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Innovation at Work: The Opportunity for Digital Factories

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Digital factories offer manufacturers critical benefits of efficiency, innovation, and stability — but they're only truly effective if they are designed, built, and operated thoughtfully. In this first session of the Digital Factory Symposium, you'll hear from top leaders about the opportunities they see for companies who are implementing a digital factory. *This session is part of the Digital Factory Symposium, a learning pathway and networking experience on Wednesday, October 16. To see all related sessions, select the "Digital Factory Symposium" filter. If you would like to attend the private welcome reception on Tuesday, October 15, please email DigitalFactoryAU@autodesk.com.

주요 학습

  • Understand the industry trends and challenges influencing manufacturing
  • Gain insights from industry leaders about the opportunities of digital transformation
  • Learn about the critical aspects and best practices of implementing a digital factory

발표자

  • Stephen Hooper
    Stephen Hooper is Vice President of Design & Manufacturing software development. Stephen has over 26 years of industry experience working for companies ranging from suppliers of industrial machinery to a software vendor of market leading solutions. Stephen started his career as a mechanical design engineer working in the UK and later relocating to the US to work for Autodesk. Experienced at every stage of the product development, marketing and sales process, from end user, through to software vendor, Stephen relishes the challenge of working in a fast moving, growth orientated environment, targeted at servicing the needs of high profile customers and partners.
  • Jeff Kinder
    Jeff Kinder is executive vice president of Product Development and Manufacturing Solutions at Autodesk. In this role, he leads strategy and execution across Autodesk's design and manufacturing portfolio. With a forward-looking focus on speed, data, cloud-based workflows, user experience, flexible business models, and customer outcomes, Kinder is helping to catalyze the digital transformation in manufacturing. Kinder previously served as chief digital officer for Autodesk and oversaw the company's digital platforms and customer experience. In this role, he was responsible for creating the connective tissue between the company's customers, products, and data. His responsibilities included building end-to-end digital platforms – from customer data and self-service to entitlements and licensing, to modern enterprise applications such as identity, order, and financial systems. In his role, Kinder led Autodesk's business model transformation from selling perpetual licenses and maintenance to growth through subscriptions and consumption. Prior to joining Autodesk in 2018, Kinder led large-scale, customer-focused digital transformations across a range of industries. Most recently, he was head of consumer products and global marketplaces at OpenTable. Before that, Kinder helped lead a digital transformation at JP Morgan Chase, the largest bank in the United States, where he was president of Chase Offers and head of digital products including Chase.com and the Chase mobile app. Prior to that, Kinder was senior vice president at Yahoo responsible for products including the company's flagship home page, as well as Yahoo Finance, Sports, News, Entertainment, Shopping, Travel, Autos, and Small Business. Before joining Yahoo, Kinder spent more than 10 years in senior roles at Cendant Corporation, Adventureseek, and the Boston Consulting Group. Early in his career, Kinder served as an officer in the US Navy. Kinder is currently on the board of directors of Switchfly, Inc. He previously served on the boards of Carlson Wagonlit Travel as well as Yahoo7, an Australian joint venture between Yahoo and 7 Media Group. He holds a Bachelor of Science in Operations Research and Industrial Engineering from Cornell University and a Master of Business Administration from Harvard Business School.
  • Stephanie Feraday
    With over 25 years' experience driving high growth software businesses, as CEO of aPriori, Stephanie Feraday has overseen the growth of aPriori through the development and launch of aPriori's Manufacturing Insight Software platform. aPriori helps major, global manufacturers with topline growth, profitability and sustainability: by helping design engineers reduce manufacturability issues, accelerating time to revenue, and improving cash flows; by enabling sourcing professionals to conduct fact-based negotiations and collaborate with suppliers, reducing cost of goods by millions of dollars; by providing visibility into the carbon impact of their design and manufacturing choices enabling them to reduce the carbon footprint of their products before product launch; and by helping suppliers win more profitable business faster by enabling them to quote faster but quote more accurately. The intelligence engine at the core of aPriori's Insight Platform makes this possible by generating manufacturability, cost and sustainability insights in seconds across the product lifecycle from the product design phase to production. Prior to joining aPriori, Stephanie held executive-level positions at marquis startup and Fortune 500 technology companies including Netegrity, Hewlett-Packard, Symantec, Delrina and Virtusa. She earned a bachelor's degree in applied science from the University of Waterloo.
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    Transcript

    STEPHEN HOOPER: Well, hello, everyone, and welcome to our first ever digital factory symposium at Autodesk University. So I'm Steve Hooper, vice president for design and manufacturing here at Autodesk. And today, I have the honor of being your MC. Now, we have a packed agenda to get to. But before we do, you might be wondering why we've brought you all here together today.

    Now, the way that we plan, design, build and operate factories is changing rapidly. So we wanted to bring industry leaders like you together to help prepare you to navigate today's complexities in the digital factory. So during today's three sessions, you'll hear from Autodesk executives and customers about the challenges that they're facing and how we can all best prepare to overcome them.

    Now we want you to walk away from today feeling inspired, as we all do, with some new ideas and best practices that you can implement in your job starting next week. And we want you to take some time to network with your industry peers. This is a fantastic event. There are so many of you here today that have interesting stories and experiences to share with each other. We want you to get the most of that.

    And as a special opportunity, between today's sessions today, we've reserved time for you to walk over to the factory experience, which you can see over to my left, where you'll learn about Fusion design, manufacturing and operations through an interactive experience where you can assemble your own electronic consumer product and take it home with you as a gift.

    Now, before I get started, I do want to say a special thanks to Adrian Finch. Where is she? There she is. Thank you very much for organizing today's session. I really appreciate it. So with that, let's get started with today's programming. Now digital factories offer manufacturers critical benefits of efficiency, innovation and stability.

    But they're only truly effective if they're designed, built and operated thoughtfully. Now, Autodesk is uniquely positioned with technology in both building information modeling and manufacturing. So to introduce you to someone who's familiar with both, let's welcome Jeff Kinder, executive vice president of design and manufacturing here at Autodesk to the stage to get us started. Jeff, please take the stage.

    [APPLAUSE]

    JEFF KINDER: Thanks, Steve. Thanks, Steve. Hello, everyone. Welcome. We should probably exhort more people in from the Expo floor. I hope you all had a chance to listen to the main stage keynotes this week last couple of days. A few themes are emerging-- transformation and reinvention, competition and change, data and AI.

    Intense competition is something you're facing in all industries. We hear this frequently in our conversations, certainly with manufacturing customers. Manufacturers are asking, they're asking themselves, they're asking us, how can they stay competitive in the face of all this change? But I would say, while the pace of change is accelerating, so is the technology available to us. And its importance in keeping you competitive to help you capitalize on all this change cannot be overstated.

    The future of making things driven by data and technological advancements is here. We're also seeing a convergence of how things are designed and made across all industries, all the industries we serve, architecture, engineering, construction, media and entertainment and manufacturing.

    Manufacturing itself is seeing a convergence of design and make processes. It's kind of a horizontal convergence, moving away from siloed point solutions with connected data and processes in the cloud. Construction companies are operating more like manufacturers by prefabricating and assembling things like apartment units, exterior walls and ductwork offsite.

    Studios are behaving like car brands by planning and pre-visualizing their entertainment properties, films, games, thinking ahead long before production just like an automotive manufacturer would plan and develop a concept car and think about its future iterations. To keep pace with the tight competition, all industries need to adopt these new ways of working. And there's no better partner-- I know I'm biased-- but there's no better partner for you in all of this than Autodesk.

    For now, we're going to focus on a very specific convergence opportunity that can set you apart from your competition, and that's planning, building, designing and operating your digital factory. Factories have come a long way in the last century, not just in how they operate, but the whole process of how they're developed, yet there's still opportunity.

    Unlike product design, which has evolved toward thinking in life cycles, adopting agile development methods and practicing concurrent engineering, factory design is still often done in very traditional ways. There are many manual, disconnected even paper-based processes. Today, factory operators spend way too much time managing information, tasks, processes and decisions that could be automated.

    And when it comes to building a factory, which involves many stakeholders using many software solutions, they're working with multiple data formats from incompatible systems. We need to treat a digital factory like a product. In product development, gaining the competitive advantage requires a new standard in manufacturing, a connected system where data flows seamlessly from concept design all the way through to production and shipping.

    A similar new standard applies to a digital factory. Just as we think about products in terms of lifecycle, that is how we should be thinking about our factories. Because a digital factory represents more than the physical process of making things. It's a concept in which the factory itself figures into the equation.

    The goal of a digital factory is to optimize manufacturing processes and the environment that houses them. So if we apply this life cycle thinking to factories, here's what it looks like. We have four phases. First, planning, which begins with logistics, understanding the products being manufactured and laying out the operation, breaking down the workflow step by step to determine each station location, the equipment placement and configuration that maximizes productivity.

    Design is about working out how we're going to realize our plans and objectives in an optimal way, both the building and the factory operations. Engineers determine how to lay the plan out in the physical space. And now stakeholders get involved, pulling from the same plan to design their specific area like an ergonomics team or to evaluate workstations or the HVAC team, mapping the movement of air throughout the facility.

    Then we move to Build, a digitally orchestrated process, leveraging BIM to coordinate between multiple teams such as architects, engineers, contractors and production engineers. That helps to reduce the risk of cost and schedule overruns. Finally operate. That's where we're concerned with optimizing manufacturing throughout the process to hit our business objectives.

    These are often treated as standalone siloed phases, but the reality is they overlap quite a bit with decisions at one stage often having intended or unintended consequences at the next. The more seamlessly we can think about, the more we think about this process, the more seamlessly they are connected, the more efficient and effective the development and operation can be.

    Treat your new factory like a new product, with the same planning and discipline, and you'll see this value in a new way. This new standard you'll see what it can deliver. Imagine the possibilities if you could create a coherent and integrated digital twin of your factory to optimize every stage of its development and operation.

    If you could create an accurate and flexible digital representation of your factory operations, workflow and layout, allowing you to test, optimize and change your factory layout to avoid machine downtime or adjust your workflow for specific production runs, if you could compress the factory development life cycle transforming sequential siloed approaches into something more agile.

    Taking a process from this to this, compressing the plan, design and build stages enabling cost and time savings in development but also a faster time to market and a faster time to revenue when you're operating your factory. What if you could connect data and put it to use to create an accurate building replica that also includes facility management data, such as warranties, installation dates and manufacturing information, ensuring you can continually optimize your factory for its entire lifespan?

    Connecting data throughout the entire factory life cycle-- from planning, to designing, to building all the way to operating-- creates greater agility and gives you a competitive edge. And this is exactly what we're enabling with our Autodesk data model. This data model will manage, organize and connect project data across our industry clouds, but even more importantly, across all of our Autodesk products and third party solutions via the Autodesk Platform Services APIs.

    The data platform is already powering interoperability between Revit and Inventor, Inventor in Fusion and AutoCAD in Fusion, and these relationships will only get stronger over time. Now, let's see this in action and learn more about Northvolt experiences using a broad range of the Autodesk portfolio from Revit for architectural design to Inventor factory design utilities to optimize factory operations and all the way to Autodesk Construction Cloud for model management.

    AXEL SAVE: What set Northvolt apart from conventional battery manufacturing is this rooted commitment to sustainability in everything we do, from the product design to the recycling approach that ties it all together. The factory is an inorganic organism where every single component needs to work together for this common goal.

    So we need to think of how can we design and work with the product in parallel with the process and production, with the facility and factory, with construction commissioning and just get it all done. Our designs need to account for that.

    FREDRIK ENGLUND: So we need to build our ecosystem around tools that work very well together. Data loss is unacceptable. Whatever he's doing, I need to see it. Whatever she's doing, I need to be able to see it and share it with the right people.

    AXEL SAVE: Autodesk provides that platform to build this toolbox for us. For the architects, we use Revit. It's very efficient to draw buildings. For more precise layouts without placement of machines on floors, we use the factory design utility tools with Inventor, with AutoCAD, with Navis in a Vault PDM environment. For BIM coordination we use Navisworks to compile everything. For model management and collaboration, we use Autodesk Construction Cloud to really have a cloud-based point of all stakeholders to watch this common model.

    FREDRIK ENGLUND: So now we're very excited about Autodesk Platform Services, which basically enables us to access many different APIs and tools within the Autodesk ecosystem and put them together in different ways that we want to bridge the gaps between the different tools and make them do almost exactly what we want them to.

    AXEL SAVE: We have proven that you can build industry in a new way, that the sustainability mission is not mutually exclusive from being profitable and commercially successful. We have been able to significantly optimize the factory design, and we can show with numbers pulled from a live model, yes, it is cheaper. It is smaller. It is more efficient.

    That's something I'm very proud of to have opened that door and open the mindset to enable the next era of industry.

    JEFF KINDER: All right, that's great.

    [APPLAUSE]

    As Northvolt's story clearly shows, Autodesk has solutions that support the entire life cycle of a factory. We are uniquely placed to help you streamline your development processes. This means we can help our customers design and make both the places and the products necessary to make their businesses a success.

    This speaks to the power of convergence between industries, leveraging all the tools Autodesk has to offer across industries to plan, design, build and operate factories. This is treating your digital factory like a manufactured product. Now, as we think about convergence of industries, construction is one industry that is in the midst of an incredible shift right now.

    New technologies and common data environments are being embraced. More and more we're seeing our construction customers utilize manufacturing practices, changing the way construction gets done. Today we have Jim Lynch, our head of Autodesk Construction, to talk more about how manufacturing and construction can learn from each other to move the industry forward. Jim.

    [APPLAUSE]

    Welcome.

    JIM LYNCH: Hi, Jeff. Thanks for having me.

    JEFF KINDER: How are you doing?

    JIM LYNCH: I'm doing fantastic. I love AU. I've been coming to AU for many, many years. A 27-year veteran with the company. But I always look forward to AU. I loved your keynote this morning. I thought it was spot right on. Looking forward to the construction keynote later today. Come hear about construction. It's an amazing industry.

    But it is important for me to point out, I was excited to come to this session today because I started at Autodesk in the manufacturing world. I ran part modeling for Inventor for the first three years of its life, actually, before its life. Interestingly enough, we built Inventor. The code name was Rubicon. And then we shipped our one, and then the company shipped me back to the East Coast to work on AEC. But it's good to always great to be back in the manufacturing world.

    JEFF KINDER: It's where you were needed the most.

    JIM LYNCH: Were they trying to get rid of me? I don't know. But it's great to be here.

    JEFF KINDER: There's no one better than to talk about the convergence of manufacturing and construction than you.

    JIM LYNCH: It's something I'm deeply passionate about and something the world needs to happen, actually.

    JEFF KINDER: I have a set of questions--

    JIM LYNCH: Of course you do.

    JEFF KINDER: --to ask you. As I just mentioned, over the past decade, we've seen a real change in the way construction companies are approaching building, specifically when it comes to incorporating manufacturing practices. So what's driving this? What's driving this shift?

    JIM LYNCH: It's a great question. I mean, listen, everybody knows construction has this reputation as being unpredictable, unsustainable, not sustainable and not very safe. In fact, several years ago, McKinsey put out a study that said, construction was the least technically astute industry, only better than hunting and fishing. It's like, come on. And I used to quote that when I first ran the construction business but I don't anymore because I don't think it's true.

    I think I've seen great advances in terms of technology adoption, but it's important to understand why it's important that we do drive more automation in construction. So by 2050, there will be 10 billion more people on this planet. And today, we don't have the homes. We don't have the residences. We don't have the schools. We don't have the hospitals. We don't have the infrastructure to support that. So it is really important that we find a better way to build.

    And the good news is the industry absolutely recognizes that technology will play a key role. The other thing that's interesting is the industry struggles with supply chains. It also struggles with labor. Every customer I talk to around the globe, bar none, talks about their challenges finding skilled labor for the job site. And it's only going to get worse. By 2031 it's expected that 41% of the current workforce, 41% will retire out.

    So the industry has to change. And the good news, it is changing. And they're really looking for ways to transform the way they work. And that's why there's this deep interest in driving more manufacturing processes into construction. And we'll talk about that.

    JEFF KINDER: I mean, it sounds like this efficiency is absolutely needed.

    JIM LYNCH: It really is. I mean, it's dire, quite frankly.

    JEFF KINDER: Well, when you're describing this, this has the ring to me of industrialized construction, something we talk about. What do you think about when you hear that term, industrialized construction? And what do you see as the opportunities regarding the industrialization of construction?

    JIM LYNCH: So for us at Autodesk, we talk about the industrialization of construction, as you mentioned earlier, really the convergence of construction and manufacturing. And at Autodesk, we look at that through really three lenses, kind of three capabilities, if you will. The first one is around prefabrication. So that's moving more work, more manufacturing, more fabrication work away from the job site and into a controlled environment.

    And now that is not a new concept in construction. Fabrication has been around for a long time. I mean, just think of MEP systems. Most MEP systems, mechanical systems for sure are built offsite and then brought and installed. But I can tell you the processes around prefabrication have a ways to go in terms of improvement. The second thing we look at when we think of industrialized construction is this idea of productization.

    So think of kit of parts. How can we turn the process of construction away from reducing the build and more of the install. Think of LEGO blocks. So that's the second lens that we look at is really productization. And then the third is what we call DfMA or design for manufactured assembly. And that's really the idea of arming the design teams with more information up front so they can get it right and design something that can actually quickly be built using that kit of parts.

    And they're all related. Prefabrication, productization and DfMA, when those come together, then you really start making a shift. You drive better decision making earlier in the process, and you really connect design and construction.

    JEFF KINDER: I passed their use. I've seen examples of where people basically bring manufacturing on. It's not off site work. They actually bring it on site. That's super cool to see.

    JIM LYNCH: There is some really interesting advances out there. I mean, one of our strategic customers, Barton Malow, has this concept they call lift build. And basically what they do-- they're based in Detroit-- what they do with lift build is they use the first floor of the building to build out a floor. And then when that floor is ready, they literally lift it and hoisted into place.

    So if it's a 10 storey building, they do the 10th floor first on the first floor, and then they hoist it up. And again, it's all about reducing waste. It's about driving more predictability and ultimately a safer environment.

    JEFF KINDER: That's great. That's great. We've talked a lot about data. I've heard a lot about data at AU. What role does data play for construction companies in this convergence?

    JIM LYNCH: So I know we're really over-indexing at AU this year on data. But it really is critically important to all our industries. And certainly construction it's so critically important. And the great news is that our customers are realizing the importance of data. But construction has been hampered with miscommunication and bad data for a long time, which leads to costly rework delays.

    And by the way, over 50% of the rework on a construction site is a result of bad data. So data is huge. The great news is our customers are quickly learning that and understanding how they can better capture and manage that data. One of my favorite quotes from one of our customers in Europe-- Mace construction-- CEO once said, we consider ourselves a data company that builds buildings. And I think that's really forward and thought leading.

    And I think you're going to see more and more customer construction teams, whether they're subcontractors, general contractors, taking that philosophy. And every conversation I've had over the last two days with our construction customers has all been about data.

    JEFF KINDER: Well, it's funny, when I hear about, when I think about a construction site and taking the data and tracking changes, there are always changes, and tracking all of that, it feels an awful lot like PLM. It feels an awful lot like PLM for construction, something that manufacturing customers are very familiar with it.

    JIM LYNCH: Absolutely. So PLM obviously enhances workflows. It improves collaboration across the teams. In construction, they have a similar concept, what we refer to as the common data environment. So the common data environment, along with some of our collaboration tools, starts to go down the path of PLM. And there's deep interest in that. And we're seeing really quick adoption of our CDE environment, which is Autodesk Docs.

    Now I will say, manufacturing is much further along, much more mature than construction when it comes to concepts like PLM. But for sure, the construction industry is really working hard in terms of managing their data and finding a way to use that data downstream. And it's that data that honestly opens the door for different ways of working like aggressively pursuing the convergence.

    JEFF KINDER: I would actually say the industries can learn from each other. So whatever PLM in manufacturing may be advanced, construction can learn from that. There's things about construction in terms of its flexibility that manufacturers need to learn too. So I think those go together.

    JIM LYNCH: Completely agree. And by the way, that's one of the reasons why I love the main stage sessions like we have today, because I think there is an amazing opportunity for our industries to learn from each other. I guarantee you, in other customer meetings that I'll have over the next couple of days, I guarantee you some of my general contractor customers will say, hey when Jeff was talking about the AI on x, y, z, how can we pull some of that into construction? So it's really important that we give that exposure.

    JEFF KINDER: That's great. Well, speaking of customers, you're meeting with customers around the world, and you're seeing some of this convergence firsthand-- manufacturing, construction coming together. Any examples you can share with the audience?

    JIM LYNCH: Yeah. I mean, I think there are a lot of great examples around the globe of what industrialized construction. There's a lot of examples of companies that have failed miserably trying to do it. That's a whole other case study. But let me tell you, let me share one story with you. This is a recent story. Last month, I was in Kuala Lumpur, Malaysia, to meet with one of our customers, Gamuda.

    Gamuda is an engineering and construction firm, and they are a thought leader. They are very innovative. In fact, I'm having the chief digital officer join me on stage today for the construction keynote, and the insights he offers is really amazing. But when I was there, I spent a day with them. And I got to visit one of their facilities they call the industrialized building system facility.

    Now, I went in there, and I was blown away. It really is industrialized construction coming to life. So what the-- I hate to call it the IBS facility, but what the IBS facility is it's a precast concrete facility completely run with robots and great process lines. And they are doing some amazing work in this factory. So what used to take 2000 workers to deliver now is down to 200 workers.

    And so everything-- essentially all the projects that they work on, the content is produced in that factory. And in fact, a great example they were sharing with me, they were able to build an eight storey data center in eight months. Now, I know to the manufacturing world you probably say, well, that seems like a long time. That is lightning speed, and it's all produced out of that factory.

    So it was really a great opportunity to see the industrialization of construction come to life. It was really cool.

    JEFF KINDER: That sounds fast to me, be honest. I mean, someone who's done some remodeling of a house, eight months, I'd be very happy with that.

    JIM LYNCH: Exactly.

    JEFF KINDER: That's incredible. I'd love to go there sometime. I'll go to Gamuda Cove sometime.

    JIM LYNCH: So the other thing, Gamuda Cove they call it a Township. And it's a small city that they're building. They are building the entire city themselves, so residences, homes, schools, hospitals. There's a water park, theme park. I got to visit that. And again, that whole Gamuda Cove is being-- the walls of those houses, of those schools are all being built in that industrialized building system facility, which is just really impressive.

    JEFF KINDER: It sounds like a resort.

    JIM LYNCH: When I first drove by it from the airport, I thought it was because you see this giant waterslide park, which I want to go back and check out sometimes.

    JEFF KINDER: This is another gift for my wife for her birthday. We're going to go to Gamuda Cove.

    JIM LYNCH: You're going to really be hitting it out of the park with this birthday.

    JEFF KINDER: So how does Autodesk partner with Gamuda? What are we doing with Gamuda?

    JIM LYNCH: So we've been their technology partner along their entire journey. They are really deeply, deeply committed to the Autodesk technology stack, both on the construction side and AEC side, design side as well as on the manufacturing side. And I think our customers on the construction side that are really engaging in industrialized construction, they're really looking to us to help them because they see that really we're in a unique position in the industry because of our leading portfolio in both AEC and in manufacturing.

    And we have competitors in both of those arenas but we don't have many that play in both of those arenas. And so the way we're helping them, really, is the work that we're doing around former around Fusion and flow, but certainly around former and Fusion in terms of the data models that we're building. You talked about the manufacturing data model. Amy talked about the AEC data model.

    First of all, capturing that data is step one and then bringing that data together, which we're doing with using the Autodesk data model or the Autodesk Platform Services. That's step one is making sure the data moves back and forth. The other thing we have to do as a company is we have to make sure that we're delivering the workflows that moves that data across from the AEC world to the manufacturing world back to the construction world.

    So that's a huge part. And then I think, listen, we need to be a true partner if we're going to help move this industry along. A great example is work that we've done with General Motors as the owner. And again, Barton Malow, if I may use them as another example as GM's general contractor. So they're both trying to implement or have implemented Autodesk technology stacks in the manufacturing side and in the AEC side.

    So what we've done is we've gone in. We've sent a team of skilled consultants and professionals in to bring those teams together to help them bring the workflows together. And as a result, they're driving great output, really great return on investment. And so we need to partner. I can tell you. We just need to be there as partners, not just technology providers.

    JEFF KINDER: That's great. I love stories like that. Big manufacturers getting together with construction firms, general contractors. That's awesome.

    JIM LYNCH: Exactly.

    JEFF KINDER: And it starts with data. And as you said, make sure that data can flow back and forth.

    JIM LYNCH: Absolutely.

    JEFF KINDER: Jim, Thank you.

    JIM LYNCH: Thank you.

    JEFF KINDER: Thank you very much.

    JIM LYNCH: Thanks for having me. Come to the construction keynote, 3 o'clock today. It's going to be really cool. The stories that John Lim from Gamuda is going to tell, really, really compelling. Thanks for having me, Jeff.

    JEFF KINDER: Thanks.

    [APPLAUSE]

    Thanks, everyone.

    STEPHEN HOOPER: All right. Thank you, Jeff and Jim for that great conversation. Let's give him another round of applause.

    [APPLAUSE]

    Now, next, I'd like to welcome another special guest to the stage, Stephanie Feraday. She's the president and CEO of aPriori. With over 25 years experience driving high-growth software businesses, she's overseen the growth of aPriori through the development and launch of their manufacturing insights software platform that is disrupting the industry status quo with groundbreaking work helping manufacturers digitally transform their businesses.

    While providing visibility to the sustainability of their design and manufacturing choices, their impact is profound, saving millions of dollars each year and accelerating time to market, all while creating a better world and future for future generations. Now, I know Stephanie personally, through our partnership with Fusion, to put design for manufacturing capabilities into the hands of our customers.

    And I can't think of a better person to speak on this topic. So with that, let's all welcome Stephanie to the stage.

    [APPLAUSE]

    STEPHANIE FERADAY: OK. Thanks, Steve. Great. Good afternoon, everybody. It's lunchtime. I'm glad to see you're here. So, first of all, I want to thank the Autodesk team for inviting us. What I'm going to talk about is a little bit of a different kind of digital factory. So we work with major manufacturers around the world like you, helping to accelerate top line revenue, reduce cost of goods and achieve a more significant carbon reduction in the products that they develop that they're bringing to market.

    And so today, I'm going to talk to you about a different kind of digital factory that works across the product development cycle to help companies achieve these fiscal goals. So as you've just seen, digital factories are critical for manufacturers to design, to build, to operate plants. However, digital factories are also invaluable during the entire product development process, starting to help a broad range of stakeholders, including design engineers and procurement teams.

    At the heart of how we help our customers is a different type of digital factory than those you've just heard about. The digital factory that I'm talking about is combined with the CAD models of the products being made to provide a broad range of insights valuable for product design, sourcing and manufacturing teams, so all three. So this combination of digital factories with CAD information creates a powerful digital thread of data that matures and grows across the product development cycle, connecting teams to make better, faster decisions about the product design, the manufacturing approaches and the sourcing options.

    So it's not just about building. It's more than that. Let me just take a minute to talk about how that all comes together. When product design and manufacturing are connected through digital factories, during the product design phase, it opens up new and valuable insights at a point in time that enables a broad range of decision options.

    During the product design process, real-time digital factory generated insights enable more engineers to evaluate different product design options, identifying which options are more manufacturable that cost less or are more carbon friendly. And when digital factories are used in the product design phase, those same digital factories can be leveraged by the procurement and manufacturing teams, giving them line of sight to the potential manufacturing and sourcing capabilities that they might need much earlier in the cycle.

    This provides critical lead times to investigate new suppliers, assess make versus buy options and assess, evaluate current plant capabilities or even undertake the development of a new plant. And with these longer lead times, it drives different outcomes, whether it's time, cost or sustainability outcomes. One company we worked with was continually scrambling to find opportunities, to find capacity to make what was coming down the product pipeline.

    Unfortunately, it wasn't often until close to the completion of the product design that they understood the manufacturing capabilities that they needed. As a result, because of the tight time to market schedules, at times they had to go outside to suppliers to get the production capacity that they needed. Because of the time crunch, this often resulted in paying a premium for an expedited job.

    Now, once they started using digital factories, they were able to plan production much further ahead and much more effectively. However, not every company wants to take a Carte Blanche approach to manufacturing to make new products. Some companies want to be able to leverage their current capabilities to ensure high utilization of the facilities that they have.

    Digital factories can be valuable in this case as well, as they can be used to guide design options. Using digital factories that represent current manufacturing capabilities provides design engineers with feedback about the feasibility of the design during the design process that's relative to the capabilities of the plants that they already have or even their supply base.

    So you can see that with this early insight, it can help keep key stakeholders in sync and give them the ability to respond to market pressures like inflation, supply chain disruptions and restructuring events in a much more agile way. So let me just take a side step here just for a minute to explain how these digital factories work, because they're very different than how the digital factory of a plant works.

    So these digital factories with the combination of CAD models. So we at aPriori, we have over 500 manufacturing simulations in our software. Customers can create digital factories by grouping the simulations that are appropriate to match their capabilities in their plants. And this is combined with other data that we have, including labor data, material, data, overhead machine data, et cetera.

    Once the digital factories are set up, they can be reused over and over. To generate the insights, our software analyzes the CAD model to identify of the products that are being made. And this analysis what it does is it provides the information about the features that need to be manufactured. That information is then fed into the digital factories to generate a wide range of insights.

    This analysis takes anywhere from a few seconds to a few minutes, depending on the complexity of the parts or the assemblies. And the digital factories don't need to be real factories. They could even be what if factories used to plan future developments. So you don't need to be an expert to use these insights. They can be used by anyone across the product development cycle.

    To give you a sense of the insights generated by a digital factory, let me just briefly give you a quick view of some of the insights in this example provided to a design engineer using this assembly to provide some of the insights. Then we'll go on to talk about how this can be utilized to enable your day to day. So here's an example of taking that assembly that we just looked at, running it through an analysis.

    So the CAD models for that assembly was run through the digital factory. And the digital factory identified this as one of the manufacturing options for one component of the assembly. Then the cost was calculated. The manufacturability risks were identified. The cycle time for the manufacturing was calculated, and finally the carbon footprint was calculated given the design and manufacturing choices that they selected.

    What's great about digital factories is that they provide a centralized set of critical datas for teams to effectively collaborate across the product development cycle. And you just heard, we need these insights to make decisions and make them quickly. Product development cycles are getting shorter than ever.

    Over the next five years, McKinsey estimates that about $30 trillion in corporate revenues will depend on products that we haven't yet brought to market. Competition is fierce with companies continually vying for market share or launching new products to address emerging challenges. Earlier I mentioned that the drive to be first to market places immense pressure on downstream team's production, procurement and supply chain operations.

    These teams are typically left to handle last minute challenges, putting out fires to ensure that everything comes together. Unfortunately, this approach doesn't necessarily achieve the optimal outcome. The most successful organizations are those that prioritize optimizing technology, fostering cross-functional collaboration and refining business processes to support new approaches.

    To achieve this kind of speed to compete in these increasingly fiercely competitive markets, we see some companies starting to operate differently and leveraging digital factories in the context of how they're operating. They've created an adaptable product operating model by establishing collaborative groups working together at the earliest stages of product development through production.

    Some companies have called this a four in a box team that's comprised of a design engineer, a sourcing professional, a manufacturing expert and a program management or a project manager. Now, these teams work as units through the development cycle to bring products to market faster by sharing critical cross-functional insights. The goal for these small teams is to have the expertise and technologies to make decisions quickly.

    It's a model that empowers teams to iterate rapidly, accelerate feedback loops and be self serving. So let's take a quick look at how this works. We know that design engineers need to focus on innovating and developing innovative products, but often they're bogged down with additional responsibilities beyond form, fit and function. Like is there a design manufacturable? What's it going to cost? Does it meet the carbon requirements?

    And they're under tremendous pressure to work faster. Program managers are constantly in a balancing act, working across product teams to assess schedules, address roadblocks and juggle changing requirements. Manufacturing engineers, on the other hand, take the theoretical and must find a way to make it possible. However, they rely on details to help determine what the optimal manufacturing approach is to enable production to move seamlessly.

    And if capacity is full, sourcing and procurement teams need to be ready and armed with the information to select the right supplier at the right time in the right location that meet target costs with favorable terms. And while these core engineering teams are working to design, manufacture and source components, key decision makers need to be kept informed of where their products are in the product development cycle to help eliminate roadblocks.

    And in some cases, these core working teams require knowledge outside of their teams and expertise that they don't have. That expertise could come from manufacturing engineers on the shop floor or sustainability experts who are building their capabilities around what carbon impacts they need to be driving towards.

    So by working together, these core teams can leverage cross-functional insights and accelerate time to market. However, enabling these teams and orchestrating cross-functional insights is challenging. You've heard some of that earlier this afternoon. Today, there's a significant amount of digital product information that often sits in silos.

    The data gets lost from stage to stage with bits of data being shared through emails, Zoom calls, drop boxes or in some cases, even faxes today. As a result, the data developed through these cross-functional discussions don't persist. I recently met with a global manufacturer who just launched a brand new product line. They were under significant pressure to get to market.

    The engineering, sourcing and manufacturing teams work flat out, but they didn't have a shared set of data to provide critical insights and enable them to collaborate across the product development cycle. The result was the product was tens of millions of dollars over the target cost. Now after product launch, they're scrambling to reduce costs after the fact by looking at redesign options, less expensive manufacturing alternatives and trying to renegotiate part costs with suppliers.

    The challenge is that 70% of the costs are locked in at this stage. However, this organization has recognized that digital factories can help them out of this situation. So to help execute those tactics, to get this product line to a better cost position, they're now leveraging the data generated by digital factories to support these activities, helping reduce the chaos and achieve a better margin.

    Let me walk through an example of a major tier one automotive manufacturer that is leveraging digital factories to mitigate these kinds of situations. DANA is a $10 billion tier one automotive manufacturer that is leveraging digital factories early in the design process, starting with their engineering teams along with their manufacturing, sourcing, product procurement teams, program management and their manufacturing teams supported by a central team that's responsible for the digital factories.

    The reason they're doing this? They want to create the design right the first time to mitigate cost and to accelerate time to market. Secondly, they want to assess the cost function relationships between different manufacturing options earlier to optimize both the manufacturing choices and the cost of the product.

    And thirdly, they want to support strategic make versus buy decisions, in addition to supporting regional supplier selection. To achieve these goals, they've created digital factories to provide insights to their teams, and they've modified their workflows to support those teams with this new data and the process. The digital factories provide the design engineers with manufacturability feedback during design to help mitigate those late stage change orders that delay time to market.

    And they've analyzed by doing some of this, it's reduced their costs at that stage by $1 million to $3 million per turn. Now, the digital factories also help analyze the cost to manufacture in different regions of the world, assess the difference between making something internally versus through a supplier, as well as evaluating the cost of different manufacturing options. And those same digital factories are used to generate a should cost to enable procurement teams to do fact-based negotiations.

    In their first year of leveraging this approach, DANA has put $100 million in spend through their digital factories that's helped them save millions of dollars. While digital factories are helping to improve internal operations and streamline workflows, manufacturers are also dealing with external factors that are continuously changing, making speed difficult and meeting cost targets a challenge.

    While COVID epitomized the worst of the supply chain disruptions, they didn't start with COVID, and they're certainly not ending there. A while ago, the chief procurement officer of GE Appliances shared some data with me where he listed the challenges they faced every year for the past 10 years in their supply chain disruptions-- the blockage of the Suez Canal, container shortages, labor shortages at their plants. The list goes on and on.

    Supply chain disruptions, geopolitical issues, tariffs wars, they've caused manufacturers like all of us to rethink how and where they manufacture. Early during the Trump discussions, we were working with a company that moved a portion of their manufacturing from China to Mexico. Now, based on some quick estimates, they believe the cost would be at least the same. Bad news, it was significantly higher.

    Later by using digital factories, they discovered the value that they could get from using digital factories. They were able to quickly do a more detailed assessment of different manufacturing options, materials, machines, other nearshore manufacturing locations that they hadn't initially considered to achieve a better financial outcome. The digital factories enabled them to run what-if scenarios to provide insights that they could have considered before making their initial move.

    These dynamic market conditions make it a continual challenge to know what to build, what to buy, what capabilities we'll need and when we'll need them, especially when we're trying to optimize many factors, including speed, quality and cost. So there are typically three critical questions that we need to ask here. Do we have the right in-house capability? Do we need to build a new plant or modify an existing one? And/or do we even have the capacity?

    However, as we've seen with the dynamic market conditions and changing product delivery time frames, it can be very difficult to answer these questions. A great example of this is personified by a conglomerate we're currently working with. They have 100 factories spread all over the world that are used by their operating divisions that have approximately a 70% utilization rate for various reasons-- machines breaking, it was cheaper to buy externally, or at they thought it was or manpower wasn't available at the time to staff that particular manufacturing line.

    Their problem was, how do they drive efficiencies inside of their factories to achieve a better financial outcome. We started working with them on the evaluation of one factory. In about two weeks, we were able to quickly replicate the functionality of that factory in a digital factory, including the machines that they utilized. Now we mapped how the parts go through those lines. We added the labor rates, the materials, the overhead rates, et cetera and validated it about a 90% accuracy that the cycle times were the same between the digital factory and the actual plant.

    Now, by modeling the factory and then running the CAD models of the products that they make through those digital factories, they were able to gain a better understanding of what they should make versus buy. And in particular, they wanted to know what could be more effective to manufacture internally. Secondly, they wanted to understand how they could create more optimal routings.

    They weren't sure whether the current way they were manufacturing was necessarily the best way. And lastly, as they look down the road at their capital expenditures, how do they pick the right machines for the future? They want to explore what capabilities they'll need given the current products they're manufacturing, as well as the future ones coming down the pipeline. While they're early in this undertaking, they're starting to see how these digital factories can provide insights to help them achieve their goals.

    So the net impact of digital factories is they provide the guidance that manufacturing, procurement and engineering teams need to accelerate time to market and mitigate supply chain risk and lower carbon footprint. So I walked through a number of examples. Let me just take you through from the product development cycle, how digital factories can enable companies to operate more effectively.

    First, let me start with Flextronics. Flextronics, $25 billion contract manufacturer. They created digital factories initially representing their sheet metal capabilities and those of some of their supply base. Now, using digital factories, they were able to assess the products that they were bidding on. And through that, they were able to look at the different manufacturing approaches.

    From that, they could assess the cost of the different manufacturing options. Then they took this data and sent it to their quoting system. Now, prior to using digital factories, their win rate was about 15% to 20% of the request for quotes they responded to. After using digital factories, their win rate went up to 68% because they're able to quote faster and quote more accurately.

    Now, Danfoss incorporated digital factories into their product design and their sourcing processes to help them stay competitive in hyper competitive markets. They were questioning if they sourced or manufactured their products at the right prices. They also wanted to understand if they were taking into consideration the most economic manufacturing processes available in the market or if their designs were optimized for cost at various performance levels.

    Using digital factories to analyze the products they made, they were able to collaborate across the product development cycle. And the net impact of doing this was a 20% to 30% reduction relative to the target cost during their product design phase and a $20 million reduction during the early stages of their value engineering assessments.

    Alstom, a major train manufacturer, leveraged digital factories differently. They worked with some of their suppliers where they had a more open book relationship to create digital factories that represent the suppliers, manufacturing capabilities and their unit economics, including margins. Now, what they did was they used the digital factories to create a quoteless sourcing process where once a design was complete, the digital factory assessed the product that was finished, and from the digital factory, they generated a report which was, in fact, the quote.

    Now, this report is sent to the supplier for verification to ensure that nothing was missed. The result of this is that Alstom has reduced their quoting times from days to hours. Now, AGCO had a different goal. The GSI division at AGCO offers a range of integrated grain systems. Their customers can select custom products and dimensions resulting in a product that is subsequently engineered to order.

    In the past, cycle times for this process were managed using individual spreadsheets, and so the accounting department recognized that the cycle times being represented in their business and MRP systems were not necessarily being replicated on the shop floor. These discrepancies made projecting labor time and cost in the factory difficult.

    So GSI needed a method for standardizing manufacturability models that was more repeatable, accurate and precise for this made to order solution. They created digital factories that match the cycle times on the plant floors. With this standardized solution, any user anywhere in the world could assess a CAD model and get the same cycle time result, enabling GSI to deliver consistent financial results.

    And lastly, companies like Carrier are using digital factories to provide insights into the carbon impact of their product design and manufacturing choices. With this feedback, they can make changes during the design process to reduce the carbon impact of the design or choose manufacturing options that have a smaller carbon impact, helping them achieve their very aggressive carbon reduction goals. And the data that's generated from those digital factories can be used in achieving their product declarations.

    To succeed in today's highly competitive market, digital factories can be game changing, and they can be used by more teams than just manufacturing. They can provide design engineers with guidance to mitigate manufacturability issues. They can provide line of sight into how new product development may impact the options needed for manufacturing and sourcing.

    And digital factories can also provide a much earlier visibility to give you time to consider the many different options you might have given enough time in terms of how you manufacture. Digital factories can help to de-risk your critical decisions. So the net takeaway I'd leave you with today is that digital factories are incredibly valuable technology across the whole product development cycle, providing critical insights for your strategic decisions. Thanks for listening. I hope you enjoy the conference.

    [APPLAUSE]

    STEPHEN HOOPER: Thank you, Stephanie. That was great insight, and I really appreciate you taking your valuable time to be here with us today. So thank you. So that wraps up this first session, but stay put, and join us in 30 minutes for our next session, where we'll hear from a panel on how they're using data to connect teams across all of their various disciplines.

    Now, during the break, don't forget to check out the factory experience directly next to us and spend a bit of time networking with your peers. You'll see there's a gentleman at the back of the room there with glasses on. His name is Jan Willem. He will escort you over to my good friend, Jonathan Odom, over there on the factory experience if you want to go through the process of building your own consumer product that you can take home with you after the event. But we'll be back in 30 minutes with our panel. Thank you.

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    오토데스크 사이트에서 고객의 행동에 관한 데이터를 수집하기 위해 Khoros를 이용합니다. 여기에는 고객이 방문한 페이지, 시작한 체험판, 재생한 동영상, 구매 내역, IP 주소 또는 장치 ID 및 오토데스크 ID가 포함될 수 있습니다. 오토데스크는 사이트 성과를 측정하고 고객의 온라인 경험의 편리함을 평가하여 기능을 개선하기 위해 이러한 데이터를 이용합니다. 또한, 이메일, 고객 지원 및 판매와 관련된 고객 경험을 최적화하기 위해 고급 분석 방법도 사용하고 있습니다. Khoros 개인정보취급방침
    Launch Darkly
    오토데스크 사이트에서 고객의 행동에 관한 데이터를 수집하기 위해 Launch Darkly를 이용합니다. 여기에는 고객이 방문한 페이지, 시작한 체험판, 재생한 동영상, 구매 내역, IP 주소 또는 장치 ID 및 오토데스크 ID가 포함될 수 있습니다. 오토데스크는 사이트 성과를 측정하고 고객의 온라인 경험의 편리함을 평가하여 기능을 개선하기 위해 이러한 데이터를 이용합니다. 또한, 이메일, 고객 지원 및 판매와 관련된 고객 경험을 최적화하기 위해 고급 분석 방법도 사용하고 있습니다. Launch Darkly 개인정보취급방침
    New Relic
    오토데스크 사이트에서 고객의 행동에 관한 데이터를 수집하기 위해 New Relic를 이용합니다. 여기에는 고객이 방문한 페이지, 시작한 체험판, 재생한 동영상, 구매 내역, IP 주소 또는 장치 ID 및 오토데스크 ID가 포함될 수 있습니다. 오토데스크는 사이트 성과를 측정하고 고객의 온라인 경험의 편리함을 평가하여 기능을 개선하기 위해 이러한 데이터를 이용합니다. 또한, 이메일, 고객 지원 및 판매와 관련된 고객 경험을 최적화하기 위해 고급 분석 방법도 사용하고 있습니다. New Relic 개인정보취급방침
    Salesforce Live Agent
    오토데스크 사이트에서 고객의 행동에 관한 데이터를 수집하기 위해 Salesforce Live Agent를 이용합니다. 여기에는 고객이 방문한 페이지, 시작한 체험판, 재생한 동영상, 구매 내역, IP 주소 또는 장치 ID 및 오토데스크 ID가 포함될 수 있습니다. 오토데스크는 사이트 성과를 측정하고 고객의 온라인 경험의 편리함을 평가하여 기능을 개선하기 위해 이러한 데이터를 이용합니다. 또한, 이메일, 고객 지원 및 판매와 관련된 고객 경험을 최적화하기 위해 고급 분석 방법도 사용하고 있습니다. Salesforce Live Agent 개인정보취급방침
    Wistia
    오토데스크 사이트에서 고객의 행동에 관한 데이터를 수집하기 위해 Wistia를 이용합니다. 여기에는 고객이 방문한 페이지, 시작한 체험판, 재생한 동영상, 구매 내역, IP 주소 또는 장치 ID 및 오토데스크 ID가 포함될 수 있습니다. 오토데스크는 사이트 성과를 측정하고 고객의 온라인 경험의 편리함을 평가하여 기능을 개선하기 위해 이러한 데이터를 이용합니다. 또한, 이메일, 고객 지원 및 판매와 관련된 고객 경험을 최적화하기 위해 고급 분석 방법도 사용하고 있습니다. Wistia 개인정보취급방침
    Tealium
    오토데스크 사이트에서 고객의 행동에 관한 데이터를 수집하기 위해 Tealium를 이용합니다. 여기에는 고객이 방문한 페이지, 시작한 체험판, 재생한 동영상, 구매 내역 및 IP 주소 또는 장치 ID가 포함될 수 있습니다. 오토데스크는 사이트 성과를 측정하고 고객의 온라인 경험의 편리함을 평가하여 기능을 개선하기 위해 이러한 데이터를 이용합니다. 또한, 이메일, 고객 지원 및 판매와 관련된 고객 경험을 최적화하기 위해 고급 분석 방법도 사용하고 있습니다. Upsellit
    오토데스크 사이트에서 고객의 행동에 관한 데이터를 수집하기 위해 Upsellit를 이용합니다. 여기에는 고객이 방문한 페이지, 시작한 체험판, 재생한 동영상, 구매 내역 및 IP 주소 또는 장치 ID가 포함될 수 있습니다. 오토데스크는 사이트 성과를 측정하고 고객의 온라인 경험의 편리함을 평가하여 기능을 개선하기 위해 이러한 데이터를 이용합니다. 또한, 이메일, 고객 지원 및 판매와 관련된 고객 경험을 최적화하기 위해 고급 분석 방법도 사용하고 있습니다. CJ Affiliates
    오토데스크 사이트에서 고객의 행동에 관한 데이터를 수집하기 위해 CJ Affiliates를 이용합니다. 여기에는 고객이 방문한 페이지, 시작한 체험판, 재생한 동영상, 구매 내역 및 IP 주소 또는 장치 ID가 포함될 수 있습니다. 오토데스크는 사이트 성과를 측정하고 고객의 온라인 경험의 편리함을 평가하여 기능을 개선하기 위해 이러한 데이터를 이용합니다. 또한, 이메일, 고객 지원 및 판매와 관련된 고객 경험을 최적화하기 위해 고급 분석 방법도 사용하고 있습니다. Commission Factory
    Typepad Stats
    오토데스크 사이트에서 고객의 행동에 관한 데이터를 수집하기 위해 Typepad Stats를 이용합니다. 여기에는 고객이 방문한 페이지, 시작한 체험판, 재생한 동영상, 구매 내역, IP 주소 또는 장치 ID 및 오토데스크 ID가 포함될 수 있습니다. 오토데스크는 사이트 성과를 측정하고 고객의 온라인 경험의 편리함을 평가하여 기능을 개선하기 위해 이러한 데이터를 이용합니다. 또한, 이메일, 고객 지원 및 판매와 관련된 고객 경험을 최적화하기 위해 고급 분석 방법도 사용하고 있습니다. Typepad Stats 개인정보취급방침
    Geo Targetly
    Autodesk는 Geo Targetly를 사용하여 웹 사이트 방문자를 가장 적합한 웹 페이지로 안내하거나 위치를 기반으로 맞춤형 콘텐츠를 제공합니다. Geo Targetly는 웹 사이트 방문자의 IP 주소를 사용하여 방문자 장치의 대략적인 위치를 파악합니다. 이렇게 하면 방문자가 (대부분의 경우) 현지 언어로 된 콘텐츠를 볼 수 있습니다.Geo Targetly 개인정보취급방침
    SpeedCurve
    Autodesk에서는 SpeedCurve를 사용하여 웹 페이지 로드 시간과 이미지, 스크립트, 텍스트 등의 후속 요소 응답성을 측정하여 웹 사이트 환경의 성능을 모니터링하고 측정합니다. SpeedCurve 개인정보취급방침
    Qualified
    Qualified is the Autodesk Live Chat agent platform. This platform provides services to allow our customers to communicate in real-time with Autodesk support. We may collect unique ID for specific browser sessions during a chat. Qualified Privacy Policy

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    사용자 경험 향상 – 사용자와 관련된 항목을 표시할 수 있게 해 줌

    Google Optimize
    오토데스크는 사이트의 새 기능을 테스트하고 이러한 기능의 고객 경험을 사용자화하기 위해 Google Optimize을 이용합니다. 이를 위해, 고객이 사이트를 방문해 있는 동안 행동 데이터를 수집합니다. 이 데이터에는 고객이 방문한 페이지, 시작한 체험판, 재생한 동영상, 구매 내역, IP 주소 또는 장치 ID, 오토데스크 ID 등이 포함될 수 있습니다. 고객은 기능 테스트를 바탕으로 여러 버전의 오토데스크 사이트를 경험하거나 방문자 특성을 바탕으로 개인화된 컨텐츠를 보게 될 수 있습니다. Google Optimize 개인정보취급방침
    ClickTale
    오토데스크는 고객이 사이트에서 겪을 수 있는 어려움을 더 잘 파악하기 위해 ClickTale을 이용합니다. 페이지의 모든 요소를 포함해 고객이 오토데스크 사이트와 상호 작용하는 방식을 이해하기 위해 세션 녹화를 사용합니다. 개인적으로 식별 가능한 정보는 가려지며 수집되지 않습니다. ClickTale 개인정보취급방침
    OneSignal
    오토데스크는 OneSignal가 지원하는 사이트에 디지털 광고를 배포하기 위해 OneSignal를 이용합니다. 광고는 OneSignal 데이터와 고객이 사이트를 방문하는 동안 오토데스크가 수집하는 행동 데이터 모두에 기초하여 제공됩니다. 오토데스크가 수집하는 데이터에는 고객이 방문한 페이지, 시작한 체험판, 재생한 동영상, 구매 내역 및 IP 주소 또는 장치 ID가 포함될 수 있습니다. 이 정보는 OneSignal에서 고객으로부터 수집한 데이터와 결합될 수 있습니다. 오토데스크는 디지털 광고 경험에 대한 사용자화를 개선하고 고객에게 더욱 관련 있는 광고를 제시하기 위해 OneSignal에 제공하는 데이터를 사용합니다. OneSignal 개인정보취급방침
    Optimizely
    오토데스크는 사이트의 새 기능을 테스트하고 이러한 기능의 고객 경험을 사용자화하기 위해 Optimizely을 이용합니다. 이를 위해, 고객이 사이트를 방문해 있는 동안 행동 데이터를 수집합니다. 이 데이터에는 고객이 방문한 페이지, 시작한 체험판, 재생한 동영상, 구매 내역, IP 주소 또는 장치 ID, 오토데스크 ID 등이 포함될 수 있습니다. 고객은 기능 테스트를 바탕으로 여러 버전의 오토데스크 사이트를 경험하거나 방문자 특성을 바탕으로 개인화된 컨텐츠를 보게 될 수 있습니다. Optimizely 개인정보취급방침
    Amplitude
    오토데스크는 사이트의 새 기능을 테스트하고 이러한 기능의 고객 경험을 사용자화하기 위해 Amplitude을 이용합니다. 이를 위해, 고객이 사이트를 방문해 있는 동안 행동 데이터를 수집합니다. 이 데이터에는 고객이 방문한 페이지, 시작한 체험판, 재생한 동영상, 구매 내역, IP 주소 또는 장치 ID, 오토데스크 ID 등이 포함될 수 있습니다. 고객은 기능 테스트를 바탕으로 여러 버전의 오토데스크 사이트를 경험하거나 방문자 특성을 바탕으로 개인화된 컨텐츠를 보게 될 수 있습니다. Amplitude 개인정보취급방침
    Snowplow
    오토데스크 사이트에서 고객의 행동에 관한 데이터를 수집하기 위해 Snowplow를 이용합니다. 여기에는 고객이 방문한 페이지, 시작한 체험판, 재생한 동영상, 구매 내역, IP 주소 또는 장치 ID 및 오토데스크 ID가 포함될 수 있습니다. 오토데스크는 사이트 성과를 측정하고 고객의 온라인 경험의 편리함을 평가하여 기능을 개선하기 위해 이러한 데이터를 이용합니다. 또한, 이메일, 고객 지원 및 판매와 관련된 고객 경험을 최적화하기 위해 고급 분석 방법도 사용하고 있습니다. Snowplow 개인정보취급방침
    UserVoice
    오토데스크 사이트에서 고객의 행동에 관한 데이터를 수집하기 위해 UserVoice를 이용합니다. 여기에는 고객이 방문한 페이지, 시작한 체험판, 재생한 동영상, 구매 내역, IP 주소 또는 장치 ID 및 오토데스크 ID가 포함될 수 있습니다. 오토데스크는 사이트 성과를 측정하고 고객의 온라인 경험의 편리함을 평가하여 기능을 개선하기 위해 이러한 데이터를 이용합니다. 또한, 이메일, 고객 지원 및 판매와 관련된 고객 경험을 최적화하기 위해 고급 분석 방법도 사용하고 있습니다. UserVoice 개인정보취급방침
    Clearbit
    Clearbit를 사용하면 실시간 데이터 보강 기능을 통해 고객에게 개인화되고 관련 있는 환경을 제공할 수 있습니다. Autodesk가 수집하는 데이터에는 고객이 방문한 페이지, 시작한 체험판, 재생한 동영상, 구매 내역 및 IP 주소 또는 장치 ID가 포함될 수 있습니다. Clearbit 개인정보취급방침
    YouTube
    YouTube는 사용자가 웹 사이트에 포함된 비디오를 보고 공유할 수 있도록 해주는 비디오 공유 플랫폼입니다. YouTube는 비디오 성능에 대한 시청 지표를 제공합니다. YouTube 개인정보보호 정책

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    광고 수신 설정 – 사용자에게 타겟팅된 광고를 제공할 수 있게 해 줌

    Adobe Analytics
    오토데스크 사이트에서 고객의 행동에 관한 데이터를 수집하기 위해 Adobe Analytics를 이용합니다. 여기에는 고객이 방문한 페이지, 시작한 체험판, 재생한 동영상, 구매 내역, IP 주소 또는 장치 ID 및 오토데스크 ID가 포함될 수 있습니다. 오토데스크는 사이트 성과를 측정하고 고객의 온라인 경험의 편리함을 평가하여 기능을 개선하기 위해 이러한 데이터를 이용합니다. 또한, 이메일, 고객 지원 및 판매와 관련된 고객 경험을 최적화하기 위해 고급 분석 방법도 사용하고 있습니다. Adobe Analytics 개인정보취급방침
    Google Analytics (Web Analytics)
    오토데스크 사이트에서 고객의 행동에 관한 데이터를 수집하기 위해 Google Analytics (Web Analytics)를 이용합니다. 여기에는 고객이 방문한 페이지, 시작한 체험판, 재생한 동영상, 구매 내역 및 IP 주소 또는 장치 ID가 포함될 수 있습니다. 오토데스크는 사이트 성과를 측정하고 고객의 온라인 경험의 편리함을 평가하여 기능을 개선하기 위해 이러한 데이터를 이용합니다. 또한, 이메일, 고객 지원 및 판매와 관련된 고객 경험을 최적화하기 위해 고급 분석 방법도 사용하고 있습니다. AdWords
    Marketo
    오토데스크는 고객에게 더욱 시의적절하며 관련 있는 이메일 컨텐츠를 제공하기 위해 Marketo를 이용합니다. 이를 위해, 고객의 온라인 행동 및 오토데스크에서 전송하는 이메일과의 상호 작용에 관한 데이터를 수집합니다. 수집하는 데이터에는 고객이 방문한 페이지, 시작한 체험판, 재생한 동영상, 구매 내역, IP 주소 또는 장치 ID, 이메일 확인율, 클릭한 링크 등이 포함될 수 있습니다. 오토데스크는 이 데이터를 다른 소스에서 수집된 데이터와 결합하여 고객의 판매 또는 고객 서비스 경험을 개선하며, 고급 분석 처리에 기초하여 보다 관련 있는 컨텐츠를 제공합니다. Marketo 개인정보취급방침
    Doubleclick
    오토데스크는 Doubleclick가 지원하는 사이트에 디지털 광고를 배포하기 위해 Doubleclick를 이용합니다. 광고는 Doubleclick 데이터와 고객이 사이트를 방문하는 동안 오토데스크가 수집하는 행동 데이터 모두에 기초하여 제공됩니다. 오토데스크가 수집하는 데이터에는 고객이 방문한 페이지, 시작한 체험판, 재생한 동영상, 구매 내역 및 IP 주소 또는 장치 ID가 포함될 수 있습니다. 이 정보는 Doubleclick에서 고객으로부터 수집한 데이터와 결합될 수 있습니다. 오토데스크는 디지털 광고 경험에 대한 사용자화를 개선하고 고객에게 더욱 관련 있는 광고를 제시하기 위해 Doubleclick에 제공하는 데이터를 사용합니다. Doubleclick 개인정보취급방침
    HubSpot
    오토데스크는 고객에게 더욱 시의적절하며 관련 있는 이메일 컨텐츠를 제공하기 위해 HubSpot을 이용합니다. 이를 위해, 고객의 온라인 행동 및 오토데스크에서 전송하는 이메일과의 상호 작용에 관한 데이터를 수집합니다. 수집하는 데이터에는 고객이 방문한 페이지, 시작한 체험판, 재생한 동영상, 구매 내역, IP 주소 또는 장치 ID, 이메일 확인율, 클릭한 링크 등이 포함될 수 있습니다. HubSpot 개인정보취급방침
    Twitter
    오토데스크는 Twitter가 지원하는 사이트에 디지털 광고를 배포하기 위해 Twitter를 이용합니다. 광고는 Twitter 데이터와 고객이 사이트를 방문하는 동안 오토데스크가 수집하는 행동 데이터 모두에 기초하여 제공됩니다. 오토데스크가 수집하는 데이터에는 고객이 방문한 페이지, 시작한 체험판, 재생한 동영상, 구매 내역 및 IP 주소 또는 장치 ID가 포함될 수 있습니다. 이 정보는 Twitter에서 고객으로부터 수집한 데이터와 결합될 수 있습니다. 오토데스크는 디지털 광고 경험에 대한 사용자화를 개선하고 고객에게 더욱 관련 있는 광고를 제시하기 위해 Twitter에 제공하는 데이터를 사용합니다. Twitter 개인정보취급방침
    Facebook
    오토데스크는 Facebook가 지원하는 사이트에 디지털 광고를 배포하기 위해 Facebook를 이용합니다. 광고는 Facebook 데이터와 고객이 사이트를 방문하는 동안 오토데스크가 수집하는 행동 데이터 모두에 기초하여 제공됩니다. 오토데스크가 수집하는 데이터에는 고객이 방문한 페이지, 시작한 체험판, 재생한 동영상, 구매 내역 및 IP 주소 또는 장치 ID가 포함될 수 있습니다. 이 정보는 Facebook에서 고객으로부터 수집한 데이터와 결합될 수 있습니다. 오토데스크는 디지털 광고 경험에 대한 사용자화를 개선하고 고객에게 더욱 관련 있는 광고를 제시하기 위해 Facebook에 제공하는 데이터를 사용합니다. Facebook 개인정보취급방침
    LinkedIn
    오토데스크는 LinkedIn가 지원하는 사이트에 디지털 광고를 배포하기 위해 LinkedIn를 이용합니다. 광고는 LinkedIn 데이터와 고객이 사이트를 방문하는 동안 오토데스크가 수집하는 행동 데이터 모두에 기초하여 제공됩니다. 오토데스크가 수집하는 데이터에는 고객이 방문한 페이지, 시작한 체험판, 재생한 동영상, 구매 내역 및 IP 주소 또는 장치 ID가 포함될 수 있습니다. 이 정보는 LinkedIn에서 고객으로부터 수집한 데이터와 결합될 수 있습니다. 오토데스크는 디지털 광고 경험에 대한 사용자화를 개선하고 고객에게 더욱 관련 있는 광고를 제시하기 위해 LinkedIn에 제공하는 데이터를 사용합니다. LinkedIn 개인정보취급방침
    Yahoo! Japan
    오토데스크는 Yahoo! Japan가 지원하는 사이트에 디지털 광고를 배포하기 위해 Yahoo! Japan를 이용합니다. 광고는 Yahoo! Japan 데이터와 고객이 사이트를 방문하는 동안 오토데스크가 수집하는 행동 데이터 모두에 기초하여 제공됩니다. 오토데스크가 수집하는 데이터에는 고객이 방문한 페이지, 시작한 체험판, 재생한 동영상, 구매 내역 및 IP 주소 또는 장치 ID가 포함될 수 있습니다. 이 정보는 Yahoo! Japan에서 고객으로부터 수집한 데이터와 결합될 수 있습니다. 오토데스크는 디지털 광고 경험에 대한 사용자화를 개선하고 고객에게 더욱 관련 있는 광고를 제시하기 위해 Yahoo! Japan에 제공하는 데이터를 사용합니다. Yahoo! Japan 개인정보취급방침
    Naver
    오토데스크는 Naver가 지원하는 사이트에 디지털 광고를 배포하기 위해 Naver를 이용합니다. 광고는 Naver 데이터와 고객이 사이트를 방문하는 동안 오토데스크가 수집하는 행동 데이터 모두에 기초하여 제공됩니다. 오토데스크가 수집하는 데이터에는 고객이 방문한 페이지, 시작한 체험판, 재생한 동영상, 구매 내역 및 IP 주소 또는 장치 ID가 포함될 수 있습니다. 이 정보는 Naver에서 고객으로부터 수집한 데이터와 결합될 수 있습니다. 오토데스크는 디지털 광고 경험에 대한 사용자화를 개선하고 고객에게 더욱 관련 있는 광고를 제시하기 위해 Naver에 제공하는 데이터를 사용합니다. Naver 개인정보취급방침
    Quantcast
    오토데스크는 Quantcast가 지원하는 사이트에 디지털 광고를 배포하기 위해 Quantcast를 이용합니다. 광고는 Quantcast 데이터와 고객이 사이트를 방문하는 동안 오토데스크가 수집하는 행동 데이터 모두에 기초하여 제공됩니다. 오토데스크가 수집하는 데이터에는 고객이 방문한 페이지, 시작한 체험판, 재생한 동영상, 구매 내역 및 IP 주소 또는 장치 ID가 포함될 수 있습니다. 이 정보는 Quantcast에서 고객으로부터 수집한 데이터와 결합될 수 있습니다. 오토데스크는 디지털 광고 경험에 대한 사용자화를 개선하고 고객에게 더욱 관련 있는 광고를 제시하기 위해 Quantcast에 제공하는 데이터를 사용합니다. Quantcast 개인정보취급방침
    Call Tracking
    오토데스크는 캠페인을 위해 사용자화된 전화번호를 제공하기 위하여 Call Tracking을 이용합니다. 그렇게 하면 고객이 오토데스크 담당자에게 더욱 빠르게 액세스할 수 있으며, 오토데스크의 성과를 더욱 정확하게 평가하는 데 도움이 됩니다. 제공된 전화번호를 기준으로 사이트에서 고객 행동에 관한 데이터를 수집할 수도 있습니다. Call Tracking 개인정보취급방침
    Wunderkind
    오토데스크는 Wunderkind가 지원하는 사이트에 디지털 광고를 배포하기 위해 Wunderkind를 이용합니다. 광고는 Wunderkind 데이터와 고객이 사이트를 방문하는 동안 오토데스크가 수집하는 행동 데이터 모두에 기초하여 제공됩니다. 오토데스크가 수집하는 데이터에는 고객이 방문한 페이지, 시작한 체험판, 재생한 동영상, 구매 내역 및 IP 주소 또는 장치 ID가 포함될 수 있습니다. 이 정보는 Wunderkind에서 고객으로부터 수집한 데이터와 결합될 수 있습니다. 오토데스크는 디지털 광고 경험에 대한 사용자화를 개선하고 고객에게 더욱 관련 있는 광고를 제시하기 위해 Wunderkind에 제공하는 데이터를 사용합니다. Wunderkind 개인정보취급방침
    ADC Media
    오토데스크는 ADC Media가 지원하는 사이트에 디지털 광고를 배포하기 위해 ADC Media를 이용합니다. 광고는 ADC Media 데이터와 고객이 사이트를 방문하는 동안 오토데스크가 수집하는 행동 데이터 모두에 기초하여 제공됩니다. 오토데스크가 수집하는 데이터에는 고객이 방문한 페이지, 시작한 체험판, 재생한 동영상, 구매 내역 및 IP 주소 또는 장치 ID가 포함될 수 있습니다. 이 정보는 ADC Media에서 고객으로부터 수집한 데이터와 결합될 수 있습니다. 오토데스크는 디지털 광고 경험에 대한 사용자화를 개선하고 고객에게 더욱 관련 있는 광고를 제시하기 위해 ADC Media에 제공하는 데이터를 사용합니다. ADC Media 개인정보취급방침
    AgrantSEM
    오토데스크는 AgrantSEM가 지원하는 사이트에 디지털 광고를 배포하기 위해 AgrantSEM를 이용합니다. 광고는 AgrantSEM 데이터와 고객이 사이트를 방문하는 동안 오토데스크가 수집하는 행동 데이터 모두에 기초하여 제공됩니다. 오토데스크가 수집하는 데이터에는 고객이 방문한 페이지, 시작한 체험판, 재생한 동영상, 구매 내역 및 IP 주소 또는 장치 ID가 포함될 수 있습니다. 이 정보는 AgrantSEM에서 고객으로부터 수집한 데이터와 결합될 수 있습니다. 오토데스크는 디지털 광고 경험에 대한 사용자화를 개선하고 고객에게 더욱 관련 있는 광고를 제시하기 위해 AgrantSEM에 제공하는 데이터를 사용합니다. AgrantSEM 개인정보취급방침
    Bidtellect
    오토데스크는 Bidtellect가 지원하는 사이트에 디지털 광고를 배포하기 위해 Bidtellect를 이용합니다. 광고는 Bidtellect 데이터와 고객이 사이트를 방문하는 동안 오토데스크가 수집하는 행동 데이터 모두에 기초하여 제공됩니다. 오토데스크가 수집하는 데이터에는 고객이 방문한 페이지, 시작한 체험판, 재생한 동영상, 구매 내역 및 IP 주소 또는 장치 ID가 포함될 수 있습니다. 이 정보는 Bidtellect에서 고객으로부터 수집한 데이터와 결합될 수 있습니다. 오토데스크는 디지털 광고 경험에 대한 사용자화를 개선하고 고객에게 더욱 관련 있는 광고를 제시하기 위해 Bidtellect에 제공하는 데이터를 사용합니다. Bidtellect 개인정보취급방침
    Bing
    오토데스크는 Bing가 지원하는 사이트에 디지털 광고를 배포하기 위해 Bing를 이용합니다. 광고는 Bing 데이터와 고객이 사이트를 방문하는 동안 오토데스크가 수집하는 행동 데이터 모두에 기초하여 제공됩니다. 오토데스크가 수집하는 데이터에는 고객이 방문한 페이지, 시작한 체험판, 재생한 동영상, 구매 내역 및 IP 주소 또는 장치 ID가 포함될 수 있습니다. 이 정보는 Bing에서 고객으로부터 수집한 데이터와 결합될 수 있습니다. 오토데스크는 디지털 광고 경험에 대한 사용자화를 개선하고 고객에게 더욱 관련 있는 광고를 제시하기 위해 Bing에 제공하는 데이터를 사용합니다. Bing 개인정보취급방침
    G2Crowd
    오토데스크는 G2Crowd가 지원하는 사이트에 디지털 광고를 배포하기 위해 G2Crowd를 이용합니다. 광고는 G2Crowd 데이터와 고객이 사이트를 방문하는 동안 오토데스크가 수집하는 행동 데이터 모두에 기초하여 제공됩니다. 오토데스크가 수집하는 데이터에는 고객이 방문한 페이지, 시작한 체험판, 재생한 동영상, 구매 내역 및 IP 주소 또는 장치 ID가 포함될 수 있습니다. 이 정보는 G2Crowd에서 고객으로부터 수집한 데이터와 결합될 수 있습니다. 오토데스크는 디지털 광고 경험에 대한 사용자화를 개선하고 고객에게 더욱 관련 있는 광고를 제시하기 위해 G2Crowd에 제공하는 데이터를 사용합니다. G2Crowd 개인정보취급방침
    NMPI Display
    오토데스크는 NMPI Display가 지원하는 사이트에 디지털 광고를 배포하기 위해 NMPI Display를 이용합니다. 광고는 NMPI Display 데이터와 고객이 사이트를 방문하는 동안 오토데스크가 수집하는 행동 데이터 모두에 기초하여 제공됩니다. 오토데스크가 수집하는 데이터에는 고객이 방문한 페이지, 시작한 체험판, 재생한 동영상, 구매 내역 및 IP 주소 또는 장치 ID가 포함될 수 있습니다. 이 정보는 NMPI Display에서 고객으로부터 수집한 데이터와 결합될 수 있습니다. 오토데스크는 디지털 광고 경험에 대한 사용자화를 개선하고 고객에게 더욱 관련 있는 광고를 제시하기 위해 NMPI Display에 제공하는 데이터를 사용합니다. NMPI Display 개인정보취급방침
    VK
    오토데스크는 VK가 지원하는 사이트에 디지털 광고를 배포하기 위해 VK를 이용합니다. 광고는 VK 데이터와 고객이 사이트를 방문하는 동안 오토데스크가 수집하는 행동 데이터 모두에 기초하여 제공됩니다. 오토데스크가 수집하는 데이터에는 고객이 방문한 페이지, 시작한 체험판, 재생한 동영상, 구매 내역 및 IP 주소 또는 장치 ID가 포함될 수 있습니다. 이 정보는 VK에서 고객으로부터 수집한 데이터와 결합될 수 있습니다. 오토데스크는 디지털 광고 경험에 대한 사용자화를 개선하고 고객에게 더욱 관련 있는 광고를 제시하기 위해 VK에 제공하는 데이터를 사용합니다. VK 개인정보취급방침
    Adobe Target
    오토데스크는 사이트의 새 기능을 테스트하고 이러한 기능의 고객 경험을 사용자화하기 위해 Adobe Target을 이용합니다. 이를 위해, 고객이 사이트를 방문해 있는 동안 행동 데이터를 수집합니다. 이 데이터에는 고객이 방문한 페이지, 시작한 체험판, 재생한 동영상, 구매 내역, IP 주소 또는 장치 ID, 오토데스크 ID 등이 포함될 수 있습니다. 고객은 기능 테스트를 바탕으로 여러 버전의 오토데스크 사이트를 경험하거나 방문자 특성을 바탕으로 개인화된 컨텐츠를 보게 될 수 있습니다. Adobe Target 개인정보취급방침
    Google Analytics (Advertising)
    오토데스크는 Google Analytics (Advertising)가 지원하는 사이트에 디지털 광고를 배포하기 위해 Google Analytics (Advertising)를 이용합니다. 광고는 Google Analytics (Advertising) 데이터와 고객이 사이트를 방문하는 동안 오토데스크가 수집하는 행동 데이터 모두에 기초하여 제공됩니다. 오토데스크가 수집하는 데이터에는 고객이 방문한 페이지, 시작한 체험판, 재생한 동영상, 구매 내역 및 IP 주소 또는 장치 ID가 포함될 수 있습니다. 이 정보는 Google Analytics (Advertising)에서 고객으로부터 수집한 데이터와 결합될 수 있습니다. 오토데스크는 디지털 광고 경험에 대한 사용자화를 개선하고 고객에게 더욱 관련 있는 광고를 제시하기 위해 Google Analytics (Advertising)에 제공하는 데이터를 사용합니다. Google Analytics (Advertising) 개인정보취급방침
    Trendkite
    오토데스크는 Trendkite가 지원하는 사이트에 디지털 광고를 배포하기 위해 Trendkite를 이용합니다. 광고는 Trendkite 데이터와 고객이 사이트를 방문하는 동안 오토데스크가 수집하는 행동 데이터 모두에 기초하여 제공됩니다. 오토데스크가 수집하는 데이터에는 고객이 방문한 페이지, 시작한 체험판, 재생한 동영상, 구매 내역 및 IP 주소 또는 장치 ID가 포함될 수 있습니다. 이 정보는 Trendkite에서 고객으로부터 수집한 데이터와 결합될 수 있습니다. 오토데스크는 디지털 광고 경험에 대한 사용자화를 개선하고 고객에게 더욱 관련 있는 광고를 제시하기 위해 Trendkite에 제공하는 데이터를 사용합니다. Trendkite 개인정보취급방침
    Hotjar
    오토데스크는 Hotjar가 지원하는 사이트에 디지털 광고를 배포하기 위해 Hotjar를 이용합니다. 광고는 Hotjar 데이터와 고객이 사이트를 방문하는 동안 오토데스크가 수집하는 행동 데이터 모두에 기초하여 제공됩니다. 오토데스크가 수집하는 데이터에는 고객이 방문한 페이지, 시작한 체험판, 재생한 동영상, 구매 내역 및 IP 주소 또는 장치 ID가 포함될 수 있습니다. 이 정보는 Hotjar에서 고객으로부터 수집한 데이터와 결합될 수 있습니다. 오토데스크는 디지털 광고 경험에 대한 사용자화를 개선하고 고객에게 더욱 관련 있는 광고를 제시하기 위해 Hotjar에 제공하는 데이터를 사용합니다. Hotjar 개인정보취급방침
    6 Sense
    오토데스크는 6 Sense가 지원하는 사이트에 디지털 광고를 배포하기 위해 6 Sense를 이용합니다. 광고는 6 Sense 데이터와 고객이 사이트를 방문하는 동안 오토데스크가 수집하는 행동 데이터 모두에 기초하여 제공됩니다. 오토데스크가 수집하는 데이터에는 고객이 방문한 페이지, 시작한 체험판, 재생한 동영상, 구매 내역 및 IP 주소 또는 장치 ID가 포함될 수 있습니다. 이 정보는 6 Sense에서 고객으로부터 수집한 데이터와 결합될 수 있습니다. 오토데스크는 디지털 광고 경험에 대한 사용자화를 개선하고 고객에게 더욱 관련 있는 광고를 제시하기 위해 6 Sense에 제공하는 데이터를 사용합니다. 6 Sense 개인정보취급방침
    Terminus
    오토데스크는 Terminus가 지원하는 사이트에 디지털 광고를 배포하기 위해 Terminus를 이용합니다. 광고는 Terminus 데이터와 고객이 사이트를 방문하는 동안 오토데스크가 수집하는 행동 데이터 모두에 기초하여 제공됩니다. 오토데스크가 수집하는 데이터에는 고객이 방문한 페이지, 시작한 체험판, 재생한 동영상, 구매 내역 및 IP 주소 또는 장치 ID가 포함될 수 있습니다. 이 정보는 Terminus에서 고객으로부터 수집한 데이터와 결합될 수 있습니다. 오토데스크는 디지털 광고 경험에 대한 사용자화를 개선하고 고객에게 더욱 관련 있는 광고를 제시하기 위해 Terminus에 제공하는 데이터를 사용합니다. Terminus 개인정보취급방침
    StackAdapt
    오토데스크는 StackAdapt가 지원하는 사이트에 디지털 광고를 배포하기 위해 StackAdapt를 이용합니다. 광고는 StackAdapt 데이터와 고객이 사이트를 방문하는 동안 오토데스크가 수집하는 행동 데이터 모두에 기초하여 제공됩니다. 오토데스크가 수집하는 데이터에는 고객이 방문한 페이지, 시작한 체험판, 재생한 동영상, 구매 내역 및 IP 주소 또는 장치 ID가 포함될 수 있습니다. 이 정보는 StackAdapt에서 고객으로부터 수집한 데이터와 결합될 수 있습니다. 오토데스크는 디지털 광고 경험에 대한 사용자화를 개선하고 고객에게 더욱 관련 있는 광고를 제시하기 위해 StackAdapt에 제공하는 데이터를 사용합니다. StackAdapt 개인정보취급방침
    The Trade Desk
    오토데스크는 The Trade Desk가 지원하는 사이트에 디지털 광고를 배포하기 위해 The Trade Desk를 이용합니다. 광고는 The Trade Desk 데이터와 고객이 사이트를 방문하는 동안 오토데스크가 수집하는 행동 데이터 모두에 기초하여 제공됩니다. 오토데스크가 수집하는 데이터에는 고객이 방문한 페이지, 시작한 체험판, 재생한 동영상, 구매 내역 및 IP 주소 또는 장치 ID가 포함될 수 있습니다. 이 정보는 The Trade Desk에서 고객으로부터 수집한 데이터와 결합될 수 있습니다. 오토데스크는 디지털 광고 경험에 대한 사용자화를 개선하고 고객에게 더욱 관련 있는 광고를 제시하기 위해 The Trade Desk에 제공하는 데이터를 사용합니다. The Trade Desk 개인정보취급방침
    RollWorks
    We use RollWorks to deploy digital advertising on sites supported by RollWorks. Ads are based on both RollWorks data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that RollWorks has collected from you. We use the data that we provide to RollWorks to better customize your digital advertising experience and present you with more relevant ads. RollWorks Privacy Policy

    정말 더 적은 온라인 경험을 원하십니까?

    오토데스크는 고객 여러분에게 좋은 경험을 드리고 싶습니다. 이전 화면의 범주에 대해 "예"를 선택하셨다면 오토데스크는 고객을 위해 고객 경험을 사용자화하고 향상된 응용프로그램을 제작하기 위해 귀하의 데이터를 수집하고 사용합니다. 언제든지 개인정보 처리방침을 방문해 설정을 변경할 수 있습니다.

    고객의 경험. 고객의 선택.

    오토데스크는 고객의 개인 정보 보호를 중요시합니다. 오토데스크에서 수집하는 정보는 오토데스크 제품 사용 방법, 고객이 관심을 가질 만한 정보, 오토데스크에서 더욱 뜻깊은 경험을 제공하기 위한 개선 사항을 이해하는 데 도움이 됩니다.

    오토데스크에서 고객님께 적합한 경험을 제공해 드리기 위해 고객님의 데이터를 수집하고 사용하도록 허용하시겠습니까?

    선택할 수 있는 옵션을 자세히 알아보려면 이 사이트의 개인 정보 설정을 관리해 사용자화된 경험으로 어떤 이점을 얻을 수 있는지 살펴보거나 오토데스크 개인정보 처리방침 정책을 확인해 보십시오.