Episode 105

Product Lifecycle Management's Momentum in Manufacturing with Jim Heppelmann


December 7th, 2022

46 mins 31 secs

Season 3

Your Host
Special Guest

About this Episode

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

In this episode of the podcast, the topic is "Product Lifecycle Management's Momentum in Manufacturing." Our guest is Jim Heppelmann, CEO of PTC. In this conversation, we talk about the why and the how of product lifecycle management's momentum in manufacturing.

If you like this show, subscribe at augmentedpodcast.co. If you like this episode, you might also like Episode 93: Industry 4.0 Tools.

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 momentum is clear, and one indication is the trend that PLM is being elevated to an enterprise system. But why is PLM such a hot market right now? One key word is greenhouse gas reduction because companies need a system of record to track their emissions, and this is not easy to do without a system in place.


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 Product Lifecycle Management's Momentum in Manufacturing. Our guest is Jim Heppelmann, CEO of PTC. In this conversation, we talk about the why and the how of product lifecycle management's momentum in manufacturing.

Augmented serves an audience of executives, industry leaders, investors, founders, educators, technologists, academics, process engineers, and shop floor operators across the emerging field of frontline operation. And it's hosted by futurist Trond Arne Undheim and presented by Tulip.

Jim, welcome to the show. How are you?

JIM: I'm great, Trond. Great to be with you here this morning.

TROND: Yeah, Jim. I thought we would talk a little bit about industrial automation and some specifics. But first of all, I wanted to talk a little bit about you. You grew up in Minnesota, got yourself a mechanical engineering degree, and became an entrepreneur, and sold your company to PTC. You were the CTO, I guess, for a while and now the CEO. It's been quite a journey.

JIM: Yeah, it's fun. And by the way, industrial automation and related topics is my favorite topic. I was born on a dairy farm in Southeastern Minnesota, part of a very large family. It was a tough life. We never quite had enough money. So I was ambitious. I wanted to do something. I wanted to have a better life than I grew up with, not that it was bad, but maybe I wanted to have a little bit more economic security.

I decided to become an engineer because I had spent a lot of time with equipment, machines, using them but also fixing them, taking them apart, putting them back together. I was good at math and science. So I went into mechanical engineering, but right away, I was drawn to software. And so I really got a major in mechanical engineering, a minor in computer science, and focused on how do you use computer science to do engineering? That led me to join a computer-aided design company, a CAD company.

As an intern, I was assigned to a new idea they had which they called product data management. It was not very glamorous compared to the graphics of CAD, where you could twirl models around on the screen and so forth. So it's the kind of thing that you assigned to a new intern. As an intern, I took to it; I mean, it made a lot of sense to me. So basically, that's what I specialized in in my career, especially the early part of my career.

And I became quite an expert at PLM, or at the time; it was called PDM. That led me, ultimately, when I was exposed to the internet, to say, "Wow, if you really leverage web technology with a light client, a web browser, make it easy for people to engage no matter what company they're in, then you could have whole supply chains working together in a very efficient way.

So that led me to create a company called Windchill Technology, kind of a funny name based on a company in Minnesota; that's where the Windchill part comes from. But PTC came to acquire this company, and the business just really took off at PTC. In the ensuing years, I became the Chief Technology Officer across all of PTC, and then, as you said, that led to becoming the Chief Executive Officer a dozen years ago.

It's been a great ride. It's been a lot of fun. We've accomplished a lot. The technology has come so far. Hard to imagine in the early days, it would end up here. But it's been a very exciting career trajectory, for sure.

TROND: So, Jim, before we move into talking about product lifecycle management, I wanted to ask you a more generic question: what is the most challenging part of being a CEO? So you've gone from being an entrepreneur to being a CEO of a much larger structure here. What's exciting, and what's challenging about that?

JIM: Yeah, I mean, I think what is exciting is also challenging, which is so much context-switching. In a single day, I go from worrying about budgets and financial plans to meeting with happy customers, sometimes frustrated customers to meeting with sales teams and R&D teams and R&D projects. And it's just a constant switch from one topic to another, which is exciting because they're all topics I like.

But it puts a lot of pressure on you to very quickly remember where you left this conversation off last time you were involved and how to dive right back in and pick it up. And I think there's some pressure that comes from that, you know, to be on your toes ready to go and just switch from topic to topic to topic. And then, of course, there's the pressure of a public company that every 90 days, we have an earnings call. And our investors want to hear good news. Fortunately, we've had a lot of good news, but there's always a lot of pressure to make sure you keep it going.

TROND: I wanted to jump then to product lifecycle management which is a specialty topic to you; it's not, right? Because you've been involved with this for a while, [laughs] and it's a passion for you. I guess in industrial automation; there are a lot of three-letter acronyms and such. But if you'd give your best way to explain how this software got started, what was the original intention? I mean, this is a while back now. We're talking 1998 when this software suite got created when Windchill started creating this software. What did it do then, and what does it do now?

JIM: Well, PLM is really the system of record for product data. So if you think of salesforce.com, they got started just a couple of years later. They're a system of record for customer information, the 360-degree view of the customer. And in most companies, they have an ERP system, and that's the system of record for the financial data, all the purchase orders, and invoices, and whatnot, and might have a human resource information system, something like Workday, that's the system of record for all your employees.

But if you're an industrial company that makes products, you have a lot of product data. And where is the system you can go to to find and interact with that data in your day-to-day job as part of that product development, or manufacturing, or customer support process? And so PLM really has become that system of record. And for an industrial company that makes products, it's a pretty important system of record. Like a CRM system or an ERP system, you're not just collecting and managing the data; you're also transacting against it, applying change orders, and building configurations of it, and whatnot. So PLM has become recognized in industrial companies as a critical anchor system of record. That's the way I like to think about it.

TROND: Yeah, and we'll get into some of it after a while. But I guess product lifecycle is something that has gone much higher on the agenda for environmental reasons and others. So, I guess, if you think about a product from its ideation and to its disposal, essentially, it's a long chain of events that such a system, theoretically, could help a company with.

JIM: Yeah, for sure. And just to go a little deeper in that, a lot of products are made of mechanical parts, electronic parts, software parts. They come in lots of different configurations. They change from year to year and sometimes month to month, so there are a lot of engineers and product managers involved. And then purchasing gets involved, and supply chain management gets involved because very few companies build everything themselves; they work with a supply chain.

Then you're bringing in the factory and production planners, and then ultimately, the production process. They need this data, and they need the right configurations and versions of it. Then you ship the product to the customer, and you provide, in many cases, service and support. And you can't do that well without understanding the configuration of the product and all the versions of mechanical electronics and software parts in it.

Really what we're talking about is, yeah, following that product throughout its lifecycle. Sometimes I like to use a golf analogy, like the front nine and the back nine on an 18-hole course. The front nine is everything that leads up to the product being manufactured, and the back nine is everything that happens thereafter. And to really do product lifecycle management, you have to think of all 18 holes, and that's kind of the focus we've had here at PTC.

TROND: To what extent is product development kind of a management discipline, and to what extent do you feel like it's a technical discipline? And clearly, the software here is enabling digital records, I guess and tracking a product process. But product development historically it's not among those areas of management that have received the most attention, I guess, arguably. So how do you see this relationship?

JIM: I think it's become more and more of a management methodology over time because you start with innovation. You can't legislate innovation. That sort of just happens naturally, organically, if you will. But every single product has a plan. It has a cost target. It has a launch date target, you know, a time-to-market target if you will. It has a quality target. More and more, it might have regulatory accomplishments or protocols it has to comply with.

So I think that what companies are trying to do is unleash innovation but in a managed process. A lot of companies historically have used management techniques like waterfall management or stage gate. More and more companies are intrigued now about could we use agile, you know, scrum management methodologies to develop hardware like we develop software? Because it really works well for software. Now, hardware is not software, so there are some special concerns there. But definitely, there's a management methodology, and I think PLM really is critical to doing that management methodology well.

You can't manage a process if you don't have access to the right information. You can't even have a dashboard if you don't have the right information. But more important than the dashboard, the people participating in the process can't be expected to do the right things if they're not given the right information to work against. And that's really why PLM is so critical to managing the whole cost, quality, time to market, regulatory, and similar concerns.

TROND: So why, then, is PLM such a hot commodity right now? Because I guess that's what you're arguing, that it's becoming more and more crucial. What are the inflection points since 1998? And what is it now that makes it such a crucial system?

JIM: Yeah, well, I think a lot of industrial companies are really leaning into digital transformation initiatives, a huge amount of spending. And it's because they see themselves potentially being disrupted or losing competitive advantage, at a minimum, if they're not sufficiently digital. And so when they lean into digital transformation, they quickly realize how much could we possibly transform a product company if we're not even managing our digital product data? So PLM quickly becomes a must-have these days in a digital transformation initiative.

And then, of course, COVID has been a huge catalyst because it was hard to share information when everybody came to work every day. But if, on any given day, 40%, 50%, 60% of your employees are working from home, how do you interact with them? You can't walk down the hall and knock on their door anymore because they're not there, and if they're there, you're not there. I think what's happened as a consequence of COVID and the hybrid workforce that we're probably now left with forever; I think PLM is just absolutely critical must-have. So we've gone from nice-to-have and engineering tool to must-have enterprise tool.

TROND: Let's talk about the hybrid workforce for a second. I mean, well, there were two massive predictions, one, this will never happen in industrial companies because we're actually talking about factories, and you can't be away from the factory. And then, of course, there were the future of work people saying, "This should have happened a long time ago. There's no need for any people, and factories are, you know, 24/7. There's technology. You don't really need to come in there." You've said some of these changes, you know, we're stuck with them forever. What does the hybrid workforce mean in an industrial organization like your own, for example, or your largest clients?

JIM: I think if you look at a manufacturing company who has factories and such, you could separate their workforce into knowledge workers; these are people who are paid to think. And frontline workers are people who are basically paid to show up and use their hands, and feet, and so forth. And I think that frontline workers have to be there, and in most manufacturing companies, they are. And they very carefully protected these workers right through COVID because if those workers don't come to work, the factory doesn't run; there are no products.

But the knowledge workers, the engineers, the finance people, the procurement people, supply chain, the planners, the service and support people, they really work on a computer all day. And whether that computer is in the office, or at home, on the dining room table doesn't matter that much in terms of their ability to get their job done so long as they have access to the right information and an ability to participate in the process digitally. So I think we're going to see...the forever state I envision here is hybrid on the knowledge worker side and in the factory on the frontline worker side, or sometimes at the customer side in the frontline worker side of the equation.

TROND: To what extent does a PLM system then actually help frontline workers? So is it more of an enterprise system that helps, I guess, the leadership?

JIM: It's an enterprise system. It is critical for the knowledge workers and informs the frontline workers. The knowledge workers need to participate in the process of creating and evolving this information over time. What's in this product we're going to launch, and how will that change? We have supply chain problems. We have to find a new supplier, okay, that's a change to the product. If we come up with new and better ideas or fix bugs, those are changes to the product. So the product information is changing. And there are a lot of people interacting with it online.

So PLM is the system that they interact with. And they might be in the office interacting with PLM. They might be at home. That's knowledge workers. For frontline workers, when they come to the factory, they're supposed to build something today. What am I supposed to build? And PLM supplies them the information: here's the product you're working on today; here's the configuration, the bill of material, and the work instructions to go build that product. So I'd say think of frontline workers as consumers of this information. And sometimes, they're given feedback because the process isn't sufficiently effective. But the knowledge workers are really the ones developing and evolving this information over time.

TROND: Give me some examples of how a PLM system is used by real customers; you know, what are the biggest use cases when you purchase such a system? And over time, what are the biggest value drivers of such a system in a real organization?

JIM: The main reason all companies buy PLM is cost, quality, time to market associated with the products. A team of engineers and product managers is going to specify an engineer, and simulate, and iterate, and they're going to come up with some product concepts. And they're going to be working with the purchasing department on who will we source these parts from. They might be working with contract manufacturers who are going to actually produce the product if we're not going to produce it ourselves.

If we're going to produce it ourselves, we have to work with the manufacturing engineers and then ultimately the factory. If this is a long-lived asset, we're going to have to figure out how would we service it? What kind of spare parts are we going to need? What kind of technical documentation and service work instructions would be required?

So there are many, many people who have to interact with this product information before that product ever comes to life. Again, if you want to do this quickly, you know cost, quality, time to market. Let's take time to market; if you want to do it quickly, you need everybody working on the right information simultaneously. If you want to have quality, you got to make sure nobody's working on the wrong information because that's the source of quality problems; somebody buys the wrong part or makes the part incorrectly, uses the wrong version of the drawing, or the model, or what have you. That's where quality problems come from.

And then on the cost, if you're trying to hit a cost target, you need to be way up front simulating if we built a product that looked like this and we bought all these parts from the suppliers, and we assembled it like this, what would it cost to do all that? All the decisions made during product development lock in cost. You don't spend so much cost, you know, so much money developing the product, but you make all the decisions that lock in cost later. If you design an expensive product, the factory is not going to make an inexpensive product; they're going to make an expensive product. People really need to collaborate.

But then there are some advanced topics. So cost, quality, time to market, everybody needs that. Some people need regulatory compliance. Some people want to drive greenhouse gas emissions reduction strategies. Some people want to do what I call platform strategies, where they reuse many modules in many different configurations to be efficient. And there's more, and we can probably get into that. But there's a series of more advanced strategies that really go more to the competitive advantage that a company is trying to develop.


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TROND: So, Jim, talk to me a little bit about the future outlook. So there are some very exciting prospects here for more ambitious uses of PLM software. If you are looking into the next, you know, two to five years, what are some of the more advanced use cases for this kind of software? What are customers trying to do? You've been talking a little bit about regulatory requirements and greenhouse gas emissions. What exactly does that use case look like?

JIM: Well, let's take regulatory first. Some products are launched into regulated markets; a good example would be medical devices. That whole product development process and use thereof is regulated by the FDA or similar agencies around the world. Or let's take aircraft; they're regulated by the FAA. Or let's take automobiles; they are regulated by a number of different standards related to safety. So, for example, there are standards around safety critical software to make sure that some supplier doesn't make a late change to the software they contributed to the automobile. And now, suddenly, your anti-lock brakes don't work anymore because they introduced a bug.

So in each case, medical device, automotive, aerospace, and there are others, what the regulators really want is traceability. They want to make sure that all of the changes that were introduced were planned and tested so that no errant change came in that produced some anomalous side effect that could kill people. And so, complying with the standards of the FDA, the FAA, or various automotive bodies is critical. And PLM is the system that gives certainty that those standards have been complied with.

PLM is tracking requirements, changes, test cases to prove we have test cases for all of the changes and all of the changes were driven by legitimate requirements. If you can prove all that, the regulators are going to say, "Great, go ahead and launch the product." So I'm oversimplifying it, perhaps, but that's sort of a way to think about the regulatory use case.

Let me pick a different one, though. Many of our customers have what they call platform strategies, and sometimes I refer to this as diversity with scale. So let me pick a great example of a PTC customer, Volvo, so if you know Volvo, they make trucks, but they also make construction equipment. And they make buses, and they make ship engines, boat engines.

And so across those very different products, they try to reuse the same engines, the same transmissions, the same telematics systems; why? Because if the truck guys develop truck engines and the bus guys develop bus engines, and the boat guys develop boat engines, we'd need a lot more engine factories, and then we'd need a lot more spare parts for all these engines that last decades.

So there's great inefficiency in unbridled innovation. So they actually want to control it a little bit and say, let's agree that the company will have a series of engines. And no matter what bus truck construction equipment or whatever you create, you should try to reuse these engines. What that means, though, is that the engine gets used in many different product configurations, many different buses, many different trucks, many different construction equipments. You get an explosion of configurations.

In fact, just for fun, Volvo says that their products come in 10 to the 84th power hypothetical configurations. Now, very few of those configurations will ever be built, but they could be built. And so, how do you manage that? Just for fun, Caterpillar was meeting with me about a week ago. They were telling us about some of their challenges. And they said that their products, Caterpillar products, come in infinity minus eight configurations. I laughed and said, "That's a funny joke." And they said, "It's not really a joke." I mean, it's not really infinity minus eight, but there are so many configurations.

Now, why is that important? Let's say you're trying to produce manufacturing instructions. You can't hand-author infinity minus eight manufacturing or service instructions. You're going to have to generate them from building blocks. So just like the products have building blocks, the information needs to be constructed in building blocks so that if you assemble a combination of building blocks to create a piece of construction equipment, you could then assemble the information building blocks to create the manufacturing instructions for that same piece of equipment and the service instructions as well.

So the configuration management of the product and all of the information building blocks has to be directly aligned and very, very sophisticated. If you change that engine, you're going to have rippling effects across many different product lines. And so I call this complexity management, sometimes diversity with scale. But how does a company get the ability to create many different products but reuse the same factory and service capabilities to the degree possible?

That's a big challenge for companies. But it's the difference between being competitive, high growth, high margin, and not being competitive. So it's a must-have in certain industries but very much an advanced topic. If you talk to a startup company, they would say, "I don't even understand what you're talking about." But these larger companies, it's absolutely critical to their financial wherewithal.

TROND: So I want to get to green- in a second, but before that, what do you say to people that would claim that industrial automation has taken a long time to get to this fairly advanced stage that you're describing here? I guess, you know, for example, from the perspective of an impatient, young software engineer who's looking at this space, they're saying, "Well, you guys, you're finally coming to cloud, you know, still have some on-premise."

And there are a lot of elements in this software. We talked about software that's been developed since 1998. There's quite some legacy, not just in your product but in every automation company's product. And certainly, your customers must have the legacy challenge as well. This is not a space where systems get changed out every six months. So tell me a little bit about that reality.

JIM: In tech, there's a saying that goes something like this, that many breakthroughs have less impact in the near term than you expected but more impact in the long term than you expected, internet being a perfect example. The first couple of years the internet, you know, it was kind of silly stuff and maybe just publishing papers and whatnot, and today it's the way the whole world exchanges information.

When I look back over my career, the technology has changed a tremendous amount. But when you look at how much is it changing this year, it looks like, well, not that much. But what happens is there are a lot of new concepts, like you mentioned, the cloud. But when I first worked on PLM, it was a mainframe application; then it became a client/server application, then it became a web application. And now it's a SaaS, a cloud application. These changes take time, but then they unleash whole new use cases, whole new value, and the products get better and better and, frankly, less and less expensive over time.

And then you get to that tipping point where it really makes sense. Maybe ERP got to that tipping point, I don't know, 15, 20 years ago, and CRM got to that tipping point 10 years ago. I think right now, PLM is at that tipping point where people really see the value, and the value proposition makes sense. What do I need to put in? What do I get back financially from an investment in PLM? That's starting to make a lot of sense to people. I used the phrase earlier we've gone from nice-to-have to must-have in the last couple of years, thanks in large part to digital transformation and then COVID.

TROND: You used agile and scrum earlier, but even beyond those techniques, there's a demand in the industry for software that can be very easily configured by non-specialists. So here we're talking about perhaps low-code software in and of itself, or at least that the user interfaces are easy to operate. And I guess you can understand that because the training challenge, for example, in manufacturing and, you know, you were referring to frontline workers. And while the training factor there is significant but also, conversely, on the knowledge worker side, to use your definition here and distinction between the two, even engineers have had to contend with a lot of new frameworks.

And they were not trained on the kind of software that you're talking about here. Many of them were industrial engineers and still actually don't receive an enormous amount of IT programming in their curriculum. There are so many other things to focus on. So what do you see there in terms of the low-code space or in terms of the interfaces? Is industrial automation also gradually simplifying? Or are we on this enormous train towards more complexity in all that chain?

JIM: Well, I think what's happening is the systems are becoming more sophisticated behind the curtain. But then we're providing different user communities with role-based views into that information. If you think about a product manager, an engineer, somebody in purchasing, somebody on the factory floor, somebody in the service bay, they all need product information, but their needs are quite different. And then when you go from one company to the next, they might be different again because the companies are different, the products are different.

So yeah, definitely low-code approaches...for example, we have a product called Navigate, which is kind of a low-code overlay onto the basic PLM system. A low-code approach that allows you to tailor what different user communities experience when they log in, I do think is very important because if I'm in purchasing, show me what a purchasing person needs to know and no more.

If I'm on the factory floor, I don't need to know what things cost; I just need to know what the work instructions are. So show me just a limited view that hides all the rest of that complexity. Certainly, there are some power users who need a lot more, but there are a lot of users who really need kind of almost looking at the information through a straw if you will. There's a fairly limited amount of information and functionality that's relevant to them. How can we serve that up to them in the simplest possible way? I do think that's critical. It needs to be tailorable in order to work well.

The introduction of low-code approaches into PLM has certainly helped with the broader adoption to go beyond the engineering department and really make it an enterprise system. It's been a critical enabler.

TROND: I want to benefit from some of your experience to think about, you know, what's going to happen next in the broader field of industrial automation? But perhaps you can kick it off with a little bit more detail on how you see the green challenge working out. Because clearly, more and more industries are starting to take the climate challenge or just even bits and pieces of it, like you were talking about earlier, the product lifecycle tracking of a product, worrying also more about the end state of their products. What are systems then having to adapt to?

JIM: Let me say; first, some companies see climate change and greenhouse gas reduction as an opportunity. And there are a lot of green tech companies launching, startup companies launching to produce next-generation products. On the other hand, there are a lot of larger companies that are under tremendous investor pressure to be more green. If you're a public company right now, you really have to be active on the environmental, social, governance (ESG) front.

You have to have a story, and it can't just be a story. There has to be some reality behind it. So what's happening now is companies are saying, "Okay, well, where does greenhouse gas come from? And, by the way, who really is a great producer of greenhouse gas?" And it turns out manufacturing companies actually have fairly substantial greenhouse gas footprints. The production of their products in their factories and the production of all the materials, you know, raw materials and whatnot, has a lot of energy use associated with it.

And then, some of these products go on to be used by the customers in a way that also consumes a lot of energy use. So manufacturing companies are saying, well, if I wanted to reduce greenhouse gas emissions, I really have to back up and think about the products I make and how could I make them with less greenhouse gas footprint. But how can I also design them so that when operated, they generate less greenhouse gas footprint? But all this stuff starts in engineering. People in factories don't get to make changes. They have to be specified by the engineering department.

So just like the engineering decisions lock in cost, frankly, they lock in greenhouse gas footprint. And the important thing is to bring awareness in analytics upstream so that when an engineer is thinking about how to innovate and solve a particular problem, they say, "Well, this approach would have a high greenhouse gas contribution, and this alternative approach would have a very low greenhouse gas approach. Let's go with this secondary approach for reasons of reducing our greenhouse gas footprint."

Again, if you really want to move the needle in a manufacturing company, you can't get far if you don't open the hood and look at the products, and the system you log in to do that is called PLM. And so PLM will be manufacturing companies' best friend as they think about over time how to consistently reduce their greenhouse gas footprint, and actually, track the progress they're making so that they can publish to their shareholders and whatnot the incremental progress in how well are they advancing toward their goals.

TROND: Well, Jim, what you're talking about now clearly is a big part of the future in the sense that this, you know, it sounds so simple when you're explaining it. But measuring that, obviously, is not something that software in and of itself can help a company in every part of it, right? I'm assuming this means a lot of rethinking inside of these industrial companies.

But if I want to benefit more from your broader view on the industry, what are some of the other things that you think in a longer time frame are happening in the industrial space? I mean, are we looking at more and more innovation from startups? Like, you came yourself from a startup. How do you see the startup innovation in this space versus sort of the giant...PTC now has become more of a giant, but obviously, like every company, you started out in a different position. What are some of the technologies that you're excited about that are going to really change this space as we move into the next decade?

JIM: Let's back up and talk a little bit more about cloud and SaaS because if you look at the PLM industry, it's very much an on-premise industry; you mentioned this earlier. If you look then at business software, in general, this is an important year because this year, more of the entire ecosystem of business software is delivered as a SaaS model than an on-premise model. This is the first year where there are more SaaS in total than on-premise, but within our little corner of the world called PLM, that's not true at all. We're very much an on-premise market.

But customers would have great benefit if we could deliver this to them via the cloud as a service rather than ship them software or let them download software to be more practical. We think, at PTC, this industry is going to the cloud. The automotive industry is going to electrification, and the PLM industry is going to SaaS. It's really that simple. Is it happening today right now? I don't know. I still drive a combustion-engine automobile. But I know at some point, I'm going to be driving an electric vehicle.

And, Trond, here in California, I mean, they just passed a law there that said by 2035, you can't even buy a combustion automobile. So I know you're going to be going to electric if you want to own a car. Again, I'm making an analogy. What's happening in the automotive industry as it relates to electrification is what's happening in the PLM industry as it relates to SaaS.

The industry is in transition. There will be winners and losers in this transition. PTC has tried to position itself to be a winner by being out front, paving the way, and bringing the industry along with us. So I think that's a pretty profound change that's coming, and it brings tremendous benefits, cost of ownership, simplification, real-time collaboration up and down a supply chain, and many others.

TROND: Do you have any advice to would-be entrepreneurs in the industrial space? It's interesting, at least to me, that, yes, we have Tesla now, and a few others, but kind of the poster child examples of startups is usually not an industrial company. Well, there are certainly many, many more of these success stories that seem to come out of the garage-type thing that is perhaps not hardware and certainly not industrial. What is your view of that?

JIM: My advice there is to focus on what's most important, and that is developing your innovation and getting it to market. I'm talking about innovations that involve physical products. But frequently, in the startup world, there are lots, and lots of electronics and software involved these days as well.

But we have several products, like our Onshape CAD product and Arena PLM products, that are pure SaaS. They have never existed in a shippable form and never will. They're extremely popular with startup companies because the startup company says, "I don't have time to hire IT people and set up software systems in my company. I'm trying to get this innovation to market. And I need things like CAD and PLM. I just don't need to own them. I need to use them."

And so products like Onshape and Arena really are popular with startup companies. And plus, in a very unique way, they enable agile product development. And again, when I say agile product development, I mean develop hardware like you develop software. You might remember I said historically; hardware has been developed with a stage gate or waterfall model. Software used to be that way, but software has gone to an agile...almost exclusively gone to agile product development scrum-type methodologies.

Could we bring those scrum methodologies back over to the hardware and develop hardware and software the same way? Yeah, that's very, very interesting to startup companies because it's all about speed. But it's pretty hard to do without SaaS because if you're going to all work on the same data and make new versions of the product every single day, well, then we need to have the data remain collected together. We can't have it distributed out on a whole bunch of desktop computers, or it just doesn't work.

So I think that startup companies need to focus on what's important, the SaaS model. And the ability of the SaaS model to enable an agile scrum approach is absolutely critical to these startup companies, the entrepreneurs that are driving them.

TROND: It's exciting your idea here of developing software, I mean, developing hardware at the speed, I guess, and with the methodology of software. Can you tell me more about what that actually would mean? What sort of differences are we talking about? I mean, for example, in terms of how quickly hardware would evolve or how well it would integrate with other systems.

JIM: Some of the most important principles of agile or scrum product development are daily builds, a highly iterative approach that's not too deterministic upfront. In a waterfall method, by contrast, the first thing you do is determine the customer requirements because that's what's going to guide your whole project.

In an agile world, you say, I'm not sure the customer even knows I'm inventing something new. The customer doesn't even know what I'm doing, but I'll need to show it to them. And they'll be able to react when I show it to them, but I want to show it to them every week or maybe even every day. I want to be able to interact either with the customer or with the product owner, which is a person who has been designated to represent the interest of the customer. And I want to every single day be able to show the progress you've made and test it.

The thing that really burns people in a traditional waterfall process is you're given a set of requirements. You develop a perfect solution. Six months later, you show the perfect solution to the customer, and they say, "That's not what I meant. I know I said that, and you're complying with the words. You're not complying with the intent because the words didn't quite accurately capture the intent." So in this waterfall process, you lose tremendous amounts of time, sometimes by going back and starting over.

In the agile project, you're showing them the digital models of the product every day, or perhaps every week, or even every month, if it makes more sense. But you're showing the customer your progress, and you're getting continuous feedback. And so you're evolving towards an ideal solution very, very quickly. Again, agile software developers have been doing this forever. But we haven't been doing it on the product side, the hardware side, because the tools really weren't set up for that.

When software engineers adopted agile, they adopted a different set of tools. As hardware engineers are adopting agile, they're also saying, "We would need a different set of tools. They'd have to be cloud-based, SaaS-based so that we were always working on the same data, and we always had the latest version of everybody's contribution right there at our fingertips," as opposed to, say, checked out on their laptop, and they're on vacation this week. So it's an interesting time in the industry. And I think there's a real breakthrough coming, which will be enabled by SaaS.

TROND: Is it frustrating sometimes that there's also, I mean, you've been talking now about the inspiration from the software side and innovation side perhaps over to the hardware side and more the industrial side. But isn't it frustrating sometimes that there is obviously a lot of history and experience on the industrial hardware side, and you have to teach new generations that some of these things are...they don't operate as quickly?

So, yes, we can bring some methodologies there, but there are some constants, I guess, around infrastructure and factories that are a little bit harder to change. So as much as we would want all of it to be developed at the speed of software, there are some additional complexities. How do you think about that as, you know, you're running an industrial automation company? There is some value on the other side of this coin, you know, explaining and perhaps working together to smooth out the fact that we're dealing with a material reality here in most factories.

JIM: Yeah, well, I mean, it is frustrating, but it's also what leads to the next generation of companies. Older companies may be entrenched in their working methods and resistant to change. Some little startup company comes along. They're not resistant at all. They're a blank sheet of paper. They can do whatever they want. They have no inertia, if you will, no organizational inertia. So they're very, very flexible.

And these new companies not only have innovative new ideas, they have innovative new approaches, and innovative new processes, and innovative new tools. When we think of all these clean tech companies, startup companies developing electric vertical take-off and landing aircraft, for example, a company I'm thinking of there is Beta Air, or they're maybe producing electric batteries like a customer we have called XING Mobile, or ChargePoint producing chargers for Teslas and other electric automobiles, these companies are saying, "I don't have time to buy systems. I don't have time to build factories.

What I want to do is bring smart people together, use tools that are already running in the cloud, come up with innovative new ideas, and pass them on to contract manufacturers. And I'll have a product in the market with very little capital in very little time. Later, I'll think about how to scale it up to be something much, much bigger."

But, for example, the use of contract manufacturers is a huge breakthrough. It means that you don't have to go build a factory before you can build a product. You just set up a relationship with somebody who already has the factory and knows perfectly well how to build such a product. It's just your ideas in their factory. And so these kinds of disruptive approaches are very, very interesting. It causes pressure on the old companies to say, "Are we really just going to stand here and let them do this to us? Or should we open our mind a little bit and be more flexible to change?"

TROND: Fascinating, Jim. It's certainly...it's a world with a lot of moving parts, the industrial one. So I thank you so much for this discussion. Is there anything you want to leave the listener with in terms of how they should view product lifecycle management as it's kind of moving into the next generation?

JIM: Let me offer up one last idea, kind of a big idea, and that is the role the metaverse will play in the industrial world. When we think of metaverse today, we generally think of gaming or social media. And there are kind of cheesy metaverse ideas, you know, you can go play a game online in some artificial universe, and it's maybe fun, but it's not meaningful.

But what we think we can do, what PTC is working on, is how can we take a setting that's real, could be a factory, could be a customer site, and how could we very quickly virtualize it into a metaverse so that we can then, from a remote place, enter that metaverse and interact with the people in it, the real people in it who have been virtualized but also the equipment and machinery? How can I go debug a problem in a factory by quickly turning the factory into a metaverse and joining the metaverse? How can I go solve a customer product problem by turning that customer site into a metaverse and joining them there?

I mean, I think there are some really interesting ideas that PTC has been working on there. And again, it's not metaverse for gaming and entertainment; it's metaverse for industrial productivity. That's going to be a big thing. We're way ahead of the market there, but wait 5 or 10 years; everybody is going to be talking about this.

TROND: So the industrial metaverse, Jim, that's going to be a real place.

JIM: It's going to be a real place. Let me add we call it a pop-up metaverse because there are so many places in the world. I don't need to virtualize them all because most of them I don't care about. But if I build a certain type of machinery and I ship it to a customer, and it breaks down at the customer site, and I need to service it using product data, well, I can buy an airplane ticket and rental car, and I go to the customer site, and I'll be there in three days.

Or I could ask the customer to whip out their smartphone, convert that situation into a pop-up metaverse and let me join into it. Five minutes later, I'm virtually standing next to the customer observing the problem and suggesting what they should do to try to correct it. It's a big, profound idea. I'm super excited about what it could do for us.

TROND: Well, that's fascinating. I certainly think that the industrial metaverse sounds a lot more useful and perhaps even more exciting than the consumer versions of the metaverse that I've seen so far.

JIM: Yeah, I totally agree with you.

TROND: All right, Jim, it's been a fascinating discussion. Thanks for sharing this and taking the time. I hope you have a wonderful day, and thank you for your time.

JIM: Yeah. Great, Trond. Thank you very much. PLM is obviously an exciting industry to me. You can probably sense that in my voice. It's a world that's really coming to light right now, a lot of growth, a lot of excitement with customers, a lot of big ideas, and I'm happy to have an opportunity to share them with you today.

TROND: You have just listened to another episode of the Augmented Podcast with host Trond Arne Undheim. Our guest was Jim Heppelmann, CEO of PTC. In this conversation, we talked about Product Lifecycle Management's Momentum in manufacturing.

My takeaway is that the momentum is clear, and one indication is the trend that PLM is being elevated to an enterprise system. But why is PLM such a hot market right now? One key word is greenhouse gas reduction because companies need a system of record to track their emissions, and this is not easy to do without a system 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 93: Industry 4.0 Tools. 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.

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