Making Everyone an Expert, with Scope AR’s Scott Montgomerie

September 11, 2019 00:32:57
Making Everyone an Expert, with Scope AR’s Scott Montgomerie
XR for Business
Making Everyone an Expert, with Scope AR’s Scott Montgomerie

Sep 11 2019 | 00:32:57

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Show Notes

The old-school way to train someone for a task involves memorization, repetition, and practice, in order to make it like second nature. Not only is that time-consuming, but also, people aren’t very good at it. So why train, when AR makes it obsolete? Scope AR aims to help companies get out of old habits, and CEO Scott Montgomerie drops by to explain how.

Alan: Today’s guest is Scott Montgomerie from Scope AR. Scott is the CEO and co-founder of Scope AR, a global leader in developing augmented reality solutions and products for industrial clients focused around field maintenance, manufacturing, and training. As the pioneer of utilizing AR for industry support and training, Scope AR are partnered with technology leaders such as Google and Microsoft. Since founding the company in 2011, Scott as one of the first executives to get augmented reality tools in use by multi-billion dollar corporations. Having launched many AR firsts, Scott has become one of the industry’s thought leaders and visionaries. He’s shared his knowledge and spoken about some of the most innovative uses of AR at several leading conferences, including South by Southwest, Augmented World Expo, Unity Vision Summit, and XRDC. Some of the clients include Unilever, Prince Castle and Lockheed Martin. To learn more about Scope AR, visit scopear.com. Scott, welcome to the show.

Scott: Thanks a lot, Alan.

Alan: Yeah man, I’m really super excited. We’ve been kind of chatting offline and it’s amazing, the work you guys are doing and you’re starting to really see this uptake of augmented reality being used in enterprise. Can you maybe give people a 10,000 foot view of Scope AR, what you’re doing, and who your clients are, and what they’re using it for?

Scott: Yeah, sure. So we really view that augmented reality is a way of interacting with the world in a way that’s much more intuitive, the way that we evolved with our hands and our eyes. And so we really view that there’s a huge market central there. I think it was a stat out there that said that, 90 percent of Silicon Valley is focused on the worker that’s at their desk, using computers and screens. And there’s a vast market out there that is untapped, in these field workers that are using their hands and their eyes. And so if we can use augmented reality to get them the information they need, at the time of need, and really help them become an expert when they need to know that information. And like I said, we think that’s a huge market. So we really approach the problem in two different ways with our products. The first is a remote assistance capability. So we were the first to market with a product called Remote AR, we launched in 2015. So it was far before any of the other 30 companies that are out there today. The idea is that it allows you to communicate over video between a technician and an expert. So it’s almost like FaceTime. If you’re looking at a piece of equipment — maybe a car engine — you take your phone or a pair of smart glasses like a Hololens, and you can look at this piece of equipment and transfer this video back to somebody with expertise. And this expert can now draw on their side of the screen, and get a really good remote guide instructions. So the problem with something like FaceTime is that the communication channel is not wide enough to provide really good instructions. When was the last time you actually communicated with a mechanic over the phone or over FaceTime? There’s no chance.

Alan: Never.

Scott: Yeah, exactly. It would probably be very painful for him to guide you how to replace something simple like a spark plug. “It’s that one right there. No, to the left. No, no, the other left!” But with augmented reality, it’s a lot easier. You can just point, drop an arrow, or some other annotation, communication channel’s much more rich. The second capability is all about work instructions. We define work instructions as any type of linear instruction that can show you step-by-step how to do things. Going back to the mechanic example, now this mechanic could maybe load up some instructions for you, and it would overlay a 3D model on top of that car engine. Nice and rich animations showing that you got to take a screwdriver, undo the screw, and… It’s a really intuitive instruction. So that can be applied to anything from training, to meetings instructions, to manufacturing instructions. The whole purpose of the company is all around making everyone an expert. So either through real time guidance, allowing an expert — who understands what he’s doing — to transmit his knowledge in real time in an efficient way to a remote technician, or by loading up these instructions to provide that technician really intuitive instructions such that you might actually not even need training.

Alan: Well, I got to try something similar at the LiveWorx Conference. I pulled apart a brake. There was a brake caliper, I held up an iPad, it said “Pull the pin. Unscrew this.” And in four or five steps, I had disassembled the brake calipers and reassembled it. I have never done that before in my life. And I was able to do it. And something else that I think is amazing is, I had this RealWear device on, where I could see a screen in front of me — it was a tiny little screen — and I was able to repair an air filter on a giant John Deere tractor. I don’t know where the air filter is. I’ve no idea. But it walked me through step by step by step how to do it. And I think as we move into exponential growth, these types of technologies are not only going to be nice to have, but they’re going to be a must-have in all enterprises.

Scott: I totally agree. As businesses need to always improve the bottom line, this is the way to do it, by making your workers more efficient, getting them with the knowledge that they need. That’s a great way to make them a much better worker. Do their jobs better, and safer, and faster. There’s also some pretty massive macroeconomic benefits to this as well. We keep hearing about the aging workforce and how businesses literally can’t find good workers. And a lot of those original workers that have been in their careers for 35 years are leaving their jobs. Knowledge transfer between those older workers before they leave, and younger workers, to get them trained up as fast as possible is really important. AR really has a huge benefit there as well.

Alan: Let’s talk numbers, because it’s one thing to say “AR provides better value.” But, let’s put it this way: If any enterprise in manufacturing, for example, were to see a 5 to 7 percent increase in efficiency, that would be reason to celebrate. And you guys are seeing numbers that are 10x that. Maybe let’s talk about Unilever, one of the case studies you have listed on your Web site.

Scott: We went to the factory in Gloucester, UK, and we introduced our remote assistance application into the factory. We saw some pretty great results in reduction of downtime. The use case around this factory was an ice cream factory. The line was going down more often they’d like. The problem is, this is a clean factory; to enter the actual facility, you have to go through a clean room process that takes a couple hours. It wasn’t necessarily that fixing the line was difficult. It was that the guy that knew how to fix the line wasn’t actually there. So whenever something went down, they had to call this guy, he had to drop what he was doing, he had walk across the campus to enter the clean room, and then go and fix the problem. This was multi hours before they could even start fixing the problem. What we did is we introduced our remote assistance application. So now when they call the guy for help, the guy can start guiding these frontline technicians on how to solve the problem. And quite often the problem is fairly simple, it’s “go replace this thing” or “it’s just a fault in this switch.” We were able to reduce their downtime by about 50 percent.

Alan: You reduced their downtime by 50 percent. Now, for every minute of downtime, there’s a specific cost for that: €80,000 a month in productivity.

Scott: Yeah. And that was on that one factory line at one facility. So scaling that across is pretty ridiculous return on investment.

Alan: So 50 percent, you’re cutting their downtime in half, which saves them 80 grand a month. And your solution costs a fraction of that.

Scott: That’s correct.

Alan: Why isn’t every company doing this?

Scott: Part of challenge is that change is hard, especially the executives. They’ve been doing the same thing that, quote unquote “works,” for the past few decades. It’s pretty tough for them to buy into. “Oh, there’s this new technology that’s putting up these types numbers, are they repeatable?” Another customer similar to Unilever, I was overhearing, one of my partners would call with one of the C level execs at this company. We’d already gone through a pilot with similar numbers to Unilever. And this exec was like, “That’s great. But have you actually replicated this?” We kind of responded to them — it was the innovation team we’re talking to — “Listen, we’re seeing 50% reduction in downtime. Even if these are ridiculously far off — by an order of magnitude — this is still a very good investment and we should probably implement this across the board.” It’s just that change, it’s almost too good to be true, which is a real big problem. With one of our other customers, Lockheed Martin — I can talk about those numbers in a second — but initially when the results came back, they were far too good to be true. So much so, that they told them to go back and do it again a second time, to prove it.

Alan: You’re the second person to say this. I spoke to Mohamed Rajani from Macy’s, and they conducted an experiment with one location, using VR for sales and marketing. And they saw 65 percent increase in sales conversions. 65 percent!

Scott: Wow.

Alan: And they’re like, “something’s wrong.” So they did it with six locations, still 65 percent. So rather than roll it out slowly, they rolled it out across their entire enterprise, so now they have over 100 locations. And now their average — across the 100 locations — is still 45 percent increase.

Scott: Wow.

Alan: So the numbers are real. They may sound too good to be true, but they are true. That is the transformative power of virtual/augmented/mixed reality. This technology is the most powerful technology we’ve ever invented. It’s crazy.

Scott: It’s merging the power of computers and their vast capacity to form infinitely fast calculations and have infinite memory, with the problem solving and mechanical ability of the human race. We as humans, we’re really good at individual problem solving, but repetitive calculations, we’re not super accurate. Whereas computers do it correctly every single time. The whole reason for training is repetition, so that you can hammer something into our brain so that when you actually need that procedure to be there, it’s there. But if you can rely on perfect infinite memory of computers and then transfer that information into your brain in an efficient way when you need it, that’s the whole benefit. So it’s really– we’re becoming cyborgs. It’s essentially what this is. But it’s for the benefit of the human race.

Alan: Yeah, it’s crazy because this has the potential to disrupt the entire education system. Our entire education system is predicated on forcing people to memorize things. We don’t need to do that anymore.

Scott: Absolutely.

Alan: We can get the answer to anything, as needed, in real time, that we need them. And with the introduction of cloud computing, edge computing and 5G, we’ll be able to get answers to literally anything in context to the world around it. So I’ll be able to look at a machine with my smart glasses on, and it’ll automatically walk me through step-by-step how to fix it. That’s what you’re doing, right?

Scott: That’s exactly what we’re doing, yep.

Alan: So if that’s the case, then you’ve got Lockheed Martin, Unilever, you’ve got a bunch of other clients. They’re all doing this. Is anybody starting to roll this out at scale now? Is that the next step? They run this through into their whole system and into their organization?

Scott: Yeah. We’re definitely starting to see scale across organizations. What are the challenges with this technology? Is it so new, that you kind of have to be careful with it? If you have a pilot that goes sideways, that can derail the whole thing. With one customer we actually implemented it in, I think three factories, and one of the factories had a really bad experience. They chose a really bad use case. They weren’t really careful about what they were doing. We actually told them that what they’re trying to do was not possible. And lo and behold, yep, it didn’t work. We had really great results in the two other factories. The third one kind of derailed the whole thing. So these days, we’re really making sure that we handhold our customers to make sure that they are using it in a way that’s appropriate, and are going to have a good experience. There’s just a few fundamental things in the technology that cause problems. For example–

Alan: Yeah, I was going to say, can we unpack that, because people listening: Listen up! This is the moment! This is the education!

Scott: It’s not a one-size-fits-all technology. And I think that’s where executives are getting confused. There’s so much FUD out there. And we’re putting up these results that are too good to be true, and in some instances, they are. So, for example, if you’re using the Microsoft Hololens, if you look at a shiny surface — the side of a big beer tank — it’s not going to track, because the lasers on the Hololens get reflected and confuse it, and so you get a lot of drift. The Hololens doesn’t work particularly well outside, because the lasers get drowned out by sunlight. There’s these little gotchas of things that, unless you really have a deep understanding of the technology, you wouldn’t expect, right? When we do implementations, first of all, we work with our customers very closely. I think one of the reason why we win deals, versus our competitors, is we’ve been told that our customer support is by far the best. And that’s why we win deals. It’s because we handhold these guys. We’re not trying to grow too fast. We’re trying to make them successful. Choosing the right pilot, get them the right numbers so that they can have success, and then we can teach them how to scale this into production, so they have the best possible outcome. The last thing we want to do is have a poor experience for anyone. Through that education, we can make those people our champions in those organizations, make them successful. And really, these people can really improve their careers by becoming experts in this, and grow it throughout the organizations.

Alan: Are you seeing people in these organizations starting to put together teams specifically for XR technologies?

Scott: Yeah, we are, yeah. And it’s kind of funny, because a few years ago these teams were basically Unity developers. They hired a bunch of Unity guys to create one-off proof-of-concepts, without really realizing that a scalable solution existed. The whole reason we built our software was so that it didn’t require anybody to have to code, because coding is not scalable, it’s not maintainable. It takes months to develop a single application for one time use. Then you basically throw it away.

Alan: Yeah, I know.

Scott: What we want to do is we want to enable guys like documentation specialists and mechanical engineers to be able to create content very quickly. Something that a team of Unity developers would take two months to develop, you can do pretty much in about a day or two with our platform. So it’s much, much faster. The iterations are much faster. And you can really get into your pilot and your production a lot faster. And then obviously there’s a whole lot of production level stuff or encryption data management and all the enterprise readiness.

Alan: What are some of the costs associated, because I know that’s a question that comes up a lot when we’re speaking with customers. How much does it cost to get started? What does that look like?

Scott: You can get into a pilot pretty cheaply, five figure range. Like I said, we try to handhold our customers, with really low numbers.

Alan: Give me a number, what’s the minimum?

Scott: I don’t like disclosing private pricing publicly. [laughs] These are enterprises and–

Alan: Yeah, but like, is it a 100 grand? A 100 grand for an enterprise is nothing. So like, is it 50 grand, is it 100 grand? What would be a starting number that people have to have in mind? Because for a lot of companies we could do a 360 video for $5,000. The guy came over and told me “It’s not the same.” And they need to understand that there is a difference between this.

Scott: We can definitely get started for less than hundred grand, substantially less than hundred grand. And then at scale, yeah, it’s in the six figures.

Alan: So that’s reasonable. An hour of downtime on a machine is potentially millions of dollars.

Scott: Absolutely. One of my slides, I think, said something like $50,000 per minute of downtime. So get started with a pilot for 50 grand is nothing.

Alan: I think people need to understand that this is not just a regular investment. A lot of times companies will invest in technology that gets them marginal results, these little incremental improvements. But this is a exponential improvement on what they’re doing.

Scott: Absolutely. This is really a generational shift in technology. I think this is going to be as big as the Internet and tablets were in terms of revolutionizing how people interact with data. This is gonna be the same thing, but on a much broader scale on the manufacturing side. You go into any given factory, most people are still doing things with paper, binders with instructions. I remember I was on the assembly line at Boeing a few years ago, and they told us they have one binder, a singular binder that’s outside of the assembly area. Because it has to be one binder, because if the instructions change, you can’t have a duplicate or an old copy sitting around. That’s incredibly 1990s, so we were pretty shocked at the lack of IT in that process. So just having the ability to have an electronic version of these instructions that’s up to date is pretty revolutionary. And then being able to give your workers the information they need, contextual information is just a sea change in how these companies operate.

Alan: Yeah, I think it’s pretty revolutionary, and I think one of the questions that’s come up a lot is, people don’t want to wear glasses. But what I think people don’t understand is, in manufacturing and field service, they’re already wearing safety glasses. That’s not anything new.

Scott: Yeah. Absolutely. I mean, I do think we have a ways to go with the hardware. The RealWear device is pretty good. It’s got certainly some limitations. But for certain use cases, it’s great. The Hololens too, I think is really interesting. Can’t wait to see what comes down in the future. I’m sure there’s lots of really cool innovations coming up in the next couple of years.

Alan: I think that’s what people really need to understand, is that this technology, if you go back five years, didn’t even exist. We had none of them. Zero. There was a couple of Google Glass type things. But in the last five years we have come absolute leaps and bounds. I remember going to SBVR and Augmented World Expo three years ago, and trying some of these things. You know, there was see-what-I-see, pick-and-pack for warehousing. And it was so crap that in my mind I was like, “This is just terrible. It’s going to be 10 years before this is something.” I went back this year, and that same demo was absolutely precise and perfect and it just worked perfectly and flawlessly. I think the time is now for brands and companies to really start investing in this technology.

Scott: I completely agree with you. And if your company is not investing in this technology now, your competitors are. And so when they start rolling out later this year, next year, they’re going to start seeing these ridiculous return on investment gains. And if you’re not even building a team that’s familiar with this technology and certainly thinking about the change management aspect of it, then you’re gonna be left behind.

Alan: And we’re already starting to see all the venture capital companies, they all invested in these platforms and stuff. Now, you guys are venture backed, right?

Scott: Yes, we are.

Alan: So venture backed companies are like Scope AR. But what they are failing to realize is that content companies are actually getting scooped up as well. PDC just bought a content studio — and I believe it was Accenture or… I think it was Accenture, was one of the two, anyway — they bought a content studio recently and New York Times bought a content studio. So there’s kind of this– you need the platforms, but you also need the content, which is why we started the XR Ignite program, to get these companies ready for that.

Scott: Absolutely.

Alan: How are you finding the content creation, for what you guys are doing? Are you building custom content, or is it just– the platform serves as as its own standalone content creation system?

Scott: We can build custom content. We have a team called Creative Services Team that will generally do a quick Google concepts and consultant pilot projects for companies. As I said, part of our value proposition is really that customer support. So we really want an organization to be successful. So when they’re consulting on a business cases and use cases, the creative services team can go in there and help and creating content is part of that. But generally we like to only create a very simple project for an organization, and then we like to hand it over with our products and allow their team to start creating. So that’s been very successful. We need to handhold those creators. But that’s the only way we’re going to get scale, is by teaching people how to use this revolutionary tool. Where I kind of see this is, that this is like introducing PowerPoint in like 1985. Unless you’ve seen what a really good PowerPoint deck looks like, you you don’t even know how to use it.

Alan: You’re creating the standards.

Scott: Yeah, I think it’s more showing what’s possible in kind of best practices. We like to call our tool “PowerPoint for augmented reality,” because it’s drag-and-drop, you don’t need to code, you don’t need to hire an army of Unity developers to create your proof of concepts. Mostly it’s people that don’t know how to code that use it and it’s all drag-and-drop. Those people typically train other people in their organization. That’s how we grow.

Alan: That makes sense. So let me ask a question. You’ve got these kind of numbers on the website, reductions in downtime, and that sort of thing. What are some of the other KPIs that you guys are using to measure success?

Scott: There’s actually quite a few KPIs that we track, depending on the use case. This is part of discovery with our sales team and our customer support team, looking at those use cases to make sure the customer has success. So in a manufacturing example, we’ll look at overall efficiency. So, how long it takes them to manufacture something. So, for example, the by now famous Lockheed Martin numbers are pretty astounding. They track things in terms of what they describe as the OODA loop: it stands for “Observe, Orient, Decide and Act.” For any given procedure, about 50 percent of the time it’s that first OOD part, Observe, Orient, Decide. What that means — I’ll give you a concrete example — they’re building a space shuttle with technology, they’ve done a whole lot of case studies around a whole bunch of different procedures and torque fastening. So on the space shuttle, there’s something like 3,000 fasteners on the space shuttle. And so in the old world, they would go into a binder. They would flip to the page that had a table of each of these fasteners, and they’d go find Fastener 1. They’d memorize the torque setting from this table. They would go find Fastener 1 in the real world, and they would set their torque setting, and set it. And then they would crawl out of the space shuttle, go back to the binder, find torque setting 2, set their torque wrench, go back in the space shuttle. So this overhead of reading the manual and then going back in, crawling in, was accounting for about 50 percent. And again, this was not an isolated case study, this is replicated across dozens of case studies now.

And so what they were able to do, simply by putting the information in the Hololens. So now in the new world, the technician goes in the space shuttle. It shows the location in 3D space of the fastener number 1. And right above it is the torque setting. So now the guy sets his torque wrench, does it. Then it flips the number 2. In 3D space, it shows him where this is. So they’re seeing a reduction in that overhead that they call time-to-information. About 99 percent. So that’s resulting in about 42 to 46 percent productivity improvements. That’s one of the really key metrics we bought is reducing that time-to-information, making it so intuitive that somebody doesn’t need to be trained and doesn’t need to go back and consult a manual. It’s just right in your heads-up-display and being shown to you in a 3D context. You don’t even have to do that mental mapping of finding something in the real world. In other cases, if we’re talking about a field service example, it can be a reduction in downtime or first time fixed rates or a first time diagnosis rates. Meantime to resolution is another metric. So it really depends on the use case. We’ve got a pretty robust return-on-investment calculator that we work with our customers on for any given pilot they do. And it’s got about a dozen different metrics in there, just depending on their use case. It could also be a reduction in travel time. That’s a huge expense. If you no longer have to fly somebody out to a remote field in Alaska to fix something, that can be a huge cost savings.

Alan: It’s interesting you say that, because we had Jonathan Moss, the head of learning for Sprint on, and they implemented augmented reality training on the phone. So they– it’s for retail workers. They pull out their phone, they point it at the thing, and they learn all about the new features. They were measuring all sorts of different KPIs and the one they didn’t think to measure — which became the important one — was travel. That saves so much time and money, not having to fly people around, that it saved them millions and millions of dollars because you’re talking 30,000 people. It’s crazy, it scales really quickly when you push it out. Then they actually had one more unintended consequence of that. The people that we’re learning from on their tablets, they actually started using their learning modules to teach their customers, because they were just so good. “Let’s use it.” There’s definitely all sorts of benefits to this technology as well. And one thing you’ve touched on right at the very beginning, the aging workforce is starting to retire. And being able to capture experts’ knowledge is vital.

Scott: Yeah, absolutely. As a matter of fact, we just rolled out a feature right before the Augmented World Expo called Session Recording. So the idea is that while you’re on a call between this technician and expert, we’re recording the call, but we’re doing it another way, recording it in three channels instead of two. So recording the audio, the video and then the 3D annotations, and either the point cloud or the mesh of what you’re looking at. So that we can then replay those annotations back on the original piece of equipment. So in this way while you’re on a call between this technician expert, you’re literally in the process of transferring knowledge from a person with knowledge to a person without knowledge. And if you can record that and then use it for future workers and potentially brain into a training type scenario, that’s incredibly powerful.

I think as time goes on, we’re gonna start seeing pretty monumental shifts. I mean, there’s so many macroeconomic factors. I could talk for hours about this, but one of the big ones is that previously — let’s call it 10 years ago — customers used to buy an engine and they own the engine. And any maintenance on it, they paid for all that they had to do. So they would probably call up the engine manufacturer and get support and they would pay a pretty penny for that support, 250 bucks an hour or something like that. And so for the manufacturer of that engine, if it broke down, it wasn’t their problem. In fact, it was actually a profit center for them to send out their technicians to go fix their faulty engine. But these days, the whole business model has shifted. They’re buying horsepower. They’re not buying furnaces, they’re buying BTUs. So it’s almost like an SLA type model. And so now when something goes wrong, it’s up to the manufacturer to go out and service that. Now it’s a cost center. What this means for the workforce is that previously, because of the profit center, if you had an older worker and a younger worker, it would make total sense for them to go out to the fields and work with each other for six months. This young apprentice could learn tons of stuff on the job. But now it’s not really economical. You want to shorten those training times because it’s a cost center. That means that these younger people in the workforce are actually getting less trained. We can’t bring in this technology soon enough, just because of so many different factors.

Alan: It’s pretty impressive. Of all of the interviews we’ve done, you’re episode 40 of the XR for Business Podcast, and it’s such a varied group of people, and training and real time collaboration comes up in almost every call. So it’s interesting that you guys have been doing this– you’ve been doing this since 2011, right?

Scott: Loosely. Really, we started taking it full time in about 2015.

Alan: How did you end up saying, “Oh, I’m going to make smart glasses for the future of manufacturing?”

Scott: It was a bit of a windy, twisty tale. I developed some computer vision technology in 2010 for a previous endeavor that didn’t pan out. I thought this might be cool to apply to augmented reality. So my first ambition was in marketing and advertising. And of course, even today we’re not seeing a whole lot of penetration in working in advertising in AR. I was trying to recognize billboards and magazine covers and stuff. At the time I was in Edmonton and I was going to Toronto trying to work with advertising executives now like, “Yeah, I don’t see the use for this.” We landed a couple small contracts, but really the big break was a big industrial company came to us and said, “Hey, we use this for training.” We thought, “Oh, that’s a cool idea.” So we did a quick proof-of-concept for them. And this was on an iPad 2 back in 2011. They thought it was amazing, but we really wanted a pair of AR glasses. They said, “Here is a big pile of money. Go buy every pair of AR glasses on the market. And if nothing’s suitable, then build some..” So we ended up randomly meeting with Epson at the time they had the Epson BT-100s, which didn’t have a camera on them. We went to the project manager and I said, “hey, can we hot-glue a camera on there?” And they said, “Yeah, I don’t see why not.” And so we ended up doing was build these glasses, where we hot-glued this webcam on it, the webcam ran to a laptop where we did the computer vision calculations, and then we used the external monitor plug and hacked to get this cable and hacked into the operating system of the glasses to accepts this video. And this was kind of one of the proof-of-concepts of the first AR glasses.

And so we showed this at a trade show in 2012 in Las Vegas. It’s this giant mining trade show that only happens every four years. And it was a bit of a novelty for this organization. And we had center stage. It was an amazing location. But we were only supposed to show the demo like three times a day over three days. And we ended up showing it over a hundred times. And every time we showed it, it was crowded by about a hundred people around me like, “Oh my god, it’s the coolest thing ever seen. This is going to revolutionize training.” And this one guy’s story kind of sticks out: he says, “I’ve been maintaining this exact piece of equipment for my entire career — it was like a quarter million dollar rock drill — maintained this for my entire career, 35 years. I’ve probably shortened the lifespan of this equipment by half by doing it the wrong way. I’ve trained hundreds of other guys to do it the wrong way, and so I probably cost the company tens of millions of dollars. So now I’m on my own. I really need this technology. How do I get it?” And we kept hearing this type of story from a ton of customers. So the lightbulb kind of went off, like “Oh, wow, I think we probably found something here.” Early on, we really didn’t know– I mean, just like yourself, you didn’t really know what to build. But we started getting contracts from guys like Boeing, and Toyota, and NASA to build out proof-of-concepts. And through these initial proof-of-concepts we realized that, “Oh wow, yeah, this is gonna be the future. A scalable platform is the way to take advantage of this technology. We could potentially be the PowerPoint of augmented reality.” In 2015 we all decided to go full-time. The tea leaves were changing. Google Glass had launched, ODG had a pretty good pair of glasses at the time. We thought this time the market would be ready to go, by the time it gets going. Here we are.

Alan: It’s funny. I thought I was OG. I got in in 2015. I was like, “Yeah, I’m the OG.” But you are like, you’ve been in it. Before we get going. If you could say to any customer “here’s the first step you need to do,” what would that first thing to do, so that they can start leveraging this power of this technology?

Scott: I think the first step is choose somebody who has been in the industry for a while and really understands what they’re doing, and can identify that use case to make you successful. You know, if you’re out of innovation teams, which is where we typically like to work these days, is, you know, a VP or somebody that really wants to implement this at scale, get in touch with someone and get started. Try really quick POC as fast as possible, just get some initial metrics, see if it works, and then start thinking about rolling this out. The sooner you get started, the better. It’s going to take time to get people comfortable with technology, with how to create it and where it’s best applied. A company like ours can really help get you started in rolling.

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October 20, 2020 NaN
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From Racing Games to Impaired Driver Simulators in VR, with Talon Simulations’ Brandon Naids

Talon Simulations was making great strides in the location-based entertainment industry, until COVID-19 hit. Now they’re pivoting the technology to suit more training-based use...

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September 29, 2020 NaN
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The Right Time to Invest in VR, with MetaVRse’s Alan Smithson and Alex Colgan

Avid listeners will have noticed a few weeks without a podcast - that’s because Alan’s been hard at work behind-the-scenes building capital for several...

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December 09, 2019 00:26:37
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Using XR to Enhance the Hardhat, with Trimble’s Jordan Lawver

It might seem like a small, even simple fix, to attach an AR device to a hardhat, but according to Trimble’s Mixed Reality expert,...

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