So that doesn't cause a problem with your flywheel. The customer sent them back because they're becoming oversensitive to the defects that don't count. And it's because they switched out staff.

So I guess what I'm trying to say here is our supply chain is undergoing this new type of stress because we're losing the type of expert system expertise that we've had from people that have worked in this industry 20 to 30 years. That's a really important aspect.

The second is we're in their line balancing all the time. I think a lot of the things you learn in class, you spend one class on load balancing or line balancing, operation and manufacturing, and then you go into a factory, and no one's doing it. So I just wanted to share two points. My one factor is doing that they cut 30% of their time.

Another system I'm working in they have one experienced supervisor managing four new people on four different setups. What I realized is there's not enough of that supervisor to go around. We're like, why don't we shoot videos like the NFL does [laughs] and watch those films of how people do their work? Because when you're an expert, Trond, and you go to do a task, you say, "That has five steps."

But if I sent you or me new, we'd look and go, "There are really about 80 steps in there." And you explained it to me in 15 minutes. How am I going to remember that? So shooting film so people can go back and watch instead of bothering your supervisor all the time, which they won't do. So what I do think, to wrap up on this point, is when you talk about technology, the camera, the video that you have in your pocket, or you can buy for $200, is the best technology you can probably apply in the next three to six months. And I would greatly encourage everyone to do something like that.

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TROND: I wanted to ask you then, derived from this, to what extent can some of these things be taught as skills on a systemic level in a university or in some sort of course, and to what extent? Do you really just have to be working in manufacturing and observing and learning with data on your own? By extension, to what extent can a manager or someone, anyone in the organization, just develop these practices on their own? And to what extent do you need mentorship from the outside to make it happen or see something in the system that is very difficult to see from the inside?

JOHN: So it's interesting you ask that because that's very much the problem I'm dealing with because as good as our universities are, the best place to learn operations in manufacturing is on the factory floor. So how do you simulate that approach? I teach lean operations at MIT Sloan. And what I do with my students is I ask them to pick a routine task, video two minutes of it, and reduce that by 30%. And I've done this two years in a row.

When you look at these projects, the quality of the value streams and the aha moments they had of time that they were losing is stunning. You know what the challenge is? They don't yet always appreciate how valuable that is. And what I want them to realize is if you're washing dishes or running a dishwasher, why is that any different from running a sterilization process for hospital equipment? Why is that any different from when you're actually doing setup so that maintenance can get their work done 30% faster?

I've given them the tools, and hopefully, that will click when they get out into the workspace. But I do have one success point. I had the students...for some classes, they have to run computers and simulations during class. So that means everyone has to have the program set up. They have to have the documentation. So you can imagine 5 to 10 minutes a class, people getting everything working right.

One of my teams basically said we're going to read...it took about five minutes, and they said, we're going to do this in 30 seconds just by writing some automated scripts. They did that for our statistics class, and then they shared it with their other classmates, beautiful value stream, video-d the screens, did it in about four or five hours. The next class they took later I found out they did that for a class project, and they sold the rights to a startup. So first is getting them that example in their own space, and then two, helping them make analogies that improving things in your own house isn't all that much different than the systemic things in a factory.

TROND: Learning by analogy, I love it. I wanted to profit from your experience here on a broader question. It takes a little bit more into the futuristic perspective. But in our pre-conversation, you talked about your notion on industry 4.0, which, to me, it's a very sort of technology, deterministic, certainly tech-heavy perspective anyway.

But you talked about how that for you is related to..., and you used another metaphor and analogy of a global nervous system. What do you think, well, either industry 4.0 or the changes that we're seeing in the industry having to do with new approaches, some of them technology, what is it that we're actually doing with that? And why did you call it a global nervous system?

JOHN: When I graduated from school, and I'm a control systems skilled in the arts, so to speak. And the first thing I did...this is back in the '90s, so we're industry 3.0. When you're in a plant, no one told me I was going to spend most of my time with the I&C or the instrumentation and control techs and engineers. That's because getting a sensor was unbelievably expensive. Two, actually, even harder than getting the budget for it was actually getting the I&C tech's time to actually wire it up. It would take six weeks to get a sensor.

And then three, if it weren't constantly calibrated and taken care of, it would fall apart. And four, you get all those three workings, if no one's collecting or knows how to analyze the data, you're just wasting [laughs] all your money. So what was exciting to me about industry 4.0 was, one, the cost of sensors has dropped precipitously, two, they're wireless with magnets. [laughs] So the time to set it up is literally minutes or hours rather than months and years.

Three, now you can run online algorithms and stuff, so, basically, always check the health of these sensors and also collect the data in the form. So I can go in, and in minutes, I can analyze what happened versus, oh, I got to get to the end of the week. I never looked at that sensor. And four, what excited me most, and this gets to this nervous system, is if you look at the way industries evolved, what always amazes me is we got gigantic boilers and train engines and just massive equipment, physical goods. Yet moving electrons actually turns out to be much more costly in the measurement than actually building the physical device.

So we're just catching up on our nervous system for the factory. If I want to draw an analogy, if you think about leprosy; a lot of people think leprosy is a physical disease; what it is is it's your nerves are damaged, so because your nerves are damaged, you overuse that equipment, and then you wear off your fingers. And if you look at most maintenance problems in factories, it's because they didn't have a good nervous system to realize we're hurting our equipment.

And maintenance people can't go back and say, "Hey, in three months, you're going to ruin this." And the reason I know it is because I have this nervous system because I'm measuring how much you're damaging it rather than just waving it. And now it becomes global because, let's say you and I have three pumps in our plant, and we need to take care of those. They are on the production line, very common. What if we looked at the name of that pump, called the manufacturer who's made tens of thousands of those? There's the global part.

So they can help us interpret that data and help us take care of it. So there's no defect or failure that someone on this planet hasn't seen. It's just we never had the ability to connect with them and send them the data on a platform like we can with a $5,000 pump today. So that's why I look at it, and it's really becoming a global diagnosis.

TROND: It's interesting; I mean, you oscillate between these machine shops, and you had a medical example, but you're in medical settings as well and applying your knowledge there. What is the commonality, I guess, in this activity between machine shops, you know, improving machine shops and improving medical teams' ability to treat disease and operate faster? What is it that is the commonality?

So you've talked about the importance, obviously, of communication and gathering data quicker, so these sensors, obviously, are helping out here. But there's a physical aspect. And, in my head, a machine shop is quite different from an operating room, for example. But I guess the third factor would be human beings, right?

JOHN: I'm going to put an analogy in between the machine shops at the hospital, and that's an F1 pit crew. And the reason I love F1 is it's the only sport where the maintenance people are front and center. So let's now jump to hospitals, so the first thing is if I work in a hospital, I'm talking to doctors or nurses in the medical community. And I start talking about saving time and all that. Hey, we don't make Model Ts. Every scenario we do is different, and we need to put the right amount of time into that surgery, which I completely agree to.

Where we can fix is, did we prepare properly? Are all our toolkits here? Is our staff trained and ready? And you'd think that all those things are worked out. I want to give two examples, one is from the literature, and one is from my own experience. I'd recommend everyone look up California infant mortality rates and crash carts. The state of California basically, by building crash carts for pregnancies and births, cut their infant mortality rate by half just by having that kit ready, complete F1 analogy. I don't want my surgeon walking out to grab a knife [laughs] during surgery.

And then second is, I ran a course with my colleagues at MIT for the local hospitals here in Boston. You know what one of the doctor teams did over the weekend? They built one of these based on our class. They actually built...this is the kit we want. And I was unbelievably surprised how when we used the F1 analogy, the doctors and surgeons loved it, not because we're trying to actually cut their time off. We're trying to put the time into the surgery room by doing better preparations and things like that. So grabbing the right analogy is key, and if you grab the right analogy, these systems lessons work across basically anywhere where time gets extremely valuable.

TROND: As we're rounding off, I wanted to just ask you and come back to the topic of lean. And you, you use the term, and you teach a class on lean operations. Some people, well, I mean, lean means many things. It means something to, you know, in one avenue, I hear this, and then I hear that.

But to what extent would you say that the fundamental aspects of lean that were practiced by Toyota and perhaps still are practiced by Toyota and the focus on waste and efficiency aspects to what extent are those completely still relevant? And what other sort of new complements would you say are perhaps needed to take the factory to the future, to take operational teams in any sector into their most optimal state?

JOHN: As a control engineer, I learned about the Toyota Production System after I was trained as a control system engineer. And I was amazed by the genius of these people because they have fundamentally deep control concepts in what they do. So you hear concepts like, you know, synchronization, observability, continuous improvement. If you have an appreciation for the deep control concepts, you'll realize that those are principles that will never die.

And then you can see, oh, short, fast, negative feedback loops. I want accurate measurements. I always want to be improving my system. With my control background, you can see that this applies to basically any system. So, in fact, I want to make this argument is a lot of people want to go to technology and AI. I think the dominant paradigm for any system is adaptive control. That's a set of timeless principles.

Now, in order to do adaptive control, you need certain technologies that provide you precision analysis, precision measurement, real-time feedback loops. And also, let us include people into the equation, which is how do I train people to do tasks that are highly variable that aren't applying automation is really important. So I think if people understand, start using this paradigm of an adaptive control loop, they'll see that these concepts of lean and the Toyota Production System are not only timeless, but it's easier to explain it to people outside of those industries.

TROND: Are there any lessons finally to learn the way that, I guess, manufacturing and the automotive sector has been called the industry of industries, and people were very inspired by it in other sectors and have been. And then there has been a period where people were saying or have been saying, "Oh, maybe the IT industry is more fascinating," or "The results, you know, certainly the innovations are more exciting there." Are we now at a point where we're coming full circle where there are things to learn again from manufacturing, for example, for knowledge workers?

JOHN: What's driving the whole, whether it be knowledge work or working in a factory...which working in a factory is 50% knowledge work. Just keep that in mind because you're problem-solving. And you know what's driving all this? It is the customer keeps changing their demands. So for a typical shoe, it'll have a few thousand skews for that year. So the reason why manufacturing operations and knowledge work never get stale is the customer needs always keep changing, so that's one.

And I'd like to just end this with a comment from my colleague, Art Byrne. He wrote The Lean Turnaround Action Guide as well as has a history back to the early '80s. And I have him come teach in my course. At his time at Danaher, which was really one of the first U.S. companies to successfully bring in lean and Japanese techniques, they bring in the new students, and the first thing they put them on was six months of operations, then they move to strategy and finance, and all those things.

The first thing that students want to do is let's get through these operations because we want to do strategy and finance and all the marketing, all the important stuff. Then he's basically found that when they come to the end of the six months, those same students are like, "Can we stay another couple of months? We just want to finish this off." I'm just saying I work in the floor because it's the most fun place to work.

And if you have some of these lean skills and know how to use them, you can start contributing to that team quickly. That's what makes it fun. But ultimately, that's why I do it. And I encourage, before people think about it, actually go see what goes on in a factory or system before you start listening to judgments of people who, well, quite frankly, haven't ever done it. So let me just leave it at that. [laughs]

TROND: I got it. I got it. Thank you, John. Spend some time on the floor; that's good advice. Thank you so much. It's been very instructive. I love it. Thank you.

JOHN: My pleasure, Trond, and thanks to everybody.

TROND: You have just listened to another episode of the Augmented Podcast with host Trond Arne Undheim. The topic was Lean operations, and our guest was John Carrier, Senior Lecturer of Systems Dynamics at MIT. In this conversation, we talked about the people dynamics that block efficiency in industrial organizations.

My takeaway is that the core innovative potential in most organizations remains its people. The people dynamics that block efficiency can be addressed once you know what they are. But there is a hidden factory underneath the factory, which you cannot observe unless you spend time on the floor. And only with this understanding will tech investment and implementation really work. Stabilizing a factory is about simplifying things. That's not always what technology does, although it has the potential if implemented the right way.

Thanks for listening. If you liked the show, subscribe at augmentedpodcast.co or in your preferred podcast player, and rate us with five stars. If you liked this episode, you might also like other episodes on the lean topic. Hopefully, you'll find something awesome in these or in other episodes, and if so, do let us know by messaging us. We would love to share your thoughts with other listeners.

The Augmented Podcast is created in association with Tulip, the frontline operation platform that connects people, machines, and devices, and systems. Tulip is democratizing technology and empowering those closest to operations to solve problems. Tulip is also hiring, and you can find Tulip at tulip.co.

Please share this show with colleagues who care about where industrial tech is heading. And to find us on social media is easy; we are Augmented Pod on LinkedIn and Twitter and Augmented Podcast on Facebook and YouTube.

Augmented — industrial conversations that matter. See you next time.

Special Guest: John Carrier.

In this episode of the podcast, the topic is "Post Lean." Our guest is Frode Odegard, Chairman and CEO at the Post-Industrial Institute. In this conversation, we talk about the post-industrial enterprise going beyond digital and higher-order organizations.

If you like this show, subscribe at augmentedpodcast.co. If you like this episode, you might also like Episode 102 on Lean Manufacturing with Michel Baudin.

Augmented is a podcast for industry leaders, process engineers, and shop floor operators, hosted by futurist Trond Arne Undheim and presented by Tulip.

Follow the podcast on Twitter or LinkedIn.

Trond's Takeaway:

Lean is a fundamental perspective on human organizations, but clearly, there were things not foreseen in the lean paradigm, both in terms of human and in terms of machine behavior. What are those things? How do they evolve? We have to start speculating now; otherwise, we will be unprepared for the future. One of the true questions is job stability. Will the assumptions made by early factory jobs ever become true again? And if not, how do you retain motivation in a workforce that's transient? Will future organizational forms perfect this task?

Transcript:

TROND: Welcome to another episode of the Augmented Podcast. Augmented brings industrial conversations that matter, serving up the most relevant conversations on industrial tech. Our vision is a world where technology will restore the agility of frontline workers. In this episode of the podcast, the topic is Post Lean. Our guest is Frode Odegard, Chairman and CEO at the Post-Industrial Institute. In this conversation, we talk about the post-industrial enterprise going beyond digital and higher-order organizations.

Augmented is a podcast for industrial leaders, process engineers, and for shop floor operators hosted by futurist Trond Arne Undheim and presented by Tulip.

Frode, welcome to Augmented. How are you?

FRODE: Pretty good.

TROND: Yeah. Well, look, talking to Norwegians living abroad that's become a sport of mine. You were born in Norway, software design from there, became an entrepreneur, moved to Silicon Valley. I also know you have an Aikido black belt; we talked about this. This could have become its own podcast, right? There's a long story here.

FRODE: [laughs] Absolutely, yeah.

TROND: But you're also the CEO of the Post-Industrial Institute, which I guess used to be called the Post-Lean Institute. But in any case, there's a big connection here to lean, which is a global community for leaders that are driving transition towards something post-lean, post-industrial, post-something. So with that context, tell me a little about your background and how you ended up doing what you're doing.

FRODE: Born in Norway, as you pointed out. My folks had a process control company, so that was kind of the industry I was born into was industrial controls, which included visiting factories as a child and installing process control systems. So I was doing, you know, circuit board assembly at age eight because when you grow up in a family business, that's what you get to do. And I quickly gravitated towards software. I think I was 13 when I was working on my first compiler.

So my first passion was really programming and language, design, implementation, and that sort of got me interested in theoretical computer science. So very far from what I do today, in some ways, but I think theoretical computer science, especially as a software architecture and all that, teaches you how to think and sort of connect the dots, and that's a good life skill.

At 17, I started a software company in high school. And when I was 22, I immigrated to the United States after some trips here. I was on a Standards Committee. I was on the Sun User Group board of directors as a European representative. It was a weird story in itself, how that happened. So yeah, 1990, 1991, I'm in Silicon Valley.

TROND: So you jumped ship, essentially. Because, I mean, I've heard a lot of people who come to the U.S. and are inspired, but you just basically jumped off the airplane.

FRODE: Yeah, I like to say I was here as an entrepreneurial refugee. Things are different now in Norway, but for a long time, they had strange taxation rules, and very difficult to start companies and scale them. But also, they didn't really have the fancy French word. They didn't really have the milieu. They didn't have a community of people trying to build companies in tech. So tech was very much focused on either military applications, that was its own little industry and community, or the energy industry, the oil industry in particular.

TROND: All of that seems to have changed quite a bit. I mean, not that you or I, I guess, are experts on that. As ex-pats, we're outside, so we're looking in, which is a whole other story, I guess. But I'm curious about one more thing in your background so Aikido, which, to me, is endlessly fascinating, perhaps because I only ever attended one Aikido training and, for some reason, decided I wasn't going to do it that year, and then I didn't get back to it.

But the little I understand of Aikido it has this very interesting principle of using the opponent's force instead of attacking. That's at least what some people conceptualize around it. But you told me something different. You said there are several schools of Aikido, and one of them is slightly more aggressive, and you belong to that school. I found that quite interesting.

FRODE: [laughs] Now I'm wondering about my own depiction of this, but the Aikido that I study is known as Iwama-style Aikido, and it's called that because there was an old town in Japan, which has been absorbed by a neighboring city now, but it was called Iwama, and that's where the founder of Aikido moved during the Second World War, and that's where he sort of completed the art. And that's a long technical story, but he included a fairly large weapons curriculum as well. So it's not just unarmed techniques; it's sword-knife stuff.

And it's a really beautiful art in that all of the movements with or without weapons are the same, like, they will follow the same principles. In terms of not attacking, of course, on a philosophical level, it calls itself the art of peace. In a practical sense, you can use it offensively to, for example, if you have someone who is grabbing your child or something like that, this person is not attacking you, but you have to step in and address the situation, and you can use it offensively for sure.

TROND: Very interesting. I was going to jump straight to what you're up to now, then, which is, I guess, charting this path towards a different kind of industrial enterprise. And you said that you earlier called your efforts post-lean, and now you're calling them post-industrial. It's this continuity in industry, Frode. Tell me a little bit more about that.

FRODE: I think a good way to think about approaches to management and understanding the world around us is that various management practices, and philosophies, and ideas, and so on, have been developed in response to circumstances that were there at the time. So if you think about Frederick Taylor and the problems that he was trying to solve, they initially had a lot to do with just getting work organized and standardized.

And then, in 1930s, you start seeing the use of statistical methods. Then you start seeing more of an interest in the psychology of work and so on. And lean kind of melts all of these things together. A great contribution from Toyota is you have a socio-technical system and organizational design where you have a new kind of culture that emphasizes continuous learning, continuous problem solving using some of these ideas and tools that were developed much earlier.

Now, in the post-war years, what we see is information technology making business more scalable, also contributing to complexity, but certainly making large companies more scalable than they would have been otherwise. And what we see in the mid-1990s leading up to the mid-2000s is the commercial internet, and then we get smartphones. That's the beginning of a new kind of industrial landscape. And what we see then is instead of an increasing tendency towards centralization in firms and business models, you start seeing this decoupling and decentralization. And what I discovered was that's actually a new thing for the human species.

Ever since the invention of agriculture 10,000 years ago and then cities in the Bronze Age a little over 5,000 years ago, and then the industrial revolutions, we've seen a culmination of improved mastery of the world, adapting the world to our needs, which is technology and increasing centralization. You had to move to where the work was, and now we're sort of coming out of the pandemic (Let's hope it doesn't come back.) that has accelerated in the pandemic, so you have this decentralization, decoupling.

And this continuity and the way I started using the term post-lean, and we can jump back and forth as you'd like, it was just because a lot of the assumptions behind the lean practices and how those practices were implemented were based on the idea that you had organizations that lasted a long time. You had long employee tenures. You had a certain kind of a...I don't like this term, but a social contract between the firm and workers and managers and workers. And they would come and do their work on-site in person at the factory, and this world is kind of disappearing now.

And so there's all of this work now being done. I think manufacturing labor forces peaked at a third of the workforce some decades ago. But now it's down to about 11%, even though manufacturing as a share of the economy has remained fairly constant since the 1940s. It's gotten more productive. So there are also all these new jobs that have been created with people doing different kinds of work, and much of that work is knowledge work.

And a lot of these industrial-era management practices and ideas have to be changed for knowledge work. And so that was sort of my initial discovery. That happened in the early 2000s. I started a company in 2004, which was called initially Lean Software Institute. I wanted to basically take these ideas and adapt them to software development. And that was generalized for knowledge work in general. And because we have big clients like Lockheed Martin in the aerospace defense sector, we rebranded the company to the Lean Systems Institute.

And so for ten years, myself and a small team, we did organizational redesign work looking at not just workflow but also a bunch of these other factors, which we can talk about, that you have to take into consideration like knowledge management and so on. And then it was about 2014, 2015, when I discovered, hey, even though we kind of extended lean to look at all these other things, there's this decentralization happening. And maybe we should fundamentally revisit what firms should look like and how the external landscape outside the organization changes the way we think about designing companies.

TROND: Yeah. I found it interesting, obviously, that you started from the software angle. And you told me earlier that, in some ways, your kind of Lean efforts are almost in parallel to, I guess, what could be called the lean movement, although there's such a variety of lean practitioners out there. They're obviously not all in the manufacturing industry. That's the whole point. Toyota managed to inspire a whole host of other companies that had nothing to do with automotive and nothing to do even with any kind of basic manufacturing.

And I guess the software industry is no different; you know, the industry as such was inspired by it. And as you said, Lockheed Martin, and perhaps not only for their manufacturing side, were inspired by it when running their software or other types of maybe even office-based knowledge work.

So as you're coming to these realizations, what sorts of things is it that you then start to think about that are the same and that are different in terms of the classic assumptions of lean, as you know, reducing waste or improving a process in a specific way with all the assumptions, so stable labor force like you said.

FRODE: In that initial period from 2004 to 2014, that's when I really worked on adapting lean to knowledge work. And so you could see some people were trying to reduce knowledge work to kind of a simplified version of itself. They were trying...and so I call that the reductionist approach where they then could count documents as inventory, and they could have a Kanban system and all of that. And the agile movement in software became very enthused about doing just that.

And I think what we did was we went the opposite route, so we took an expansionist approach. So we said, well, we got to keep adding practices and models to the original lean to deal with not just the value stream architecture of an organization but also its structure, so organization architecture, how it manages information, and the shape of that information, where it's stored, and how it's designed. And it's also that's information architecture.

And, of course, what we know from wonderful people like Melvin Conway, who discovered that there's a direct relationship between your technology architecture and the shape of the organization, is we really need to also take into consideration what we then called product architecture. Because if your product architecture, and your organization architecture, and your workflow, your value stream architecture is mismatched in product development as well as in manufacturing, that leads to huge misalignment. And that's a cause of massive inventory problems and so on.

And then the last of the five dimensions that we have in this model, which we call the lean systems framework, was a way to look at an organization's culture. So there are values that you explicitly promote, so we call them the organizational ideals. And then you have the actual behaviors that don't always live up to the ideals. And then you have people's beliefs about the past, the present, and the future, so we call all of that social architecture.

And I think the last bit of work we did in this model, which is a pretty rich model or a metamodel of organizations, is we added the way to look at leadership styles and leadership effectiveness as a function of character and competence of perceived effectiveness. So this was used in a bunch of mostly large organizations over a period of 10 years, and Lockheed was able to get a 72, 73 production in lead time, largest subcontractor in the Future Combat Systems. I think that's the biggest defense project in the history of the United States. [laughs] It was canceled by Congress in the end, but yeah, they got some great results.

And a lot of that was because workflow bottlenecks were caused by these other problems in these other four dimensions that had to be addressed, so that was kind of our initial realization. And then there's that big break where we look at decentralization, and how is that causing us to revisit the assumptions about organizational design? So it's not like we get new dimensions of organizational design as much as starting to think about what's the ideal design. And those answers turn out to be very different than they have been up till now.

TROND: So that's interesting. So both...you were kind of discovering some...maybe not weaknesses, just, you know, some social change that was happening that is affecting organizations nowadays, you know, in America or anywhere else trying to implement lean principles.

But also, what you were saying about the agile movement and what's happening in software industrial organizations that it doesn't reflect what needs to be happening in industries across the board and perhaps not even in their own organizations because it is, I guess, if I paraphrase you a little bit, the agile principles they are very valid for achieving a very smooth software development process. But they're not so valid for a lot of other aspects having to do with social and organizational phenomena that you also need to take into account eventually.

So, I mean, if that's correct, it's interesting, right? Because everybody obviously focuses on what they are doing. So the agilists, I guess, they're optimizing a software development process. The lean folks, the classic lean folks, are optimizing a production line. But today's knowledge work is, I guess, over these years also, Frode, it has changed a bit.

FRODE: It has changed, and there is more machine systems, software systems. We have more tools, although we're still in the early stages of what's going to come with the use of AI to make knowledge work more productive and so on. But I think one thing that's important, because I don't want to throw anyone under the bus here, is practitioners. There's a lot to be learned from practitioners.

Often, they're kind of apologetic, "Oh, I'm not doing the pure X, Y, Z method. We have to adapt it a little bit." Well, guess what? That's what Toyota did. And so what happened is a lot of western companies they were just trying to copy what Toyota did without understanding why those things work there. And it's when you can adopt it, so that's also sort of martial arts. --

TROND: That's actually a fantastic point, Frode, because if you're very, very diehard lean, some people would say, "Well, lean is whatever Toyota does." But on the other hand, for Toyota, lean is whatever Toyota does, right? And it seems to have worked for them. That does not even mean that Toyota would tell you to do exactly what they are doing because they will tell you what makes sense for your organization. In a nutshell, that seems to be –

FRODE: And I was there. I mean, I was, you know, I remember one time I was really thinking about standardizing work. And I was reading about the history of all this and reading about Frederick Taylor and the very early days of all of this. And I was coming up with a checklist for housework. I was trying to implement standard work for housework. And guess what? It didn't really work. My girlfriend was upset. [laughter]

TROND: Implementing standards for housework. I like it.

FRODE: Yeah. I mean, if you see something that needs to be cleaned, just clean it. I was like, "No, no, we need a checklist. We need your exit and entry conditions."

[laughter]

TROND: You should work at ISS, you know, the big cleaning professionals company.

FRODE: There you go. And people have done that, right? But I like to tell this joke about how do you know the difference between a terrorist and a methodologist? And the answer is you can negotiate with a terrorist.

TROND: Yeah, that's right.

FRODE: So the methodologist believes that his or her methodology is the answer to all things. And so what we were trying to do with the Lean Systems Framework was not to say, "Ah, you know, all this lean stuff is invalid." We were trying to say, "Well, the methods that they had and the practices that they had that were available to us via the literature...because we never went to visit Toyota. We talked to a bunch of companies that were doing a lot of these things, and we were familiar with the literature.

But we realized there's a whole bunch of other things that are not being addressed, so we have to add those. And that's why I called it the expansionist approach as opposed to the folks taking the reductionist approach, which is we have to shoehorn everything into making it look like manufacturing. But, you know, product development is not manufacturing. And Toyota's product development practices look nothing like their manufacturing processes. It's completely different. And that's a much less well-known area of lean...although the Lean Enterprise Institute has published good stuff on this book. Lean product development is completely different from lean production. And that was not as well-known and certainly not known by the people in the agile world.

Our attitude was always, well, the circumstances change or even from one company to another, the tools might have to change. And so the skill you want to develop in our case as researchers, and advisors, and teachers, or in the case of practitioners, as leaders, or implementers, is keep learning about what other people are doing and what works for them and try to understand what the deeper principles are that you then use to construct a solution that's appropriate for that situation. That's really all it is.

TROND: That's fabulous. So tell me then, apart from Lockheed Martin, what are some of the other organizations that you've worked with? How have they thought about these things? I mean, how does your community work? Is it essentially, I mean, before COVID at least, you met, and you discuss these things, and you sort of reflect on how they show up in your organizations and discuss best practices. Or do you kind of write papers together? How does this knowledge evolve in your approach?

FRODE: It's important to point out here, like in the history of the company, which has been around now for (I'm feeling old.) 18 years, so after the first ten years, there was a big break because that's when we started working on okay, well, what comes after even the expansionist version of lean that we were doing, which was called the Lean Systems Framework? And that's when we started working on all of this post-lean stuff.

And so the companies we worked with in the first decade were the likes of AT&T, and Sony, and Lockheed, and Honeywell, and mostly large companies, a few smaller ones too. But they had a lot of problems with complexity. And often, they were doing a combination of hardware and software. And they were in industries that had a lot of complexity. So in 2014, 2015, there was a big shift where I'd spent about six months to a year reading, talking to a bunch of people, trying to come up with what was going to be the next new thing.

And that was kind of the journey for me as a founder as well because I felt like I'd done all this organizational redesign work, soup to nuts. And it wasn't just Kaizen. We did Kaikaku, which is much less known in the lean world, and that's radical redesign, basically. And we did this working on a board C-level with a lot of companies.

TROND: Tell me more about Kaikaku. Because, like you said, it's not a vernacular that's really well-known outside of the inner circle of lean, I guess.

FRODE: Yeah. So Kaikaku is where you look at an organization, and basically, instead of thinking about how do we put in mechanisms to start improving it incrementally, you say, "Well, there's so much low-hanging fruit here. And there's a breakthrough needed in a very short time. And we're just going to put together a design team, basically, a joint design team, and essentially redesign the whole thing and implement it. So it is a radical redesign. It hasn't been; at least, at the time we were doing it, there were not a lot of details available in the literature.

And you heard stories like Ohno-san would walk into a factory and just say, "Well, this is completely unacceptable. Move this machine over here, and this machine over here. And can't you guys see..." So we didn't do it that way. We didn't tell the clients what the answer should be. We taught them. We had the executive spend a week with us learning about the Lean Systems Framework, and they mapped out the organization they had. And then, basically, we facilitated them through a process that could take sometimes a few weeks designing the organization the way it should be. And then there was an implementation project, and they put it in place, so...

TROND: But Kaikaku basically is a bit more drastic than Kaizen.

FRODE: Very much so.

TROND: Yeah. So it's like a discontinuous sort of break. It's not necessarily that you tell people to do things differently, but you make it clear that things have to be different maybe in your own way. But you're certainly not going for continuous improvement without any kind of disruption. There will be disruption in Kaikaku.

FRODE: I mean, it is disruption. And if you think of the Fremont Factory Toyota took over, that was a reboot. [laughs] And so now --

TROND: Right. So it's almost as if that's where you can use the software analogy because you're essentially rebooting a system. And rebooting, of course, you sometimes you're still stuck with the same system, but you are rebooting it. So you're presumably getting the original characteristics back.

FRODE: So I think of it as sort of a reconfiguration. And in the case of the Fremont factory, of course, there were a bunch of people who were there before who were hired back but also some that weren't that we tend now to avoid just because the knowledge people had was valuable. And in most cases, the issue wasn't that people were malicious or completely incompetent. It was just that the design of the organization was just so wrong in so many ways. [laughs]

And what we had to do, it was more of a gradual reboot in the sense that you had to keep the existing organization running. It had customers. It had obligations. And so it wasn't a shutdown of the factory, the proverbial factory, it wasn't that. But yeah, after I started looking at the effects of decentralization and starting to question these assumptions behind lean practices the way they had appeared in the mainstream, that was around the time, early 2015, I started to use the term post-lean.

It wasn't because I thought I had all the answers yet or certainly, and still, I don't think I do. But it was clear that there was an inheritance from lean thinking in terms of engaging people in the organization to do things better. But the definition of better I thought would change, and the methods I thought would change. And the assumptions behind the methods, such as long-lasting organizations, long employee tenures, tight coupling between people in organizations, organizations taking a long time to grow to a large size, and human problem solving, which already was being eaten by software back then or elevated, I should say, by software, all of these assumptions needed to be revisited so...

TROND: They did. But I have to say, what a gutsy kind of concept to call it post-lean. I mean, I co-wrote a book this year, and we're calling things Augmented Lean for the specific reason maybe that we actually agree with you that there are some things of lean that are really still relevant but also because it takes an enormous confidence, almost a hubris, to announce something post a very, very successful management principle.

FRODE: It was the theoretical computer scientist in me.

TROND: [laughs]

FRODE: So I thought that surely from first principles, we could figure this out and not that it would be the same answer in every situation. But I think it was also, at that point, we had a decade of field experience behind us in doing customized organizational redesign with clients in many different industries. So we knew already that the answer wasn't going to be the same every time. And in a lot of the lean Literature, the assumption was that you weren't really going to dramatically change the organizational structure, for example, which we had a lot of experience with doing.

And we already had experience with teams of teams, and just-in-time changes, and reconfigurations, and so on because we thought of organizations the way software people think of organizations which are, you know, they're computational objects that have humans, and then there are social, technical objects. And they're reconfigurable. And I think if you grew up in a manufacturing world, the shape of the organization is sort of attached to... there are physical buildings and equipment and all of that. So --

TROND: And this is so essential to discuss, Frode, because you're so right. And that's a real thing. And that's something we write about in our book as well. There is a very real sense that I think, honestly, the whole manufacturing sector but certainly the first automation efforts and, indeed, a lot of the digital efforts that have been implemented in manufacturing they took for granted that we cannot change this fact that we have infrastructure. We have people; we have machines; we have factories; we have shop floors. All of these things are fixed. Now we just got to figure out how to fit the humans in between, which is how they then interpreted waste, being let's reduce the physical waste so that humans can move around.

But really, the overall paradigm seems to have been, and you correct me if I'm wrong, but it seems to have been that the machines and the infrastructure was given, and the humans were the ones that had to adapt and reduce all this waste. And no one considered for a second that it could be that the machines were actually wasteful themselves [laughs] or put in the wrong place or in the wrong order or sequence or whatever you have. But with other types of organizations, this is obviously much easier to see it and much easier to change, I mean, also.

FRODE: Yeah, yeah, absolutely. And software is an example of this because now we take for granted that a large percentage of the population works from home and don't want to go back. But if you are part of that 10%, 11% of the population working in a factory and you have to show up at the factory because that's where the machine is that goes ding, that, you know, [laughs] it's not work that requires only a low level of education of course. That hasn't been the case for a while. And these are people with master's degrees. And they're making sure all of this equipment runs. This is fancy equipment.

So what we learned in that 10-year period was this is not just about workflow. It's a five-dimensional model, so there's workflow, organization structure, and knowledge management, the technology, architecture, the product you're making, and the culture. And all of these are five axes if you will, So 5D coordinate system and you can reconfigure. You can make organizations into anything you want.

Now, the right answer might be different in different industries at different lifecycle stages of companies. And basically, our thinking was that we weren't going to just teach our clients or even help our clients. We certainly weren't going to just tell them the answer because I always thought that was a terrible idea. We were going to help them redesign themselves for their emerging landscape, their emerging situation, but also help them think about things, or learn to think about these things in general, so that if their landscape changed again, or if they merged with another company, then they had the thinking skills, and they understood what these different dimensions were to be able to redesign themselves again.

TROND: That makes a lot of sense.

FRODE: That's kind of the whole –

TROND: I just want to insert here one thing that happened throughout, well, I mean, it was before your time, I guess. But remember, in the '70s, there was this concept among futurists, Toffler, and others that, oh, we are moving into a service economy. Manufacturing the real value now is in services. Well, that was a short-lasting fad, right? I mean, turns out we are still producing things. We're making things, and even the decentralization that you're talking about is not the end of the production economy. You produce, and you are, I mean, human beings produce.

FRODE: No, I never thought that we would see the end of manufacturing. And the term post-industrial, he was not the person that coined it, I think. It was coined 10 or 20 years earlier. But there's a book by Daniel Bell, which is called The Coming of Post-industrial Society, where he talks about both the sociological challenges and the changes in the economy moving to a more service-based knowledge-based economy. Of course, what happened is manufacturing itself became more knowledge-based, but that was kind of the whole idea of what Toyota was doing.

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TROND: So, Frode, tell me a little bit about the future outlook. What are we looking at here in the lean post-industrial world? What will factories look like? What is knowledge work going to look like?

FRODE: Yeah, so I think what we're going to see is that companies that do manufacturing are slowly but surely going to start to look like other kinds of companies or companies that do knowledge work. The content of manufacturing work has become more and more filled with knowledge work already. That's a process that's been going on for decades.

As manufacturing technology improves, I think after many, many generations of new technology platforms, we are going to end up in a world where basically any product that you order is going to be either printed atom by atom in your home or in a microfactory, if it's a big bulky thing, in your neighborhood where you can rent capacity in a just-in-time basis.

That's not going to happen overnight. This is going to take a few decades. But you can easily see how this kind of mirrors what happened to old chains like Kinko's and so on where if you needed something to be printed, I mean, I remember there were printers. [laughs] And then you had to go to the equivalent of a Kinko's, and you could, you know, if you wanted to print 100 copies of a manual back in the day when we still did that, you could get that done, and that was surely more efficient than doing it at home.

And in your home office or at your office, you would have a laser printer. And now we have a $99 inkjet printer, or you just might get it included when you order your laptop, or you may not even care anymore because you have a tablet, and you're just looking at it on the tablet. So there's this phenomenon of some of the things getting smaller and almost disappearing.

Now what has happened...this was underway for a while, but the relationship between people and companies has increasingly become more loosely coupled. So a big part of the post-industrial transition is that individuals are empowered, and organizations now become more of a means. They're not institutions that are supposed to last for a long time. I think that ideal is fading. And so they're in a means to an end to produce economic value.

And every investor will agree it's just that they're going to be much more reconfigurable, a lot of management work. There's managing resources, tracking progress, tracking inventory, communicating with customers. A lot of that stuff is going to be eaten by software and powered by AI. That doesn't mean people go away. But I think that a lot of the repetitive management administrative work, much more than we can imagine today, will be eaten by software and AIs.

TROND: But one of the consequences of that surely, Frode, is somewhat risky because there was a certain safety in the bureaucracy of any large organization, whether government or private, because you knew that, yes, they might be somewhat stiflingly and boring, I guess, or predictable, whatever you might want to call it, but at least they were around, and you could count on them being around.

And if you wanted to know what approach was being applied, if you had experienced it once, you knew it. And if you were a government, you knew that this is the GE Way or this is the whatever way, and it was stable. But what you're charting here is something where the only stability might be in the configuration of machines but even that, of course, you know, evolves really rapidly. And even the algorithms and the AIs and whatever is put into the system will evolve. And then, the humans will move around between different organizational units a little quicker than before. So where do you control [laughs] what's happening here?

FRODE: So one of the things to keep in mind...I'll answer this from a technical perspective but also from a sociological perspective. So I'll take the latter first. So we are used to a world of hierarchies. So from the invention of agriculture, that's when silos were invented. The first organizational silos were actually centered around corn silos [laughs] and so a shared resource, right? And we need governance for that, you know, who gets the corn and how much your family's already had enough this week and so on.

And then, in the Bronze Age, you see more specialization of labor and more hierarchies. So the pyramids were built by determined organizations. [laughs] so just like Melvin Conway would tell us. And the same happened with The Industrial Revolution. So you had management; you had oversight. And then as we are thinking about this matured, you know, we developed this notion of organizational values. So that had to do with the day-to-day behavior so people, including managers, and how they should treat their people and what the employee experience should be like.

And then kind of management is about organizing people or organizing people and resources to pursue short or long-term objectives. So, what happens if the AI goes crazy? What happens if there's a bug in the software if there is a flaw? On the technical side of this, what I would say is just like we have people who are concerned about safety with robots, industrial robots in factories, you're going to have people who look at the same kind of thing in organizations. You're also going to have AI watching AIs. So you're going to have a lot of software mechanisms that are there for safety.

People also have the option to leave. The threshold for quitting your job now and you log out from your current employer if you're sitting in your home in the Caribbean somewhere [laughs] because you can live wherever you want and logging in somewhere else and taking a job, that threshold is lower than ever. So organizations have an incentive to treat their people well.

TROND: Well, the interesting thing, though, is that Silicon Valley has been like that for years. I mean, that was the joke about Silicon Valley that you changed your job faster than you changed your parking space.

FRODE: [laughs]

TROND: Because your parking space is like really valued territory. It's like, okay, here's where I park. But you might go into a different part of the office building or in a different office building. So this has been part of some part of high tech for the industry for a while. But now I guess you're saying it's becoming globalized and generalized.

FRODE: Yeah. And part of it it's the nature of those kinds of jobs, you know, of doing knowledge work that's where you're not tied to equipment or location as much. Now, of course, in Silicon Valley, you've had people go back and forth about, and not just here but in other innovation hubs too, about the importance of being together in the room. You're doing brainstorming. You are talking to potential customers. You're prototyping things with Post-it Notes. People have to be there.

And I think there's an added incentive because of the pandemic and people wanting to work from home more to develop better collaboration tools than Post-it Notes on whiteboards. But the last data we have on this is pre-pandemic, so I can't tell you exactly what they are today. But the employee tenures for startups in Silicon Valley when we looked last was 10.8 months average tenure. And for the larger tech companies, you know, the Apples and the Googles and so on, was a little bit more than two years so between two and three years, basically.

And so because more jobs in the economy are moving into that category of job where there's a lower threshold for switching, and there's a high demand for people who can do knowledge work, you're going to see average employee tenders going down just like average organization lifespans have been going down because of innovation.

TROND: Which presumably, Frode, also means that productivity has to go up because you have to ramp up these people really fast. So your incentive is Frode started yesterday. He's already contributing to a sprint today, and on Thursday, he is launching a product with his team. Because otherwise, I mean, these are expensive workers, and they're only going to be around for a year. When is your first innovation?

FRODE: It depends on where the company focuses its innovation. And this will not be the common case, but let's say that you are developing a whole new kind of computing device and a whole new operating system that's going to be very different. You have to learn about everything that's been done so far, and it takes a lot to get started. If what you are doing is more sort of applied, so you're developing apps to be used internally in an insurance company, and you're an app developer, and you know all of the same platforms and tools that they're already using because that was one of the criteria for getting the job, yeah, then you ramp up time is going to be much shorter.

All of these companies they will accept the fact, have had to accept the fact, that people just don't stay as long in their jobs. That also gives some added incentive to get them up and running quickly and to be good to people. And I think that's good. I think it's nice that employers have to compete for talent. They have to have to treat their people well. I think it's a much better solution than unions, where you would basically try to have a stranglehold on employers on behalf of all the workers.

And the less commoditized work is, the less standardized the work is in that sense. The less business models like those of unions, whether they're voluntarily or involuntarily, because the government sort of makes it easier for them to set up that relationship and sort themselves.

The thing that surprised me is that now and as we're coming out of COVID, unions in the United States are making somewhat of a comeback. And I'm sort of scratching my head. Maybe this means that there are a lot of companies where they have scaled because of IT, Amazon being an example. They wouldn't have been able to scale the way they have without information technology. But they haven't yet gotten to the point where they have automated a bunch of these jobs.

So they've hired so many people doing soul-sucking repetitive work, and they're doing their best to treat them well. But the whole mentality of the people who have designed this part of the organization is very Taylorist. And so people are complaining, and they're having mental health problems and so on. And then yeah, then there's going to be room for someone to come and say, "Well, hey, we can do a better job negotiating for you." But gradually, over time, fewer and fewer jobs will be like that.

One of the sort of interesting aspects of the post-industrial transition is that you have industries...well, some industries, like online retail on the historical scales, is still a young industry. But you have industries that when IT was young, you know, I think the oldest software company in the U.S. was started in 1958. So in the aftermath of that, when you started seeing software on mainframes and so on, what software made possible was scaling up management operations for companies. So they made them more scalable. You could open more plants. You could open more offices, whether it was manufacturing or service businesses.

And this happened before people started using software to automate tasks, which is a more advanced use. And the more complex the job is, and the more dexterity is required, physically moving things, the higher the R&D investment is required to automate those jobs. The technology that's involved in that is going to become commoditized. And it's going to spread.

And so what you're going to see is even though more people have been hired to do those kinds of jobs because the management operations have scaled, fewer people are going to be needed in the next 10-20 years because the R&D investment is going to pay off for automating all of those tasks. And so then we're going to get back to eventually...I like to think of Amazon as just like it's a layer in the business stack or technology stack.

So if I need something shipped from A to B or I need to have some sort of a virtual shopping facility, [laughs] I'm not going to reinvent Amazon, but Amazon has to become more efficient. And so the way they become more efficient is drone delivery of packages and then just-in-time production. And then, they take over everything except for the physical specifications for the product to be manufactured.

TROND: It's interesting you say that because I guess if you are Amazon right now, you're thinking of yourself in much wider terms than you just said. But what I'm thinking, Frode is that I'm finding your resident Scandinavian. I'm seeing your Scandinavianhood here. The way you talk about meaningful work, and knowledge work, and how workers should have dignity and companies should treat people well, I found that very interesting.

And I think if that aspect of the Scandinavian workplace was to start to be reflected globally, that would be a good thing. There are some other aspects perhaps in Scandinavia which you left behind, and I left behind, that we perhaps should take more inspiration from many other places in the world that have done far better in terms of either manufacturing, or knowledge work, or innovation, or many other things. But that aspect, you know --

FRODE: It's a big discussion itself. I mean, I was kind of a philosophical refugee from Norway. I was a tech-oriented, free-market person. I didn't like unions. I didn't like the government.

TROND: [laughs]

FRODE: But at the same time, that didn't mean I thought that people should not be treated well that worked into the ground. I thought people should just have healthy voluntary sort of collaborative relationships in business or otherwise. And I've seen technology as a means of making that happen. And I have no sympathy with employers that have trouble with employees because they treat people like crap. I think it's well deserved. But I also have no sympathy with unions that are strong-arming employers.

TROND: You have just listened to another episode of the Augmented Podcast with host Trond Arne Undheim. The topic was Post Lean, and our guest was Frode Odegard, Chairman, and CEO at the Post-Industrial Institute. In this conversation, we talked about the post-industrial enterprise.

My takeaway is that lean is a fundamental perspective on human organizations, but clearly, there were things not foreseen in the lean paradigm, both in terms of human and in terms of machine behavior. What are those things? How do they evolve? We have to start speculating now; otherwise, we will be unprepared for the future. One of the true questions is job stability. Will the assumptions made by early factory jobs ever become true again? And if not, how do you retain motivation in a workforce that's transient? Will future organizational forms perfect this task?

Thanks for listening. If you liked the show, subscribe at augmentedpodcast.co or in your preferred podcast player, and rate us with five stars. And if you liked this episode, you might also like Episode 102 on Lean Manufacturing with Michel Baudin. Hopefully, you'll find something awesome in these or in other episodes, and if so, do let us know by messaging us; we would love to share your thoughts with other listeners.

The Augmented Podcast is created in association with Tulip, the frontline operation platform that connects people, machines, devices, and systems 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, and you can find Tulip at tulip.co.

Please go ahead and share this show with colleagues who care about where industrial tech is heading. To find us on social media is easy; we are Augmented Pod on LinkedIn and Twitter and Augmented Podcast on Facebook and YouTube.

Augmented — industrial conversations that matter. See you next time.

Special Guest: Frode Odegard.

In this episode of the podcast, the topic is Lean Manufacturing. Our guest is Michel Baudin, author, and owner of Takt Times Group. In this conversation, we talk about how industrial engineering equals the engineering of human work and why manufacturing and industrial engineering education needs to change because it has drifted away from industrial work and a future where manufacturing is not going away.

If you like this show, subscribe at augmentedpodcast.co. If you like this episode, you might also like Episode 84 on The Evolution of Lean with Professor Torbjørn Netland from ETH Zürich.

Augmented is a podcast for industry leaders, process engineers, and shop floor operators, hosted by futurist Trond Arne Undheim and presented by Tulip.

Follow the podcast on Twitter or LinkedIn.

Trond's Takeaway:

Lean manufacturing might mean many things, but industrial work has largely been a consistent practice over several hundred years, which is not necessarily a bad thing. Having said that, if we want to go about improving it, we might want to stay pretty close to the workforce and not sit in statistics labs far removed from it. Efficiency is tied to work practices, and they cannot be optimized beyond what the workforce can handle or want to deal with. As we attempt to be lean, whatever we mean by that, we need to remember that work is a thoroughly human endeavor.

Transcript

TROND: Welcome to another episode of the Augmented Podcast. Augmented brings industrial conversations that matter, serving up the most relevant conversations on industrial tech. Our vision is a world where technology will restore the agility of frontline workers.

In this episode of the podcast, the topic is Lean Manufacturing. Our guest is Michel Baudin, author, and owner of Takt Times Group. In this conversation, we talk about how industrial engineering equals the engineering of human work and why manufacturing and industrial engineering education needs to change because it has drifted away from industrial work and a future where manufacturing is not going away.

Augmented is a podcast for industrial leaders, process engineers, and shop floor operators hosted by futurist Trond Arne Undheim and presented by Tulip. Michel, welcome. How are you?

MICHEL: Fine, thank you. How about yourself?

TROND: Things are good. Things are looking up. I'm excited to talk about lean manufacturing with you, having had such a rich, professional background. Michel, you're French. You originally, I think, were thinking of becoming a probability researcher, or you were actually, and then you went to Japan and studied Toyota. You have had this career in English, German, Japanese sort of consulting all the way back from 1987 onwards on exciting topics, lean manufacturing, and especially implementing it, right? The real deal.

You've authored at least four technical books that I know about. And I think you listed probably a while back, having written 900 blog posts. You've been very busy. You are the owner of the Takt Times Group, which is a consulting firm on lean manufacturing. And you love math, but you have this very interesting attitude, which we'll talk about, which is math is great, but it's not always the best communication tool. Tell me a little about that to start off. You're a probability researcher that doesn't use math; I think that's fascinating.

MICHEL: I use it, but I don't brag about it with people that it turns off. So I have to be in the closet for this because people who work in manufacturing usually focus on concrete things, things that they can see and touch, and abstraction is not something that they respond well to. So whenever you explain a principle, my approach is to state this principle and then dig into some very specific examples right away; otherwise, I'm losing the people I'm talking to. But anyway, that's what I've had to do.

TROND: So, did I capture your background okay? I mean, you've had a very international life so far. I hope it's been enjoyable and not just professional because you've spent your time in Germany, and Japan, and in the U.S., So you're really enjoying the different kinds of manufacturing environments. Or is it that you just want to be close to where it's all happening?

MICHEL: I've enjoyed living in many different countries. And so you mentioned I'm French. I was born and raised in France, but I'm an American citizen, and I spent most of my life in the U.S. I think of myself as being part French, part American, part German, part Japanese. Because when I'm in a country, I tend to immerse myself in the culture; I don't stay aloof from it.

TROND: Well, I'm curious about that because in the abstract... so if we are in the world of math, then you could maybe say that efficiency techniques are global; that was the idea. Some people have that idea, let's say, that efficiency is a global thing, and there's one thing called efficiency, and everybody should just learn it because then it's all better. It seems to me that because you spent a lot of time in three different places, it shows up differently.

MICHEL: I don't use the word efficiency so much because it's limited. There are techniques to improve manufacturing performance in every aspect of it, efficiency only being one of them, and these techniques are pretty universal. Now, when you're trying to help people in different countries, it's a postulate. You have to postulate what works in one place will work in another. So far, I haven't found any reason to believe otherwise.

I have encountered many people who are saying things like, "This is country X, and these techniques don't work because our people are from country X." It's one of the most common techniques to refuse to implement anything new. The fact is the Toyota Production System wasn't supposed to be applicable to American workers until Toyota applied it with American workers in its joint venture with GM in the early 1980s at NUMMI specifically. It became a showcase.

Later, Toyota opened its own factory in the U.S. in Georgetown, Kentucky, and applied the system there. And then, a few years later, it opened its own factory in France, and it worked with French workers. So it's really the idea that this only works in certain cultures or this only works in Japan. It's just the reality is different. It works pretty much everywhere.

TROND: Well, that's fascinating, though, because, like you said, you have immersed yourself in these different factory and industrial cultures, if you may, and you are implementing lean in all of them or advising on lean methods. Why don't we start with that, then, perhaps? Tell me a little bit, what is lean to you?

MICHEL: Lean to me...and I use the term less and less because I think over the past 30 years, it's lost a lot of its meaning. When it first came out, it was the latest in a number of labels that have been applied to the same thing. In the early 1980s, you talked about just-in-time then there was world-class manufacturing. A number of different terms were used and never really caught on. This one caught on.

And the way I took it, I took it to mean generic versions of the Toyota Production System. There are very good reasons why you can't call what you're proposing to a company that makes frozen foods a Toyota Production System. There are also very strong reasons why you can't even go to a car company and do this. It's very awkward for a car company to openly admit to be using a competitor's system. So you have to have a label that refers to the content but doesn't refer to where it's coming from.

TROND: So for you, at the basic level, if you strip away everything, it still is essentially the Toyota Production System, and lean is just to you, I'm just paraphrasing, it's a convenient wrapping for a way to explain it in a way that's non-threatening. But it is essentially the lessons from the Toyota Production System from a while back.

MICHEL: That's the way I took it. That's why I adopted this label in the early 1990s, but a lot of time has elapsed since then. Because it became popular, very many people started using that label. And the content they were putting under it was pretty much...they were attaching this label to whatever they were doing. It has lost a great deal of its meaning which is why at this point, I rarely refer to it.

TROND: So you're saying a lot of people are attaching lean to whatever they're doing, I mean, understandably so, Michel, right? Because it's become a very successful term. It sells books. It sells consulting. It does refer back to something that you think is real. So can you understand why people would do this if you are in consulting, or even in teaching, or you work in an industry, and you're managing something, why people would resort to this label?

MICHEL: First of all, consultants have to have a brand name for what they're selling. It was useful. As a brand name, you have to call what you're offering by a given name, and clients look for this. It's a keyword they look for, and that's how they find you. So it's really necessary. I'm not criticizing consultants for using that.

TROND: No, no, I understand it. And, I mean, you're also a little bit in a glass box in the sense that you are within the general tent of lean yourself. So I understand that. I fully understand it.

MICHEL: What happens when it's successful is that more and more people jump on this bandwagon and say, okay, I'm going to offer a lean. When you look at what they're saying, it does not reflect the original content. By about 2000s, it had evolved into...what most consultants were offering was drawing value stream maps and organizing Kaizen events. Those two keywords are absent from the Toyota Production System.

TROND: Can you explain...so this is interesting. Because I was going to ask you exactly this, what are the types of elements that you react to the most that you feel is really...because one thing is to say it diverged from the original content, but if it is kind of a valuable extension of something...but you're saying value streams and the Kaizens, the Kaizen practices they have very little to do with the Toyota Production System in your reading.

MICHEL: That's right. The value stream mapping is a new name for a technique that they call; I mean the translation of the original name is, Materials and Information Flow Analysis (MIFA), Mono to Joho no Nagare in Japanese, flow of materials and information. So that's one idea.

And there is a particular graphic convention that has actually evolved from Toyota that became the value stream mapping graphic convention, but it never was in the Toyota context. Mike Rother's own admission (He wrote Learning to See, which promoted this technique.) said it was not an important topic at Toyota. It has some uses, but if you go on factory tours in Japan, you don't see a lot of value stream maps.

And so it's been taken...it was a specific tool for a specific purpose like figuring out how to work with a particular supplier. And then it was made into this supposedly all-powerful analytical tool that is the first thing that you have to do when you go into a factory is map its value streams, so that's taking a very small part of what Toyota does and make it into this big thing.

As for Kaizen Events, it's actually an American invention. It's something that came out of...in the early 1990s; there were a number of executives who were frustrated with the slow pace of lean implementation with other methods. So they came up with this format they called the Kaizen Blitz, that became the Kaizen events. It's also traced back to some Japanese consulting firms, which found this particular format as a convenient way to make good use of a trip from Japan to the U.S. They would organize one-week events at their clients because it was a good way to justify essentially the cost and the trouble of flying over.

TROND: I'm going to go with your story here. So let's say these two are kind of examples for you of things diverting from the original content. Why don't we speak about what the original content then is for a minute? What is the core of the Toyota production method or of lean in its original form for you?

MICHEL: Well, the Toyota Production System is something I'm very interested in and still studying. And it's not a static thing. It's something that, for example, the first publication about it was from the early 1970s, an internal document from Toyota with its suppliers. And then there have been many, many other publications about it through the decades. And it's changed in nature, and the concepts of manufacturing have evolved.

By definition, the Toyota Production System is what Toyota does. They're very good at making cars. And so it's always important to try to keep up with what it is they're doing, knowing that there is a 5 to 10-year gap between the time they come up with new concepts and the time that the rest of the world gets to know about them.

And so, in the early 1990s, there were essentially concepts of how to organize production lines, how to lay out production lines, how to design operator workstations. And there were concepts on how to regulate and manage the flow of materials and the flow of information between stations and lines and between suppliers and customers. And there was also an approach to the management of people and the whole human resource management aspect of hiring people for careers, having career plans for everybody, including shop floor operators, managing to improve the operations based on this infrastructure.

So it's a very rich concept, and it encompasses every aspect of manufacturing, logistics, and production control, all the way to accountability. So it's compared with other things like the Theory of Constraints or TPM that are much more limited in scope. There is an approach to quality that Toyota has. The quality improvement is not all of the Toyota Production System. It's a complete system for making a product covering all the bases.

TROND: Let me just pick up on one thing, so you're saying it's a complete system. So one thing you pointed out was the HR aspect, and hiring people for careers is one thing, but you also said the career plans for shop floor operators. So I took two things from that, and I was going to ask about this because this has been used as one example of why you cannot implement the Toyota Production System in the same way in different countries, namely because that is one aspect of society that a company doesn't fully control because it is regulated.

So, for example, in Europe and in France, which you know, really well, and Germany, you know, employment is regulated in a different way. If a company was going to have the same HR policy in three different factories in three different countries, they would have to have, first of all, obviously, follow the national regulation. But then they would have to add things on top of that that would, you know, specific employee protections that are perhaps not part, for example, of U.S. work culture. So that's one thing I wanted to kind of point to.

But the other thing is interesting. So you said career plans for shop floor operators meaning Toyota has a plan for even the basic level worker meaning the operators, the people who are on the floor. And that seems to me a little bit distinct. Because in the modern workplace, it is at least commonly thought that you spend more time both training and caring about people who are making career progression.

And you don't always start at the bottom. You sort of hope that the smart people or whatever, the people who are doing the best job, are starting to advance, and then you invest in those people. But you're saying...is there something here in the Toyota Production System that cares about everybody?

MICHEL: Yes. But let me be clear about something. The way Toyota manages HR is not something that there are a lot of publications about. There's probably a good reason for this is because they probably consider it to be their crown jewel, and they're not that keen to everybody knowing about it. A lot of the publications about it are quite old. But there's nothing in the regulations and labor laws of any country that prevent you from doing more for your employees than you're required to.

TROND: That's a great point. That's a great point.

MICHEL: So there are laws that forbid you from doing less than certain things, but they're not laws that prevent you from doing more. There is no rule that you have to offer career plans for production operators because there's nothing preventing you from doing it. In a completely different situation, a large company making personal products ranging from soap to frozen foods...I won't name what the company is, but they have a policy of not being committed to their workers. Essentially, if business is good, you hire people. If there's a downturn, you lay people off.

They wanted to migrate from the situation where you have a lot of low-skilled employees that are essentially temps to a situation where they have higher level of qualification and fewer people. So the question is, how do you manage the transition? The way this company eventually did it in this particular plant was to define a new category of employee like, say, technical operator.

And a technical operator will be recruited at higher a level of education than the general population of operators. They will be given more training in both hard skills and soft skills and the specific processes they're going to be running, and some additional training on how to manage the quality of these processes, that sort of thing. But at the level of a production operator, they will be put in charge of these processes. And this small group would be separate job categories than the others. And gradually, this evolves to a situation where you only hire into this group. You don't hire any more of the traditional operators.

And then, you provide a transition path for the other operators to become members of that group so that over a period of time, gradually, the general population of less skilled, less stable operator shrinks. And you end up over a number of years with a situation where all of the operators that you have are these highly trained operators who are there for the duration. So that's one kind of pattern on how you can manage this kind of transition.

TROND: Super interesting. Can I ask you a basic question? So you've been in this consulting part of this venture, you know, of this world for a long time. Where do you typically start? When do you get called, or when do you sign up to help a company, at what stage? What sort of challenge do they have? Do you visit them and tell them they do have a challenge? What is the typical problem a company might have that you can help with or that you choose to help with?

MICHEL: There are a lot of different situations. One particular case was a company in defense electronics in the U.S. had a facility in Indiana, and they were migrating all this work to a new facility in Florida. What they told me...they called me in, and they told me that they wanted to take the opportunity of this move to change the way they were doing production. Generally, my answer to that would be, well, it's really difficult to combine a geographical change of facility with an improvement in the way you do the work. Normally, you improve first where you are. You don't try to combine transformation and migration.

TROND: It's a funny thing, I would say. It seems like the opposite of what you should be doing to try to make one change at a time.

MICHEL: But there were several circumstances that made it work. You can have general principles, and when you're in a real situation, it doesn't always apply. One is the circumstances under which they were doing this migration was such that the people in the old plant were in an environment where there was a labor shortage, so none of them had any problem finding jobs elsewhere if they didn't want to move to Florida. If they wanted to move to Florida, they could, if they didn't want to move to Florida, they had to leave the company, but there were plenty of other companies hiring around.

And so there was not this kind of tension due to people losing their jobs and not having an alternative. And then, the transition was announced way ahead of time, so they had something like a 15-month period to plan for their transfer. And to my great surprise, the operators in the old plan were perfectly...were very helpful in figuring out the design for the new lines and contributed ideas. And there was no resentment of that situation.

TROND: In this particular example and in other examples, to what extent is production, you know, process redesign a technology challenge, and to what extent is it a human workforce challenge? Or do you not separate the two?

MICHEL: I try not to separate the two because you really have to consider them jointly. A technical solution that nobody wants to apply is not going to be helpful. And something everybody wants to apply but that doesn't work, is not going to be helpful either. So you have to consider both. And in this transition, by the way, between these two plants, most of the labor difficulties were in the new plant, not in the old one, because this plant became a section of the new plant. And none of the other lines in that new plant did anything similar, so it stood out as being very different from what all the other lines did.

What all the other lines did is you had a structure that is common in electronics assembly where you have rows of benches at which people sat and did one operation, and then the parts were moved in batches between these rows of benches. And instead of that, we put cells where the parts moved one at a time between different operations. And it was also organized so that it could be expanded from the current volume of work to higher volume of work. And so a lot more went into the design.

I was a consultant there, but I don't claim credit for the final design. It was the design of the people from the company. They actually got a prize within the company for having done something that was exceptionally good. And when I spoke with them a few years later, they had gone from having something like 20% of the space used for production in the new facility to having it completely full because they were able to expand this concept.

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TROND: Michel, I know that you have a consulting life and a consulting hat, but you also have a teaching hat and a teaching passion. Why did you write this recent textbook which is coming out on Routledge this fall, I believe, with Torbjø Netland from ETH? It's an Introduction to Manufacturing but with a very specific kind of industrial engineering perspective.

You told me when we talked earlier that there's a really specific reason why you wrote this textbook, and you have some very, I guess, strong views or worries about how manufacturing education, but perhaps the way it's taught really needs to change. And you feel like some schools are drifting away from the core. What's happening there?

MICHEL: Well, industrial engineering as a discipline is about 100 years old, take or leave a decade or two. It started out as...the way I describe it is the engineering of human work in the manufacturing environment. And it expanded to fields other than manufacturing, even at the time of pioneers like Frank and Lillian Gilbreth.

For example, we know the way operating rooms in hospitals work with the surgeon being assisted by nurses who hand all the tools to the surgeon; that particular form of organization is due to Frank and Lillian Gilbreth, industrial engineers who looked at the way operating rooms worked and figured that you really don't want to leave a patient with his belly open on the table while the surgeon goes to fetch the tool. You got to have some people giving the tools to the surgeon so that the surgeon can keep operating on the patient.

It sounds obvious now, but it wasn't obvious in 1910. And so they were immediately some applications outside of manufacturing, but the bulk of the work was on manufacturing. And the way it's evolved, especially in the past few decades, is that it's gotten away from that focus on human work. And when you look at the research interests of the academics in this field, you find that it's completely dominated by operations research and math.

TROND: So we're back to the math. [chuckles] So I find it fascinating that...well, you obviously have a deep insight into it, so you are sensitized to the challenges of overfocusing on one technical discipline as kind of the mantra and the fodder, I guess, the research data for all kinds of processes. I mean, why is math such a big problem, and what do you mean by human work in industrial manufacturing? Because to many people, the advanced work right now is about digitization, digitalization, and it has to do with machines and computers, and one would assume with big data or at least with data. Are you arguing against that trend?

MICHEL: No. I mean, if you ask the question of what is human work? The classical answer that I would give is what happens when the guy picks up the wrench. That's one answer. But what happens when the operator sees an alarm message on the control screen of a machine, that's a different answer, a more modern answer. So you had people with the torque wrench applying the right torque to a bolt manually, and then the torque wrench would tell him when the torque was achieved. That's one form of human work.

But monitoring and looking after multiple machines that are connected and have a central control system is also human work. You also have people doing it. And they have to feed these machines. They have to make sure that the machines have the right kinds of tools and dyes available to them. They have to maintain these machines. They have to program these machines, and they have to monitor them during production. And one particular problem with automatic systems is micro stoppages. Are you familiar with that term?

TROND: Well, explain it to all of us, micro stoppages. I mean stoppages, obviously, anything that stops the production line, whether it's a minor, major, I mean, that would be what I think you are saying.

MICHEL: Well, if it's a big problem, the operator doesn't solve it. The operator calls maintenance, and maintenance sends somebody to solve it. Micro stoppage is a problem that's small enough for the operator to deal with. And so, in daily life or in any office life, one very common micro stoppage problem is the copier, right? You tell the copier to print 20 collated copies of a document, and you walk away expecting to find these 20 copies ready when you come back. It doesn't happen because there are some paper jams and so you have to clear the paper jam and restart.

You have a lot of things like that in production where parts jam and shoots and stop coming down in automatic system. You have all sorts of issues like this which cause production lines to stop in a way that the operator can resolve in half a minute or a minute and restart. What these things cause is that you have to have an operator there.

And so if you really want to have an automatic system that are fire and forget...when you press a button, you move away to do something else while the machine goes through an automatic cycle. When that automatic cycle is finished, you come back. Micro stoppages prevent you from doing that. And they're very difficult to avoid, but they're a major problem, even today.

TROND: Michel, I wanted to keep talking about the educational part. But before that, I just wanted to benefit from your experience here and ask you a much more basic question which is so you're writing this textbook about the future or introducing prospective students to industrial engineering and manufacturing.

My question is, historically, factories were a very, very big part of manufacturing. Nowadays, meaning in the last few years after the pandemic and other things, a lot of us start to spend a lot more time on an issue, which I'm assuming you have spent a lifetime working on as well, which is supply chain which goes far beyond the factory because it's not located in any one factory, if anything, it's a system of many factories, and it's obviously the supplies of material flows into the factory.

And the reason I'm asking you about this is in thinking about the future, which I'll ask you about in a second, a lot of people are sort of factory of the future, this and that. And there are visions about how this is going to change. But it strikes me that manufacturing is and has always been so much more than the factory. What are the components that you really worry about? So, humans, you worry about humans. And you worry about materials. And then you obviously have to worry about the physical infrastructures that are regulating these things. What else goes into it on the macro level? What is this book about, I guess?

MICHEL: We're talking about supply chains as well because, as you mentioned, they're a very important part of manufacturing. And when you design a manufacturing system to make a product, you have to make decisions about your products, about components of your product, and what you make in-house, and what you buy from the outside.

And there's a major difference between supply chain issues relating to customers, on one hand, the suppliers on the other. It's not just suppliers; it's both sides, incoming supply chain and the outgoing as well. One major difference with what happens in the factory is that you don't control what other people decide, what other organizations decide. So when you manage a supply chain, you have to manage a network of organizations that are independent businesses.

How do you get this network of independent businesses to work with you, to cooperate with you, to make your manufacturing successful? That is a big challenge in supply chain management. Inside a factory, that's an environment you control. It's your organization. What management says is supposed to go; it doesn't always, but it's supposed to go. And you have a lot more control over what happens inside than over what happens in the supply chain.

And how much control you have over what happens in the supply chain depends greatly on your size. For example, if you're a small customer of a special kind of alloy that only has one manufacturer in the world, you're a very small customer to a very large manufacturer, a metals company. You're not in a position of strength to get that supplier to work with you.

If you're a car company making 10 million cars a year and you're dealing with a company that is making forgings for engine parts, you have a lot of control. You have a lot of influence. You represent a large part of their business. They can't afford to lose you. You can't afford to lose them. You can replace them if they don't perform. They can't afford to lose you. They might go out of business if they did. So it's a very different kind of position to be in.

And so when you deal with that sort of thing, you have to think through, what is my position with respect to suppliers and customers? Where is it? Where's the driving influence? And it's not always...power in a supply chain is not always resident with the company that does the final assembly of consumer products. In electronics, for example, semiconductor manufacturers are much more key than people who assemble computers.

TROND: I wanted to ask you a little bit about the trends and how these things are evolving in the next decade and beyond that. And one example you gave me earlier when we talked was pilots and jetliners because manufacturing in...well, the aviation industry is an example of an industry that, yes, it has an enormous amount of high tech. It's a very advanced science-based development that has produced air travel. But yet these pilots...and I experienced it this summer, a pilot strike stops everything.

So the role of people changes as we move into more advanced manufacturing. But people don't always disappear. What do you see as the biggest challenge of manufacturing and the role of manufacturing in the emerging society? What is going to happen here?
MICHEL: What I think is going to happen is that in many countries, the manufacturing sector will remain a large part of the economy, but as economies advance, it will have a shrinking share of the labor market. So it's a distant future, maybe like that of agriculture, where 2% of the population does the work necessary to feed everybody else.

And manufacturing is now about 10% of GDP in the U.S., 20% in Germany and Japan, about 10% in England, France, Italy. In China, we don't really know because they don't separate manufacturing from industry. And industry is a broader category that includes mining, and it includes road construction, et cetera. They don't separate out manufacturing, but really, it's a big sector of the economy.

And so it can remain a big sector, that's not a problem. But you have to think through a transition where the number of people that you employ doing this kind of work goes down, their level of qualifications go up, and the nature of the work they do evolves towards telling machines what to do and maintaining machines. So telling machines what to do can be programming machines when you develop processes, or it can be scheduling what work the machines do.

TROND: Is that incidentally why you have gone into teaching in a kind of an academic setting or at least influencing curriculum in an academic setting so much that you see a role here in the future? Beyond what's happening in factories today, you're quite concerned about what might happen in factories ten years from now, 20 years from now when these students become, I guess, managers, right? Because that's what happens if you get education in management at a good school, reading your hopefully great textbook. It takes a little time because you trickle down and become a manager and a leader in industry.

So I guess my question then is, what is it that you want these people to know ten years from now when they become leaders? What sort of manufacturing processes should they foster? It is something where humans still matter for sure, and machines will have a bigger part of it. But there's things we need to do differently, you think?

MICHEL: The airline pilot metaphor, you know, you have this $300 million piece of equipment. And how much money you make from operating it depends on these two people who are in the pilot's cabin. You have to pay attention to the work of people. And in most factories, the work of people today is an afterthought. So you put in machines. You put in production lines without thinking how will people get from the entrance of the building to where they actually work?

TROND: I was going to say it's a fascinating example you had with the airline industry in the sense that, I mean, honestly, even in the old industrial revolution, these machines were expensive, but I guess even more so. I don't know if you've done any research on this, but the amount of dollars invested per worker presumably has to go up in this future you are talking about here where we're increasingly monitoring machines, even these perhaps in the past viewed as low-skilled jobs or operator jobs.

I mean, you are operating, maybe not airplanes, but you're operating industrial 3D printers that cost hundreds of thousands of dollars with presuming error rates that could be catastrophic, either for you, for the production line, or for the product you're making.

MICHEL: Or photolithography machines that cost millions.

TROND: Right. But then that begs the question for me, Michel, how on earth is it possible? If you are right about this that education has been somewhat neglected and skills has been neglected, how's that even explainable? If you are a responsible factory manager or executive of a large manufacturing firm, how could it have gotten...and I'm obviously paraphrasing here. I don't know if you think it's that bad. But how could it get this bad that you actually had to come out and say it's a massive problem?

MICHEL: What happens is that you hear a lot about systems thinking, which, to me, it's pretty obvious there's more to a factory or more to a manufacturing system, to supply chain than the collection of its components; it's pretty obvious. And when you change the way a supplier delivers parts, it has an impact over what happens at the assembly workstations where these components are being used, for example.

You have to think of the whole as a system. And you have to think about whenever you make any changes to it; you have to think through how these changes affect the whole. What's happening is that there has been a great deal of specialization of skills; I'm not talking about factory workers here. I'm talking about engineers and managers that have been put into silos where they run production control. They become production control manager in the factory. Their next career move is to become production control manager in the factory of a different company.

TROND: So here's my open-ended question to you; you're sort of saying that industrial engineering, in one sense, needs to go back to its roots where it was. But the other side of the coin here is you're also talking about a world that's changing drastically. So my question is, the industrial engineer of the future, what kind of a person is this ideally, and what sort of skill sets and what sort of awareness does this person have?

MICHEL: The skill sets that this person should have are both technical and managerial. It's management and technology considered together. So they may not be able to write code, or they may not be able to design how to cut a piece of metal, or how to tweak the electrical properties of a circuit, but they know the importance of these things. They've been exposed to them through their education and career. And they have an appreciation for what they are.

So, for example, one particular task that has to be done in every manufacturing organization is technical data management. You have to manage the problem definition, the process definitions, which machines you use to do what, down to the process program that these machines run. All of this is data, technical data that has to be managed, put under revision control. And you'd expect someone with training in industrial engineering to understand the importance of revision control on this.

If you change something to the cutting program of a milling machine, you may affect what happens elsewhere. You may affect the mechanical properties of the product and make it difficult to do a subsequent operation later. And that's why before you implement this change in production, you have to have a vetting process that results in revision management. So I would expect an industrial engineer to understand that.

TROND: Well, you would expect an industrial engineer to understand that, but, I mean, some of the challenges that come from these observations that you're making here they impact all operators, not just engineers. And they certainly impact managers because they are about this whole system that you are explaining. So it sounds to me that you're mounting a pretty significant challenge to the future manufacturers, not just in skills development but in evolving the entire industrial system.

Because if we're going to make this wonderful spacecraft, and solve the environmental crisis, and build these new, wonderful machines that everybody expects that are going to come churning out every decade, we certainly need an upskilled workforce, but we need a whole system that works differently, don't we?

MICHEL: Yes. Can I give you a couple of examples?

TROND: Yeah.

MICHEL: One company outsourced the production of a particular component to a supplier then there were technical problems with actually producing this component with the supplier. So the customer company sent a couple of engineers to the supplier, and they found some problems with the drawing that had been provided to the supplier. And they made manual corrections to the drawings, the copies of the drawing in possession of the supplier. And it worked. It solved the immediate problem. But then, at the customer company, they didn't have the exact drawing. The only place with the exact drawings was at the suppliers. And a few years later, they wanted to terminate this supplier.

TROND: Aha.

MICHEL: You can see the situation. You want people to be able to understand that you just don't do that sort of thing.

TROND: Right. So there are so many kinds of multiple dependencies that start to develop in a manufacturing production line, yeah.

MICHEL: And then you find a company that's a subcontractor to the aircraft industry. And you find out they route parts through a process that has about 15 different operations. And the way they route these parts is they print a traveler that is 50 pages long, and it's on paper. And the measurements they make on the parts that they're required to make by their customer they actually record by hand on this paper. What's wrong with this picture?

TROND: So yeah, multiple challenges here.

MICHEL: Yes.

TROND: Are you sensing that these things are fixable? Are you optimistic in terms of this awareness of all aspects of the systems changing both among managers and next-generation industrial engineers, and perhaps even among the operators themselves to realize they're getting a more and more central role in the production system?

MICHEL: I won't try to prophesy what will happen to industry as a whole but what I'm confident about is that the companies that know how to address these problems will be dominant. Those are the sort of basic mistakes that really hurt you and hurt your competitive position. So there will be a selection over time that will eliminate people who do these kinds of mistakes.

TROND: Michel, I don't want to put you on the spot here. And you have spent your career researching and tracking Toyota as an excellent, excellent manufacturer that has graciously taught other manufacturers a lot. And also, people have copied and tried to teach them Toyota methods, even if Toyota wasn't trying to teach everyone.

Are there any other either individual companies or things that you would point to for the eager learner who is trying to stay on top of these things? I mean, so lean, obviously, and the Toyota Production System is still a reference point. But are there any other sources that in your career or as you're looking at the future where there is something to learn here?

MICHEL: Oh yes. Toyota is a great source of information, but it's by far...it's not the only one. One of the key parts of Toyota's management system is Hoshin Planning. Hoshin Planning didn't come from Toyota; it came from Bridgestone tires. And so that's one case where a different company came up with a particular method.

Honda is a remarkable company as well, so there are things to learn from Honda. HP was, under the leadership of its founders, a remarkable company. And they had their own way of doing things which they called The HP Way. Companies have recruited a lot of people...electronic companies have recruited a lot of people out of HP. And you feel when you meet the old timers who have experienced The HP Way, they feel nostalgia for it. And there were a lot of good things in The HP Way. They're worth learning about. So I also believe that it's worth learning about historical examples because history is still with us in a lot of ways.

The Ford Model T plant of 100 years ago was a model for a lot of things at the time. It also had some pretty serious flaws, namely, its flexibility. And you still see people putting up the modern-day equivalent of a Model T plant with new products and new technology but without thinking about the need. That particular plant may have to be converted in the not-too-distant future into making a different product. So it's always worth looking at examples from 100 years ago, even today, not for the sake of history but because, in a lot of ways, history is still with us.

TROND: Well, on that note, history is still with us; I thank you for this, Michel. And I shall remember to forget the right things, right? So history is still with us, but [laughs] you got to know what to remember and what to forget. Thank you so much.

MICHEL: Culture is what remains once you've forgotten everything.

TROND: [laughs] On that note, Michel, thank you so much for your time here and for sharing from your remarkable journey. Thank you.

MICHEL: You're welcome.

TROND: You have just listened to another episode of the Augmented Podcast with host Trond Arne Undheim. The topic was Lean Manufacturing. Our guest was Michel Baudin, author, and owner of The Takt Times Group. In this conversation, we talked about how industrial engineering equals the engineering of human work and why manufacturing and industrial engineering education needs to change because it has drifted away from industrial work. And indeed, we are looking at a future where manufacturing is not going away.

My takeaway is that lean manufacturing might mean many things, but industrial work has largely been a consistent practice over several hundred years, which is not necessarily a bad thing. Having said that, if we want to go about improving it, we might want to stay pretty close to the workforce and not sit in statistics labs far removed from it. Efficiency is tied to work practices, and they cannot be optimized beyond what the workforce can handle or want to deal with. As we attempt to be lean, whatever we mean by that, we need to remember that work is a thoroughly human endeavor. Thanks for listening.

If you liked the show, subscribe at augmentedpodcast.co or in your preferred podcast player, and rate us with five stars. If you liked this episode, you might also like Episode 84 on The Evolution of Lean with Professor Torbjørn Netland from ETH Zürich. Hopefully, you'll find something awesome in these or in other episodes, and if so, do let us know by messaging us because we would love to share your thoughts with other listeners.

The Augmented Podcast is created in association with Tulip, the frontline operation platform connecting people, machines, devices, and 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, and you can find Tulip at tulip.co.

Please share this show with colleagues who care about where industry and especially where industrial tech is heading. To find us on social media is easy; we are Augmented Pod on LinkedIn and Twitter and Augmented Podcast on Facebook and YouTube.

Augmented — industrial conversations that matter. See you next time.

Special Guest: Michel Baudin.

In this episode of the podcast, the topic is Innovating Across the Manufacturing Supply Chain. Our guest is Antonio Hill, Head of Manufacturing Digital Solutions, Global Supply Chain at Stanley Black & Decker.

In this conversation, we talk about lean leadership, productivity, the challenge of digital transformation across operations and supply chains, and how augmented lean means every organization has their own transformation approach.

If you like this show, subscribe at augmentedpodcast.co. If you like this episode, you might also like Episode 94 on Digitized Supply Chain with insights from Arun Kumar Bhaskara-Baba, Head of Global Manufacturing IT at Johnson & Johnson.

Augmented is a podcast for industry leaders, process engineers, and shop floor operators, hosted by futurist Trond Arne Undheim and presented by Tulip.

Follow the podcast on Twitter or LinkedIn.

Trond's Takeaway:

Stanley Black & Decker is a huge organization where any improvements by tweaking their own operations or by adding insight from what happens along the whole supply chain can mean significant productivity gains. I find it interesting that they have their own version of the augmented lean approach tailored to where they are and, most importantly, building on the insight that the workforce is where the innovation comes from. By giving shop floor workers access to insights on big-picture manager deliberations, they are freed up to operate not only more efficiently but also more autonomously. When all of industry works that way, manufacturing will make tremendous advances more rapidly and sustainably than ever before.

Transcript:

TROND: Welcome to another episode of the Augmented Podcast. Augmented brings industrial conversations that matter, serving up the most relevant conversations on industrial tech. Our vision is a world where technology will restore the agility of frontline workers.

In this episode of the podcast, the topic is Innovating Across the Manufacturing Supply Chain. Our guest is Antonio Hill, Head of Manufacturing Digital Solutions, Global Supply Chain at Stanley Black & Decker.

In this conversation, we talk about lean leadership, productivity, the challenge of digital transformation across operations and supply chains, and how augmented lean means every organization has their own transformation approach.

Augmented is a podcast for industrial leaders, process engineers, and shop floor operators hosted by futurist Trond Arne Undheim and presented by Tulip.

Antonio, welcome to the podcast. How are you?

ANTONIO: I'm good. How are you doing?

TROND: I'm doing great. I'm looking forward to thinking and talking about manufacturing supply chains and the rollout of digital technology. So, Antonio, you are actually a business major by origin from North Texas, and then your master's is in HR. And then you're fashioning yourself as a lean leader and an operational expert working on productivity and now much on digital transformation. And you're heading the rollout of digital solutions for Stanley Black & Decker. I'm curious, what was it that brought a business major into the manufacturing field?

ANTONIO: For me personally, businesses is great. I'm a big advocate of free markets. And so for me, the whole time you think of how widgets are created and wanting to understand that aspect in manufacturing, creating widgets. Like you were saying, with a master's in human resource development, my thoughts there were learning that a lot of the cost from any organization is going to be labor and material. So having that understanding was great.

And then transitioning to making widgets and learning under some ultimate awesome leaders in the space along with great engineers that really, really, hand in hand taught me so many things. And then one of the leaders in lean as well having hands-on conversations, walking the site with this person that is known for lean just really, really strengthened my capabilities. But the thought of the digital side is always going to come into our space, in our world. And so to be able to do that for a large fortune 500 company is obviously amazing. I'm like a kid in the candy store.

TROND: [laughs]

ANTONIO: Those concepts really changed the way from an organizational side because business is business no matter how you look at it. We're trying to improve our margins and capture market share just like anyone else. But ultimately, it's just a different way of doing it.

TROND: I wanted to stop a little around lean first because in our pre-conversation you said lean touches everything. I'm just curious, what do you see as the key things in lean that you have learned that you are bringing into this work that we're going to be talking about a little bit?

ANTONIO: I think that it boils down to a way to create continuous improvement by impacting ultimately the lead time. I'm part of the global supply chain so obviously, I'm always looking at a holistic approach. That's why it's all aspects for me from a business standpoint. At the same rate, from a lean perspective, we can find waste in anything. So there are always opportunities to improve in that aspect in every single function.

Every function within the organization can be an aspect of lean. So that's the part for me that I get excited about, and I've touched every single function. So it's really an opportunity for any organization to continuously improve on and removing what they say muda from the origination of the concept in any organization.

TROND: I'm curious; some people would say that lean is or I guess was important early on but that contemporary organizations are somehow different, and digital, which we'll talk about, is one reason, but there are perhaps other things. What are some of the things that you, I mean, I don't know if you agree with this, but what are some of the things that you're incorporating into your thinking here that may be either different or where you have to adjust it to the organization you're actually in at any given moment? I'm just curious.

ANTONIO: You're thinking lean from a digital standpoint or just lean?

TROND: Well, lean was developed in its original form a very long time ago. So I guess the first question I'm asking is how can you be confident that the original insights are still valid? Is that because you're walking around and experiencing it every day, and it resonates with you? I guess, firstly, just curious about what lean generally means today in an organization like yours, and then obviously, we'll talk about the rollout of digital solutions, which you've been doing so much now.

ANTONIO: Right. And that's a great question, and I'm excited to be the person that has to answer that question.

TROND: [laughs] Well, you didn't think I was going to give you easy questions, Antonio. [laughs]

ANTONIO: Lean, the concept, I think, will never go away. And so for those that think that it will, really do not understand engineering from that standpoint because when you think about engineering, an engineer solves problems. And so we know number one, there's always going to be problems. I'm sure that there are a lot of people that say, "Hey, I got something for you to solve. I got a problem for you," so from that perspective, we know.

But then, on top of that, think about innovation from an engineering standpoint, as you see something improved, even if it's making it better, even if it's something like making it better for the customer, ultimately, that transition of change even the slightest or something large, every organization has to do it. They have to embrace it. And so a person that knows those techniques, that are really good and seasoned and experienced, which I would say I do fit in that; I feel mighty confident in that space, and I feel mighty confident in manufacturing, we could see it quickly. You see it immediately.

Like, you see a process, and it just stands out. And I think that you can't wish that away to be able to see the inefficiencies of any system. And if you do not have a system in your approach, then that to me is already folly, you know what I mean? Like, that's an error. If you can't create systems, especially in manufacturing, I think that that's no bueno.

[laughter]

TROND: Got it. I'm then curious, digital. How does digital factor into all of this? So I guess I'm understanding a little bit more of your conception of continuous improvement, lean, whatever you really want to call it, and engineers that are such a crucial part of the kind of organization you represent, Stanley Black & Decker.

So now, clearly, there's been a push in most organizations across fields to go digital and arguably, manufacturing organizations perhaps were resisting it a little bit because there was such an amount of automation in there already, and then now comes digital on top of that. And has it been easy? Has it been difficult? What goes into even the decision to say, "We're going to have a major digital transformation?" Tell me a little bit about the journey that you've gone through with Stanley in that respect.

ANTONIO: So, really great question. And so I'm going to take you down a little bit of a history lesson and introduce how it impacts. So when you think about things of the world, because you always have to relate to what's going on in the real world, you have the introduction of the smartphone. You have to credit that smartphone for that interaction of this interface because it's putting that into a lot of operators' hands to interface with something.

Now, when you think about digital, industry 4.0 touches a lot of things; it's very vast, very broad. But when you think about the insights and paper throughout your organization that's there but being able to in manufacturing...and I'll make this a little bit specific to manufacturers. There are so many points where you actually need data to improve throughout that process, and like I said, it's a system. And so if you can capture it in a digital way, now you can analyze it. Now it's an insight. Now you can take all of this, and you can do predictive analysis. You can add algorithms, AI, whatever you want once it's digital.

And it's transforming your operation to be able to enhance it in this digital way so you can advance and be a little bit more productive and get better, and so it still comes back to lean. [chuckles] Once you've created it digital, now it's like, what am I going to do with the data? Because you can do the wrong things with data. It can give you the wrong insight. And just making those decisions of where you are going to improve, I think that is really huge.

So for me, that transition starts with realizing the digital side, removing some of the paper. I mean, there are so many people that are old school I would say that do everything with paper. And if that paper was digital, then what could be? I'm smiling now because it gets me excited because there are so many processes that are old that people just pull out a paper and they use it even though we're in this digital age.

TROND: So I thought I would then move us a little bit into the aspect of having a digital platform. So digital means a lot of different things to different people. You say having access to digital gives us options basically because then you have data, but you have to do the right thing with it. First off, what kind of a decision and who was involved, I guess, in the decision at Stanley going digital in that sense? Because there are many different echelons of an organization that could potentially use data.

Who was the most excited, I guess, to use new data in your organization? How did that even come about? Was it a leadership decision? Was it mid-level managers that said, "Other organizations, our peers have more data?" Or was it analyzing, you know, Gemba Walks and walking around and saying, "Hey, the operators could be more productive with more data?" Where did the decision point come from?

ANTONIO: To answer your question, short answer would be leadership. We're pushing for the next edge in innovation and pushing forward to create change. And then it's what can be that thought, and I would say the collective. If you were to embrace true employee engagement and start from the shop floor, it's going to be things that they don't know that they're requesting, something digital, so to speak. They're just saying, "Hey, this would be cool. This is what I need in order to do my job effectively."

And then what about the supervisors to the middle managers that are trying to share insight of it's great to say that you hit your numbers or you produced your widget in a successful time or faster than you anticipated, but what about the opposite? What about when you did not meet your numbers? Being able to speak to that with data that's a huge win. Who wouldn't want that? And there are a lot of areas that are little dark areas in a manufacturing facility that you don't have that capability. And that's why you need some type of way to be able to shed light on those areas and capture that in a very effective way.

TROND: Tell us a little bit about the digital rollout process at Stanley. What went into it, and what is the situation? What sort of systems have you opted for, and how are you rolling them out?

ANTONIO: So within our organization, everything comes out with governance so thinking of and a way of controlling exactly what's completed, what's being done, what you are going to put within the facility, and then creating some type of uniformity around that. The interesting thing about our organization is we're a huge conglomerate. We produce many different parts and units. And it's just a lot of complexity and diversity as far as the people are diverse, but I'm just saying end product.

Manufacturing facilities...I'm global, so I'm facing all over the world different processes that we do and so being able to have a very tactic way to roll that out in a uniform way. That's really the strat there, really thinking it out. But then also allowing for those unique scenarios to come about, having what we call citizen developers. It's that employee engagement part, thinking about someone that's really close to the process. They may figure out a way that, hey, we need this type of solution, listening to them.

And then the fact, like I said, I'm global, I'm seeing way more than they are. And I can be like, and our team can look and say, "Hey, this actually could be used at several sites that look just like this one." And so we can get that MVP and create it in a very standard, uniform way so then we can roll it out on an enterprise level. And so all of this together is the way that we go about rolling out digital solutions.

TROND: So, Antonio, I'm curious about this because in classical automation, usually, it's a big sunk cost, and the system is stable, perhaps, but everyone has to learn it and do it one way. Is the current wave of digital transformation that you're talking about here does it allow for both strong governance, which you clearly need in a large organization, but also for those citizen developers to emerge with their more kind of not exactly bottom-up, but they are certainly factory-based, or they are site-based perhaps innovations?

Did you have to choose technologies that allowed for that, or how did that factor in? Because classic solutions of automation is like one size fits all, but you seem to be talking about, yes, the need for governance, but there's also the need for citizen developers. How did you enable those citizen developers?

ANTONIO: So the first thing is that you need to figure out something that's adaptable. And so for us, we use something zero code, so it's really, really easy for them to use. And so the thing is that you don't want to discourage innovation at all. You want to embrace employee engagement all that you can. At the same rate, there's another team that's going to make sure that cybersecurity and all of that that I'm playing within the confines and the rules, and if I do not, then definitely there'll be a discussion about it.

And so understanding that you're really balancing both, and you're controlling that citizen developer as much as you possibly can, being aware of what that individual may do. And at the same rate, watching and being able to take away their permissions if need be if we feel that it goes into...I don't want to say a danger, but it's not good from a governance standpoint of what they're doing due to some federal regulation or law or whatever have you. So it's just the balance of the two of having a platform that can give you that adaptability in order to control.

TROND: Antonio, can you expand a little bit on innovation? Again, in the context of a workplace that is becoming more and more automated, how do you inspire innovation? What does it mean for Stanley, innovation?

ANTONIO: When you think about what can be...let me give you an example of something that we created; I think that it will shed light. Every organization they go through physical inventory. So you have to count all your inventory and make sure that what your books say [laughs] that's what you have. It's just comparing those two from a financial standpoint. So you're going through that process.

And normally, this process is very manual where you're physically going; someone is sending out, making that count, writing on a sheet of paper of what they were able to capture, and then running that sheet of paper to some control room where everyone is conducting...basically calculating where you are now. And so everything's live. So you go, and you audit that area, and they come back.

So basically, someone is running around facilities. And if you look at some of our facilities, they're pretty ginormous, pretty big. So to go to one end to the other it's going to be a hike. And this is all on physical paper for the most part. This is all live, speed. So the thought came up when you say innovation, someone was like, "Is there a way to do this digitally? Why can't we do this digitally?" Just to speed things up, just to figure out, hey, where are we right now? Instead of getting all of these sheets of paper and then typing them again in some system.

And I go back to lean. That's rework. That's overprocessing. Even within this system, rework is someone already wrote it down on a sheet of paper. Now they're going to hand it to someone else to literally type it into another system. That redundancy can be removed. So you see that there is an opportunity there to save time because no one wins when we're doing a physical inventory. The site is shut down, and we're not making widgets. So you don't want that.

So anyway, there was a person that was like, "Hey, can we do this digital? There's an opportunity." So that's the innovation there. It starts with an idea and then sharing that idea saying, "Hey, is this possible? What can be? What is possible?" And then you have a very diverse team look at it along with accepting that idea. And you transform it into an application in order to conduct physical inventory. And we did just that, and it was huge.

And obviously, it's within, like I was saying, you get that MVP. And now we can just copy and paste that across the board to different sites and use it as much as we want from that standpoint with those same winnings, those same gains, and the same objective in order to help the site and use as much waste that is normally committed in a physical inventory.

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TROND: Antonio, you speak of apps. What are those apps that you speak about here, and how do you explain the concept of an app, I guess, to your operators? Because I'm assuming there is a bit of an educational journey there, too, when you're introducing certain new digital processes going, like you said, in a basic sense from paper to digital. And then you said it comes through these apps.

How do you explain the concept of apps, and how do they materialize, I guess, on the shop floor? I mean, they clearly are created. Are they created mostly by the vendors that you contract with, or are they created by your own engineers? Or are they created factory specifically, or how does this app development work? And what is an app?

ANTONIO: So they're created by our engineers. And this is actually pretty funny that you asked me what an app is. And so that thought is really important because this is something that we have to do out there on the floor. And so when approached with someone that you want to use this application, I don't think that I ever even say the word app to an operator as I have physically trained operators on an application. And it's just more so the process of what you would like them to do.

And one of the reasons of perfection, so to speak, is what you strive to do when it comes to the user interface and the user experience. You want to make the least amount of steps. You want to do the least amount to interfere with this individual that has a really, really important job to make widgets. And so the thought here is the explanation of what you're trying to accomplish and then the steps that they need to do to interact.

And like I said, what helps is obviously smartphones, you know, everyone's interacting with it. So, in our times today, I think that it's a little bit easier. If you were to take it maybe 15 years ahead, maybe it'd be a little bit more challenging, but I would say that not everyone is ready for that change. It's still new to them despite smartphones being there saying, "Hey, I have to interface with this iPad or a tablet, or touch screen," whatever have you; however, they're interacting.

So the ideal state is to create it where it's more automated. And so the application is just kind of like, it's a matter of fact. We're capturing all this data, and you're just doing your job. And we're just using triggers to be able to indicate what you're doing. So that's really how I would go about describing an app, never really saying app and just saying, "Hey, this is a process that we would like to use as you do your job really."

TROND: Antonio, would you speak specifically about Tulip as a digital solution? And what is that being used for, and how is that being rolled out? I mean, to the extent you can go into some detail, what is that platform doing for Stanley?

ANTONIO: For us, using Tulip is really, really advantageous because there are a few things that it's really, really great at. You can create pretty much what you want. I don't want to put it too much out there. And the easiest way where you don't...I mean, I have software engineers that work for me. But you don't have to be a software engineer; you could be just anyone. So that part makes it a great deal simple and then what it's capable of connecting to. So it can just easily integrate within your organization in order to achieve some of the things that you want to achieve, so from the standpoint of hey, we just need this very simplistic way of doing this.

And then what's more important? The UI. So it's like, what do you want this interface to look like and do? Because sometimes, I don't want to speak specifically to some organization or tool, but some tools that you can use make it very challenging with the user interface where it's just too much buttons or too difficult to get to what you want to. Versus, you have with Tulip a little bit more autonomy to make it and cater it to what needs to happen, where you've leaned out a lot of it and just say, hey, just come touch this button and do this, and that's it.

Because you want to make it simplistic, but maybe there's something else and another look, another view that you want to use. And so, using the same platform, you can make a view for someone else that will be looking at that data in a different way. And so that's the cool thing is it's all on one platform. So that makes it a little bit more powerful that from an operator standpoint, you've given them what they need, very simplistic, the limited amount of buttons. And then, for a different audience of a managerial role, you've given them the insights that will help to improve productivity within the shop floor.

TROND: What are some of the use cases that you then identified so far and are rolling out in these kinds of apps on that platform? And what are some of the things that one might think of? Or is that more of an iterative process that it's like, can you even map that out a year ahead where it's going to be used? Or is that like it's such an iterative process that it will evolve more organically? But either way, where's the starting point? What kinds of things have you now digitized this way?

ANTONIO: Within every manufacturing facility, they're going to say safety is first, and Stanley Black & Decker is no different. I can tell you what number one is, what 1A and 1B it’s...I can't say the other one is 2. So 1A is going to be safety, 1B will be quality. And so the difference here...and I want to differentiate something really quick because it's very important.

Being able to identify from the factory floor what's going on this is something totally different. From the operator's point of view and the data that they can create, that's different. Looking at other things is interesting, but what actually goes on on the manufacturing facility shop floor that type of data that's where it's important.

And so, to your question, you can, for instance, audit something. You can audit a process. That's something that's very, very easy. And you can do it in both realms. You can audit a process for safety. You can audit a process for quality. Those are two examples there. And obviously, you can advance that even more as you touch the product that you're making. And then once you touch the product that you're making, now you can relate that. That's where my business side comes in. Now I can take this beyond from a holistic approach.

So for me being global supply chain, this one place where it was touch, I can go backwards. So I can go further upstream to the vendor, to the site, to any other buffer in between that, let's say a distribution center, to the customer, back from the customer, and then a thread that goes all the way through. The insights are endless, and the capability and possibilities are endless when you can capture it all at the shop floor.

So that's really what we aim to do, really lighting up those dark spots and getting as much with the operator. And that's why operators, I mean, what's going on in our world and not just Stanley Black & Decker, as automation and digitizing the factory floor, this is going to definitely augment and amplify shop floor workers in a different way. And it's going to be really, really advantageous for you to be alongside that operator and enhance their skills to be able to be within a manufacturing facility to change because it's obviously changing. But you can make it where they're advantageous to the organization of what they do and give them a little bit more skill set.

It's almost like giving them more information, like going to university, so to speak, because they're able to see what they know. But now that cognitive data, we can take it from them digitally, and so now you can do more. You don't have to be thinking about that. It's like, oh yeah, we'll capture all that. Let's put something else on you. Because we'll take that cognitive data and store it for point solutions later on and now if need be. So it's a very interesting time within manufacturing of where we are now and what I foresee in the next 5, 10 years.

TROND: Do you think that manufacturing shop floors have trusted operators enough? Or was it just that the opportunity now of seeing more of the big picture is only now being realized with these digital apps so that this information is there and then you can trust them more? But it was interesting to me. I just want you to talk a little bit more about the new role of shop floor people, basically, that are now perhaps able to take on different things because of this new set of information that's being tracked.

ANTONIO: So when you really think about the frontlines, I would love to say and sit here and talk about how great I am and what I do for the organization. Oh, I think of all of these ideas. But for our organization and probably any organization, it's the people that make the widgets that are the most important people within the organization I would say. They're the workers, and the knowledge that they have of that process is so important.

At the same rate, we would say that the majority of those workers do not have fancy degrees or anything like that. And so we tend to think that possibly...well, I don't want to say that we tend to think that. It talks about the capability of what they're capable of, and so now with this, and if you can do it in a way for a digital transition, you can now look at what those capabilities are, the insight that they have. Okay, you do understand this process, then what's next? How do we improve it from a lean standpoint?

But you also intricately know, let's say, for instance, this machine you work on it every single day. But now we're going to create a way where you don't have to work so much on your, like I was saying, the things that you think about. We'll create something to do that for you. Now we would like for you to do something else. You see how this change comes up. We need you to just do this or that. And I don't want to be specific, but that's really how the change is occurring.

And to be honest with you, it's a huge win because there are many operators that actually enjoy...they want you to know and understand the data of what they do. It changes things because it can be a very technical job within manufacturing where you pull out a drawing. There's a certain specification that you have to hit, and that's going to make a difference if that part is manufacturable or not. And we're talking about sometimes you're pulling out calipers to get it within 2000s where it's got to be exact. It's almost like an exact science. That grace invariant is not that much.

And so, to be able to record that data digitally and view it that way, the operators are all for that because it helps to explain things that maybe they can't put into words, but the data will show it. And it's just like, "You see? You see what I'm saying? Right about this time at 4:00 o'clock, this machine always does this," I'm just giving an example. But you can see that from a data standpoint, and that will help the operator as far as transition into this new manufacturing operator, I believe.

TROND: So, Antonio, I think I'm now understanding a bit more about how this works on a given factory floor. Can you help me understand more about how this works all across the supply chain, which you were talking about earlier? Because now, I'm assuming the use case for you is not just one individual operator or sets of operators and teams doing one product in one location. You're talking about coordinating this across a larger supply chain. Now, how can these apps then come into play? Because now we're talking about different geographies, a lot of different contextual information that would need to be put into place.

How do these apps truly help smooth out the supply chain? It would seem to be a much perhaps more complicated challenge than just simply making an individual worker or team's life easier with safety and quality with precise work instructions. When you're talking supply chain, what do you really mean there? And what are the first, I guess, apps that are coming out that are going to truly impact the full supply chain?

ANTONIO: So know this, [laughs] it's like...I'm going to give an analogy because I want to make sure that you can understand because it can get really advanced when looking at things, so hear this out. So think about those pictures where you have the picture, and everything has a number. And so you go you're number one, and let's say number one is blue. So you fill in all the blue. And then number two is yellow or whatever. At the end, it's going to be a picture that you see, and you can recognize, oh my God, a parrot, when you're at the end.

So the way that the approach here is is that we know that it's a parrot. We understand that. And so the other functions within our organization know that it's a parrot, and maybe they're only focused on the blue, but they know that it's a parrot. And so, having certain datasets will fill in the blanks for them. Something that didn't have color now has more color, so they can make more of an informed decision on what they do because everything is connected. You cannot get away from the other.

So everything really starts where you make the widget, I think. It doesn't necessarily start there because you got to get the supplies to be able to make it. But what I'm saying is is that's the money time. But at the end of the day...and I'm going to go back to what I said earlier of how I summed up lean. Everything is lead time.

So I'll give you another analogy. I love kombuchas. When I go to the store, there's a certain kombucha that I want, and when it's not on the shelf, I'm going to go somewhere and get that kombucha. I'm not going to keep going to that store. And so, at the end of the day, this is the type of data that's needed throughout the whole global supply chain in order to ensure that our customer has that kombucha, so to speak. And all of that data insight is imperative to not only understand it but be able to do magic with it, so to speak, and make changes to continuously improve.

TROND: Interesting. As you're thinking about how these developments are affecting the future outlook in the manufacturing industry, or for your company, or maybe even wider for society, because some of these things, when they're compounded they, could have perhaps larger impact, what are some of the things that you think is going to come out of this in a 3 to 7 or 10-year timeframe? You've talked about shop floor operators becoming something even more special, perhaps. So I'm assuming that's one thing.

And then, if you want to think maybe about the larger workforce, what are some things that this will lead to? And then, finally, we just talked about the supply chain. Thinking ahead, what is likely to change when this has permeated throughout many organizations' supply chains with a lot more information available? What are the potentials here? What are the impacts?

ANTONIO: The main thing I think that will happen, and I think that it's already happening, is there will be a through thread through all the functions. I think that that's imperative. But I think that it will be a little bit easier with data. So the latter of those three that you was talking about from the future standpoint, I think that the through thread with that data as we advance and make even better applications for the shop floor to get even more data, you will be able to take that data to other functions to make changes, to improve, and reduce costs within your organization all across the board. So that's where the future will lead.

The former part of the question, as far as the change of the shop floor worker, I believe that from my perspective, I think that the world is changing. Education is changing. The cost of education is changing. And I think that from the older workforce, not to put an age on it, and what manufacturing was in the past is adapting. And the type of worker that is within a facility is different than it was because the people are different. We think different. We have Twitter, and Instagram, and Snapchat.

And so I'm throwing these things out here just saying, hey, we have a different workforce. They think different. And so I believe that manufacturers are adapting to this different workforce, and with that will come much change and much-needed change. And the capability of what a worker is expected to do, I think, will increase, but it will increase for the better. There are different roles for individuals to have within manufacturing facilities, and I think that we'll see that just come over time because we need data.

Data is going to be very, very important for any organization, and how we obtain that data, how we get that data, it's just better to have that person in the room having a big impact. And I'm saying that person, that operator in the room without having them in the room, so to speak, by getting their data to impact those decisions in their own way, but also using employee engagement with the data that they provide. So I think that's going to be really the change.

I think the number two question I kind of forgot. I apologize. I went from the last to the first.

TROND: No, it's fine. I mean, I was talking about the operators and then the advanced supply chains, which is, I guess, just another layer of complexity, and we have talked about it at length. But I'm just wondering, as these technologies, the digitization really advances and permeates throughout the supply chains, what are some of the cascading changes or not that might occur?

Because I'm assuming, just like you said, shop floor operators will have a different reality. They can do different things because some things are just taken care of or the beans are counted. They can do other things. What are those other things that organizations now can do because their supply chains will become more and more digitized?

ANTONIO: Yeah, those things are really...when you think about the footprint of what a facility needs to be, now that changes. Because one thing that's really, really important in any facility is space, so now this will impact it. Hey, we got this covered; could you go take care of these things? And then also I believe, so this is just going to be my opinion, I think that there's going to be more training. Now we can train up in another skill set to allow someone to have dual if not triple capability within their self to do more.

Let me tell you a little bit more about this machine because what we needed you for we good on that. Let's teach you about this other aspect of this machine in order to make it, you know, the upkeep of it, the PMs and TPMS, you know it. We've automated that and made it digital, but let's advance your knowledge a little bit more so you can understand. And I think that that's what we're about to witness here as we move forward.

To me, it's a really, really beautiful time. And it's going to be really, really interesting here in the next I would say ten would be the keymark, 5, especially with the climate today. And not to speak about the elephant in the room, but it truly is the perfect storm, all of these things happening. Like, going into a supply recession and then possibly having demand to drop, I mean, it's just a perfect storm of all of these things. But you'll see that those that are able to survive this will be better off because of it.

You never wish these things to happen. But you can say that you will improve, and you'll be stronger because it happened. And this also will impact what's needed in the future, especially on an operator level. So it's really interesting where we are today and how digitization will impact our lives and manufacturing from here on out. There won't be a point where it's not there. It will always exist for quite a bit of time unless there's some drastic change or an invention of some sort.

TROND: Antonio, the last question I'm going to just throw at you is, what are the training consequences? And how do you see training going forward in the medium-term future? Because you have pointed out that shop floor operators are going to be asked to do more things, more advanced things. They will get more of a bigger-picture view.

You're going to need a lot of true engineers, and then you might need a lot of engineers, meaning their engineering like they are trained with a mindset of an engineer in the sense that they are trained on improving, and suggesting, and tweaking, and adjusting the way that an engineer did. But surely, all of these people can't go to engineering school.

ANTONIO: [laughs]

TROND: How are you going to do this? Because the way I'm seeing you painting the picture of an emerging manufacturing workforce here, I mean, unless you're not talking about the same people, how are those same people going to adjust to this new reality?

ANTONIO: Right, yeah.

TROND: Is the UI going to be the key here, the UI just has to be simple the way you've explained that apps have to be kept simple so that training is limited? Or are you foreseeing that complexity still will increase so that people are going to have to become trained on still sophisticated piece of equipment? Because it could go two ways here, either you're doing advanced things, but you're keeping it simple still, or you're doing advanced things, and it's complicated. [laughs]

ANTONIO: So this is a great question, and I'm really excited to answer it. So the thought here is is, I'm going to take a CNC, a computerized numeric control machine. That is a very sophisticated piece of equipment, and an operator runs it already. No matter what they do, they're already running it, and so they're capable. And yes, they didn't go and get this advanced engineering, and those that receive those advanced engineering degrees they're worth every penny. It's teaching you on a vast scale.

But in a manufacturing facility, on what you're doing, you're removing some of the noise and saying, hey, I just need you to learn this. This is this process. So just this, just eat what's on your plate. Don't worry about any of this other stuff. And we'll guide you through. We will layer on, and layer on, and layer on the knowledge that we want you to have in order to enhance you on this process. And this process is core to manufacturing. See how that sounds a little bit different?

Because when you go and get your degree, I'm just going to pick engineering, you're learning all types of things, and they're all important. And there's a lot of physics and just a lot of things that you need to understand. At the end of the day, if you were to take an engineer off the streets that just got their degree and throw them in, how different would they be if you had a seasoned, experienced operator that knows this process and you compare the two? That would be an interesting comparison. I actually would like to see a study on that.

I think that, not to get deep, I just think that there would be a point where if you were to graph it where they would intersect, and that person with the advanced engineering would supersede this operator. But how long that would be would be interesting if you've created an environment and a very easy way through applications and digital solutions to improve this operator where they have knowledge and a different way of explaining it to them, all of these things where you've advanced and upped one. Like, you've upped this operator to this process. I think that would be interesting.

I think that that's going to be the future. You're going to have core competencies of manufacturing operators where they can feel proud. Despite that, they would be labeled blue-collar; I believe that their skill set and their knowledge would be probably more than what their label of blue-collar will be because they will be strategically very important to that manufacturing facility because of the knowledge that they know about that core competency of the process. And then just think about this, you learn one, you can learn something else. [chuckles] You know what I mean? And so I think that it just continues. So that's the way that I see it playing out.

TROND: Antonio, I think, to me at least, when I listen to this, it feels inspiring. And it certainly should feel inspiring to whether they are younger or older people who are interested in manufacturing because this spells a day and age where perhaps yet again, this kind of insight of knowing how to work machines and knowing how to coordinate with others on a shop floor or producing something tangible is going to be re-appreciated the way it was in other types of industrial upheavals and revolutions.

It's interesting to me that this is perhaps where we are, this inflection point where the kind of skill sets this will take and perhaps the kind of specialization that now seems perhaps within reach for a different cadre of people. Because clearly, MIT and, Carnegie Mellon, and UCL would have to scale up their training or offer everything they have for free online in order to train 10x, 100x, 1,000x more engineers.

Or these skills are just going to have to be taught in a combination of community colleges; I would assume, and on the shop floor directly by yourselves in these organizations themselves or perhaps a mix of the above. But either way, it would seem to me that it's not all that bleak of a future for manufacturing if what you're saying comes to --

ANTONIO: Fruition.

TROND: Fruition here.

ANTONIO: I agree. And this is really what I see, and that's why I'm excited. I'm happy to be a part of it. And it's one of those things...someone said this to me the other day "Industry 5.0." [laughs] I'm just like, okay. You can hear that concept, but from a societal standpoint and a person that is an advocate of free markets, I think that this is the moment in time in our world because we have to make widgets where we'll define what that is.

And before we talk about this industry 5.0 talk, the human part has to be addressed. And if you do it in the way that we're discussing, it makes for an interesting future. If you do it and bring other things into the discussion room already, I think that it changes basically what's being spoken about and not really discussing, okay, what is really going to move the needle and move us forward as a manufacturing group together? Because we compete against each other in some realms if we're in the same market, but it's all the same game no matter where you are.

And you're taking this from a guy that they would put in the plane and drop in a facility and now have to go through and just figure things out and could actually make change. But one of the things that I recognized everywhere I went in all the facilities that I've been to, all the facilities that I visited, were the people. The people were the important aspect. And you just definitely want to make sure that they're in the equation and in the dialogue of whatever change may happen. And I believe that platforms that allow that will be key for now and the future.

TROND: Antonio, you've been very generous with me, your time. It's been super interesting. Thank you so much.

ANTONIO: Thank you. I appreciate it.

TROND: You have just listened to another episode of the Augmented Podcast with host Trond Arne Undheim.

The topic was Innovating Across the Manufacturing Supply Chain. Our guest was Antonio Hill, Head of Manufacturing Digital Solutions, Global Supply Chain at Stanley Black & Decker. In this conversation, we talked about Lean leadership, productivity, and the challenge of digital transformation across operations and supply chains.

My takeaway is that Stanley Black & Decker is a huge organization where any improvements by tweaking their own operations or by adding insight from what happens along the whole supply chain can mean significant productivity gains. I find it interesting that they have their own version of the augmented lean approach tailored to where they are and, most importantly, building on the insight that the workforce is where the innovation comes from. By giving shop floor workers access to insights on big-picture manager deliberations, they are freed up to operate not only more efficiently but also more autonomously. When all of industry works that way, manufacturing will make tremendous advances more rapidly and sustainably than ever before. Thanks for listening.

If you liked the show, subscribe at augmentedpodcast.co or in your preferred podcast player, and please rate us with five stars. If you liked this episode, you might also like Episode 94 on Digitized Supply Chain with insights from Arun Kumar Bhaskara-Baba, Head of Global Manufacturing IT at Johnson & Johnson. Hopefully, you'll find something awesome in these or in other episodes, and if so, do let us know by messaging us. We would love to share your thoughts with other listeners.

Special Guest: Antonio Hill.

In this episode of the podcast, the topic is "Augmented Lean Prelaunch." Our guest is Natan Linder, in conversation with host, Trond Arne Undheim.

In this conversation, we talk about the background of our co-authored book, Augmented Lean, a human-centric framework for managing frontline operations, why we wrote it, what the process has been like, the essence of the Augmented Lean framework, and the main lessons of this book for C-level executives across industry.

If you like this show, subscribe at augmentedpodcast.co. If you like this episode, you might also like Episode 96 on The People Side of Lean with Professor Jeff Liker.

Augmented is a podcast for industry leaders, process engineers, and shop floor operators, hosted by futurist Trond Arne Undheim and presented by Tulip.

Follow the podcast on Twitter or LinkedIn.

Trond's Takeaway:

Industrial revolutions are rarely chronicled as they are happening, but this industrial revolution will be. There is an ongoing shift in the way technology and workforce combine to produce industrial change, and it is happening now. We are lucky to be situated in the middle of it. And I personally feel fortunate that I was brought along for the ride.

It has been a life-changing experience to realize the power and impact of living through a shifting logic of manufacturing and, perhaps more importantly, to realize that as excited as we can be about automation, an augmented workforce represents the best combination of the most important technology we have which is human workers themselves with the second best machines that humans create. The fact that making humans and machines work together is no trivial task has been pointed out before but documenting what happens when it does go well in the biggest industrial companies on the planet feels like a story that deserves to be told.

Transcript:

TROND: Welcome to another episode of the Augmented Podcast. Augmented brings industrial conversations that matter, serving up the most relevant conversations on industrial tech. Our vision is a world where technology will restore the agility of frontline workers.

In this episode of the podcast, the topic is Augmented Lean Prelaunch. Our guest is Natan Linder, in conversation with myself, Trond Arne Undheim.

In this conversation, we talk about the background of our co-authored book, Augmented Lean, a human-centric framework for managing frontline operations, why we wrote it, what the process has been like, the essence of the Augmented Lean framework, and the main lessons of this book for C-level executives across industry.

Augmented is a podcast for industrial leaders, for process engineers, and for shop floor operators hosted by futurist Trond Arne Undheim and presented by Tulip.

Natan, good to have you in the studio. How are you today?

NATAN: I'm great. How are you? It's been a minute.

TROND: It's been a little minute for us. It's crazy with book launches. It takes a little out of you. And you are running a company in addition to that, so you had some other things on your plate too.

NATAN: Yep, running a company and having a book coming is an, I don't know if an artifact, but definitely, company is a lot about changing the status quo. And the book tries to capture a movement. So I think they go along nicely.

TROND: Yeah, Natan. And I wanted to bring us in a little bit and converse about why this book was written. Certainly, that's not my benefit. You brought it up to me. But what were we thinking about when writing this book? So I want to bring it back to way before I came into the picture with the book because it was your idea to write a book. What was on your mind? What were the main reasons that you thought I really want to write a book?

NATAN: When I was coming up as an engineer...and my background, I'm not a pure manufacturing production type engineer, but I've been around it my entire career just because of the type of products that I've been involved with whether it's mobile phones, or robots of all sorts, 3D printers. So you get to spend a lot of time in these operational environments, shop floors, machine shops, and the like.

And when we started working on Tulip, it was pretty clear pretty quickly that there's a moment that is emerging in operations that no one has captured the story. And this is back even; I don't know, maybe five or six years ago. We are maybe one or two years old, and I'm already starting to think about this post-lean, or classical lean movement that I'm sure is happening. That really is the genesis of the book in the early, early days.

And fast forward to when we started talking, I think we got Tulip off the ground. But really, that was a platform to meet all those different people who helped operations transform digitally, whether it's all sorts of consultants, or academics who are researching operations, or business leaders, you know, tons of factory managers and the engineers that work with them, and the executive, so a whole bunch of people. And they're all basically talking about the same thing and the deficiencies in lean, the complexity of technology, and how they're trying to change, and it is so difficult.

So I think that's a good description of the landscape before diving in to try and capture what the book attempts to capture.

TROND: Yeah, Natan, I remember some of our early discussions. And we were dancing around various concepts because clearly, lean is a very broad perspective in industrial manufacturing focused on reducing waste and many other things. It's a broad concept that people put a lot of different things into.

But I remember as you and I were thinking about how to describe this new phenomenon that we do describe in the book, we were thinking a little bit that a lot of these new influences come from the digital sphere. So there's also this term agile. There are some people who say, well, you know, let's just replace lean because it's an outdated paradigm. And I remember you were quite adamantly arguing that that's not the case. And this goes a little bit to the message in our book. We are in no way really saying that lean isn't relevant anymore.

NATAN: On the contrary.

TROND: Tell me a little bit about that.

NATAN: A really simple way I think to frame it is that whether you're practicing lean formally or some variant of it, of lean, or Six Sigma, or some program that formalizes continuous improvement in your operation...and we're talking about frontline operations. We're talking about factories, and labs, and warehouses, and places like that. You are practicing lean because this is how the world..., even if you're not doing it formally; otherwise, you're not competitive. Even if you're in a bank or a hospital, you might be practicing lean.

And that's where agile comes to the picture, and it was adopted widely by operations practice in general and pushed into areas that are not pure manufacturing. So, in a way, lean is a reality. Some organizations are more formal about it, some are less, but definitely, they're doing it.

Here's the issue, and this is the main thesis of the book. When lean came about...and we know the catalyzing text. We know the teaching of Taiichi Ohno. We know about The Goal. We know about The Machine That Changed the World. And those are seminal texts that everybody reads. And we know about Juran and lots of great thinkers who thought about operations as a data-driven game, some from the school of thought of quality, some from pure operation research, some from how do you put emphasis on classic just-in-time, Kanban, Kaizen, all those continuous improvement things.

But at the end of the day, all of that thinking, which still holds true, was not done when digital was top of mind, where data is everywhere, where people need to live in such data ecology. It was done, so to speak, in analog times. And it doesn't mean that the principles are wrong, but it doesn't mean they don't need to get augmented. And this is maybe the first time where this idea of augmentation, which, to me, augmentation is always about...I always think about augmentation from a people's perspective or an org perspective. It's just a collective of people. That's where it starts, and that's where we had something to say. So that's one aspect to think about.

The second big one is actually very simple. It's kind of like; we heard ten years of industry 4.0 is going to change everything, and all we got is this lousy OEE graph. And that's kind of like a little tongue-in-cheek on we were promised flying cars, but we only got 140 characters. I mean, come on, stop talking about industry 4.0. It's like, who cares?

If the tools and digital techniques and what have you is not adopted by the people actually doing the work, that then collectively, one engineer, another engineer, another operator, a team lead, the quality lead, and so on come together to transform their org, if that's not happening, then that's not sustainable transformation, and it's not very relevant. Again, augmentation.

TROND: Right. And I think, Natan, that's where maybe some people are surprised when they get into this book. Because it would be almost tempting to dismiss us as traditionalists in the sense that we are not really going whole hog into describing digital as in and of itself, the core of this principle. So there is a little bit of a critique of agile as an idea that agile or using that as a kind of a description for all digital or digital, right? That digital doesn't change everything.

And I guess I wanted to reflect a little bit on that aspect because I know that you, as a business leader now hiring a lot of people, we are spending a lot of energy bringing these two perspectives together, and it's not very obvious. You can't just take a digital person who is completely digital native and say, "Welcome to the factory; just do what you do. And because you do things better than everyone else, we are now going to adapt these factories." How do you think about that?

In factories, you could conceive it as the IT versus OT, so operational technologists versus information technologists and the various infrastructures that are quite different when those two things come into play.

NATAN: So my frame of reference is the most value...and it's a very engineery frame of reference because I'm an engineer at the end of the day. It's like, the most value gets unleashed when people truly change how they work and adopt a tool, and that's true for operations and manufacturing. But, by the way, it's also true for the greater business perspective.

And a lot of people, when I talk to them about Augmented Lean, really take us to the realms of what is the future of work, and I think it's very timely. We're kind of in a post-COVID reality. Working remote has changed many things, working with data. Big ideas like citizen development, you hear them all over the place. And use of advanced platforms like the no-code/low-code that allow people to create software without being software engineers become a reality. So there's a much broader thing here.

But if I focus for a second on what you're asking, the way I see it is when people truly change how they work, it means that they believe, and that belief translates into action, that the tool that they're using is the best way to do something. And they become dependent and empowered by it at the same time because they're not willing to go back to a state where they're not thinking and working with data, or back to the clipboard, or back to being dependent on an IT department or a service provider to give them some technical solution. People have become more self-sufficient.

And it turns out that if you do that, and sometimes people would refer to that as you let people hack or go nuts in the factory floor or in whatever operational environment, that could be a concern to people, and that's a fair observation for sure. And that's where when you look at the book, when we were kind of constructing the framework we call Leader HG where HG stands for hack and govern... We are used to Silicon Valley startups being like, oh yeah, you all just need to hack. And that's a very glorious thing, and everybody understands that.

And they want them to hack when they are a 50,000-person software company. They're still hacking, but they're doing it in a much more structured way, in a much more measured way. So even in hacking, there's governance. And in operational environment, governance is equally important, if not more, because you're making real things. That is something we've observed very empirically.

Talking to a lot of people seeing what they do, it's like, yeah, we want the best ideas from people. How do we get it? What do we do? We tried this approach, that approach. And I think we were sometimes very lucky to be observers to this phenomena and just captured it.

TROND: Yeah. And I wanted to speak to that a little bit. I want to thank you, actually, for bringing me into this project because you and I met at MIT but from different vantage points. I was working at Startup Exchange working with a bunch of very, very excellent MIT startups in all different domains, and you were an entrepreneur of several companies. But my background is more on the science and technology studies but also a management perspective on this.

But I remember one of the things you said early on to me was, "I want to bring you in on this project, but don't just be one of those that stays at the surface of this and just has like a management perspective and writes future of work perspectives but from like a bird's eye view. Come in here and really learn and go into the trenches."

And I want to thank you for that because you're right about many things. This one you were very right about. And this clearly, for me, became a true research project in that I have spent two years on this project, a lot of them in venues and factory floors, and discussing with people really at the ground level.

And for me, it was really a foundational experience. I've read about many things, but my understanding of manufacturing, frankly, was lacking. And you could have told me as much, but I actually, frankly, didn't realize how little I knew about all of the factors that go into manufacturing. I had completely underestimated the field. What do you say to that?

NATAN: It's interesting because I feel like the last two years, everything I think I know [laughs], then I found out that I don't know enough. It just kind of motivates you to do more work to figure out things because it's such a broad field, and it gets very, very specific.

Just listening to your reflection on the past couple of years, the reality is that there is a gap in the popular understanding of what operations and manufacturing is all about. People think that stuff comes from some amorphous factory or machine that just makes the things. And they usually don't see, you know, we have those saying, like, you don't want to see how the sausage is made, which is obviously very graphic.

But you also don't see how the car is made unless you're a nerd of those things and watch those shows like how things are made, but most people just don't. And they don't appreciate the complexity and what goes into it and how much technology and how much operation process it consumes. And as a society and as a set of collective economies and supply chains, it is so paramount to what's actually happening.

Just take things like sustainability or what happens with our planet. If we don't learn to manufacture things better and more efficiently with less people because we don't have enough people in operations, for example, our economies will start to crumble. And if we don't do it in a way that is not just sustainability from the perspective of saving the planet, also that, but if we don't become more efficient in our supply chains, then businesses will crumble because they can't supply their customers with the product that they need.

And this thing is never-ending because products have life cycles. Factories have life cycles. And the human species, that's what we do; we take technology, and then we turn it into products, and we mass produce it. That's part of how we survive. What we need is we increase awareness to this. And I think The Machine That Changed the World and Toyota Production System unveiled those concepts that you need to eliminate waste to build better organizations, to build a better product, to have happier customers; there's something really fundamental there that did not change.

The only thing that changed is that now we're doing it in a reality where the technology is out there; data is out there. And to wield it is difficult, and there is no escape from putting the people who do the work in the center. And to me, if we are capable of doing that, the impact of this is recharging or rebooting lean in the classic sense for the next three decades. And that's my personal hope for this book and the message we're hoping to bring in. We would love people to join that call and fly that flag.

TROND: Yeah. I wanted to take us now, Natan, to this discussion. A lot of people are saying, "Oh, you got to market manufacturing better, and then people will come to this area because there are interesting things to do there." But more broadly, if we think about our book and why people should read that, my first reflection is building on what I said earlier that I didn't realize not just the complexity of manufacturing but how interesting it was.

My take after two years of studying this is actually that there's no need to market it better because it is so interesting and fundamental for the economy that the marketing job, I think, essentially has already been done. And it's just there's a lag in the system for new employees, new talent. And society overall realizes how fundamentally it is shifting and reconfiguring our society.

But I guess I want to ask you more. What is the reason a C-level executive, whether they work in manufacturing, in some industrial company, or really, if they work in any company that is interested in what technology and manufacturing is doing to their business reality...how they can implement some of those ideas in their business. What would you say to them? I mean, is our book relevant to a business leader in any Fortune 500? Or would you say that our messages are kind of confined to an industrial setting?

NATAN: I think it applies to all of them. And the reason is that these types of roles that you're describing, folks will best be served if they learn from other people's experience. And what we tried to do in the book is to bring almost an unfiltered version of the stories of their peers across various industries, from medical devices, to pharmaceuticals, to classic discrete manufacturing, all sorts of industries. And they're all struggling with the same kind of stuff. And so those stories are meaningful and can contextualize the thinking of what those C-levels are actually trying to cope with.

What they're really trying to do, everybody, I'd say, is why do people think about and talk about those big terms of digital transformation? It's really because they want to make sure their companies don't stay behind or, in other words, stay competitive. This stuff is an imperative for organizations that have real operations that span digital and physical, and I don't know many that don't. Of course, there are some service industries that don't have anything but still have operations.

You can't avoid handling the subject and what it entails. It entails training your people differently. It entails defining technology stacks. It entails connecting using various technologies, protocols, what have you, across organizations and finding value in this data so you can make good decisions on how you run your billing cycles, or how you order your stock to build, or how you ship your end product and everything in between.

And I don't think that the book is groundbreaking in the sense that we're the first people who ever thought about it. But I think if we've done anything, is we've observed long and hard. And we've listened very carefully to what people are telling us that they did, and they struggled. And it's a timely book. And maybe in a decade, it's a classic, and, wow, these are good stories. And it's like reading about the first people booting up mainframes or PCs. And if that happens, I'm actually pretty happy.

But you know why I would be happy? Trond, let me tell you something, it's because technology, like, the human needs change much slower than how technology evolves and gets deployed, but still, good technological-driven transformation take a long time.

TROND: That's exactly what I was going to say is that the future is an interesting concept because what's tomorrow to some people is today for others. So you say we're not writing about something that's so new or unique but to industry overall and to some manufacturers, what we're writing about is the future because they haven't implemented it yet.

To some of Tulip customers, to some of the great companies that we have researched in the book, whether they be J&J, Stanley Black & Decker, DMG MORI, a lot of other companies in medical device side, and also smaller and medium-sized companies, even some startups that are implementing some the Augmented Lean principles, to them, this is of course not the future.

And maybe, you know, we're not saying that leaders who try to implement Augmented Lean need to change everything around; we're saying common sense things. It's just that; clearly, all of industry is not human-centric, right? There are parts of industry where you adjust 80% to your machines, and you make economic decisions purely based on the infrastructure efficiency improvements you're trying to make. I guess what we're saying is the innovation argument; people are the most innovative, and you have to restructure around your workforce, even if you are making machine and robot investments.

NATAN: Yeah, automation would always require strong reasons to automate that, you know, some of them are complexity, safety risk, things like that or throughput to like how much product do you need and that kind of stuff. But even if you have the best automation, you typically have people around it, and nothing is just only machine-driven or only human-driven.

The reality is that most stuff gets made through a combination of several manufacturing technologies working in unison with people at the beginning, middle-end doing things from the planning, to running automation setups and machinery, to taking the output, doing assembly, doing tests, audits and checks, and packaging, and logistics, and at the end of the day, human-intensive type of operation in most of the areas we roam, at least.

And as such, to think that in this day and age you don't focus on people is to me nuts when all those people carry a supercomputer called a smartphone in their hand and have uber-connected homes with a million CPUs streaming all this data, and we call that media, whatever. And they're so accustomed to interfacing to their world and their businesses through that.

And you and I are Gen Xers, and let's just think about the generation that comes after us and after us. These are digital natives par excellence. They expect as much, and organizations that don't do that, whether they choose the Augmented Lean approach or any other approach, they're just not going to have employees. That's a little bit of a problem.

TROND: Yeah. But it's important what you're saying in one respect which is there are many reasons to dismiss a book, a management book, a technology book. And one could be like; all these people are just that. And one, I guess, gut reaction when people look at the title or perhaps hear some of the things that you and I are saying is that, oh, these people are Luddites; they're against technology.

But I wanted to, certainly on my end, just to state very clearly there's nothing in our book that's against technology. We're simply saying to optimize for the simplest technology, that is, you know, to our great inspiration here, who was a big inspiration, I know, for you and now for me because you brought her into my sphere. Pattie Maes' perspective from MIT on Fluid Interfaces and the importance, you know, no matter what advanced technology you're going to bring into whatever context, if that context of the technology, the use interface is not a fluid interface, you are simply doing yourself a disservice.

You could have bought a $1 million CNC machine or maybe a $10 million whatever robot, but it has to work in your own organization, and this is just so important. So we're not against technologies. We're just saying these investments will be made. But you have to think about other things as you're making those investments. So I just wanted to make that point and hear your comment to that.

NATAN: Yeah, look, I have a slightly...I guess a complementary angle to this is like when you think about it; I think that technologically democratized organizations in the day and age we living in the future. And what makes, I think, Augmented Lean span beyond the frontline operation perspective is because it tells a story of democratizing operation where fundamentally before lean...and we're talking about the mass production era. Mass production came from a military structure, you know, divisions, and battalions, and commanders, and ranks, and all that kind of stuff.

Enters lean, and democratization starts. Forget technology. It starts because suddenly everybody on the Gemba Walk, you know, the walk where they have an equal voice to find problems on the shop floor, and list them up, and think about a solution, everybody has a voice. So these are fundamental things that shifted things like how you manage your warehouse, or how you do just-in-time, or how you are supposed to do continuous improvement. But you have to collect data to prove that this improvement is actually worthwhile doing.

And this is exactly what agile took, and this is exactly the transition you saw in, well, because the market moves so fast and the internet is here, and clouds are real, why don't we not spend two years in a bunker doing waterfall software development? And, boom, we're now talking sprints and all that kind of stuff. And no one is even questioning that. And that's a lean approach we call agile, lean approach to how you do software development.

And what I'm trying to say is, de facto, when I run a day in a company, like, I talk to my peers, and my leaders, and folks I work with on a daily basis. Everybody talks, yeah, we're on an operation sprint. We are on a marketing sprint. We are on a whatever sprint. What is that? That is a democratized organization with specific leaders owning functions and owning interfaces using tech stacks all over the place: the marketing stack, the sales stack, the HR stack, whatever.

And where we roam also, we're part of the operational or OT stack, and that's what they're doing. And all this book is doing is saying, like, hey, it's actually happening. Let's give this a name. Let's put the beacon on this. Let's try and find what's the commonalities. Let's get the best stories that share the successes and the failures. We have plenty of failures there in the book that teach you something at this moment in time and set up the next decade.

This next decade to me, is seminal. It's not very different to when technologies reached maturity, like clouds and what have you. 10, 15 years ago, you're talking about this thing, cloud, some people will go like, "What cloud? What are you talking about?" That's done. That's the disappearing edge of technology. Now we say AI and all that kind of stuff. And then the problem gets solved and disappearing, you know, it's like, so that's going to happen. I just think we gave it a good name and a good description at this point in time.

TROND: Natan, I love the...personally, I'm a runner. I love the metaphor of a sprint, and for a couple of reasons, not just because I know what a sprint is and what it takes. But I love the fact that a sprint in a management context refers to sprinting partly together because it's a team-based effort. So some people need to sprint a little faster in certain aspects of that team process in order to deliver things that the team needs.

But rounding up and thinking about how people can sprint with us, Natan, how should people think about learning more? So, obviously, reading the book. It's available on every bookstore, and Wiley published it, and it should be everywhere. There's even an e-book.

But beyond that, what are your thoughts about how people can get in touch, join the movement, join the sprint of thinking about Augmented Lean? Which by the way, there is no one Augmented Lean principle. It's a menu of choices. There are ways that you can engage. There are ways you can implement it. It's not like a one, three-step process that everybody has to do. But there are ways that people can connect. We have this Augmented Podcast. What are your thoughts if people are gelling with this message?

NATAN: I can talk about my heart's desire, okay, and my hallucination around this. And this is like, really, kind of living the dream and making sure democratization continues. If we are successful, at the moment, we are starting a movement. And there are millions of people who self-identify as lean Six Sigma quality professionals out there that know exactly what we're talking about viscerally. They spend their days trying to solve problems like that. They pore over data; they train people. They are the people creating the reports and trying to kind of help their organization take another step and another step in the never-ending journey of continuous improvement.

We need to work on a much larger manifesto for Augmented Lean, and this is not for you and me; this is for a greater community to come together. So my recommendation is if you dig this and this is something you want to do, you know where to find us; go to augmentedlean.com. There's a contact email, our contact information. And I guess we can share it for that purpose somewhere in Augmented Podcast or our various other channels. And tell us what you think. And just join us.

We're not sure exactly...we're starting from the excitement around launching the book with our close network of partners, and friends, and customers, and collaborators, and all our network. And it's a very exciting moment for us. But we're going to open it up, and it's going to be in the book tour, and it's going to be in various conferences.

And the first law of creating a movement is show up. So I'm calling everybody to show up if you're okay with lean and the way it's going so far for you and Six Sigma. But if you feel the need to change and observed or experienced some of the stuff we're talking about in Augmented Lean, come tell us about it, and let's shape it up and get people together. The internet is the best tool on the planet to do that, and we'll get it done. Stay safe.

TROND: Right. So, on that note, I want to round us off. I think that it should at least be clear from this conversation that both of us strongly feel that there are greater things ahead for industry and that manufacturing is not just a relevant piece of society, but there are things happening here that are coalescing that we are describing in the book, but that will happen independently of us and the very few examples we were able to put into the book.

And folks that are interested in exploring what that means for them as individuals, as knowledge workers in the factory floor, or as executives who just want to be inspired the way people were inspired by the Toyota lean movement or other movements, they should come and contact us. Natan, thanks for spending the time today.

NATAN: Yeah. Thanks, Trond. Always a pleasure. Will see you very soon.

TROND: You have now just listened to another episode of the Augmented Podcast with host Trond Arne Undheim.

The topic was Augmented Lean Prelaunch. Our guest was Natan Linder, in conversation with myself, Trond Arne Undheim. In this conversation, we talked about why we wrote a book and why C-level executives should read it.

My takeaway is that industrial revolutions are rarely chronicled as they are happening, but this industrial revolution will be. There is an ongoing shift in the way technology and workforce combine to produce industrial change, and it is happening now. We are lucky to be situated in the middle of it. And I personally feel fortunate that I was brought along for the ride.

It has been a life-changing experience to realize the power and impact of living through a shifting logic of manufacturing and, perhaps more importantly, to realize that as excited as we can be about automation, an augmented workforce represents the best combination of the most important technology we have which is human workers themselves with the second best machines that humans create. The fact that making humans and machines work together is no trivial task has been pointed out before but documenting what happens when it does go well in the biggest industrial companies on the planet feels like a story that deserves to be told. Thanks for listening.

If you liked the show, please subscribe at augmentedpodcast.co. And if you liked this episode, you might also like Episode 96 on The People Side of Lean with Professor Jeff Liker, who wrote the best-selling book, The Toyota Way. Hopefully, you'll find something awesome in these or in other episodes, and if so, do let us know by messaging us because we would love to share your thoughts with other listeners.

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

Augmented — industrial conversations that matter. See you next time.

Special Guest: Natan Linder.

The topic is "The People Side of Lean." Our guest is Jeffrey Liker, academic, consultant, and best-selling author of The Toyota Way. In this conversation, we talk about how to develop internal organizational capability and problem-solving skills on the frontline.

If you liked this show, subscribe at augmentedpodcast.co. If you liked this episode, you might also like Episode 84 on The Evolution of Lean.

Augmented is a podcast for industry leaders, process engineers, and shop floor operators, hosted by futurist Trond Arne Undheim and presented by Tulip.

Follow the podcast on Twitter or LinkedIn.

Trond's Takeaway:

Lean is about motivating people to succeed in an industrial organization more than it is about a bundle of techniques to avoid waste on a factory production line. The goal is to have workers always asking themselves if there is a better way.

Transcript:

TROND: Welcome to another episode of the Augmented Podcast. Augmented brings industrial conversations that matter, serving up the most relevant conversations on industrial tech. Our vision is a world where technology will restore the agility of frontline workers.

In this episode of the podcast, the topic is the People Side of Lean. Our guest is Jeffrey Liker, academic, consultant, and best-selling author of The Toyota Way. In this conversation, we talk about how to develop internal organizational capability, problem-solving skills on the frontline.

Augmented is a podcast for industry leaders, process engineers, and shop floor operators, hosted by futurist Trond Arne Undheim and presented by Tulip. Jeffrey, how are you? Welcome to the podcast.

JEFFREY: Thank you.

TROND: So I think some people in this audience will have read your book or have heard of your book and your books but especially the one that I mentioned, Toyota. So I think we'll talk about that a little bit. But you started out as an engineering undergrad at Northeastern, and you got yourself a Ph.D. in sociology. And then I've been reading up on you and listening to some of the stuff on the musical side of things. I think we both are guitarists.

JEFFREY: Oh, is that right?

TROND: Yeah, yeah, classical guitar in my case. So I was wondering about that.

JEFFREY: So I play also a classical guitar now. I played folk and rock earlier when I was young. But for the last more than ten years, I've been only studying classical guitar.

TROND: Well, so then we share a bunch of hours practicing the etude, so Fernando Sor, and eventually getting to the Villa-Lobos stuff. So the reason I bring that up, of course, beyond it's wonderful to talk about this kind of stuff with, you know, there aren't that many classical guitarists out there. But you said something that I thought maybe you could comment on later. But this idea of what happened to you during your studies of classical guitar actually plays into what you later brought into your professional life in terms of teaching you something about practicing in particular ways. So I hope you can get into that.

But obviously, you've then become a professor. You are a speaker and an advisor, and an author of this bestseller, The Toyota Way. Now you run some consulting. And I guess I'm curious; this was a very, very brief attempt at summarizing where you got into this. What was it that brought you into manufacturing in the first place? I mean, surely, it wasn't just classical guitar because that's not a linear path. [laughs]

JEFFREY: No. So for undergraduate, I had basically studied industrial engineering because I didn't really know what I wanted to do with my life. And my father was an engineer. And then I literally took a course catalog and just started reading the descriptions of different kinds of engineering. And industrial engineering was the only one that mentioned people. And in theory, industrial engineering is a systems perspective which integrates people, materials, methods, machines, the four Ms.

And in the description from Northeastern University, they said it's as much about human organization as it is about tools and techniques. So that appealed to me. When I got to Northeastern...I was not a particularly good high school student. So I didn't have a lot of choices of what colleges I went to, so Northeastern was pretty easy to get into. But they had a cooperative education program where you go to school, and you work. You go back and forth between school and work and had a pretty elaborate system for setting you up with jobs.

I got one of the better jobs, which was at a company called General Foods Corporation at the time, and they make things like Jell-O, and Gravy Train dog food, and Birds Eye vegetables, and a lot of other household names, Kool-Aid, all automated processes, even at that time in the 1970s. And they had been experimenting with something called socio-technical systems, which is supposed to be what I was interested in, which is bringing together the social and technical, which no one at Northeastern University had any interest in except me.

But I was very interested in this dog food plant where they were written up as a case study pioneer. And the basic essence of it was to give groups of people who are responsible, for example, for some automated processes to make a certain line of Gravy Train dog food, give them responsibility for all their processes, and they called them autonomous workgroups. And what we try to do is as much as possible, give them all the responsibility so they can work autonomously without having to go and find the engineer or deal with other support functions, which takes time and is kind of a waste.

So that fascinated me. I studied it. I wrote papers about it even in courses where it didn't fit. But the closest I could get to the social side was through sociology courses which I took as soon as I was able to take electives, which was about my third year. And I got to know a sociology professor closely and ultimately decided to get a Ph.D. in sociology and did that successfully, published papers in sociology journals at a pretty high level. And then discovered it was really hard to get a job.

TROND: Right. [laughs]

JEFFREY: And there happened to be an advertisement from an industrial engineering department at University of Michigan for someone with a Ph.D. in a social science and an undergraduate degree in industrial engineering. And I was probably the only person in the world that fit the job. And they were so excited to hear from me because they had almost given up. And I ended up getting that job quickly then getting to Michigan excited because it's a great university.

I had a low teaching load. They paid more than sociology departments. So it was like a dream job. Except once I got there, I realized that I had no idea what I was supposed to be doing [chuckles] because it wasn't a sociology department. And I had gotten away from industry. In fact, I was studying family development and life’s course development, and more personal psychology and sociology stuff. So I was as far away as I could be. So I had to kind of figure out what to do next.

And fortunately, being at Michigan and also being unique, a lot of people contacted me and wanted me to be part of their projects. And one of them was a U.S.-Japan auto study comparing the U.S.-Japan auto industry going at the same time as a study at MIT and Harvard that ultimately led to the book The Machine That Changed the World, which defined lean manufacturing. So this was sort of a competitive program. And they asked me to be part of it, and that's what led to my learning about Toyota. I mean, I studied Toyota, Nissan, Mazda mainly and compared them to GM, Ford, and Chrysler. But it was clear that Toyota was different and special.

And ultimately, then I learned about the Toyota Production System. And from my perspective, not from people in Toyota, but from my perspective, what they had done is really solve the problem of socio-technical systems. Because what I was seeing at General Foods was workers who were responsible for technical process and then were given autonomy to run the process, but there was nothing really socio-technical about it. There was a technical system, and then there was social system autonomous work groups and not particularly connected in a certain way.

But the Toyota Production System truly was a system that was designed to integrate people with the technical system, which included things like stamping, and welding, and painting, which were fairly automated as well as assembly, which is purely manual. And Toyota had developed this back in the 1940s when it was a lone company and then continued to evolve it.

And the main pillars are just-in-time and built-in quality. They have a house, and then the foundation is stable and standardized processes. And in the center are people who are continuously improving. Now, the socio-technical part the connection is that just-in-time for Toyota means that we're trying to flow value to the customer without interruption.

So if what they do is turn raw materials into cars that you drive, then anything that's turning material into a component or car physically is value-added, and everything else is waste. And so things like defects where you have to do rework are waste. And machines are shut down, so we have to wait for the machines to get fixed; that's waste. And inventory sitting in piles doing nothing is waste. So the opposite of waste is a perfect process.

And Toyota also was smart enough, and all that they figured out was more like folk learning or craft learning. It was learning from doing and experience and common sense. And they didn't particularly care about linking it to academic theories or learning from academic theories, for that matter.

So their common sense view is that the world is complicated. Humans are really bad at predicting the future. So the best we can do is to get in the ballpark with what we think is a good process and then run it and see how it fails. And then the failures are what lead to then the connection of people who have to solve the problems through creative thinking. So that was the integration that I did not see before that.

TROND: Just one thing that strikes me...because nowadays, comparing the U.S. or Europe and Asia in terms of business practices, it's sort of like, oh, of course, you have to compare them because they are culturally different. But it strikes me that in the automotive industry, was it immediately really clear to you at the outset that there would be such striking differences between the Japanese and the U.S. auto industry? Or is that actually something that had to be studied? Or was it something that was known, but no one really knew exactly what the differences were?

JEFFREY: So it wasn't like the American auto companies figured out that if they get good at using chopsticks, they'll be good at making cars. They weren't looking for something peculiar in Japanese culture. But they were addressing the more general problem, which was that Japanese companies were making small fuel-efficient cars at low cost with high quality. And none of the American companies could do that. The costs were higher. The quality was terrible compared to Japan. They took a long time to do everything, including developing cars.

So somehow, the Japanese were purported, they weren't convinced this was true, but according to the evidence, the Japanese were purported to be better at just about everything. And the Americans wanted to know why particularly. And at that time, there had been an oil crisis, and there was a demand for small cars. The real question they were interested in is how could they make small cars that were competitive with the Japanese? So they had to understand what the Japanese were doing.

Now, they realized that some of what the Japanese were doing were purely technical things that had nothing to do with culture. And then there was also a level of attention to detail and motivation that maybe was, for some reason, peculiar to Japan. But they needed to figure out how to replicate it in the United States.

And then, in addition to that, they had Americans like Dr. Deming, who had gone to Japan and taught the Japanese supposedly quality control methods. And Japanese companies had taken quality control methods that were created in the United States more seriously than the American companies. So part of it was relearning what came from America to Japan and got done better. So it wasn't necessarily this kind of strange place, and how can we emulate this strange culture?

TROND: Right. But that becomes then your challenge then, right? Because what you then discover is that your field is immensely important to this because what you then went on to do is...and I guess part of your consulting work has been developing internal organizational capability. These are skills that particular organizations, namely Toyota, had in Japan. So you're thinking that this then became...it's like a learning process, the Japanese learned some lessons, and then the whole rest of the automotive industry then they were trying to relearn those lessons. Is that sort of what has been happening then in the 30 years after that?

JEFFREY: Yeah, the basic question was, why are they so good? Why are we so bad? And how can we get better in America? Then there were lots of answers to that question coming from different people in different places. My particular answer was that Toyota especially had developed a socio-technical system that was extremely effective, that was centered on people who were developed to have the skills of problem-solving and continuous improvement. And while the study was going on, they were doing a study out of MIT that led to The Machine That Changed the World.

And around that same time, a joint venture between Toyota and General Motors had been formed called NUMMI. It was in California. And in their first year, it was launched in 1983, and in the first year, they had taken what was the worst General Motors plant in the world, with the worst attendance, the worst morale, workers who were fighting against supervisors every day, including physically fighting with them, terrible quality, and General Motors had closed the plant because it was so bad.

And then, in the joint venture, they reopened the plant and took back 80% of the same workers who were like the worst of the worst of American workers. And within a year, Toyota had turned the plant around so that it was the best in North America with the best workers.

TROND: That's crazy, right? Because wouldn't some of the research thesis in either your study or in the MIT study, The Machine That Changed the World, would have to have been around technology or at least some sort of ingenious plan that these people had, you know, some secret sauce that someone had? Would you say that these two research teams were surprised at finding that the people was the key to the difference here or motivating people in a different way?

JEFFREY: Well, frankly, I think I probably had a better grasp that people were really the key than most other researchers because of my background and my interest in human-centered manufacturing. So I was kind of looking for that. And it was what the Toyota people would say...whenever they made a presentation or whenever you interviewed them, they would say, "People are kind of distracted by the tools and methods, but really at the center are people."

And generally, most people listening to them didn't believe it, or it didn't register. Because Toyota did have cool stuff, like, for example, something called a kanban system, which is how do you move material around in the factory? They have thousands of parts that have to all be moved and orchestrated in complicated ways. And Toyota did it with physical cards.

And the concept was a pulse system that the worker; when they see that they're getting low on parts, they take a card and they post it. They put it in a box, and then the material handler picks it up. And they said, okay, they need another bin of these. On my next route, I'll bring a bin of whatever cards I get.

So they were replenishing the line based on a signal from the operator saying, "I need more." So it was a signal from the person who knows best what they need. And it also, from Toyota's point of view, put the employee in the driver's seat because now they're controlling their supply in addition to controlling their work process. And it didn't require that you predict the future all the time because who knows what is happening on the line and where they're backed up, and where they maybe have too many parts, and they don't need more? But the worker knows. He knows when he needs it and when he doesn't.

It was kind of an ingenious system, but the fact that you had these cards moving all over the factory and thousands of parts are moving just to the right place at the right time based on these cards, that was fascinating. So a lot of the consumers were more interested in that than they were in the people aspect, even though Toyota kept talking about the people aspect.

TROND: But so this is my question, then there was more than one element that they were doing right.

JEFFREY: There were multiple elements, yeah.

TROND: There were multiple elements. Some of them were structural or visual, famously.

JEFFREY: Right.

TROND: But you then started focusing, I guess, on not just the people aspect, but you started structuring that thinking because the obvious question must have been, how can we do some of this ourselves? And I guess that's my question is once you and the team started figuring out okay, there are some systematic differences here in the way they motivate people, handle the teams, but also structure, honestly, the organizational incentives minute by minute, how then did you think about transferring this? Or were you, at this point, just really concerned about describing it?

JEFFREY: Like I said, I was kind of unusual in my background, being somewhere between industrial engineering and sociology and being in industrial engineering departments. So maybe I wasn't as constrained by some of the constraints of my academic colleagues. But I never believed this whole model that the university gathers information structures that formulates it, then tells the world what to do. I never thought that made any sense. And certainly, in the case of lean, it didn't, and it wasn't true.

So the way that companies were learning about this stuff was from consultants, largely, and from people who had worked for Toyota. So anybody who had worked for Toyota, even if they were driving a forklift truck, in some cases, suddenly became a hot commodity. I consulted to Ford, and they were developing the Ford Production System.

They were using a consulting firm, and all their consulting firm's business was to poach people from Toyota and then sell them as consultants to other companies. And that company literally had people every day of the week who were in their cars outside the gates of Toyota. And as people came out, they would start talking to them to try to find people that they could hire away from Toyota.

TROND: It's funny to hear you talking about that, Jeff, right? Because in some way, you, of all people, you're a little bit to blame for the fame of Toyota in that sense. I mean, you've sold a million books with The New Toyota --

JEFFREY: Well, that was --

TROND: I'm just saying it's a phenomenon here that people obsess over a company, but you were part of creating this movement and this enormous interest in this. [laughs]

JEFFREY: I didn’t feel that that was...I personally had a policy because I had a consulting company too. So I personally had a policy that I would not hire somebody away from Toyota unless they were leaving anyway. That was my personal policy. But the important point was that there were a lot of really well-trained people coming out of Toyota who really understood the whole system and had lived it. And they could go to any other company and do magic, and suddenly things got better. [laughs]

And what they were doing was setting up the structures and the tools, and they also were engaging the people and coaching the people. They were doing both simultaneously, and that's how they were trained. Toyota had sent an army of Japanese people to America. So every person who was in a leadership position had a one-on-one coach for years, a person whose only reason for being in the United States was to train them. So they got excellent training, and then they were able to use that training.

And then other people once they had worked with a company and then that company got good at lean, then, within that company, you'd spawn more consultants change agents. Like, there was a company that I was studying called Donnelly Mirrors that made exterior mirrors for cars. And one of the persons that was trained by a Toyota person became a plant manager. And he ended up then getting offered a job as the vice president of manufacturing for Merillat Kitchen Cabinets. And now he's the CEO of the parent company that owns Merillat. And he's transformed the entire company.

So little by little, this capability developed where most big companies in the world have hired people with lean experience. Sometimes it's second generation, sometimes third generation. And there are some very well-trained people. So the capability still resides within the people. And if you have someone who doesn't understand the system but they just set up a kanban system or they set up quality systems, and they try to imitate what they read in a book or what they learned in a course; usually, it doesn't work very well.

TROND: Well, that was going to be my next question. Because how scalable is this beyond the initial learnings of Toyota and the fact that it has relied so heavily on consulting? Because there is sort of an alternate discourse in a lot of organizational thinking these days that says, well, not just that the people are the key to it but actually, that as a leader, however much you know or how aware you are of people processes, it is the organization itself that kind of has to find the answers.

So there's perhaps some skepticism that you can come in and change a culture. Aren't there organizations that have such strong organizational practices, whether they are cultural in some meaningful way or they're simply this is the way they've done things that even one person who comes in has a hard time applying a Toyota method? What do you think about that kind of challenge?

JEFFREY: Okay, so, anyway, I think what you said is...how I would interpret it is it’s a gross oversimplification of reality. So first of all, in the second edition of The Toyota Way, because I realized from the first edition, which was fairly early back in the early 2000s, I realized that some people were taking my message as copy Toyota, even though I didn't say that in the book. And I specifically said not to do that, but I said it in the last chapter.

So I put out the second edition a year ago, and I say it in the first page or first few pages. I say, "Don't copy Toyota," and explain why. And then, throughout the book, I say that, and then, in the end, I say, "Develop your own system." So it's probably repeated a dozen times or more with the hope that maybe somebody would then not ask me after reading it, "So, are we supposed to copy Toyota?"

So the reason for that is because, as you said, you have your own culture. And you're in a different situation. You're in a different industry. You're starting in a different place. You're drawing on different labor. You have maybe plants around the world that are in different situations. So the other thing I said in the book, which is kind of interesting and counterintuitive, is I said, "Don't copy Toyota; even Toyota doesn't copy Toyota."

TROND: So what does that mean? Did they really not?

JEFFREY: What it means is that...because Toyota had this dilemma that they had developed this wonderful system in Japan that worked great, but they realized that in auto, you need to be global to survive. So when they set up NUMMI, that was the first experiment they did to try to bring their system to a different culture.

And in reality, if you look at some of the cultural dimensions that make lean work in Japan, the U.S. is almost opposite on every one of them, like, we're the worst case. So if you were a scientist and you said, let’s find the hardest place in the world to make this work and see if we can make it work, it would be the United States, particularly with General Motors workers already disaffected and turned off.

So Toyota's perspective was, let's go in with a blank sheet of paper and pretend we know nothing. We know what the total production system is and what we're trying to achieve with it. But beyond that, we don't know anything about the human resource system and how to set it up. And so they hired Americans, and they coached them. But they relied a lot on Americans, including bringing back the union leader of the most militant union in America. They brought him back.

TROND: Wow.

JEFFREY: And said, "You're a leader for a reason. They chose you. We need your help. We're going to teach you about our system, but you need to help make it work." So that created this sort of new thing, a new organizational entity in California. And then what Toyota learned from that was not a new solution that they then brought to every other plant, whether it was Czechoslovakia, or England, or China. But rather, they realized we need to evolve a cultural system every time we set up a plant, starting with the local culture. And we need to get good at doing that, and they got good at doing it.

So they have, I don't know, how many plants but over 100 plants around the world and in every culture you can imagine. And every one of them becomes the benchmark for that country as one of their best plants. And people come and visit it and are amazed by what they see. The basic principles are what I try to explain in The Toyota Way. The principles don't change. At some level, the principle is we need continuous improvement because we never know how things are going to fail until they fail. So we need to be responding to these problems as a curse. We need people at every level well trained at problem-solving.

And to get people to take on that additional responsibility, we need to treat people with a high level of respect. So their model, The Toyota Way, was simply respect for people and continuous improvement. And that won't change no matter where they go. And their concept of how to teach problem-solving doesn't change. And then their vision of just-in-time one-piece flow that doesn't change, and their vision of building in quality so that you don't allow outflows of poor quality beyond your workstation that doesn't change.

So there are some fundamental principles that don't change, but how exactly they are brought into the plant and what the human resource system looks like, there'll be sort of an amalgam between the Japanese model and the local model. But they, as quickly as possible, try to give local autonomy to people from that culture to become the plant managers, to become the leaders. And they develop those people; often, those people will go to Japan for periods of time.

TROND: So, Jeff, I want to move to...well, you say a lot of things with Toyota don't change because they adapt locally. So my next question is going to be about future outlook. But before we get there, can we pick up on this classical guitar lesson? So you were playing classical guitar. And there was something there that, at least you said that in one interview that I picked up on, something to do with the way that guitar study is meticulous practice, which both you and I know it is. You literally will sit plucking a string sometimes to hear the sound of that string. I believe that was the example.

So can you explain that again? Because, I don't know, maybe it was just me, but it resonated with me. And then you brought it back to how you actually best teach this stuff. Because you were so elaborate, but also you rolled off your tongue all these best practices of Toyota. And unless you either took your course or you are already literate in Toyota, no one can remember all these things, even though it's like six different lessons from Toyota or 14 in your book. It is a lot.

But on the other hand, when you are a worker, and you're super busy with your manager or just in the line here and you're trying to pick up on all these things, you discovered with a colleague, I guess, who was building on some of your work some ways that had something in common with how you best practice classical guitar. What is that all about?

JEFFREY: Well, so, first of all, like I said, the core skill that Toyota believes every person working for Toyota should have is what they call problem-solving. And that's the ability to, when they see a problem, to study what's really happening. Why is this problem occurring? And then try out ideas to close the gap between what should be happening and what is happening. And you can view that as running experiments. So the scientific mindset is one of I don't know. I need to collect the data and get the evidence.

And also, I don't know if my idea works until I test it and look at what happens and study what happens. So that was very much central in Toyota. And they also would talk about on-the-job development, and they were very skeptical of any classroom teaching or any conceptual, theoretical explanations. So the way you would learn something is you'd go to the shop floor and do it with a supervisor.

So the first lesson was to stand in a circle and just observe without preconceptions, kind of like playing one-string guitar. And the instructor would not tell you anything about what you should be looking for. But they would just ask you questions to try to dig deeper into what's really going on with the problems or why the problems are occurring. And the lesson length with guitar, you might be sweating after 20 minutes of intense practice. This lesson length was eight hours.

So for eight hours, you're just on the shop floor taking breaks for lunch and to go to the bathroom and in the same place just watching. So that was just an introductory lesson to open your mind to be able to see what's really happening. And then they would give you a task to, say, double the productivity of an area. And you would keep on trying. They would keep on asking questions, and eventually, you would achieve it. So this on-the-job development was learning by doing.

Now, later, I came to understand that the culture of Japan never really went beyond the craftsman era of the master-apprentice relationship. That's very central throughout Japan, whether you're making dolls, or you're wrapping gifts, or you're in a factory making a car. So the master-apprentice relationship system is similar to you having a guitar teacher. And then, if you start to look at modern psychology leadership books, popular leadership books, there's a fascination these days with the idea of habits, how people form habits and the role of habits in our lives.

So one of my former students, Mike Rother, who had become a lean practitioner, we had worked together at Ford, for example, and was very good at introducing the tools of lean and transforming a plant. He started to observe time after time that they do great work. He would check in a few months later, and everything they had done had fallen apart and wasn't being followed anymore. And his ultimate conclusion was that what they were missing was the habit of scientific thinking that Toyota put so much effort into. But he realized that it would be a bad solution to, say, find a Toyota culture --

TROND: Right. And go study scientific thinking. Yeah, exactly.

JEFFREY: Right. So he developed his own way in companies he was working with who let him experiment. He developed his own way of coaching people and developing coaches inside the company. And his ultimate vision was that every manager becomes a coach. They're a learner first, and they learn scientific thinking, then they coach others, which is what Toyota does.

But he needed more structure than Toyota had because the Toyota leaders just kind of learned this over the last 25 years working in the company. And he started to create this structure of practice routines, like drills we would have in guitar. And he also had studied mastery. There's a lot of research about how do you master any complex skill, and it was 10,000 hours of practice and that idea.

But what he discovered was that the key was deliberate practice, where you always know what you should be doing and comparing it to what you are doing, and then trying to close the gap. And that's what a good instructor will do is ask you to play this piece, realize that you're weak in certain areas, and then give you an exercise. And then you practice for a week and come back, and he listens again to decide whether you've mastered or not or whether he needs to go back, or we can move to the next step.

So whatever complex skill you're learning, whether it's guitar, playing a sport, or learning how to cook, a good teacher will break down the skill into small pieces. And then, you will practice those pieces until you get them right. And the teacher will judge whether you got them right or not. And then when you're ready, then you move on. And then, as you collect these skills, you start to learn to make nice music that sounds good.

So it turns out that Mike was developing this stuff when he came across a book on the martial arts. And they use the term kata, which is used in Japanese martial arts for these small practice routines, what you do repeatedly exactly as the master shows you. And the master won't let you move on until you've mastered that one kata. Then they'll move to the second kata and then third. And if you ask somebody in karate, "How many katas do you have?" They might say, "46," and you say, "Wow, you're really good. You've mastered 46 kata, like playing up through the 35th Sor exercise.

So he developed what he called the improvement kata, which is here is how you practice scientific thinking, breaking it down into pieces, practicing each piece, and then a coaching kata for what the coach does to coach the student. And the purpose of the scientific thinking is not to publish a paper in a journal but to achieve a life goal, which could be something at work, or it could be that I want to lose weight. It could be a personal goal, or I want to get a new job that pays more and is a better job. And it becomes an exploration process of setting the goal.

And then breaking down the goal into little pieces and then taking a step every day continuously toward, say, a weekly target and then setting the next week's target, and next week's target and you work your way up the mountain toward the goal. So that became known as Toyota Kata. He wrote a book called Toyota Kata.

And then, I put into my model in the new Toyota Way; in the center of the model, I put scientific thinking. And I said this is really the heart and soul of The Toyota Way. And you can get this but only by going back to school, but not school where you listen to lectures but school where you have to do something, and then you're getting coached by someone who knows what they're doing, who knows how to be a coach.

TROND: So my question following this, I think, will be interesting to you, or hopefully, because we've sort of gone through our conversation a little bit this way without jumping to the next step too quickly. Because the last question that I really have for you is, what are the implications of all of this? You have studied, you know, Toyota over years and then teaching academically, and in industry, you've taught these lessons. But what are the implications for the future development of, I guess, management practice in organizations, in manufacturing?

Given all that you just said and what you've previously iterated about Toyota's ideas that not a lot of things change or necessarily have to change, how then should leaders go about thinking about the future? And I'm going to put in a couple of more things there into the future. I mean, even just the role of digital, the role of technology, the role of automation, all of these things, that it's not like they are the future, but they are, I guess, they are things that have started to change.

And there are expectations that might have been brought into the company that these are new, very, very efficient improvement tools. But given everything that you just said about katas and the importance of practicing, how do you think and how do you teach preparing for the future of manufacturing?

JEFFREY: And I have been working with a variety of companies that have developed what you might call industry 4.0 technologies, digital technologies, and I teach classes where a lot of the students are executives from companies where in some cases, they have a dual role of lean plus digitalization. So they're right at the center of these two things.

And what I learned going back to my undergraduate industrial engineering days and then to my journey with Toyota, I was always interested in the centrality of people, whatever the tools are. And what I was seeing as an undergraduate was that most of the professors who were industrial engineers really didn't have much of a concept of people. They were just looking at techniques for improving efficiency as if the techniques had the power themselves.

And what I discovered with people in IT, and software development, and the digital movement is often they don't seem to have a conception of people. And people from their point of view are basically bad robots [laughs] that don't do what they're supposed to do repeatedly. So the ultimate view of some of the technologists who are interested in industry 4.0 is to eliminate the people as much as possible and eliminate human judgment by, for example, putting it into artificial intelligence and having the decisions made by computers.

I'm totally convinced from lots of different experiences with lots of different companies that the AI is extremely powerful and it's a breakthrough, but it's very weak compared to the human brain. And what the AI can do is to make some routine decisions, which frees up the person to deal with the bigger problems that aren't routine and can also provide useful data and even some insight that can help the person in improving the process.

So I still see people as the ultimate customer for the insights that come out of this digital stuff, Internet of Things, and all that. But in some cases, they can control a machine tool and make an automatic adjustment without any human intervention, but then the machine breaks down. And then the human has to come in and solve the problem.

So if you're thinking about digitalization as tools to...and sometimes have a closed loop control system without the person involved. But in addition, maybe, more importantly, to provide useful data to the human, suddenly, you have to think about the human and what makes us tick and what we respond to. And for example, it's very clear that we're much better at taking in visual information than text information. And that's one of the things that is part of the Toyota Production System is visual management.

So how can you make the results of what the AI system come up with very clear and simple, and visual so people can respond quickly to the problem? And most of these systems are really not very good. The human user interface is not well designed because they're not starting with the person. And the other thing is that there are physical processes. Sometimes I kind of make a sarcastic remark, like, by the way, the Internet of Things actually includes things.

TROND: [laughs]

JEFFREY: And there's a different skill set for designing machines and making machines work and repairing machines than there is for designing software. There are a lot of physical things that have to go on in a factory, changing over equipment, be it for making different parts. And the vision of the technologists might be we’ll automate all that, which may be true. Maybe 30 years from now, most of what I say about people will be irrelevant in a factory. I doubt it. But maybe it's 100 years from now, but it's going to be a long time.

And there was an interesting study, for example, that looked at the use of robots. And they looked at across the world jobs that could be done by a human or could be done by a robot. And they found that of all the jobs that could be done by a human or a robot, 3% were done by robots, 97%...so this kind of vision of the robots driven by artificial intelligence doing the work of people is really science fiction. It's mostly fiction at this point. At some point, it might become real, but it's got a long way to go.

So we still need to understand how to motivate, develop people. But particularly, the more complex the information becomes and the more information available, the more important it is to train people first of all in problem-solving and scientific thinking to use the data effectively and also to simplify the data because we're actually not very good at using a lot of data. We actually can't handle a lot of bits of data at a time like a computer can. So we need simple inputs that then allow us to use our creativity to solve the problem.

And most of the companies are not doing that very well. They're offering what they call digital solutions, and I hate that term, on the assumption that somehow the digital technology is the solution. And really, what the digital technology is is just information that can be an input to humans coming up with solutions that fit their situation at that time, not generic solutions.

TROND: It's fascinating that you started out with people. You went through all these experiences, and you are directly involved with digital developments. But you're still sticking to the people. We'll see how long that lasts. I think people, from the people I have interviewed, maybe self-selected here on the podcast, people and processes seem enormously important still in manufacturing.

Thank you for your perspective. It's been a very rich discussion. And I hope I can bring you back. And like you said if in X number of years people are somehow less important...well, I'm sure their role will change, will adjust. But you're suspecting that no matter what kind of technology we get, there will be some role, or there should be some role for people because you think the judgment even that comes into play is going to be crucial. Is that what I'm --

JEFFREY: There's one more thing I want to add. If you look at industry 4.0, it'll list these are the elements of industry 4.0, and they're all digital technologies. But there's something that's becoming increasingly popular called industry 5.0, where they're asking what's beyond industry 4.0? Which has barely been implemented. But why not look beyond it? Because we've talked about it enough that it must be real.

Once we kind of talk about something enough, we kind of lose interest in it. We want to go on to the next thing. So none of these things necessarily have been implemented very well and very broadly. But anyway, so industry 5.0 is about putting people back in the center. So I call it a rework loop. Uh-oh, we missed that the first time. Let's add it back in.

TROND: So then what's going to happen if that concludes? Are we going to then go back to some new version of industry 4.0, or will it --

JEFFREY: Well, industry 4.0 is largely a bunch of companies selling stuff and then a bunch of conferences. If you go and actually visit factories, they're still making things in the same way they've always made them. And then there's a monitor that has information on a screen. And the IT person will show you that monitor, and the person on the floor may not even know what it is. But there's a disconnect between a lot of these technologies and what's actually happening on the shop floor to make stuff.

And when they do have a success, they'll show you that success. You know, there's like hundreds of processes in the factory. And they'll show you the three that have industry 4.0 solutions in there. And so it's a long way before we start to see these technologies broadly, not only adopted but used effectively in a powerful way. And I think as that happens, we will notice that the companies that do the best with them have highly developed people.

TROND: Fantastic. That's a good ending there. I thank you so much. I believe you've made a difference here, arguing for the continued and continuing role of people. And thank you so much for these reflections.

JEFFREY: Welcome. Thank you. My pleasure.

TROND: You have just listened to another episode of the Augmented Podcast with host Trond Arne Undheim. The topic was the People Side of Lean. Our guest was Jeffrey Liker, academic, consultant, and best-selling author of The Toyota Way. In this conversation, we talked about how to develop internal organizational capability.

My takeaway is that Lean is about motivating people to succeed in an industrial organization more than it is about a bundle of techniques to avoid waste on a factory production line. The goal is to have workers always asking themselves if there is a better way.

Thanks for listening. If you liked the show, subscribe at augmentedpodcast.co or in your preferred podcast player, and rate us with five stars. If you liked this episode, you might also like Episode 84 on The Evolution of Lean. Hopefully, you will find something awesome in these or in other episodes. And if you do, let us know by messaging us, and we would love to share your thoughts with other listeners.

The Augmented Podcast is created in association with Tulip, the frontline operation platform that connects people, machines, devices, and 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, and you can find Tulip at tulip.co.

Please share this show with colleagues who care about where industry and especially where industrial tech is heading. To find us on social media is easy; we are Augmented Pod on LinkedIn and Twitter and Augmented Podcast on Facebook and YouTube.

Augmented — industrial conversations that matter. See you next time.

Special Guest: Jeffrey Liker.

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 and 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, and presented by Tulip, the frontline operations platform.

Trond's takeaway: Lean might be an ever-evolving concept centered around how to best improve industrial performance. The orthodoxy around what it means is not helpful yet clarity about clear objectives and tactics is important. The role of technology in Lean is controversial. But one thing is for certain, Lean is primary to technology.

Thanks for listening. If you liked the show, subscribe at Augmented podcast.co or in your preferred podcast player and rate us with five stars. If you liked this episode, you might also like Episode #21: Lean Manufacturing in the USA with guest Karl Wadensten, who is the CEO of VIBCO. Hopefully, you'll find something awesome in these or other episodes. If you like what you hear, let us know by messaging us, we would love to share your thoughts with other listeners.

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. Please share this show with colleagues who care about where industrial tech is heading.

To find us on social media is easy, we are Augmented Pod on LinkedIn and Twitter, and Augmented Podcast on Facebook and YouTube:

LinkedIn: https://www.linkedin.com/company/augmentedpod
Facebook: https://www.facebook.com/AugmentedPodcast/
Twitter: https://twitter.com/AugmentedPod
YouTube: https://www.youtube.com/channel/UC5Y1gz66LxYvjJAMnN_f6PQ

See you next time. Augmented--industrial conversations that matter.

Special Guest: Torbjørn Netland.

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 and 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), and presented by Tulip, the frontline operations platform.

Trond's takeaway: Life sciences are challenging: the traditional paradigm of industrial techniques. Bio-manufacturing in particular poses challenges to many existing systems. As such, the industry's work with ISP's pharma 4.0 initiative is bearing fruit. However, the dialogue with regulatory authorities still seems to be one the industry is trying to educate governments on. Nevertheless, once governments get it and are willing to adapt regulations, we might see even more rapid advances given the importance and scope of the new manufacturing techniques that are opening up and await regulatory approval.

Thanks for listening. If you liked the show, subscribe at Augmented podcast.co or in your preferred podcast app and rate us with five stars. If you liked this episode, you might also like episode 31 Pharma 4.0 with Michelle Vuolo, who is a quality practice leader.

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. Please share this show with colleagues who care about where industrial tech is heading.

To find us on social media is easy, we are Augmented Pod on LinkedIn and Twitter, and Augmented Podcast on Facebook and YouTube:

LinkedIn: https://www.linkedin.com/company/augmentedpod
Facebook: https://www.facebook.com/AugmentedPodcast/
Twitter: https://twitter.com/AugmentedPod
YouTube: https://www.youtube.com/channel/UC5Y1gz66LxYvjJAMnN_f6PQ

See you next time. Augmented--industrial conversations that matter.

Special Guest: Dr. Gilad Langer.

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), and presented by Tulip, the frontline operations platform (@tulipinterfaces).

Trond's takeaway: Business process intelligence is the "why" of technology. Because smoother operations are where the value of technology is realized. The future outlook for low code in industrial operations is bright because it has the potential to streamline workflows in manufacturing and logistics. However, it is important to keep in mind that to leverage automation to do better decisions, and not just to squeeze out more with less--that starts with keeping in mind what the real problem is and steering with that in mind. If you don't know, figure out the problem and then invest in the process and if technology gets you there, invest.

Thanks for listening. If you liked the show, subscribe at Augmented podcast.co or in your preferred podcast player and rate us with five stars. And if you liked this episode, you might also like episode 73 The Challenge of Front Line Operations. Hopefully, you'll find something awesome in these or in other episodes.

And if so, do let us know by messaging us because we would love to share your thoughts with other listeners. 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. Please share this show with colleagues who care about where industrial tech is heading.

To find us on social media is easy, we are Augmented Pod on LinkedIn and Twitter, and Augmented Podcast on Facebook and YouTube:

LinkedIn: https://www.linkedin.com/company/augmentedpod
Facebook: https://www.facebook.com/AugmentedPodcast/
Twitter: https://twitter.com/AugmentedPod
YouTube: https://www.youtube.com/channel/UC5Y1gz66LxYvjJAMnN_f6PQ

See you next time. Augmented--industrial conversations that matter.

Special Guest: Prabhjot Singh.

In this conversation, they talk about the operational aspects of industrial manufacturer DMG Mori's pathbreaking digital transformation.

[Please note that this episode was recorded in November of 2021.]

Trond's takeaway: Deep industrial transformation is not just a digital challenge but requires a fundamentally different operational mindset, beyond Lean Management, one that more fully embraces the potential of the human, industrial frontline worker. That shift is a journey, not a switch. On the other hand, the impact over time, measured in months not in years, is not only an immense return on investment but also a transition from dirty, dangerous and dull jobs to ever cleaner, safer and more exciting jobs.

Thanks for listening. If you liked the show, subscribe at Augmentedpodcast.co or in your preferred podcast player, and rate us with five stars. If you liked this episode, you might also like episode 20, The Digitalization of Körber, episode 23, Digital Manufacturing in the Cloud, or episode 27, Industry 4.0 Tools. Hopefully, you'll find something awesome in these or other episodes. If so, do let us know by messaging us, we would love to share your thoughts with other listeners.

The Augmented podcast is created in association with Tulip (@tulipinterfaces), 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.

Please share this show with colleagues who care about where industry and especially industrial tech is heading. To find us on social media is easy, we are Augmented Pod on LinkedIn and Twitter, and Augmented Podcast on Facebook and YouTube:

LinkedIn: https://www.linkedin.com/company/augmentedpod
Facebook: https://www.facebook.com/AugmentedPodcast/
Twitter: https://twitter.com/AugmentedPod
YouTube: https://www.youtube.com/channel/UC5Y1gz66LxYvjJAMnN_f6PQ

Augmented--industrial conversations that matter. See you next time.

Special Guest: Marius Schmiedt.

In this conversation, we talk about the following: What is frontline operations? What are the specific needs industrial companies have when they want to digitize their operations? What are some key Tulip use cases? What will industrial operations look like over the next decade?

Trond's takeaway: Frontline operations is an increasingly crucial business function whereby a function that previously was considered back office or lower priority, that of the industrial worker, receives increased attention. When the frontline gets digitally augmented and managerially supported, workers feel empowered just like white collar knowledge workers with desks. Connecting machines to serve people, simplifying technology implementation, operators can carry the key task of uniting industrial production with consumption needs. Over time, this might eradicate inefficiencies in the supply chain. This development will not only shape industrial operations over the next decade, in some companies, it is already in place.

Thanks for listening. If you liked the show, subscribe at Augmentedpodcast.co or in your preferred podcast player, and rate us with five stars. If you liked this episode, you might also like episode 50, The Last Mile of Productivity, episode 49, Lean manufacturing in the USA, and episode 41, Scaling Software Movements. Hopefully, you'll find something awesome in these or other episodes. If so, do let us know by messaging us, we would love to share your thoughts with other listeners.

The Augmented podcast is created in association with Tulip, 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.

Please share this show with colleagues who care about where industry and especially industrial tech is heading. To find us on social media is easy, we are Augmented Pod on LinkedIn and Twitter, and Augmented Podcast on Facebook and YouTube:

LinkedIn: https://www.linkedin.com/company/augmentedpod
Facebook: https://www.facebook.com/AugmentedPodcast/
Twitter: https://twitter.com/AugmentedPod
YouTube: https://www.youtube.com/channel/UC5Y1gz66LxYvjJAMnN_f6PQ

Augmented--industrial conversations that matter. See you next time.

Special Guest: Jason Dietrich.

Please share this show with colleagues who care about where industry and especially industrial tech is heading. To find us on social media is easy, we are Augmented Pod on LinkedIn and Twitter, and Augmented Podcast on Facebook and YouTube:

• LinkedIn: https://www.linkedin.com/company/augmentedpod
• Facebook: https://www.facebook.com/AugmentedPodcast/
• Twitter: https://twitter.com/AugmentedPod
• YouTube: https://www.youtube.com/channel/UC5Y1gz66LxYvjJAMnN_f6PQ

Augmented--industrial conversations that matter. See you next time. 

Special Guest: Andy Burton.

Trond's takeaway: So much of what determines success with the rollout of technology in manufacturing has to do with simplification. You aim to simplify, you make the process simple, and you choose simple apps to start with. The end result is a simpler work process which makes you more efficient. If any of those steps are complex, you risk adding further complexity to an already messy reality of complicated supply chains, work processes, and workforce challenges. That's why customization of industry 4.0 approaches heavily depends on people who lead with clarity.

Thanks for listening. If you liked the show, subscribe at Augmentedpodcast.co or in your preferred podcast player, and rate us with five stars. If you liked this episode, you might also like episode 36, Digital Lean, episode 29, The Automated Microfactory or episode 8, Productizing Quality. Hopefully, you'll find something awesome in these or other episodes. If so, do let us know by messaging us, we would love to share your thoughts with other listeners. 

The Augmented podcast is created in association with Tulip, connected frontline operations platform that connects the people, machines, devices, and the systems used in a production or logistics process i n 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. 

Please share this show with colleagues who care about where industry and especially industrial tech is heading. To find us on social media is easy, we are Augmented Pod on LinkedIn and Twitter, and Augmented Podcast on Facebook and YouTube:

• LinkedIn: https://www.linkedin.com/company/augmentedpod
• Facebook: https://www.facebook.com/AugmentedPodcast/
• Twitter: https://twitter.com/AugmentedPod
• YouTube: https://www.youtube.com/channel/UC5Y1gz66LxYvjJAMnN_f6PQ

See you next time. 

Special Guest: Dan Ron.

In this conversation, we talk about how to create a company culture that fosters lean manufacturing practices, becoming a learning organization, and how to be an industry leader who always inspires your employees.

Augmented is a podcast for industry leaders and operators, hosted by futurist Trond Arne Undheim (@trondau), presented by Tulip.co (@tulipinterfaces), the frontline operations platform, and associated with MFG.works, the industrial upskilling community launched at the World Economic Forum. Each episode dives deep into a contemporary topic of concern across the industry and airs at 9 am US Eastern Time every Wednesday. Augmented--the industry 4.0 podcast--industrial conversations that matter.

After listening to this episode, check out:

• Karl Wadensten: https://www.linkedin.com/in/karlwadensten/ 
• Vibco: http://www.vibco.com/

Trond's takeaway: Lean manufacturing is not just a process you can implement for efficiency, it is a culture you need to build for impact on the whole organization and the people in it. Quality follows from inspired, encouraged, and empowered workers who act on ideas and provide exceptional customer experiences.

Thanks for listening. If you liked the show, subscribe at Augmentedpodcast.co or in your preferred podcast player, and rate us with five stars. If you liked this episode, you might also like episode #43, Digitized Supply Chain, episode #3, Reimagine Training, or episode #2, How to Train Augmented Workers.

 Augmented--industrial conversations that matter.

Special Guest: Karl Wadensten.

In episode 45 of the podcast (@AugmentedPod), the topic is: The Startup Studio for Manufacturing. Our guest is Renan Devillieres, CEO at OSS Ventures, who is based in Paris, France.

In this conversation, we talk about co-creating the software bricks manufacturers need to achieve autonomy, using a venture building strategy. We discuss exciting European digital manufacturing startups, how the Tesla way might be as influential as the Toyota production system, and much more. 

Augmented is a podcast for industry leaders and operators, hosted by futurist Trond Arne Undheim (@trondau), presented by Tulip.co, the frontline operations platform, and associated with MFG.works, the industrial upskilling community launched at the World Economic Forum. Each episode dives deep into a contemporary topic of concern across the industry and airs at 9 am US Eastern Time every Wednesday. Augmented--the industry 4.0 podcast--industrial conversations that matter.

After listening to this episode, check out:

• Renan Devillieres: https://www.linkedin.com/in/renan-devillieres-9349151b5/
• OSS Ventures: https://www.oss.ventures/

Trond's takeaway: Digital manufacturing is coming of age, both in the US and Europe and collaboration between corporations and startups has never been more intense. By combining the best of both worlds, industrial tech will make leaps forward, but the emerging system is still fragile.

Thanks for listening. If you liked the show, subscribe at Augmentedpodcast.co or in your preferred podcast player, and rate us with five stars. If you liked this episode, you might also like episode #40, Israel meets New England on Industry 4.0, episode #18, Transforming Foundational Industries, or episode #5, Plug-and-play Industrial Tech. 

Augmented--industrial conversations that matter.

Special Guest: Renan Devillieres.

In episode 47 of the podcast (@AugmentedPod), the topic is: Industrial Machine Learning. Our guest is Roy Shilkrot, Lead Scientist, Tulip (@tulipinterfaces).

In this conversation, we talk about Machine Learning in Manufacturing. Emerging applications using Tulip and beyond, we discuss emerging use cases, the impact of a future with MES ML, that is, machine learning built into the manufacturing execution system.

Augmented is a podcast for industry leaders and operators, hosted by futurist Trond Arne Undheim (@trondau), presented by Tulip.co, the frontline operations platform, and associated with MFG.works, the industrial upskilling community launched at the World Economic Forum. Each episode dives deep into a contemporary topic of concern across the industry and airs at 9 am US Eastern Time every Wednesday. Augmented--the industry 4.0 podcast--industrial conversations that matter.

After listening to this episode, check out:

• Tulip: https://tulip.co/
• Roy Shilkrot: https://www.linkedin.com/in/royshilkrot/

**Trond's takeaway**: Industrial tech is not what it used to be and will never again be a bulky, legacy, inflexible instrument. Rather, we are entering an age with immediate feedback, rapid adjustments and a combination of human and machine monitoring.

Thanks for listening. If you liked the show, subscribe at Augmentedpodcast.co or in your preferred podcast player, and rate us with five stars. If you liked this episode, you might also like episode 29, The Automated Microfactory, episode 22, Freedman's Factory: What is nocode?, or episode 19, Machine Learning in Manufacturing. 

Augmented--industrial conversations that matter.

Special Guest: Roy Shilkrot.

In episode 36 of the podcast (@AugmentedPod), the topic is: Digital Lean. Our guest is Edward Atkins, Head of Customer Success, Tulip (@tulipinterfaces).

In this conversation, we talk about achieving customer success with classic Lean Operations and beyond. We explore performance transparency, how operators can produce parts tracking procedures digitally, creating quality gates through inspection applications and being conscious about quality measurement. What am I making? At what quality? We also go into more complex things like work material flow, Kanban loops and taking inventory and how no-code is an exponential uplift since you no longer are burdened by logging and can collect as much information as you want.

After listening to this episode, check out Tulip's and Edward Atkins' profile on social media:

• Tulip (@tulipinterfaces): Tulip.co. 
• Edward Atkins: https://www.linkedin.com/in/edward-atkins-77022213/ 

Augmented is a podcast for industry leaders and operators, hosted by futurist Trond Arne Undheim, presented by Tulip.co, the frontline operations platform, and associated with MFG.works, the industrial upskilling community launched at the World Economic Forum. Each episode dives deep into a contemporary topic of concern across the industry and airs at 9 am US Eastern Time every Wednesday. Augmented--the industry 4.0 podcast--industrial conversations that matter.

**Trond's takeaway**: Implementing digital lean on a client site especially enabling improvements to be done near 100 percent by the clients themselves is now possible with the leading frontline operations software and is game changing for industrial performance. 

Thanks for listening. If you liked the show, subscribe at Augmentedpodcast.co or in your preferred podcast player, and rate us with five stars. If you liked this episode, you might also like episode **22, Freedman's Factory: What is nocode?, episode 24, Emerging Interfaces for Human Augmentation, and episode 14, Bottom up and Deep Digitization of Operations. 

Augmented--upskilling the workforce for industry 4.0 frontline operations.

Augmented reveals the stories behind the new era of industrial operations, where technology will restore the agility of frontline workers. 

In episode 36 of the podcast , the topic is: Digital Lean. Our guest is Edward Atkins, Head of Customer Success, Tulip

In this conversation, we talk about achieving customer success with classic Lean Operations and beyond. We explore performance transparency, how operators can produce parts tracking procedures digitally, creating quality gates through inspection applications and being conscious about quality measurement. What am I making? At what quality? We also go into more complex things like work material flow, Kanban loops and taking inventory and how no-code is an exponential uplift since you no longer are burdened by logging and can collect as much information as you want.

After listening to this episode, check out Tulip's and Edward Atkins' profile on social media:

• Tulip (@tulipinterfaces): Tulip.co 
• Edward Atkins: https://www.linkedin.com/in/edward-atkins-77022213/ 

Augmented is a podcast for industry leaders and operators, hosted by futurist Trond Arne Undheim, presented by Tulip.co, the frontline operations platform, and associated with MFG.works, the industrial upskilling community launched at the World Economic Forum. Each episode dives deep into a contemporary topic of concern across the industry and airs at 9 am US Eastern Time every Wednesday. Augmented--the industry 4.0 podcast--industrial conversations that matter.

**Trond's takeaway**: Implementing digital lean on a client site especially enabling improvements to be done near 100 percent by the clients themselves is now possible with the leading frontline operations software and is game changing for industrial performance. 

Thanks for listening. If you liked the show, subscribe at Augmentedpodcast.co or in your preferred podcast player, and rate us with five stars. If you liked this episode, you might also like episode **22, Freedman's Factory: What is nocode?, episode 24, Emerging Interfaces for Human Augmentation, and episode 14, Bottom up and Deep Digitization of Operations. 

Augmented--upskilling the workforce for industry 4.0 frontline operations.

Special Guest: Eddy Atkins.