Episode Summary
The episode titled "The Digital Thread as a Service — Ideation and the Future of PLM" delves into the evolving landscape of Product Lifecycle Management (PLM) with a focus on digital thread services and customer-centric ideation processes. Hosted by Michael Finocchiaro, the conversation brings together Liz Graham from AdaIQ and Oleg Shilovitsky from OpenBOM. AdaIQ specializes in leveraging fragmented data to enhance consumer product development through advanced analytics and AI, aiming to create products that resonate with customers. OpenBOM focuses on organizing product information and workflows to make PLM more agile, connected, and collaborative for businesses.
The episode highlights the importance of integrating customer feedback throughout the product lifecycle, moving beyond traditional backend processes to incorporate real-time ideation and data-driven decision-making. Key insights include the shift towards treating data as a critical asset rather than just an application, with Oleg emphasizing that data's value will increasingly determine business success. Additionally, Liz discusses how digital thread services can streamline consumer product creation by consolidating disparate data sources, making the process more intuitive and enjoyable for engineers.
For PLM and engineering professionals, the episode underscores the necessity of embracing emerging technologies to enhance customer experience and operational efficiency. The key takeaway is that future PLM systems must be designed with seamless integration of front-end ideation and back-end execution, leveraging robust data management strategies to support continuous innovation and adaptability in a rapidly changing market landscape.
Full Transcript
Michael FinocchiaroWell, hello and welcome to this inaugural webcast of the Future of PLM. I'm joined by Liz Graham of AdaIQ and Oleg of OpenBOM. And we wanted to spend a little time introducing ourselves and what we wanted to do. We actually had two other people invited of the Future of PLM. I'm joined by Liz Graham of AdaIQ and Oleg of OpenBOM. It's advanced technology, I love it. Okay. So that means the live streaming is working. It's not live. Well, it's live streaming. So some people might actually be listening to it as we're talking. We had two other people that one dropped because I missed a scheduling change and the other one got ill, which seems to be going around. I was just in Rome with a dead boat lying in state in the Vatican or in St. Peter's last week. But I'm very glad to be here. My name is Michael Finnecke. I've been doing PLM for about 30 years and kind of all over the place. I mean, I've known Oleg for years. I met Liz. I had the pleasure meeting Liz at the ACE event last month that Eris put on. So why don't we first go around? You want to introduce yourself, Liz, what you do and what's AdaIQ? Sure. Thanks, Michael. Great to see everybody today. Liz Graham, I'm the CEO of AdaIQ. And AdaIQ is focused on taking the guesswork out of consumer product creation. So you can think of it as a money ball for consumer product development. We're helping to pull together a lot of fragmented data that isn't usually talking to each other to help brands build products customers love. And my background's been at various startups around the Boston ecosystem, which is where I'm based in digital, physical and sustainable products. And I've always been motivated by delivering an amazing customer experience so we can dig in more into how we're utilizing customer feedback in our product. But I'll popcorn it over to Oleg for his intro. Great, Oleg. Yes. Hello, everyone. My name is Oleg Shilovitsky.
I'm CEO and co-founder of OpenBOM. At OpenBOM, we help customers to make better decisions using data. We help them to organize product information and organize their workflows in the way that we make them agile, connected, and collaborative. OpenBOM is online and available for everyone, and it's open. And my background was in different PLM ventures. worked for the SO, I worked for Autodesk and was involved with several startups. I live in Boston and I just want to echo these. It's a great, great, great environment with a lot of really amazing people and innovative founders and companies. And Michael, your article about roots of PLM and Boston many years ago, I posted on my blog an article. It's a PLM highway, which is literally going 128 between PLM headquarters. So yeah, so again, excited to be here, Michael. Thank you very much for inviting me and happy to share more about the topic. Fantastic. like I said, we originally had Rob Ferroni and Valentina Futuro-Nova that were going to join us. One of the concepts we were going to talk about with Rob, actually you formulated with him, Oleg, right? That digital thread is a service. So maybe you could mention that a little and explain that. And then I thought that Liz, because you were working more on the front end, the ideation part where we're getting customer feedback on the digital thread. It would be interesting to see how that works and how those two worlds come together because traditionally when we talk about PLM, we're always kind of on the backend. We're taking the e-bomb. pushing it back to ERP or an MES, and we're not really necessarily integrating this feedback from the customer. So maybe we start with Oleg, if you can explain your digital thread as a service. Sure, absolutely. Like Rob and I, I think we had kind of an online moment of love where we've been exploring different topics. And again, something that I didn't mention,
Publishing beyond the PLM blog, gosh, for how many years? It's certainly more than 15. Over 30 you said in your interview when we... No. Yeah. again, the ideas sharing, I found it's very powerful and helpful to connect with people through the writing. And it was part of what I do for many years. And that's what happened, I think, between Rob and us and myself. So what the idea was is we are discussing digital thread, which is becoming some sort of evolution of PLM that started where the attempt was to like, the idea was to put everything in a single database. I mean, it worked until it stopped because the database became too big and the companies became too complex. everything became too distributed. So I think the evolution, natural evolution of ideas of product lifecycle management was how to connect different companies and different processes with the data. the idea, I think, was not born yesterday. And I think the ideas of this goes like 15 years ago, where companies largely in the defense and aerospace industry realized that they need to connect different pieces of information and processes. But the evolution of this idea was as we are moving in the world where everything is available as a service, the digital thread can make sense when it connects companies and people and processes. as a service because you don't need to create servers. You don't need to make like one year development IT project. So it's just about how to make technology available easier and how to make technologies flexible to connect the different companies and processes together. Now, where I think it's extremely important now is because everything in manufacturing is interconnected.
I seem data brought a topic of digital web. I think there are some companies that developing different connectivities that open bond. speak about manufacturing networks, connectivity, it's a big topic because you see many, many businesses, successful businesses in the last 20 years where I created on the idea of network and connection. So industrial network, manufacturing network. This is a graph of connections. And I think this is where we are coming with the ideas of digital trend as a service, just to make it available, to make a platform that capable to work with different companies at the same time, connect them together, connect processes. So this is in a nutshell, the idea, but I'm sure we will becoming more and more solid in our thinking and as we develop it further. But in one of my intents in creating this environment was to talk it through and maybe start thinking about how it would work in the real world, how we're going to connect that to customers and their pains and their use cases. So Liz, in your world, it's closer to that ideation stage. How do you see? Well, how does what kinds of customers is it? A to IQ help? And how does digital thread is it? Are you already using maybe this idea of digital as a service and Let us know what you think. Yeah, absolutely. So we're focused right now in the footwear space. The early R &D for our academic research was done with a major global footwear brand. so the things that are interesting to us are there's a lot of unexplored consumer feedback around products. mean, the obvious places are customer reviews, surveys, user group testing, things like that. But there's a universe of conversations that are happening about products, whether that's Reddit threads or blogs or vlogs. And most companies struggle to really incorporate that information into their product development process. So we're focused on the
fuzzy front end that's, as you noted, of the creation to prototyping and where you were seeing a lot of opportunity is creating connectivity between all these fragmented pieces of data and then pulling that innovation thinking into the PLM space. typically what we're seeing in in most companies that we're talking to is that testing the market or sort of testing the consumer feedback stops at a certain point when the design is selected. And then it moves into manufacturing. isn't the opportunity for sort of continuous listening to, we headed in the right direction? If we had to make changes, is that going to impact? customer reception and we're focused primarily on consumer products. So probably less critical for aerospace application, right? But I think we all know we live in a very fickle consumer environment. So trends do shift quite quickly and the opportunity to reset or modify is significant. both help shortening that product development cycle, but also thinking about, as you are mostly developing a tops down PLM where somebody's keying in information, like how can we create a bit more of a bottoms up where information that we're developing and that innovation piece sort of feeds in to the rest of the digital thread. And you really start to get that full end end-to-end view and you don't lose the knowledge of what was sort of ideated but discarded. There are a lot of things that I think recycle back. know, people come up with like, we tried this and somebody's like, yeah, we tried that five years ago, you know. And so I think there's a lot of benefit in pulling all this information through and connecting it to the
digital thread and I think you know from friendly conversation we had at the ACE event like that that was always the original vision of the digital thread was really it did kind of pull the whole way through the product creation process. like when we're doing it sounds like the information that you're getting from the consumers that it should be much closer tied to the requirements management phase of the product development right? And like, so with OpenVM, in your experience, how, I mean, I know a lot of PLM platforms have kind of a bolt on for recurrence management. PTC just bought CodeBeamer a couple of years ago for that. But it's always been a bit of a sidestep, right? mean, IBM doors was the standard for so long. I mean, how do you see this connection between a very robust requirements management system? Should that be part of the digital thread, like a separate system of record that's referenced by the PLM system and then enriched by the ideation system? And how do you think that should work? And this concept of a digital thread as a service? Yeah, think it's great question because to me, like it's a question like Everything should be included because when you design product, when you're making decisions, you need to be able to pull right, to pull right information that will help you to do it. Now it can come from requirements. It can come from manufacturing, from supply chain, because those are multiple constraints. Now the problem that we have is that the environment is very much siloed. and engineers do what they do just because they've been doing it for the last 20 years. So, and we've been buying from the suppliers for the last 15 years, so we'll continue to buy from them. So I think all information needs to be incorporated together. And this is the one of those challenging and complex technological decisions, because let's take, let's take like,
chat GPT, read everything on the internet now. It's I don't know, like a gigantic number of books and times that you can spend to read it and then you speak to a person. Likely you speak to the person who read all these books. It's fascinating. I want to speak to someone. I want to talk to someone that connected source of information that helps me to understand everything about the requirements of customers about the product and everything that we've been using. in our design decisions and reviews and everything that we've been doing in our supply chain decisions. Like I want to get all this information together connected and see what is the impact. Specifically for requirements, I think it's becoming increasingly important from a place where I see it because products are becoming much more complex. And for a simple product, it's easier to understand the design intent. and what is the impact of the different design decisions and manufacturing decisions. Now, if you have a multifaceted product with the mechanical, electronic software and many complex behaviors, it's a very end consumer behavior. It's very hard to understand how it all comes together. That's why I think requirements increasingly come in as an answer of let's rationalize everything that we build. Why did we build it in this way? And if you will change it, how it will impact the customer behavior. So I think this is where requirements increasingly will be coming now as an important element that before it was ignored because just products were simple. Like my toaster for some reasons, there is has a wifi card. I don't know why it's needed, but I mean, it sent me messages. The toast is ready. Yeah, I got it. But you can imagine the amount of complexity that goes all over the places. So I think it indeed comes all together as an information that's connected. So Liz, when you're looking at the customer requirements, do you have your own searchable database where you're storing all this information and then you're distilling it? And then ideally, a digital service would be able to pull that information out and find the right place to place it in the product lifecycle so that feedback gets taken into account.
account? absolutely. think we've got capabilities that focus on the requirements. also have very interesting applications for concept evaluation. So this is where the sort of moneyball piece of our tech comes in, where you can actually start to stack products that are in development against products that are out in the market right now and evaluate across a specific set of attributes where your concept will outperform or underperform. And so that then that data set attaches to the design. can have half a dozen designs that you're evaluating. And now instead of a handful of people locked in a room sort of course trading which design is going to advance, you bring more objective data into that. absolutely. And then you can really start thinking about some of what Oleg was touching on, is, I'll call it sort of the human single point of failure where, you know, decisions get locked in people's brains and not necessarily sort of exposed within the systems that they are using. And I think there's a a very powerful opportunity here to, when you think about the role of agentic AI to learn the way decision-making gets done within an organization and start to de-risk some of that capability. I mean, we're probably still a little ways away from being able to sort of do the Harry Potter thing where you pull the thread out of someone's head and like drop it into the bowl. But I do think that there's a lot of opportunity for you particularly understanding where trade-offs were made or what decisions were made and sort of what the information set that went into that decision was. I I think all of us have had lives where we've been building work instructions or MMPs and sometimes those things get followed and sometimes they get sort of pencil whipped depending on
on sort of where the teams are in the life cycles. So I also, I think the breadcrumbs that get left are an important part of what will make the digital thread continually useful in informing the systems that it ties into. Absolutely. And in your experience so far, mean, you guys are at the point where you're talking to your customers, right? You said you were talking to... I would just like to understand because if we're talking about the future PLM, we're obviously going to be talking about agentic AI, we're to be talking about MC, MCP and all this stuff. But I, in some talks I had with some guys, some customers and some analysts, there seems to be a lot of resistance, particularly from the CFOs saying, well, it's not mature enough, it's changing every day, you know, how, how can I even back up this thing? Or do I have to back up? all the LLMs at what point in time and with how many parameters and it was at the queries. So how, in the real world with your customers in the real world, how, when you're talking about using AI in that context, how are you getting around that kind of resistance where the CFO might be saying, well, no, that's too much money. And besides it's all speculative and it's going to be hallucinating anyway. Yeah, no, it's a, it's a great point. The, the core the core that you have to build is trust. I mean, people have to be able to trust the information that you're providing and the decisions that they're taking off of them. And, you, so that that's a lot of where our focus is right now. And we're showing, customers where our datasets have really distinct information. If you compare it to, you know, what chat GPT would put up, there's maybe 20 % overlap and there's really significant advantage in having something that's tailored to your enterprise and you are curated a array of information that's being used. I think that we are still early in the process of working with customers on bringing their data into our platform. A lot of what we've been doing for early pilots is using
publicly available data to create insights to again, sort of build that trust like, hey, you can rely on the information that we have and just think about how much more exciting and useful this would be if we can pair it up with the information that you're already using. And I think, know, dare we say sort of the tariff environment has also forced a lot of people to think about, you know, how to optimize all like, I'm sure you You're deep in this space right now, but we're seeing a lot of opportunities to create interlocks between these different systems that help people make the best selection very early in the process, even in a sort of dynamic environment. But I'm interested, Oleg, since you tackle more of the supply chain, and back end side, some of the things that you're hearing there too. Yeah, great. Yeah, absolutely. See, one of the things that we see a lot with our customers is that they are looking how to move fast and circle back and continue the improvement. there's a lot of... A lot of questions here. just bring example from one of the customers. The challenge is that they design machines, complex equipment, and the components there are coming again from different places and ordering them on time. And those components are expensive, it's important. Otherwise, they will be delaying the project. So they delaying project that cost million dollar to two months to customer, it's huge impact. Now, how to make it not to be delayed is to plan ahead of time. To plan ahead of time, you need to collect all this information and you need to be able to connect this information with different people that involved into this process. Now, those are not huge companies. This can be companies of hundreds of people.
Like not huge companies. And for those companies, the existing paradigm of PLM just doesn't fit because the existing paradigm of PLM is pretty simple. It's like 30 years ago, let's put everything in the single database. Guess what? You just cannot do it for these companies on this scale because this is like... one big space of enterprise, but those companies just not getting any excitement about this system. They want to be connected. They want to send information to contractor. They want to send information to people that involved in the design. They just cannot do it with the traditional systems. This is where I believe the paradigm shift is coming. The old PLM practice was mostly about let's organize a single database of everything, solve the problem. Guess what? If you have two PLM systems, they still cannot talk together today. Even if you put them on Amazon, they still the same databases that you need to expert Excel from one system and files and put it in another. So it's just something that doesn't work. And I think that this is the place where the technologies that we developed at OpenBOM. with a very non-unique name, Collaborative Workspace, that helping the people to put information and make changes differently. It's like I will give you a simple example. You can create Google spreadsheets and make changes simultaneously, even if you work in multiple companies and you own only part of the spreadsheet. You can do it today with OpenBOM. I can share a piece of information between two companies working with two different accounts. try to do it with any PLM system, cannot. Why? It's because the database one, database two, and novice was thinking that these databases can work together. So this is where the real digital thread starts, because you start connecting pieces of information together and you start making this information available to everyone. So that's where I think that the starting point and I believe that...
the opportunity is gigantic because you know, it's how like 100 years ago, the cigarettes were acceptable only for men and everyone was trying to sell them cigarettes. The market saturated. So, and then everyone figured out that we can sell cigarettes to women. The market jumped up. Yeah, it was very interesting. marketing propaganda around this, maybe for another conversation about marketing, But the point is that today, everyone is trying to sell PLM to enterprises. They cannot make enterprises to buy more PLMs anymore. They already have every company, have two, three, four PLM softwares and organization. There are a lot of them. So when now PLM system dies, you can replace it. they open the market, it's open the market to the connectivity between these companies. And this is where I think digital trade as a service can come because it will connect all these companies in the network. But will this be like new vendors that are going to do that? I know it's a you know, we already have classes of vendors like EQ technologies, right? That has their EQ thing. We have vendors like Boomi that do, you know, more of a data as a service. We have even things like Tableau where you just do a BI, a mashup of all your data. Is it that or, you know, it was very exciting at ACE when Eris introduced Innovator Edge, which is a way of abstracting some of the capabilities of Eris and then connecting that to other companies. I'm trying to understand like how, you know, where where does it get implemented, the digital threads of services? Is it going to be a new standard that each PLM company is going to have to have? I mean, let me roll that back. Is it like another, a new OData standard where every PLM platform will expose a certain number of services or providers like Liz will expose their data through a certain service. And then is it the PLM they're going to be pulling on that service? it sort of becomes the digital threads of service bus?
I'm just trying to understand what you think it would look like. And then Liz, of course, you can react as one of the people on the. You know, I think thinking about standards, it's a little bit like we are past this stage. I think for the last 30 years, you've been trying standards is a magical thing. And I think we created standards. There are standards. Jason is a standard. So for some companies, XML is still a standard and they use it. If you think about MCP that you mentioned, MCP is a standard that just recently was invented and started to implement. How broadly it's used? Well, we can see it. So it will be standards created in this world. that will allow us to connect pieces of information. you can think Internet to a certain degree is a standard and we can communicate with the information that's stored online. So I think it will be an evolution here that will help us to understand this information in a better way and make sense of this information based on what we have. Some information will be connected, some information will be... managed by a system, but I don't see it's like an ultimate, okay, let's create standard, everything in a single place, the problem. I think it's going to happen because people are, the companies are innovative. They want to move forward. Like you cannot bring them to kind of level, single level and say, this is what you do. And with regards to information, companies are doing it all the time. So they put information in Excel and send it. You cannot stop this. No one can. Like people come into OpenBOM, making manipulation, exporting data. Like we are open, they're sending this data in Excel, like, because everyone understand it. So it's, it's again, when they realize there is an opportunity to share, they share, but it's, it's, it's, it's, it's an evolution. I don't see it as like stop today and tomorrow will be different. So Liz, how, how do you, how are you thinking about that in terms of you're going to be more of a, you're going to be more of
person giving feedback rather than consuming it, right? So how is Ada IQ? How do you guys see it? Putting your stuff on the digital thought? Obviously, you want to protect it because you don't want any buddy to do it. You only want your subscribers to be able to get that information from a to IQ. So how are you looking at that problem? Yeah, so we're I mean, we're in the space of a value. I'd say creating kind of a hybrid where we can either deliver as a data as a service or have more of a SaaS like experience. And some of that's going to be driven by the customer preference. And to your point about Tableau, do they want information piped into their BI environment so they can mash it up with other capabilities that they have? I think the more you kind of into the enterprise space that you go, the more protective folks are of their environments. And so we want to be able to make it easy to work. You have endpoints that people can can connect in with the really sort of fascinated by Oleg's perspective on this. collaboration and multi-company environment that everybody lives in. mean, you're, very few companies are sort of so vertically integrated that they're doing it all themselves, right? And you think about 10 years ago or 15 years ago, I guess was probably closer to 10 than 15, as the Google suite of products was starting to make its way into companies. My experience was, companies that were sort leaning into innovation, you grab that capability to do a lot of collaboration. We had the example earlier of sort of sharing a Google Sheet around. It's very easy to collaborate on those documents, but then there are other places where everything's completely locked down. And maybe that's because of contractual reasons or just the leadership decisions. So I fully agree with Oleg's
perspective that it's, you there probably isn't one standard that's going to be universally applied here. I think it's going to be, there are companies that already have the DNA where they are collaborating across systems, just not in this specific space. And they're going to be the ones that I'll be, I think, first to see the benefit of this opportunity. And then other industries because of their constraints or their approach will continue to sort of have this challenge of how do you connect things? The benefit of the vision I see that Oleg describes is everyone's gonna have real-time information of where things are, what's going on, where are the holdups? And especially if you're working asynchronously across geographies. mean, that's incredibly valuable for speed to market. And so I do think we're going to see the need for some culture shift and reinvention of the way companies are working. And maybe it's competitive pressure that creates that environment. It makes me think about the fact that PLM has always been, course, a system record, and it's been really good at connecting with systems of engagement, CAD, ECAD, what it hasn't done, and maybe what we're really talking about here, and AdaIQ seems to be a great example of a system of insight, So maybe that is that what we're doing with digital threads as a service? Are we taking the existing infrastructure of systems engagement, systems of record that We know how to work with as engineers for, and we've been working with it for a long time. And now we're trying to go over the boundary towards this AI future. And what we're trying to do really is connect intelligently these systems of insight without having to dump my entire database, without having to expose my IP to the whole world and protect my own intellectual property. What do you think?
Is that another way of saying it, Oleg? Well, there are two things here that I would like to unpack in what you said. So first, as far as I completely agree and seen it many times, is what you said. People pulling systems like Google Spreadsheet, starting sharing data because they can. And this is what they need. They need to work. So that are the... system of engagement, Michael, that your brother are connecting together. Why? It's because if the only way for me to engage with someone is to pull this information to Google spreadsheet and share it, I will use it in a company. If no one gives me anything else, I will use it. So is it the most optimal system for engagement? Probably not, but this is what we have today for some companies. This is what leadership allowed them to do. You know, in the past 20 years, know, SharePoint was the system because it was like the only way to share something. people were doing it now, but I would not be placing it only as an engagement without underlining data because we are engaging between people. the information that I would like to have access to and the information that will allow me to be smarter. It's actually from these systems of records and the connectivity between them and actually in the thread, in this network. So it's like Airbnb, they have a network of providers and the network of people that wants to rent. So they're getting a lot of intelligence around these pieces. So the same amount of intelligence we can get from the graph of data. that is connected between different companies. So this is the underlining foundation of OpenBoom, connecting to other databases, getting this information in an easy form, building intelligence. This is where the power. But then on the other side, people are communicating, and as people communicating, the data is lost. Let me give an example. People communicating on engineering change order, they're making some assumptions, talking to each other, making decisions. Where this decision is stored?
Like where the reasoning about this decision is stored? Nowhere. So this is what a system of engagement allows us to capture. But then we've been buying this part for the last 20 years for different prices. How can I get this information? This is a system of records. So it's all intertwined together and making a big giant product knowledge graph with all connected information that's becoming an industrial and industrial knowledge and industrial data becoming more smarter. I remember like many, years ago when we just started to use Google, people said Google sometimes bring better results than someone else. That's how they went to the market, might not remember. But then someone else said, I'm sitting in the room and I'm connecting to internet, I can use Google, I can be the smartest person in the room because I will get the answer. So today the same, by the way, with ChatGPT. So I can be much smarter if I will start talking to ChudGPD. I want to have the same capabilities, connectivities between data and bringing this intelligence in requirement work, in the planning, in any decision making. And it's only will come through the connectivity and building this graph of information. And that's why I think it will become different. And this is where we build a differentiation at OpenBOM as well. But what about the systems of insight though? Where are they going to sit? Because we're going to need the analytics behind that. Or maybe that's where Liz becomes one of the providers of the systems of insight. Liz's, 8IQ would be providing insight in terms of consumer feedback, as opposed to maybe another provider that would be looking at the IoT data, the real-time performance of the product and giving Performance feedback. So maybe, you know, maybe there's a Part of this digital Thursday service that needs to be able to take into account the insights that can be gained and those need to be somehow pushed into again the requirements or so that the product reflects what the people want and and Also is repaired when the performance isn't up to snuff. What do you think this? Yeah, I mean, I think this is part of the opportunity for creating a I mean if if Oleg has his
his ability to build these knowledge graphs, then you can create a continuously learning environment that's taking in that sort of live IoT feedback from actual product performance, it's taking in the consumer perspective, the user perspective, all of these things interlace with manufacturability and you know, design, all of those things. So I think that, probably, you know, not to date myself, but probably not so much our generation, but you know, the my daughter and the folks of her generation, they're, they're not going to be held by, you know, sort of, you know, controlled ways of accessing information, they are going to want natural language approaches, they are going to want to be talking with their, you know, sort of smart glasses to feed them information about things. So they're not having to, you know, have the delays of keying information into systems. And so I do think that this direction helps free, you know, free up a lot of innovation and capability for systems to provide the combination of that system of record information with the insights that enable it to create recommendations or direction or sort of have that real-time connectivity and ability. think it's... the ability for people to just interact with it in whatever language they want. it's, I think it'll definitely be a multi provider environment where you, and one of the limitations of the current large language models is they are generic. And so if you're talking about some of these deeply specialized product environments, you're going to need something that
actually can go deep and understands those workflows, understands the elements that go into it and the risk involved. So I think it's not going to be as easy as just slapping a of agent or chat bot layer on top of this digital thread. I think it's going to probably be some deep vertical. expertise to really be able to deliver, deliver, you know, meaningful insights. Yeah, I think so too. And I think the another place companies are going to struggle is when when you're faced with some of the monolithic PLM systems, right, the big three, and particularly the two biggest of the big three, you know, they're very much, you know, this is all the information where They're not as open and it's gonna be really hard if the customer's gone down the road with one of the more monolithic PLMs to take advantage of digital services. So if they're using OpenBOM or Aira as something really open, it's really easy. Once they start using 3D experience or TeamCenter, I think that it's a little bit more complicated. What do you think, Oleg? this discussion about monolithic, I think it's going a little bit crazy for the last couple of days. there is no chance for the future that all information that we are talking about will be located in the single database. I mean, this is impossible. think this is not sustainable. and companies will need to figure out. Like Lizzie said, I want to talk with someone with the deep expertise. And I'm considering this as the same association. Like I want to talk to some specific database of suppliers. Or I want to talk about some specific database of experience of people with the footwear that they shared and this information is collected.
So these all pieces of information are collected. And today, I like the trend, it's called data products. So you create these data products in a way of models that allows you to blend the decision and information from this. I think that will become a more way of communicating and gathering this information and then providing this information to others. So the system that is... controlling, for example, for a specific company development process, can pull information from other data products. And at the same time, also can share information about specific elements of this process. Now, the problem here is the business model. Because for the last 30 years, the only business model that was sustainable is to lock data. and upsell applications. So this is how the enterprise business model was developed. You find a person with a title and budget in a large company, and then you add to his name award management, and you get an enterprise software now. So because you can go to this person with this domain expertise and award management to ask him for a budget, and he will put data and he will do something. It's across everything. you get all possible variation. If you can break this paradigm, think it's unknown. I don't think it is in the process of being changed, especially when I'm hearing the people that still supporting and saying it's like monolithic, let's put everything in the single database. SAP is placing all PLM, MRP, ERP, all together. And then we have the SO and everything is together.
it's very, very to go. I don't know. Yeah, I had that. I actually worked with Airbus on that particular question, but they've made the strategic decision to go all through the experience and it makes it incredibly hard even imagine doing microservices or inspired or what we'd call here DTAs. We're getting close to the end of me. Maybe you guys have some closing comments, Liz? Yeah, I mean, I I think what's so exciting about this is that people are gonna, in my experiences, people get frustrated with the limitations of the systems that they're working in and they find creative ways around it. Whether you, and your opportunity here is to build something that will provide a fast and intuitive and informed solution for folks or your frustrated engineers are going to sort of... go out and explore and use these emerging tools to kind of do some end runs. So, you know, I think that this is an exciting time to, you know, create some of these capabilities, you know, develop some really powerful ways of pulling this information together in a way that really makes it like, you know, maybe not a joy to work with, but certainly like much more enjoyable than kind of the current state of play. So that's what I'm excited about. You bring up a good point there because you mentioned your daughter. think that if the tools don't evolve relatively quickly when that next generation comes, there's going to be a big problem because they're going to be like, no way Jose, I'm not going to use that old... I can't do that. I'm not going work that way. That's going to be a bit of a conflict when we have this generational change. Oleg, do you have any closing thoughts? Yeah, I just want to echo what Liz you mentioned about the power of the data and connectivity. And I the data is becoming more valuable to companies than applications. It's the oil, right?
Yeah, we can call it whatever. But I think what companies are more focusing is how they preserve data, how to organize this information and how they can reuse it. And the people will be able to switch between applications and still the focus will be how to preserve the history of data and how to preserve all information because there are decisions. will be coming from the data. And if I use PLM-1 for 10 years and I am moving to PLM-2, I'm mostly concerned how I can get access to information and intelligence from my processes from PLM-1. Because if it will die, then I'm losing the business. I'm losing the reasons why people buy it and why we decided to switch from this design to another design. 15 years ago in another PLM system. This is really going to be about data more and in a different ways to organize this data, language models, graphs, like many ways. It's going to be about data, not about the applications and the database that support this application. So that's just my take. Yeah. So was like the shift. I remember when I was working for HP, we were only caring about servers for long time. And then suddenly this new concept of DAS, basically the distributed disk systems came out. And suddenly that was the big thing because we even realized back then that data was important. Well, I wanted to sincerely thank Oleg and Liz. Thank you guys. We're gonna try to do this again in a couple of weeks, probably around May 19th. Hopefully our other two... panelists will be more available. There was Valentina from Aveva and Rob Ferroni, the PLM plumber. And I had another idea of another guest or two. And I think we'll continue on the same vein of digital service and connecting from ideation all the way back to the asset, which is what Valentina can talk about. And so I look forward to and then of course, we can get Rob's perspective because he was the other
a genius behind this DTA as concept besides Oleg. So anyway, I wanted to say thank you and goodbye to everybody. And hopefully we'll talk to you in a couple of weeks and take care. Thank you. Thank you very much. Thank you. Thank you. bye.