Hands-free AR devices like those made by Kognitiv Spark are changing the way we work by helping us all work smarter, not harder. CEO Yan Simard drops in to remind enterprises shy to get started enhancing the workplace with XR technologies will — should they wait too long — be left in the dust.
Alan: Welcome to the XR for Business Podcast with your host, Alan Smithson. Today’s guest is Yan Simard, the CEO of Kognitiv Spark. He’s designed and led many innovative business ventures through his own startups. He also has extensive professional experience with companies such as CGI, Zaptap, Vision Coaching, AIS, Incite Wellness, Bell Canada, Industrial Alliance, and more. I’m just going to read this quick quote from Yan. “We believe that mixed and augmented reality, if used right, can not only allow frontline and field workers to stay relevant, but make them more crucial than ever before.” With that, I’d like to welcome Yan and it’s kognitivspark.com.
Yan, welcome to the show, my friend.
Yan: Thanks, Alan. It’s a pleasure to be here.
Alan: It’s my absolute pleasure to have you. And I can’t wait to dive in here. Maybe just give us a 10,000-foot view of Kognitiv Spark and the great work you guys are doing there.
Yan: So Kognitiv Spark, we do mixed reality communication technology to better provide support to our remote field workers. Our product is called RemoteSpark. It’s an application that has been optimized for the Microsoft Hololens platform. In a nutshell, what it does if you have a field worker that is facing a piece of equipment that stopped working and that worker doesn’t know what to do, that worker can put on the Hololens, start RemoteSpark, and communicate with — let’s say — an engineer at the head office that can help out. The engineer, through a computer, is able to see in real-time what the worker is seeing. They can talk to the person, but they can also provide 3D holographic guidance on top of things. So as an example, if they have a 3D CAD file, that could help the worker figure out what are the steps that need to be done to perform a repair, the expert can drag and drop that on the computer side of things, and the CAD file is going to show up as a 3D hologram in the field of view of the worker, so that the worker can perform the repair.
Alan: So if a field worker’s either in a factory or a warehouse and they’re looking at a machine, the machine breaks, why don’t they just pick up the phone?
Yan: Yeah. And while most of the time that’s what they do right now, the problem with phones — or even tablet-based chat systems, or phone-based ones — is that you have to hold something in your hand, so you can do the repair or do the process or the task that you have to do, at the same time as you’re getting the information and the knowledge. So it’s always a two-step process. With mixed reality, you can just do it all together at the same time. So they’re doing the work, they have their hands greasy and dirty, and they getting the knowledge at the same time. So it’s much more efficient. And also, there are many studies that show that in terms of knowledge retention, it’s about 80, 85 percent higher when you learn about a given task at the same time as you’re doing it with your hands.
Alan: If you look at this from an ROI standpoint, what is the investment to get started with Kognitiv Spark? Obviously you need a Hololens. So that’s, call it $3,500. And then what else do you need after that?
Yan: Yeah. So our software is a service one, and we have two offerings. One is on public cloud, the other one is on private cloud. Most of the time we sell the public cloud version of it. It’s a yearly fee of $6,000 a year — Canadian — to activate one Hololens unit. So you can have as many remote experts as you want on the computer, but our economic basis is the Hololens unit.
Alan: Great. And so somebody sends up, they pay their thing. What is the onboarding, I guess? How do people get started with this? Is it out-of-the-box, ready-to-go, or how does it work?
Yan: Yeah, when it comes to deploying with a customer, the technology side is very easy. Our application is available through the Microsoft Store and we can activate the licenses remotely. The ramp-up is really getting used to mixed reality in general, and then our app. So I would say our experience shows that typically the user is ready to go within 30 minutes. And I’m talking about somebody who has more experience whatsoever about mixed reality or the Hololens, to the point where they are comfortable enough to get in the field and try it out.
Alan: That’s fantastic. So now, do you got to go into the field as well and work with these people to get this up and running? Or is it just a software-as-a-service, buy it, and that’s it, you’re on your own?
Yan: We don’t have to go. We tend to like to go when we have a chance. And the reason why is that we’ve discovered that to make our customers successful in the long run, typically for a very hands-on, very involved at the beginning, helping them out, figure out their 3D holographic strategies and mixed reality strategies, and it sets them up on the right foot for future success. So we typically try to get involved, especially if a customer is doing a proof-of-concept with us, or something like that. We just get there on the ground whenever we can, or we’re just there supportive as well remotely. And then after that, they’re all set to scale and grow with us, which is great.
Alan: How many deployments have you done of this, or is this a new thing? When did you start doing this?
Yan: So we launched the alpha version of a RemoteSpark in the fall of 2017. I’m not going to disclose the number of active customers we have, but it’s tens of different customers in North America, Europe, and Asia. We tend to work with Fortune 500 companies, as well as some small and medium businesses. And the initial deployments we do are always proof-of-concepts or pilots. But there’s always that vision to scale to hundreds or thousands of units over a period of, I would say one to two years.
Alan: You’re perfectly timed and situated for that, because I’m assuming — and we’ll talk more about this in the podcast — that the benefits of using Kognitiv Spark over, let’s say, phoning it in or whatever like that, I think the benefits are probably quite measurable and quite substantial. How do you measure success for a company? How do you prove them the ROI?
Yan: Yeah. The ROI in our case is fairly easy. So customers buy our product for three reasons. The first one is they want to cut down on equipment downtime and that’s typically very quantifiable. And also you can train, translate that into dollars. Your typical industrial use case, any hour of downtime is going to cost thousands and tens of thousands of dollars. The other thing that we sell on is that when we’re saving experts, the trouble of travelling onsite to do troubleshooting. It also has a very direct impact on the bottom line. So we saved up your travel costs as well. But also that expert now has more time to devote to a high value add tasks such as helping people out, figure out what’s going on, instead of travelling. This one is less quantifiable. Companies have to take the industry 4.0 journey and get going. And they find that using RemoteSpark is kind of a great way to get started with mixed reality, with something that you can still sell to the CFO and to the procurement team and they will say, “OK. So that makes sense. It’s not only wishful thinking. There’s action an ROI right from the get-go.”
Alan: Great reasons to buy: 1, cutting down downtime, I mean, that one alone, if a machine’s down for a day — depending on the machine — but you’re talking in the tens of thousands, to hundreds of thousands, perhaps millions of dollars. And I know one of the customers or a couple of the customers that you have are in the defense and military sectors. These could be life or death scenarios. So definitely cutting the downtime to a fraction is a huge measurable ROI. And I think also it encourages brands and companies to really be pushing the limits. This technology’s not really that new anymore. We’ve been using– Hololens came out five years or four years ago. And so now it’s becoming mainstream. I almost feel that we’re getting to that point where if companies don’t use this technology, they are seen as laggards. Is that what you’re seeing in the field?
Yan: I think there’s a growing sense that they have to do something. And one of the things that we like to tell customers that are kind of hesitant that prefer sometimes to be smart followers, is that there’s a cost to not getting started now. And the cost of not getting started is to not be ready for when these things go mainstream. Because we have to think that the technology is now getting fairly mature. What is not mature is how it impacts the way people are running their businesses, how it changes a process that a worker is going in, day in, day out. So that takes time to figure out, and to be able to start now, I do a solid proof of concepts learned from them. It gets organizations ready for when the tide comes and when everybody will have to do it, because they will lose their competitive advantage if they don’t. So I think you’re right. There’s a growing awareness that you have to do it now.
Alan: Yeah, there’s a groundswell coming, and the interesting thing about the timing of this is that you’ve been working on this, you said you launched 2017 your alpha. And you’ve already got two years into this, and you guys have presumably made a lot of mistakes. Which we all do in technology, you build something, you go, “Oh, that didn’t work.” And having that experience of working with customers from the early days, I think is going to really position you guys quite comfortably as you move into this place. You’re looking at this from boots on the ground. You’re seeing companies start to work with it. We’re in Canada, so we’re a fast follow nation in general. We see America do something and then we wait. But being in candidates, it’s much more difficult to sell these concepts in. But you’ve managed to do that. What are your timelines around seeing mainstream adoption? Not in consumer, but in the industrial world? What do you think? We’re looking at timelines before this is in every company.
Yan: I think people will start hearing about that in pretty much any big industrial company within the next 12 to 18 months. And I think one of the triggers of that is the Hololens 2. I really believe that the form factor of that new device and its performance will make it interesting for more companies to deal with. Now, it’s not going to be at scale within that timeframe, don’t get me wrong, but it’s going to be that awareness phase, where the everyday industrial worker will be aware that some guys sometimes are just walking around with those weird glasses on their heads. And if you had another 12 to 18 months, that’s probably when it’s going to become just normal to see people with mixed reality glasses on their heads. Now, these are only the industrial world figures, so–
Yan: –consumer is going to take probably more time. And I don’t think there’s yet any compelling use case for that on the consumer side. On the industrial side it’s quite different.
Alan: So let’s say 2020 and 2021, the awareness starts to build, the groundswell is there, people start wearing these headsets. 2021, -22, -23, we start to see this kind of mainstream adoption within enterprise. And then 2023, kind of beyond is– nobody really can see out that far at this point. But look at 2023/4/5/6. That’s I think where it’ll trickle down to the consumer. Being in that enterprise, you’re working with military, you’re working with the fence, you’re working with industrial. One of the videos on your website really blew my mind. It was a huge room-sized centrifuge. You want to talk about how that’s being used?
Yan: Well, in that video, what we show showcases is our typical use case. So you have a very complex piece of equipment in that case. It’s the largest geotechnical centrifuge in Canada, which is in Newfoundland. So a massively-complex piece of equipment. The subject matter experts and the OEMs are all across the world, so some are in Germany and France and so on. So when that thing decides to not cooperate and breaks down, well, it can take weeks to get the right expert to address the problem. Now, with something like RemoteSpark, you can have the technician onsite wearing a Hololens, and you can have any subject matter expert anywhere in the world, even in other companies that are able to help them out in a timely fashion. It can take situations that would take weeks to address, and cut them down sometimes in a matter of hours.
Alan: I had a chance of speaking with Shelley Peterson from Lockheed Martin. And they’re using the Hololens almost in the exact same way: they put on the Hololens, they’re able to see step by step instructions with 3D objects overlaid over to the real world, and they’re able to have their hands free. Now, one of the things that she was saying that on their original trials, they actually reduced the time to do the task by 99 percent. And then they, obviously being a big company, they went “That doesn’t make sense.” So they ran the test again, and they ran it again and again. And the average was 85 percent reduction in times to completion of task. And if you think about it, if you’re assembling — let’s say, for example — a jet engine or a centrifuge, and you’re looking at it, and you’ve got a paper manual, and page by page you have to flip the page, look at the manual, go over, pick up the screw, put it in, lock the bolt in, go back to the page, check it off that you did it, next page. And so one by one, you can do that. And that takes a long time. But when you put on the Hololens, not only are you able to then get the instructions and fix it, but it’s also able to capture photos and videos of you doing that, for either future manuals or even just a record of the repair. You guys have that ability to capture that as well. How is that being used, that kind of expert capture?
Yan: Yeah, well, it’s used in many ways. It might be about producing artifacts to document an inspection. It can be sometimes if you want, we can dig a picture of the video of what the work is looking at, annotate that on the computer side of things, so the expert side. And then the annotated picture shows up in 3D at the other end. So it’s all about really empowering the worker to do the job right the first time, every time. And in the examples you gave — and I think that’s what we’re seeing as well — sometimes it’s about empowering a technician that just doesn’t have the knowledge on how to do a repair, to be able to do it. And I can give an example. We have a customer in the US. It’s a very large utility. They have a certain type of furnace. So it’s a blast furnace that is quite widely used in their business. And it breaks down quite often. The repair itself is not super complicated to do, but the people that know how to do it are not that many. So they built a CAD file and a 3D model, that has the embedded process on how to perform that repair. So if something goes wrong with that furnace, any technician that has access to a toolbox and is reasonably good with their hands, they can go there, follow the step-by-step animation, and do the repair. So, in that case, you were talking about the reduction on troubleshooting and on task performance. That’s where it comes from. It’s allowing the person that would not otherwise be able to do it, to do the job.
Alan: I think as we move into a time where more and more people are retiring from the workforce — the average workforces in their 50s now — and more and more experts are retiring, there’s got to be a way for us to capture that knowledge and then transfer it to younger generations. So I think this is a great way of doing that. What are some other ways that this technology is being used? Are there any companies that are using this in ways that you didn’t anticipate?
Yan: Yes, sure. We get all kinds of requests all the time. So we sell mostly in defense, aerospace, energy, utilities, oil, and gas, manufacturing, industrial engineering. So it’s a fairly broad field. But we may get requests every now and then, that are just outside of what we normally do. So our technology, as an example, is used to perform repairs in the Canadian Arctic, in very remote locations — that happen to have Internet connectivity. We’ve been approached as well for remote medicine, so how to help a nurse in Labrador assess a patient and help a patient, provide care with the help of an expert maybe in Toronto or somewhere down south. So there was another one that I mentioned. And actually this one that we’re building it with a partner, so using RemoteSpark, we’ll be able to allow workers in nuclear plants to be able to — when they go in the room that is exposed to radiation — be able to see a radiation cone coming out of a hole in the wall where radiation is coming from. So that helps a worker behave more safely, make sure that they do whatever they have to do with getting as little exposure as possible.
Alan: Is that a partnership with [Shachar] Weis? From Packet39?
Yan: No, sorry. This one is a partnership with Canadian Nuclear Labs.
Alan: Oh, because there’s a gentleman — I’m interviewing him later this afternoon — that has built a Hololens CONE OF RADIATION. So, I’ll make an introduction. [laughs] What are the odds that we get two people working on nuclear visualisations in one day?
Yan: Yeah, well, it’s one of those fields where there are plenty of very compelling use cases and where really worker safety, is at risk. So any chance we have to make it a little safer and a bit more efficient for workers is always worth it.
Alan: I’m going to switch directions a little bit here. What are some of the analytics you’re able to gather around this? So, for example, I’m fixing a machine. How do you measure before I use the Kognitiv Spark system, and after? What do you do from, like, an A/B testing, so that you can say to our customers, “we’ve improved your process by X percent?”
Yan: Yeah, we typically try to establish a baseline with all the customers we’re using, especially if they’re running a pilot where they have to demonstrate a certain KPI to be able to get further budget. The way we do it, we try to see if they have data in an ERP system or work order processing system of some kind. They may have an IOT platform as well, so we can connect with those platforms. As an example, if you have an ERP system that’s generating the work orders, it will typically include a component about time to resolution or completion time and so on. So we can connect to those systems. So then when the work order is open, the workers on-site, they will work harder and might be displayed in RemoteSpark. They do whatever they have to do and then they mark it complete. So in that case, it’s a very quick way of showing that for a certain category of tasks, if you run it a number of times, you’ll be able to demonstrate as a percentage what’s the improvement. And we kind of have to customize that each time we work with the customer. So sometimes they don’t have such a system, it’s more tracked in an Excel spreadsheet or things like that. But we’re always trying to make sure that we understand what we’re– what they’re trying to achieve. And again, it’s time to resolution, cutting down equipment downtime, cutting down on travel for experts. That’s our bread and butter, really.
Alan: Travel time’s a huge one as well. The first time I heard about this, this being used, they were explaining how a machine will go down and they’ll fly in two experts from Germany to fix this machine. It was a specific mining machine. And they say it takes two days for them to get there, machine’s down for a day before they even get there, then it takes two days to get there, then they spend a day repairing it, and then they fly back. And so the whole process is four days or five days. But three of those days is downtime for this machine. And they said every day of downtime is $150,000. And I mean, that’s– I’m assuming and certain in oil and gas and manufacturing and nuclear, that can range from tens of thousands of day to millions a day in downtime and productivity. Not to mention just the travel costs alone of flying two people from Germany. That’s in the tens of thousands of dollars, plus their time. So the cost savings in one downtime repair more than pay for your $6,000 a year license, plus $3,000 for the Hololens. So call it $10,000 with everything in — call it 20 — and you’re still way, way ahead with not having to travel one expert on location, is that correct? Your license is $6,000 a year, plus the Hololens of $3,000, so that’s 10. Plus another 10 days to set it all up. So call it $20,000 a year. If you look at that, it is a very small amount compared to even an hour of downtime on some machines.
Yan: Yeah, absolutely. One comment that we hear all the time from customers is they will tell us “If we use RemoteSpark once or twice in a year, it’s paid for many times.” So we’d like for our customers use it more often, but some are super happy to use it only once a month, because it’s just going to be a highly critical situation, or one of those situations where the costs are running so high that any way they can cut it down, it makes planning sense.
Alan: [chuckles] I mean, it just– when you do the dollar figuring out– and I think this is one of the problems with virtual and augmented reality, mixed reality over the last couple of years. It’s been this crazy hype cycle of, “Hey, look how cool this technology is. You can put the Hololens on. You can see a machine, and you can look at the holograms. Look how cool it is.” But nobody in business cares about how cool things are. That’s nice for a minute. They go, “That’s great.” But then when you start to say, “Oh, and by the way, it can save you tens of thousands of dollars a day. Every day you need this, is a day you’re gonna save $10,000.” And I think this is a wonderful way of positioning this technology. And the fact that companies like Boeing and Lockheed Martin, the fact that they’re realizing the benefits of it and not only realizing it, but also sharing it and allowing companies like Kognitiv Spark and you to come on podcasts like mine and writing articles, I think it’s really starting to make it– the awareness of this technology around the world is starting to take off. And it’s gonna be a matter of time before companies realize, first of all, the benefit. Second of all, if they don’t do it, they’re actually at a competitive disadvantage. What would you say to companies that are saying “We’re going to wait and see”? What do you tell companies when they want to push this investment down the road a bit?
Yan: Our message is always that if they want to be ready for when the market goes crazy with mixed reality, now is the time. It’s not just a widget you buy; you buy a technology that will change the way you are doing your work. It changes the way we run business. It’s the human element, really, and the process element that takes time to figure out, not the technology. So the sooner you can figure out what are those problems that you will be facing when you try to scale, the more equipped you will be when it’s time to do so.
Alan: Is there anything else you want to share, on the adoption side of things?
Yan: Yes. There’s one thing I’d like to share. There’s a reason why Kognitiv Spark is doing probably better than most when it comes to sales and revenue. Part of it is that we developed a product that works really well. But also we really took the time to understand what are our customers’ constraints. I’ll give an example. There are three reasons why people pick us, instead of some of the other options on the markets. So first of all, we are the only company that can do real 3D communication. So it’s not a 2D communication that includes 3D elements. So we’re still — as far as I know — the only company that can do that. The second is security. So we baked in security end-to-end right from the get-go. It’s not an afterthought. It is because customers told us right from the get-go, it’s got to be secure, otherwise I will not be able to make it past my CISO. And the third point is bandwidth.
Recently I asked our director of customer operations, “Can you tell me how many of our customers are dealing with bad or inconsistent bandwidth on the worksite?” She gathered data, and their response was 100 percent. So RemoteSpark is famous for being able to work on very bad bandwidth, like 256k. We can actually run calls at 128 sometimes. While the closest competitor we have are probably two megabytes a second. Well, on industrial sites, two megabytes a second is a luxury, it almost never happens. Because the place is full of metal equipment, there’s going to be dead zones and so on. So 100 percent of our customers deal with that. And we baked that in — again — right from the get-go. So we have to get out a lab environment — where we have ideal bandwidth and stable bandwidth — and get in the real world and see what people are facing. The mixed reality and the XR field as a whole, sometimes we have a tendency to just stay in our clean offices and not get in the field. I think that the field as a whole would gain a lot by just having different players talk to customers more often.
Alan: I think it’s interesting that when we build stuff in MetaVRse, we do the same thing. We have an iPhone 11 and the Samsung Galaxy 10, and we’ve got all the newest phones, and then we’ve got a collection of all of the phones back to iPhone 5 and 6, and we test them on different bandwidths. This is vital and you guys are focused on one device — being the Hololens — which technically uses a lot of bandwidth. But you guys have managed to make that a non-issue, which is wonderful. And I think you definitely nailed the three things. And it’s funny, because as you were talking about bandwidth, you cut out. [laughs] And so we have to deal with this, we have to deal with the fact that bandwidth comes and goes. And especially with a VR or an AR headset on your head, you run the risk of making people nauseous if you don’t do it properly. So I think that’s wonderful that you guys have thought of that. What is the most important thing that businesses can do right now to start leveraging the power of XR?
Yan: The most important thing to do is to just get started. Learn from it. When I mean get started is just not buying a few units and trying it out again in a lab environment. Get them to the field, get them in the hands of workers that are going to be the end-users and the adopters of that technology. And listen to them, listen to what they’re going to tell you. Being able to listen to those lessons learned early on is going to be what dictates the future success of XR initiatives in business, as far as I’m concerned.
Alan: Now, what is the best business case of all of the things that you’ve seen? What is the best business case, the one that drives the most value that you’ve seen in the last little bit?
Yan: There are many that are pretty good, and obviously I like ours a lot, because we have that clear ROI each time we’re using it. I think I would mention something that we did with the Royal Canadian Navy. We developed our offerings so we put RemoteSpark in a private cloud environment, so that if you have a navy ship at sea and you want to run a call between a mechanic doing some work inside the ship and the ship’s head engineer that is on the front deck, you’re able to run the call within the ship, even if you don’t have Internet connectivity at all. For me, the reason why I really like this one is that there is the time of resolution being able to — in that case — not have production downtime, might result in saving lives, might result in a better outcome for that ship as a whole. So I think there is that emotional component to that use case, even though really RemoteSpark is used in that setting the way we use it anywhere else,.
Alan: This technology is saving lives. That couldn’t be more important. My last question, Yan, is what problem in the world do you want to see solved using XR technologies?
Yan: Yeah, I can tell you a story about this one. We use that as inspiration here all of the time. We all have people in that we know — family or friends — that are an older generation of workers that maybe didn’t go to school as long, that are good at what they’re doing, they’re manual workers. But sometimes they feel left behind by technology. So digital transformation hasn’t impacted the way they’re doing the work. And now we live in a world where change is always faster, and more often and more disruptive. You know, whether it’s AI and disintermediation and automation, all those things, these people feel threatened. And what I’d like to see happening with mixed reality is that if we can empower those workers to not only stay relevant, but be even more relevant than before, just by getting them access to the right information and the right knowledge and the right experts at the right time in the right format, I think that we can serve millions, if not billions of people around the world with that technology. And it’s all about making a human shine. I don’t want to see AI shine. I want to see AI work for humans. And I think that’s what XR can do.
Alan: Amazing. Well, that is a wonderful way to wrap up this conversation. Yan, are there any last words that you want to share with the listeners?
Yan: Well, I’d like to thank you. I think it was a great chat. It’s an exciting field. We’ll see more and more companies do great things. So my advice and my last words are: feel free to experiment. Try things out, fail fast, and make it better. [chuckles]
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