字幕表 動画を再生する 英語字幕をプリント [MUSIC PLAYING] MICHAEL PORTER: Today, at this moment, there is a major inflection point just starting to get underway, which is going to affect not only competition and productivity in the economy, but it's also going to affect humans and our role, and how we work in society. Where we've come from, really, has to go back to a world in which products and machines were physical. They were mechanical. Information was collected manually and stored in paper files. But then, starting in the early '60s, what we like to call Wave 1, was the advent of computers in the early '60s, which allowed us to start automating various processes across the value chain. And those computers not only allowed us to do the process more efficiently, but also to collect and gather and analyze data in quantities that we'd never ever had opportunities to do so before. But then we started moving into Wave 2, and that was driven by the advent of the internet. We were able to start linking the parts of the value chain, connecting the dots. But the really big wave, the one that's going to be the most significant in the long run, is Wave 3, which is the advent of what we call smart, connected products. And that's created a lot of improvements in productivity and capability of products and the value that products can create. But it's created, now, the next big problem. The amount of data available is just overwhelmingly greater than ever before. How do humans actually access and utilize all this data? We get data on 2D screens, flat screens. And then we got to figure out how to translate it into the real world. Bridging the gap between digital and physical is taxing. A great example of this problem is illustrated here. We have a GPS screen in our car, and then we have to look up at the real world through the windshield and try to figure out how to take what we see on the screen and actually make it real, in terms of, should we turn here or should we turn 100 feet up the road. And of course, as we're looking down at the screen and looking back and trying to figure out what to do, we make mistakes. We're distracted. Hopefully, we won't have an accident. Well, to solve that problem, we have to take advantage of the senses that we humans have. The powerhouse of our senses for gathering information is sight. When we look at a room, we get massive amounts of information instantaneously. The problem now is that the digital interfaces we have today are really not maximizing our most powerful information source, which is our sight. Augmented reality is a set of technologies that allow us to actually take the digital information we have and the choices we have, and actually overlay them on a human's view of the real physical world in real time. What you see here is, the information is not on the 2D screen on your dashboard in the car. In heads-up display, the information is actually overlaid on your windshield. It's projected on your windshield. So you're looking at the real world. You're not having to look down and up. You're seeing what you need to know overlaid on the actual real world, where you're going to have to make the choice about what to do about it. And this just massively improves your capacity to assimilate and process this information. JIM HEPPELMANN: It starts with physical things. And if these things are smart and connected products or smart and connected operations, that means they're streaming data up to the cloud. We now have a way to interpret the sensor data. And quite frankly, we could send control commands back down to the objects out in the real world. But when we're looking at the data, we're not looking at the physical world. And when we're looking at the physical world, we're not really looking at the data. What augmented reality does is it brings this data down into devices. Then, what I see becomes augmented with information coming down from the cloud, from this digital twin, and illuminates digitally what I see physically. Now, it's hard to conceptualize AR, and it's actually pretty easy to demonstrate it. Say I want to interact with this motorcycle. The software, looking through the computer vision technology, can see that motorcycle. This would work fine with a real motorcycle. It's just a little difficult to bring the real motorcycle into the room here for this event. You see it's actually morphing between digital and physical. Now it's a 3D CAD model of the digital twin. Well, what could I do with this? Well, I could do a sales and marketing use case. And it says, Jim, let me tell you about the features. For example, here's what you should know about the motorcycle. It has the 1190 RC8 engine, and it's highlighting the engine in the details. But let me switch to our end user view. So now I'm the owner of the motorcycle. And I might say, for example, tell me the status of this motorcycle. And it's using IoT or smart, connected product data now to map a dashboard onto the motorcycle. Now, if I just use my hand here to move the motorcycle, you see that the data is literally attached to the motorcycle. So it's communicating to me both physically and digitally at the same time. Now, a service technician might use this idea and say, help me assess the condition of the product. And it uses some data that's coming down from the cloud, some analytics explaining what the problem is. And then I might say, well, why don't you show me how to fix it? And it gives me a procedure here, where you see the rear wheel, some bolts are coming out and, the caliper is being removed, and then the axle nut is coming out. The axle itself gets removed. And then finally, the rear wheel will come off. Using the camera, the iPad could see the physical motorcycle. And it said to the cloud, tell me what you know about that motorcycle. And the cloud gave me a way to visualize, for example, how much gas, how much fuel, what's the temperature, to instruct somebody in the operator sequence or a repair sequence. It allowed me, potentially, to interact with the motorcycle. I could have said start, and maybe the motorcycle would have actually started. But anyway, a very powerful way for a person to interact with the physical and the digital in the very same integrated, visual experience. There was no cognitive distance, no cognitive load in trying to understand what was happening there. PTC did some studying of our industrial customers. And we asked them, what are you using augmented reality for? And the percentages here actually showed the distribution of use cases across design, manufacturing, sales and marketing, operations, service, and training. So that tells me that this technology has the potential to impact practically everything that a company does. What we found is that most companies are reporting 30% to 50% improvements in human productivity for operations that can be guided and optimized with augmented reality technology. So smart, connected products is really about digital technology that makes the product better. And now we're talking about technology that makes humans better. And that's a great segue, I think, to what you want to talk about, Michael. MICHAEL PORTER: Well, thank you, Jim. And as all of you have seen, there is much to talk about here. But let me step back a little bit from all of this technology and all of these business applications to think a little bit more broadly about what AR might mean, actually, to how our society evolves. The capacity and capability and optionality of machines is dramatically improving. But as we discussed, it's very hard for humans as we are to actually access the power in the data and the capabilities and the analytics of these supercharged machines. And that is kind of limiting the access of humans, particularly those that don't have computer science degrees and engineering degrees to actually access this digital transformation. They're kind of getting left out. But what we know and from careful study is that, actually, humans have unique advantages. Humans can come up with new ideas. They can change the frame of reference in thinking about something. If you're playing checkers and then you turn to chess, the human can easily switch from checkers to chess. A human can kind of fix or repair any part in a machine and not have to be programmed to do that. We have these enormously powerful capabilities. But it's been very, very challenging so far for the humans to take advantage of the increasing power and productivity advantage and optionality of these new powerful machines. Augmented reality is the great equalizer. It is going to create a balance between what the machines can do and what the humans can add, by making the humans able to access the power of the data and the analytics and the machine advantages. AR also is transformative of the whole process of education and training. We've been sitting in a classroom. Now, we can actually work with real objects and participate in this digital transformation that's well underway. AR is both a profound next step in transforming competition in business, but it's also going to be, I think, a very important force in kind of resetting and reenergizing the capability of humans to really participate in the economy, something that we've been losing over the first decades of the IT transformation. And so in that sense, it's very, very encouraging. [MUSIC PLAYING]
B1 中級 米 ホワイトボードセッションすべての組織にAR戦略が必要な理由 (Whiteboard Session: Why Every Organization Needs an AR Strategy) 30 2 歐小拉 に公開 2021 年 01 月 14 日 シェア シェア 保存 報告 動画の中の単語