Garth Coleman Podcast Transcript
Garth Coleman joins host Brian Thomas on The Digital Executive Podcast.
Brian Thomas: Welcome to Coruzant Technologies Home of The Digital Executive Podcast.
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Welcome to The Digital Executive. Today’s guest is Garth Coleman, a strategic innovator. With more than two decades of experience in enterprise software, Garth Coleman brings a unique blend of technical depth and business leadership to Canvas GFX.
He is recognized for advancing product lifecycle management, 3D visualization and generative AI technologies that help organizations turn complexity into competitive advantage. Before joining Canvas GFX, Garth Coleman held multiple vice president roles at Dasso Systems where he helped define global strategies for 3D visualizations, PLM, and AR VR solutions.
He also led initiatives to accelerate generative AI adoption across brand marketing and product organizations driving efficiency and innovation at scale. His deep expertise in scaling products and businesses positions Canvas GFX for its next chapter of growth and market leadership.
Well, good afternoon, Garth. Welcome to the show.
Garth Coleman: Hey, Brian, thanks for having me on.
Brian Thomas: Absolutely, my friend. I appreciate it making the time. Obviously, you’re in the Boston area in Massachusetts. I’m in Kansas City, so just an hour apart, luckily today. But we’re gonna jump right into your first question. Garth, you’ve spent more than two decades working at the intersection of enterprise software 3D, visualization and product lifestyle management.
What experiences along your journey shaped your leadership approach and ultimately brought you to Canvas GFX?
Garth Coleman: Well, I appreciate that question, and without getting into a full kinda LinkedIn interview session here I would say that underlying everything that I’ve been doing has been around technology and software working with a lot of amazing teams that have produced amazing tech.
That just needs to get in the hands of the people that need it. So, as a mechanical engineer by way of education and my first real job, let’s say and getting into technology to help companies do better things, I’ve had a couple of really long stints at a couple of companies which allow me to progress my career in amazing ways with great teams, as I said.
When you try to take something that is complicated, a lot of engineering is complicated, there are a lot of problems in there, so you get into these problem solving modes, and for me it’s never been about solving the one problem. It’s been about trying to take. Pieces of things that are there that could help solve that, but put them in a way put them together in a way that where the, you know, the sum is bigger than the, what is it?
The hole is bigger than sum of the parts, whoever that goes. But then making it in a way that other people can then use it. So you’re not solving one problem, you’re solving that problem that everybody seems to have. And I’ve done that over and over again on many different ways, many different teams, many different areas, whether that was into Product lifecycle management and reinventing that for mid-market a couple different times 3D visualization and moving it from say, dumb 3D that you turn around on the screen into making it something that is a really a powerful communication vehicle. And that’s really when this, the journey right now that I’ve, I’ve kind of led me to Canvas and vision started 20 years ago when I was in a small little startup called Seage.
And this was a 3D technology that was just unlike anything that had been in the market before. And we got acquired by Dasso Systems. And that’s began a 19 journey, 19 year journey there for me, where we basically took this product, brought it into market, put it through all kinds of different, sales channels and industry offerings and really helping companies use the power of 3D.
To go beyond engineering and to solve communication challenges, but the challenge, of course, there was that while that was a massive revolution in productivity, we still had the challenge of when you want to digitally deliver that, you had the problem of like, how do I control this thing?
Where do I put it? And we always had to put it in some kind of box, some kind of container, some kind of application to really make it do all those things downstream. And, fast forward 20 years with all the different things I’ve been able to do at Dasso Systems and then getting into, artificial intelligence and gen ai and trying all these different technologies.
I came across Canvas and vision by way of a contact that I’d had for many, many years. His name was Peter Schroer. He was the founder of Aris, PLM. And I had known him before that and we just connected over the summer and he’s like, Hey, I’m on a board of this company. It’s got some amazing tech.
You should check it out. They need some help. And I saw it and I’m like, Hey, they’ve solved that problem from 20 years ago. They are the container. And we’re able to now make it super easy to, to not only author work instructions, but deliver those things digitally. And what I saw, a few months ago was kind of the same feeling I had 20 years ago when I saw, mage back in the day.
And I’m like, but we’ve solved the problem. So now I feel like, 20 years have gone by, these problems are still there, and now I can kind of almost go back in time to fix those problems with the technologies of today, with the, the knowledge and experience and wisdom from all that time. And I’m really excited about that because that’s the main reason why I joined Canvas and Vision, not because I wanted to do the same thing I did before, but because now I believe we can finally solve a lot of these problems and get this part of the world, the manufacturing and service work construction world, kind of outta the stone ages and into modern tech.
And that really fits with the transformation, troubleshooting, innovation, scaling that I’ve done my whole career.
Brian Thomas: That’s awesome. I really appreciate the backstory. Software and technology, obviously building great teams over the years. You got into tech to help companies solving that big problem, you know that one that everyone has.
And because of your experience and again, connections in the industry, knowing people and doing some great things, obviously recommended things come together and, because you had solved basically a lot of problems in the past. You’re able to come in and solve today’s problems with your experience, and I think that’s awesome that you’re sharing kinda where you started and where you came and that journey along the way.
So, thank you and Garth, Canvas GFX focuses on helping organizations simplify complex technical information through visualization and digital content. Why is the ability to translate complexity into clarity becoming such a critical competitive advantage for modern enterprises?
Garth Coleman: Well, this fits very well into why I, I joined Canvas GFX, and I break it down into a three-pronged challenge.
If you look at manufacturing, there’s, I look at it, three pillars. You’ve got product pillar. You’ve got a process pillar, and you’ve got people, and clearly on the product side, there’s been so many evolutions and innovations in engineering, the modeling and simulation all kinds of things around digital threads, digital twins, virtual twins.
I mean, it’s just amazing what’s been able to be done. And that has increased complexity dramatically. All the configurability, all of the tailoring that can be happening. This has been, amazing in the last 20, 30 years, and I’ve been around a lot of that. It, it’s been exciting to be part of that.
On the process side, you’ve got a lot of governance. This is the product lifecycle management that I’ve been involved heavily in and how do you orchestrate and govern activities and IP and then also you bring that to manufacturing and you’ve got your manufacturing execution systems and smart factories and all this kind of amazing tech and all that, again, gets more sophisticated, more complicated every year.
But then on the people side, it’s a little bit left wanting when you get to the workers that have to do all this work, they have this increasing complexity coming at them more rapidly, uh, more complex than ever before. And yet the ways that we give information to these people is still from 20, 30 years ago.
You’re still getting screenshots, drawings, static PDFs checklists and they’re generic. They’re not always precise, and they don’t flex based on the way you’re working or the devices that you’re on or the skill level that you have, and. When I, I’ve just been talking to some, some customers recently, I’m like, I can’t believe they still work this way.
But because there hasn’t been another way, taking knowledge and authoring that into instructional format that then can be delivered and consumed, that’s a hard problem to solve. ‘Cause there’s a lot of people in that mix and all this tech hasn’t really solved that problem. And to me, this is what I call a last mile and first mile problem of this digital thread.
You know, the first mile is, capturing the knowledge that exists, whether it’s tribal knowledge, whether it’s from, IP and locked in CAD systems or other process systems, and getting that out and authored in a way that is instructional. And then the last mile, the digital thread is in delivering that digitally interactively, dynamically to the person that needs it, but also pulling their feedback and.
Activities that they’re doing back into the digital thread to return that loop for equality, for innovation and so on. So that to me is, is a huge area where all this complexity can be resolved, let’s say, through a visual layer that, that up until now has been mostly missing. But what makes this urgent is the workforce dimension.
Where you’ve got a lot of workers retiring and taking all that knowledge and wisdom with them, and that really hasn’t been extracted out into, the dusty binders on the shelf. You know that that never get used. So, we’ve gotta capture that knowledge and we can use AI to do that. Now we can use the technology that we bring and that some other companies bring, and then that’s the first part.
And then the last mile part we can figure out is really supporting. The new workers coming in that are digital natives, that they want stuff that is instant, immediate visual that tailors itself based on what I need. Maybe I just need a too long, don’t need, don’t read because I just need to know what’s different here.
Maybe a safety protocol, maybe a pause to check something, but otherwise don’t bother me. Or I got someone who’s kind of new that needs all the information and needs to be able to get all that extra additional information and the old ways of working, which is documents and visual aids. Doesn’t do that.
So, if we wanna kind of extract the knowledge from the, the talent that’s leaving and transfer that knowledge into the incoming workforce, we have to do it in a different way. And of course when you do that, then you’ve got retention, you’ve got better performance, you got better safety, better quality. You know, all those hard dollar manufacturing metrics can now be improved by solving this, this knowledge gap.
When people call this like a connected worker strategy, I call it a connected knowledge strategy that, uh, we basically can take all of this people side of the problem. Where they’ve kind of been working by candlelight and everyone is working by, electricity and we’re kind of plugging them into the power grid and we’re using AI to help us do that.
Brian Thomas: I appreciate that. You talked about that three, those three, that three-prong challenge pillar, product processes and people. Of course there’s a lot of complexity that you went into in that. But at the end of the day, the big message I took away is around the people, is how we share that knowledge.
We train, we communicate, and again, I, I. Big thing that I took away is, as you call it, the connected knowledge strategy, which I think is pretty cool. And that analogy used about plugging into the power. So, Garth, moving into the next question. Many organizations struggle to connect engineering product and marketing teams around a shared digital workflow.
How can platforms like Canvas GFX help bridge those gaps and improve collaboration across departments?
Garth Coleman: Yeah, I mean, again, this is where I’m getting into this, this visual layer, and not only just to marketing, ’cause you obviously you gotta sell product, but once you sell, you’ve gotta produce, you’ve gotta deliver, you’ve gotta deploy, you’ve gotta retain that customer.
So now you’re talking about manufacturing and assembly, you’re talking about delivery, you’re talking about service and support and maintenance. All those departments are downstream of engineering. And as I mentioned, there is this gap this digital gap, this knowledge gap that again, I believe that we can solve this with this, what I’ll call a visual execution layer.
And this is not just a one-way passive, Hey, this is what it is. Go figure it out. You know, this is the ability to deliver it in a way that is instructional for the person that might need it, and tailoring it for them based on the screen that they have, based on the device that they’re using. And then also allowing the data collection or data entry to return back onto the digital thread.
So this is really, we, the people are the gap, but we can use what people need. The people are, we’re very visual. Another analogy is, you know, you ever watch the movie The Matrix and Neo is looking at the screen when he is on the ship and he sees all the green lines on the screen, the popular screensaver and he doesn’t know what it is, but the other guy’s like, oh, he can read it. He can see what’s going on. And this is just like someone in engineering, right? They know what the long part numbers are, they know these types of things. They’ve seen it a million times and they can look at that flow of information and understand it.
Someone new just sees gobbledygook and making that visual is like plugging ’em into the matrix, so I think this is really we’ve gotta be able to adjust that. And use visuals in a way that allow people to really understand what they need, when they need it. And I got tons of examples and things that we’re working on.
And AI is, is really a force multiplier here. Doesn’t replace people, but it actually empowers them and connects them better than ever before. So, you know, the digital thread, digital twins, virtual twins, all these things are built for systems, not built for people. So, we really have to make that visual to, to solve that, and that that goes back to that last mile problem.
All these disconnections are, are different forms of that last mile problem to, to extend it into the broader workforce.
Brian Thomas: Thank you, I appreciate that. And you did talk about adjusting and customizing that process because people, they’re the gap and they are visual, visual learners and AI is a great tool.
But again, at the end of the day having that technology again, as you mentioned, was for those technology platforms, not necessarily for the people. And you gotta make sure that things are visual, easy to learn and understand the process. So, thank you. And Garth, the last question of the day. If you could briefly share as we look ahead, how do you see technologies like Gen AI, immersive 3D and digital twins reshaping enterprise software and industrial workflows over the next decade?
Garth Coleman: Yeah, I’m, to explain kind of the future, I’m gonna go back to the past a little bit and, when we were first acquired into Dasso systems there was a vision that was coming from Dasso Systems and it was called, see what you mean? Which was basically using 3D to help you, basically articulate the value of what it is you want to the person that needs it.
And I look forward and I say, you know, that’s still kind of the overall need is the visualization part. And unfortunately, visualization over the 20, 30 years has been relegated into visual aids. Or maybe just some dumb three DI rotate around or I do some like clicking and hotspotting and, kind of interesting but basic.
It’s not really sharing and transforming what you do and knowledge and, and so on. That’s evolved. You know, there’s been a lot of work we’ve been doing over the years, in engineering. Obviously digital mockups and design reviews and all this great stuff for engineering has been evolving and growing and I’ve seen some new technologies new companies that have been doing amazing things here.
But we gotta get that beyond engineering. And when I look at, AI and Gen AI and digital twins and so on, break this down into three pieces. Information, knowledge, and wisdom and AI can really help us extract that. Tons of information, knowledge, from videos, from old documents from manipulating and understanding 3D objects.
And use that to extract it so that the people that know things can build that into knowledge. They can add their context, they can add the relevance, they can structure it and sequence it in the right ways. And AI can help put that into a format then that people can use. So, we need people in the loop.
We need the wisdom. The wisdom can, obviously train the AI even better. But the ultimate thing is to put it in that container, put it in that framework that can then be digitally delivered. And that again is I come back to the, this visual execution layer, this container that can go anywhere, kinda like PowerPoint on steroids.
It has to be easiest PowerPoint, but it has to be deployable, anywhere connected, pushing and pulling information. And, you know, Gen AI at the front end of that, solving this first mile problem to get the content into that format in the first place. And then you’re able to put that everywhere.
So, if I summarize, you’ve got AI helping to generate the information and put it in a format that’s useful. Experts extracting their knowledge and wisdom using AI to author that in a way that’s consumable, that’s interactive, that’s dynamic, and then putting that into a visual execution layer.
Basically, turn that into knowledge that workers can actually use and get their jobs done and what they’re gonna do. So, I’m really hoping in the next decade that visual execution layer then unlocks extreme potential. Because instead of me going to a system of record, that by nature is complicated because it’s dealing with complicated info that when I’m ready to do something, I hit the play button, I hit the easy button, you.
And the visual execution layer comes up and understands what device I’m on. Am I on a 20 inch monitor? Am I on a 70 inch monitor with no keyboard? Am I on an iPad, an iPhone? Am I gonna be on a wearable device? Am I in an AR environment, a VR environment? And let this visual execution layer do that interpretation and basically the fusion point of the human to all this digital tech.
That’s what we’re working on. That’s what I, I believe is the future of connecting people into this loop of product process People.
Brian Thomas: Thank you, and I appreciate where you started. You had that terminology see what you mean using 3D to show the value to people. But you really highlighted that visual execution layer, and we talked, you talked about taking this beyond engineering leverage, AI.
To really dive into that info knowledge and wisdom info, using AI to collect and build that, that information knowledge where experts can extract and use that information. Obviously wisdom, putting that into a visual layer for people to see and understand. So, I really appreciate you unpacking all that for our audience today.
And Garth, it was such a pleasure having you on today and I look forward to speaking with you real soon.
Garth Coleman: Alright, I appreciate it, Brian. Thank you for the chance to share.
Brian Thomas: Bye for now.
Garth Coleman Podcast Transcript. Listen to the audio on the guest’s Podcast Page.
