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Turning the Key to Data Completion: How to Maximize Digital Deliverables

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Owners may specify what they want in their deliverables, including data assets, but they may not always be aware of what that entails. In this session, we’ll go over how to chart a course to provide useful digital and data deliverables to the owner, starting from project inception. This includes assets such as federated intelligent models, COBie data, energy analysis reports, clash reports, and more. The method will start from the end and work backward to the beginning, providing a definition of each deliverable, its relevance, and the setup of a schedule for delivery. So, if you want to advocate for your team join this session!

주요 학습

  • Learn how to decide the kind of data owners need based on contract deliverables and delivery methods.
  • Learn about different report types like sustainable criteria, construction data, operations data and more.
  • Learn how BIM assets like federated models, COBie reports, and clash detection can be used as deliverables.
  • Learn about planning the deliveries out with defined expectations and a schedule to help you achieve the results and deliver to the owner.

발표자

  • Tadeh Hakopian 님의 아바타
    Tadeh Hakopian
    Tadeh Hakopian leverages BIM, VDC and Design Technology to provide his teams with impactful tools for project success. He has over 10 years of experience in the AEC field developing methods and practices to improve project outcomes. With a background in Architecture he has worked with designers, engineers and contractors in all phases of building design and construction. Over the years he has been a part of large, complex projects in Commercial, Sports, Education, Healthcare and Residential sectors. His current focus is on design automation, data insights in projects and comprehensive workflows that come full circle in planning project life cycles. He is an active speaker at conferences including Autodesk University, ATG Midwest University, BILT NA, BIM Forum, Python Conferences and his local community meetups. Current Professional Goals: Help move the AEC profession into new horizons using value driven solutions and innovative research.
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    Transcript

    TADEH HAKOPIAN: Welcome to Turning the Key to Data Completion, How to Maximize Digital Deliverables. I'm Tadeh Hakopian. Let's get started.

    A little bit about the session. This is all about working with owners, the deliverables, the data assets, and basically, how to help them get what they want. There's so much data out there in the world. There's so much information, whether it's our model data, our web data, our project data, our energy analysis data, and so much more, that we have a treasure trove of content that the owner could benefit from at project completion. So we'll talk about what data is out there, how we can work with owners to get that data, and examples some projects I've worked on that could show the potential early on and through advanced stages of what that data can do in order to help people achieve that data success in their projects and make the owner satisfied and show value to the project.

    Just a couple of learning objectives today. We'll understand what kind of data we have and the kind of contract deliverables that data might be able to satisfy. Talk about sustainable criteria, construction data, operations data, and more. Learn about how federated models, cash reports, and other data deliverables can be used in this effort, and how, most importantly, we can plan this out with defined expectations and help your team schedule achieve the results to the owner in a concise way.

    A little bit about myself, Tadeh Hakopian. I've been experienced in over 10 years in large scale projects in the AEC sector, working for every part of that AEC acronym, architects, engineers, contractors, and much more, working with the data and DC individual points. So I've done a lot of big projects, contract reviews, requirement definitions, compliance, hands offs. So I've been there, done that for many years. I find big projects and big deliverables and data very worthwhile and interesting, and that's something that I've done over the years. And I encourage everybody else who has a chance to that to try it themselves.

    And a question for you all as we talk about this, think about the opportunities you've had to prepare document handover at the end of a project. What does that look like? How has that felt? I've been in situations myself where sometimes we have a pretty well defined idea of what kind of content we're handing over to an owner, to a facility management, to whoever needs to get that content from us. Other times, it is a waiting game, a guessing game, or we might have a line item to figure out on a contract that says you have to provide a digital deliverable, a data deliverable at the project close out for specified items defined by the owner, just a line item, and it turns out it ends up being two months of work.

    So as you could see, this landscape can go from very vague and not explicit at all to hyper explicit. So consider the kinds of projects you've been involved with and how you've experienced that yourself over the years, because I've gone from very explicit, query defined requirements, to vague requirements on big projects that take a long time to figure out. So see if we have any kind of common ground as we discover these options.

    So part one of this, understanding the owner, also known as becoming a mind reader for the owner. And part of understanding the owner's expectations and what they want is to understand where they're coming from. And we can start here in the construction value chain. And it all starts with data.

    With data, you get enough information and context and everything from the project to supply every step along the way, including being able to share that data. If they don't want so and so, good. If you cannot get it out of its silo, get it out of its files get it out some way to share it over the cloud, in a concise, structured way.

    That can then provide information to design the project. The project can't be started if you don't have any design documentation, which could then go to help understand what it takes to get the project to completion, which have a defined design criteria in programming and sizing, what have you, help finance and figure out the cost of a project. You can then build it.

    And once you build it, you want reports. You want information. You want to be able to account for all that. But again, it all starts with data. This is the value chain, owners looking at these dates as we need to figure out what's happening on these projects, what we're building, how we're building it, why it's designed in such a way to cost a certain amount of money, and you go back to the data collection stage here.

    So what does that data look like? What is the owner interested when it comes to data? Well, there's lots of data out there. There's data from the field. This is always overlooked, in my opinion. You have all sorts of things, like total stations, laser scan stations, drones, phones, all sorts of stuff out on the field that is a great source of data that can help document what happened to a project in the physical space. That can be high definition, real time. That can really benefit the operations of the construction project, but also the closeout, because that's about as high definition of data and timely data you will get by the time the project's ready to go. So just the field equipment on its own is very valuable.

    You also have data for project management, whether that's cloud resources like Autodesk Construction Cloud, project manager resources like Airtable, databases like SQL Server, what have you. There's lots of project management data that contains a lot of the files and resources that we take for granted every day, whether that's your BIM models, spreadsheets, cost models, scheduling, you name it, PDFs. It's all there, and that's a great source of data. These are the kind of things owners can take advantage of, because the kind of data that owners care about that can help a long term effort is data for facility management.

    This is an example of that is think of all the hardware, mechanical equipment, everything inside a building the owner has to actually maintenance with building maintenance and operations maintenance for years and years. We've all heard, for example, that the 80% of the cost of building is actually from operations over the cost of decades and decades of operating the building, and maybe 20%, possibly less, depending on the building, is just the actual cost of construction, again, depending on how the building is used and what it takes to keep it operational for many years to come. Some buildings can last well over 100 years before significant restoration or demolition occurs.

    So from an owner's perspective, this is what they care about day to day. Once it's ready to build, ready to move in, or it's been renovated, it's the kind of thing they have to pay attention to make sure that their operations are smooth, not just the capital expenditures to build the project, but also the capital expenditures and the operating expenditures to make sure the project runs smoothly. And that's the kind of thing owners want to get facilitated to and have this available to them more efficiently in a timely manner for every project. And I've been seeing that over the years myself, that owners want to get more data for facility management operations and for their portfolio of assets.

    So consider a data driven design, a data driven approach to design and construction. It can do a lot of things like empower design review, to make sure everybody has the right resources available to them, and avoid duplication and time wasted. You have the right resource at the right time to check your work. You can improve document management by having a higher standard of coordination of file storage and file sharing and a single source of truth, a common data environment. All these things can be beneficial in a better data driven approach to construction and design.

    And of course predictive analytics can eventually come out of all this. If you already have great design review that rationalizes and resolves the project and good document management that shows everybody in the project where resources are, you can feed that all to the operations phase of the building structure and make it easier for an owner to figure out how their purchased items from you, that is a mechanical equipment, the lights, furniture, the architectural design, the structural design, everything, how that works. Can they feed this into predictive analytics to figure out what will break when, what needs to be replaced when, how long the lifecycle of the door is before it needs to be modified, replaced, fixed? These are the kind of things that benefit every portion of a project and every party involved.

    And I'd always recommend the funnel everything through one common data source, and usually it's been the billing information model. You can funnel that design, the data, the geometry in one place. And whether that's a BIM model or another format we use, be aware they should, as much as possible, be located in one directory. Of course Autodesk has lots of great products for BIM, and cloud collaboration, and everything along that lifecycle, then, so there's a lot of great resources out there already to make sure your BIM models are able to account for all these changes in the project.

    So this does not come free. It takes effort. You have to create a database for all this. You have to have adherence on standards by all parties on the project, and you have to have clear responsibilities and contingencies for all parties. So no one's misunderstanding the requirements. No one's misunderstanding the standards, and everybody's using the same database, the same source for all the information.

    Now there's lots of people listening to this right now who might be very savvy technically, very experienced in what they do day to day, but thinking I'll agree with me that actually getting everybody to play nice is a big challenge in this world. And this is where I found myself having the most headaches. That either one or multiple parties in the project have a hard time adhering to standards, or there is no standards, or you're on your own. Or the owner doesn't have anything outlined that can really guide the entire project team. Or it's all a traditional model of work where there's a hand-off one team to another.

    So there's a lot of challenges to get to a place where we have standards, databases, and responsibilities lined out. So we'll talk about where that can happen in the project, and really how to get the best buy in preview in. Hint, answer. If you can get the owner to really have a baseline of rules and requirements for everybody in the project, this is a lot easier. Again, there's a portion here that we have to make sure the owner is able to take guidance from people who've already been down the road, but also be able to lead. And not just have a lot of say a fair approach to project coordination, because you can't get good data if you don't have a good process to get that data.

    So with that in mind, we'll talk about project planning resources, defining roles and priorities as a starting point. And with roles, we have this nice little circle, and everybody involved. This building here represents the owner and their operations and facilities. This awesome drawing here represents the designers and architects coming up with the content for the next project, and of course this crane here represents the builders.

    These are the roles typically found at project. Would be much more complex, of course. There's logistics, there's supply, there's all sorts of things, but we'll get started with this. So let's talk about the owner and what they usually care about.

    Operating costs, budget, they care about this a lot. This is their priorities. They care about asset management. Again, if you're a designer or builder, once that project is done, you move on to the next project. But the owner has to worry about that and make sure everything they bought and paid will last for years and years, if not decades, and that is something they always have to be on top of to avoid any kind of degradation of their assets. And logs and records. These are usually kept in paper format, and these days moving to digital, but there's lots of logs and records to maintain what they've done in the past. So these are the kind of things the owner of facility management usually keeps in mind.

    What about the architect design team? They care about data, and course design data, operations data, but data to back up their project information. Also drawing sheets. Architects and engineers are very sensitive to drawing sheets to this day for contract deliverables, but also accurately defining what they are making in every facet of the project. And of course details to make sure that there's no misunderstanding about the specific nuances of a given design.

    If we go to the general contractor, they care a lot about coordination between all parties of all designers, subcontractors, suppliers. This is day to day work for a general contractor. Quantities for quality take off, estimation, purchasing, organization, this is a big important part of their day to day work as well. And of course operations, scheduling their project, making sure that the right resources are on the site, and being able to account for that and being able to get a job done at the right time.

    So consider if you're in one of these different buckets of work what your priorities are. But also be sympathetic to the other people you work with and their priorities, because again, you have to work together to make the dream a reality. And that dream is data. And we'll show you a great case study right now.

    Project one. Case study of doing your best. And this is something I worked on personally in the past. It's called the UCSD, that is the University of California, San Diego, Learning Living Neighborhood. Precursor project to a lot of the things I've learned over the years about data management.

    And this used to be a parking lot. This was a big old parking lot with two terraces. They-- the facility owner, which was the UCSD campus, wanted to change that. So it had this big plan, they want a million gross square feet campus facility, mixed use residential, 1,000 beds for the students. Fully within the campus, which gave the campus and college a lot of control over what happens on this project. And they want a design build project approach, with the architect and general contractor working together from day one, and reporting directly to the owner. And without having any intermediary owner reps, which is beautiful, so there's a lot of good coordination, a lot of good synergy between parties here.

    I worked for the architect at the time. HKS architects, and we paired with GC, general contractor, Clark Construction. We won the competition. We got awarded the project. And the owner said, let it rip. And we got started to complete this project in 2020 with the starting phases in 2016.

    So ambitious, lots of scope, $500 million project. So what happened with the owner? Well, the owner here had no requirements. UCSD only required PDF and CAD plans required at hand over. There was no communication from the owner throughout the production process for data or document requirements until the very end, and they had no specified requirements for us for cloud environment or blue BIM studio sessions or Autodesk Construction Cloud or anything like that. It was whatever we felt like doing.

    So what do we do? Well, the design build team Clark HKS has had a plan, because both sides worked on a lot of projects over the years that were large, how a lot of resources them, and we have to make sure all of our parts are coming together cleanly. We already had internally to ourselves with no requirement from the owner a lot of plans to get ready on every stage, including the model content, the document content, and even some of the data content.

    We set aside requirements for system units to use for measurement. That precision, phasing requirements, design option requirements, what kind of data reporting we do internally. Our standards for using CAD and BIM software level development definitions, our matrix responsibilities. So we had the right party making the right content at the right time. And assigning that and making sure everybody was able to deliver that.

    Quality control, and clash detection built into it, and we all signed off. Everybody working on this project reviewed the plans we had in mind, co-led by HKS and Clark, and we signed it off for everybody. They were aware what they would have to do that was responsible in their scope. And what we did to get that set up, we had a common data environment cloud, we used BIM build 60 for every fast through BIM environment. So we were all in the same place, with a shared database. We already had that in mind. So we weren't wasting time sharing exchanging files.

    We weren't lost in which file is the most recent. It was already taken for us. Taken care of for us for us in the cloud. And that was true whether we're working on PDF sessions, project management. There was always some cloud repository for all this. We wouldn't get mixed up. That's really important when you have a fast track design build project.

    We made sure our data alignment was correct for the site. Cannot emphasize this enough for something that big. You can easily lose track of time and space and take things for granted. And we were able to have that aligned.

    Clash coordination, again wholly decided upon by a team to make sure we had not only design documentation from the design engineers and architects, but also subcontractors were making their own models. Clash shared, that clash process took two years, and we were able to resolve a lot of issues before they showed up in field saving a lot of time and money for the project. And of course, we had a lot of definitions for level development, what model looks like at different times and phases. So this is all what we did on our own. Again, the data was there. Like I showed you earlier with all the data resource in the field, and your project management. It was all there.

    And this is what our BIM environment looked like. Cloud hosted models, each one of these files in different colors here represents a different building. And each one of those had an interior model inside of it. And the architect set the stage at a high quality definition of the models, and the model environment, and the alignments. That way the starting point here of 10 or 12 different models would then be able to be taken as examples for the entire project team that eventually ended up being nearly 60 Revit models posted on the cloud, following the same standards, data and everything. And then the contractor can reliably use that to do the clash detection.

    As an interesting example, the kind of models we build just for architecture scope, complete inside and out model data, room data, FF&E, areas, you name it. This is everything we use to track our own content in Revit, in BIM, in our quantities, in our estimating, in our design review, you name it. The client, UCSD, did not ask for any of this. This is what we did to make sure design build operations for a project of this scale work smoothly.

    Just give you a little bit more zoom here, you can see that we had a pretty detailed facade here, different floor plans. But also you zoom in to the inset here, every floor and every room inside that floor had every piece of furniture, that we wanted to count everything ourselves to make sure we were on target, because again, this needed to be ready day one. Fall 2020, this had to be turnkey ready. We couldn't take anything for granted and just have simple symbolic references. Everything was modeled in their worked in environment. You can do a full walk through every floor in this building, and see everything from the furnishings, to all the other models, including the engineering models for electrical and what have you.

    That was all there. Plus we thoroughly mocked up everything with PDF sessions to make sure that we had a log of all the changes between the clouds and revisions to something that would be ready to review, that would be shared on a common database between the designers, architects, engineers, consultants, and the contractor and the subcontractors. And during these sessions we would actually work with the owner so they can see everything we picked up and changed. All from the same models, put the PDF, reviewed consistently, week after week after week, so we weren't having any kind of divergence between the documents that's here, and the models.

    And Clark construction was really great at operations in the field. They use drones to look at the excavation topography. The blues here are lows, and the yellows here are highs. That way they had a pretty good idea of what the landscape was with a drone flying in the sky, taking these kind of images so they won't have to spend days or weeks trying to analyze this the old fashioned way, with levels. Because this is a big site. Multiple acres, and we had to move fast, so they used a lot of technology, again. Clark's operations all on their own. And the clash review that the Clark operated took two years, and included the entire design team at every model, and we start off one level after another after another based on requirements we set aside at execution time.

    Well, UCSD was picking up on a lot of this, and realized we had a really good stuff that we did on our own. So they said, hey, guys, since you have some great content here, what would it take to take all those assets, especially in the BIM sphere, condition them, and be able to deliver to them a facility management model? To be able for them to then tie-in to a system called IBM maximal, pretty common in the facility management world that can track tickets for equipment, breakdowns or facility updates, what have you.

    And we looked at our proposal, it was an ad service at that point, not part of the original budget because they didn't have a requirement for this. And once we gave them a proposal for how much it costs to run this, and you can see here in this diagram, they're looking at Autodesk Forge as part of that back end to make this work with IBM maximal and our models, we had a lot of ideas in mind. Without consulting evolve from the owner side, and we worked it out. But ultimately due to the cost of the ad service and the pace of the project, they started to put a hold on this, and decided to move on to the next project to do something like this.

    So we had some lessons learned from this approach. Talk early and talk often with owners and managers. Because again, we're all stuff you saw us do on this big project here, that was what we were going to do anyway. So we could have brought this up to your attention, say, hey, we've got this great stuff for you guys if you want to use it early on, if we had something like this 2016, early 2017. So they could see what we're up to, and maybe find a way to bake it into the project early on, or at least take a less expensive as an ad service. And it could be a simple conversation, and reach out maybe to your project manager, executives, talk to the owners, facility manager, to see what it would take to get there. What would take the bridge to gap what's possible now at least have a conversation about it if no one is really clear.

    Upon a data strategy at high level with your management, I can just clarify what you have just like I showed you on our BIM models and the scope and operations. We had a lot of great stuff. How do we connect those dots? Is there something we can hand off to the owner of high quality that could benefit the owner's operations?

    And if the owner doesn't know what they want, they see some great stuff but they don't know, provide some guidance. Say, hey, these are the possibilities. They could be used for a condition model at the end that could account for all the equipment in the project. Maybe the owner doesn't need to know everything about say the interior walls, or the stairs, but maybe they're interested in the furniture. That we saw my models I'll showing you there, we had every piece of furniture model. Owner really likes the idea of having an inventory of all the furniture they bought. To show them what's possible at easy level.

    Well, you might be thinking, great, but what do we do now? But here's the cool thing. We get to do it again. That might surprise you, but this is an interesting scenario. So remember I said to you that the project, the UCSD project, here is the campus map. Well we call that project Torrey Pines Living and Learning Neighborhood, which was completed in 2020. So it's been operational for two years already. And there's another project they're looking at that was also a parking lot. They also want to build a campus facility. At the time they called it Future College that they want to build in 2023, and we heard about this in 2019 as a possible opportunity for another project.

    Well, wouldn't you know? Isn't that interesting? Right down the street. You walk right down there, a five minute walk across the campus, and you end up in a similar environment. So we had a chance to do this all over again with a very similar team, in a short amount of time. Just to give you a time scale, we wrapped up a lot of the design of Torrey Pines in 2018, so by the time the next project came around as an opportunity in 2019, a lot of the same people were able and ready to go. All the lessons learned, fresh in their minds, from every perspective of that project, not just my own.

    So the next project we got to level up. This is awesome. How often you get to do this? We get to work with the client, at this time they had a better idea based on their own experiences as an owner, as an operator, for data deliverable requirement. Most of the same team was able to return on the design side, and by coincidence some other partners we worked with were also able to return, and they were aware of what we did last time that worked and what didn't work, and we were all going to communicate with each other a lot better since we already knew each other.

    The contractor was a little different this time, and a different contract to work with, but they had a full prefab unit, which helped us go even further with integration, because we were designing with them at this point to make sure what we were designing was also something they could do on prefab side. And what we can do to have a digital project planning side. Awesome opportunity to apply lessons learned within a year of wrapping up last project.

    So this is a chance to show you what we were doing, and check this out. We call this now the UCSD Theater District. This the idea for it. It is the Southern gateway and facade, if you will, entrance to the campus. So they want to really bring it out in a big way. And this is done by HKS architects, Kitchell contractors, same client, same campus, UCSD. Again, happened to be a very, very, very similar program, 1 million square foot gross. Mixed use residential, 1,000 beds, all [INAUDIBLE] facilities for recreation, education, dining, you name it, it's all built in just like last project. Again, design build, architect and contractor working together to deliver something to the owner. So expected key completion in 2023.

    So we had this. We presented our project. It was accepted, and starting in 2019 we all worked together to make this happen. So how cool is that?

    And with this Theater District project we had a lot more chance for data analysis, to climb on to see more from us on what we're going to do with reducing cost, with prefab construction. We had, again, the control contractors have their own offsite prefabrication operations they could use to really control quality and cost. While the piece of the project is seeing the top graphic, how that all comes together, with the architect's design intent.

    And figure out how we can show a very efficient concept for renewable, sustainable design. This is very close to the Pacific Ocean, only about a mile away from the actual ocean currents, in the image below you can see the kind of analysis we did to see what the fluid flow of air through the units looks like to really utilize the environmental context. And again, how can we take all this data for prefab, environmental analysis, BIM, and put it together in a way that can really show off to the owner what we can do.

    So we had an enhanced BEP, execution plan, and data requirements. More data than last time for this design build scenario. A very robust execution plan with a client template, which sounds amazing, given that they had no template before. They had a full bore template to work with.

    And everything lining up for a fast paced design, again, from time to concept came together as a project proposal, RFQ, RFP, in 2019 to time they want this complete as turnkey ready, in 2023. Four years, which if you're in California is a speed of light from design to construction completion, we have to get the most data out of our project to make that work. So we'll talk real quick about project planning revision and rethinking our approach to make sure we hit the targets before we go into all the stuff we did with this new project.

    So we've got a roadmap plan. For anybody who works with any kind of long term planning, I highly recommend creating a roadmap. And a roadmap is just a diagram. Think of it as a communication document that shows the intent of what you're going to do in a project, process, you name it. It doesn't have to be elaborate. It's not going to be a construction schedule that has every day and week labeled out. So it's much more simple than that.

    And I go with the KISS principal. K-I-S-S KISS principle. Keep it simple, stupid. Do not make this complicated. Do not make this complex. The roadmap you try to communicate a strategic plan, like our beautiful target here at the very end, that tent. You're trying to show people how to get there. Right? In the very straightforward way, all the twists and turns and links, but very straightforward, where you start, where you go. Strategically and graphic not much more complex than this.

    Because after all, the reality is very complex. And that's where all the nuts and bolts of day to day, week to week, month to month work comes to play. This is important. You shouldn't take that for granted. But this is not going to be easy to communicate. So what you want to do is simplify it in a broader review that the entire project team, your managers, your specialists, the owners, everybody can get real quick so they know what to expect, and they don't leave anything on the cutting room floor.

    So for example, you can use simple graphics to help map out your process to help you prepare for a road map. I would say, for example, some of the operations I use, I said again, filter and funnel everything. Design data geometry that we saw earlier in this presentation. And to them. That's my strategy. Your strategy might vary a little differently.

    This is the approach I took, because if I put everything in a BIM context, that's put everything in one place for the BIM models on a common day environment on a cloud, I can get all this great stuff out of it. I mean pre-construction information, quantitative data, design plans, LCA life cycle analysis data for the renewable aspects of this, and great visualizations, all from the single source. This is how I can make the project operate efficiently, with the same resources. I had of one source of knowledge to BIM.

    And from there I can get derivative content like the structure coordination, and quantity data, and design plans go to VDC, virtual design construction, to get things that clash coordination, and 4D timelines of the operations. And then I could take the other aspects of this design plans, visualization, LCA data, get project flexibility data information. That would be great for handoff. You pair that with the actual project control distribute data, that comes with the projects built and finished, you can then get a digital twin project out of that.

    A digital twin is basically a dashboard visualization of the project that can be walked through if the built environment along with streaming data of all the hardware feeding into that dashboard. That's a topic for another discussion. But if you guys are interested, check out digital twin projects in architecture or construction. Check out Autodesk 10 for more, because there's a lot of great stuff in that space, and BIM really does make a difference there.

    And of course with the VDC operations we can get a nice, beautiful record model delivery to the owner, rationalize, resolve, and clash free and federated that the owner can say yes, this is. We can say to the owner, yes, this is a good model that you can use for your operations, because we clean it up, it's beautiful. It's already federated. Nothing to worry about. We'll put that all together and we have some great content for the building maintenance to owner.

    And I say let's all start to make sure everything's in BIM, because all the Derivative content downstream can start in one place. So I map that up, make sure I know what I want out of it. Otherwise it's going to be hard to communicate to other people.

    And with a simple roadmap I highly recommend again a chart, where you have, for example different phases. Again, you have to say months or anything, just phases of project. And the OKRs here are just tasks, things you try to finish which are objectives key results. That's just my own terminology. You can just say tasks, or projects. Mini projects.

    From top to bottom, you have priorities, from left to right, you have time. I'll show an example of this. But this is a great starting point because you can literally take this, copy it, and make your own, and show it off your team for any project you're doing whatsoever. It's really easy to follow. It's hard to mess this up. So try doing something like this, one page diagram of any project you're working on. OK.

    With all that in mind, let's talk about project two. A case study of what to do and what you can do with the right resources in place. So again, Future College, also known know as Theater District UCSD. A lot more elaborate facade, a lot of great outdoor spaces. So we had to figure out how to make the most of this project for the owner. Again, this is a year after we wrapped up the design of the Torrey Pines project on the same campus, which was under construction at this point.

    And the owner, like I mentioned, gave us their full template for a facility data deliverable, and we just called on the project BIM execution plan. And again, this is something the owner gave to us. This is their template. We didn't give them to them, but the owner trusted us to take this, the design build team take this, fill it out, answer every part of this that we could answer, give guidance to the owner to help them understand what we could and couldn't do, or what was rational to complete and what was not really worth our time to worry about on this project, because it wasn't part of the scope. Because this thing had everything and the kitchen sink inside of it.

    So we couldn't account for 100% of it, but we account for a lot of it given the scope of this project. And we did want to account for as much as possible to get the best content out of that project. And avoid doing what we did last time, where we had everything you could imagine, but we just didn't have it available in a way the owner provided us.

    So what we did is we reviewed this, work with the owner's documentation, and came with a plan with them. And we call it the project execution plan.

    And we came up with some actionable goals. So let's do these goals. We'll have a live day model as a single source of truth, which I elaborated upon that mapping process. Integrated review. So we're not using different data sets or different models or PDF sheets or anything. Everything's integrated, basically the same thing. We did the first time, we're going to double down on that this time.

    Cost estimates are derived from models. Not from any other source. The models had the most recent version of everything, a fast track project. We don't want to model something printed out review or PDF in a digital space, review that, then we get enough data. That's too many steps. Let's get it straight from the models. So we have the best information. Sorry about that.

    Construction timeline modeling. So we can get a 4D model, that means a model timelapse of how things are built, based on, again, our BIM models, the single truth so we know what it takes to get those prefab units in there. The scheduling of the construction project. Clash coordination of design, to make sure everything's resolved ahead of time. So we have no issues in the field, no problems in the field, everything is good before it gets built.

    As build condition model it means a model we get ready by the time this project is finished, that we have a 100% resolved, everything looks the way it's built model, that we can hand over to the owner. And a managed model, that means the model we took care of based on the first six points here, that we could hand over the facility management, deliverable to UCSD, and they get what they want based on that template they gave us.

    And we also help make it easy to digest this information. We clarify what the overlaps on the BIM scope are for these digital deliverables. We said, BIM is able to take care of the product side, design engineering graphics, technology, including hardware, sustainability, procurement, and marketing. And BIM is very versatile when you think about. Product in this case, think of the prefab units we're building off size of product that we can really focus on. It wasn't just something we would build on the side. It was already ready to ship, now hundreds of those. So we can say how can we really take care of that prefab product side of things with BIM, make sure that's a specific defined asset we can focus on.

    So with more modular construction, more prefabrication construction in mind, think in ways you can really dial in those areas of how BIM and products can go together and get the most out of those data sheets. Because you already have a lot of that defined before you get construction. Design engineering, course graphics, but also model for planning graphics, analysing graphics, also model exchange, center operating procedures, SOPs that we can elaborate and make sure everybody is playing by the same rules, nobody's inventing their own process or doing their own thing.

    Technology, same software platforms and hardware and PC and everything. We make sure everybody has the right capabilities, resources to get started. Sustainable analysis. We can take the models and use it for lifecycle analysis. For example, with BIM 360 integrations can actually give you some pretty reliable carbon and energy costs built into the model. And data sheets resulting from that. So that's something we take advantage of for this kind of projects.

    We can get a lot of great data for the cost of the project. We kind of take offs and the VDC process and marketing. We already have the 3D graphics as a project in the BIM models we're designing anyway. So could we use that for visualizations and walkthroughs and VR and renderings? Again, use what we got. So this is a great way to show off the entire team for those who aren't specialists in this world of game in Revit and all things data. What we can do with it, put out our documentation, make it easy to digest.

    And of course spell out our software stack. What do we use? We have Revit, the Blue Bean, we have Procore, we have IBM Maximo. These are things we have to specify say this is we're going to use the project team. Revit's our BIM environment. Procore is our schedule environment. IBM Maximo is what the UCSD facility teams is trying to use to make sure the tickets for their maintenance by the time projects [INAUDIBLE] ready to go are handled, and Revu is just for PDF markups.

    These all come from different people doing different things. I myself would love if if it were just one big bucket of operations, one big sign in, and of course, since this is artist talk. There are a lot of great things all of us can handle for a lot of these folks, but you have to figure out the way to make these things work as tightly as possible. So we have to outline our software stack, how are we going to use them, and make sure everybody's aware of how this works.

    So always label it out, clarify that, don't take it for granted, because somebody might think Revit's over there, and Procore's over here. No, no, they should all talk to each other as much as possible. So you don't have different realms separating from each other. Always figure out a way to make sure everything talks to each other as smoothly as possible to get the best results at all these stacks, make sure they're all have synergistic results.

    And again, map out the process. This diagram I showed you earlier, I walked you through, this is valid for the project we're working on in other projects. I clarify we need to put everything in BIM, make sure we get all the root and downstream results. That's how we get all the goals settled out. And a process planning for predictable outcome. You can see here we have parts 1 through 6 in the columns, and we're working through a tree here to make sure that everything we design in a design update can be verified and corrected along the way.

    And each one of those diamonds, orange diamonds, is a yea or nay. We get-- we hit our mark or not. Did we get the correct quantities? That we can then review in our model updates. Yes or no, if there's anything to fix, we go back and fix it. If not, we do a full review of the model. Is there anything that needs to be added? Yes or no, if no, we can do an update with our proper sheet templates that can then go into PDF sheets, and plan review sheets for the team review.

    Does anything have to happen at this point? Yes or no? If yes, we start all over the back, because that might be a major change to facade or floor plates, which happened many times this project. If not, we're done. This might seem obvious, and this might be something that plays out your head. Please write this down. I highly recommend writing this down so everybody knows what it takes to get from A to B to Z to whatever.

    These kind of things really elaborate the operating procedure and elucidates why you need to have a certain amount of control in your data environment without the Revit model as SQL database, PDFs or whatever. Always spell it out. Because then we can get this, our goals.

    So we talked about the goals earlier, but here we label on the left column what we define as goals for the entire project team to achieve. How are we going to get there with our BIM models? And the measurements we're going to use to get there.

    For example, in the first one here we want to achieve day one operational readiness by implementing a facilities information strategy. And be ready for operations on turnover. And we're going to make sure our asset management digital data in urban environments are ready for that by having a handover process that accounts for that. How do we get there? We make sure we have regular meetings, established for milestone review, to make sure everybody, all parties design, construction, operations, whoever, are available. Review it, have confidence in the process so far, can provide remarks, and make sure we're ready for operational awareness.

    And we have that all listed for the rest of those goals we talked about earlier. You can-- if you measure something, you can control the outcome. So we had to make sure we had measurements. KPIs, what have you. Always make sure you have a way to measure it.

    And this is what we showed off to the owner saying this is how we're going to do it for every step of the way from cost estimating to authoring to as build handoff model. It was beautiful. Everybody shared content. Everything that we worked on, given that this project teams are distributed, this is pre-COVID, by the way. So we were way ahead of the curve here, was if it was a BIM model, it was an BIM 360 cloud, so you never had to worry about where anything lived. It was always on the internet. We used our Procore technology platform for project scheduling, and issue tracking for bigger project coordination.

    We have Bluebeam Studio online for PDF markups. Everything was online, everybody had access to it. We don't have to worry about it being locked away in some silo, and these all spoke to each other. So that we had content from one platform being able to link to another. So here we wanted to know where the interesting models are. We specify that Procore, and say with everything else. Everything linked to each other. And you get a sense of what we talked about earlier, road mapping.

    Here's our beautiful road map to show the different phases, 1, 2, 3, 4, 5. We didn't put the eights, which is what the phases there are. Programming schematic, design development, construction documents, construction, close out. We started with the big ticket items at top, priorities, estimation, programming side analysis, to authoring, to coordination, to record at the bottom, all the way to manage modeling that can be ready for a condition model to hand for the owner, again turn over day one operations.

    This is what we explain to people as our roadmap, as our schedule, in a broad sense. So it's easy to follow. You don't have to worry about the jargon of BIM or VDC or anything. You just understand what we're trying to do at each phase as a communication document, to make it clear to anybody working with us what they can expect. Easy, copy paste emails, put into your documentation. This is an example, what we did for our project.

    If it comes to data requirements, we made sure that the owner's template, which is this document right here, that shows the system on the left column, the subsystem like if we had the system as a plumbing system, the subsystem would be evolve. And then the middle column in color there, orange, is the class number. This is what the owner required us to fill out for all these systems, and we did diligently. And on the right there will this be part of IBM Maximo. This is something we have to track with IBM Maximo, yes or no.

    So we have to fill this out for every part of the model and project and then, label it inside the model. On the left there is circle example what we're trying to do here. Make sure we filled it out, vetted it, make sure it's something we have to deliver to the owner or not. Classified and on the left, make sure it was actually updated in the model environment. For every bit of it. That way what we had was good data that can be tracked every step along the way.

    We also had a nomenclature system. Again, we had every model, every building has its own model, easy to track, easy to follow. They're all standalone in their own way. Everything is on 360. And 360. And we made sure we tracked each piece of this per discipline with the same naming system, in the same formats, nobody was doing it their own way. Because if we have different ways of managing models and naming models, it would be very hard to then condition them to follow a similar scope and format.

    And here's an example of that in an LED matrix, specifying which building, by which discipline, at which time the process would be modified for which scope of work. Is very important for next scope, which is the review and verify the data, whether that's VDC, clash detection, or in this case, DTO. This is Autodesk Assemble that we use from our BIM 360 models. This is why it's great to have things on cloud, a synergize that we can then use that quantities for estimation.

    In this case in the early stages, we were able to make sure that things were being tracked and coordinated for sizes, so we weren't out of scope for owner requirements programming. Something we took advantage of, but this wouldn't work if we didn't have better strategy, the template requirements, the nomenclature, all that has to be pinned out for us to make something like this work downstream. And can then feed it to everything else, including prefabrication and markups.

    Here's the example of taking the digital models we had in this model environment on the right here, and showing off the realworld counterpart that was a mockup that we use to make sure everything we're designing and building was going to work in the real space. Because the owner wanted to see what was going to look like, they're going to build hundreds of these types of rooms, so they had to have a high confidence in what was being built, because they're buying all of this, again, paying for you to do this. And of course, keeping this going, we made sure we followed suit on having mockups for the facade prefabrication units that will go on the buildings. And we could clarify to the owner what we were able to do in that regard for them.

    So you could see it. We had all our ducks lined up in a row, and we're able to get to the point where every little bit of building was countable in a data hand off early on. That by the time the project is over, this is all part of baked into the model including all the equipment and furnishings, you name it. So what are the results in the second project? We have better preparation, project design, start to close out. We don't have anything out of scope that need to be in scope, it was all there. Fewer ambiguities and design to fabrication to maintain a tight schedule. This was a huge help to make sure everything was speaking from those models all the way to construction fabrication.

    Data was connected from design, to estimate the fabrication to close out. So that we wouldn't have some gaps in data, or uncertainties. And the owner saw that the design build team, [INAUDIBLE] control and everybody working with us, can provide value and quality in a deliverable process. They like that, when we provide value and quality. They like it when you can show off what you can do and make them happy with what they're paying you to do. Again, this is money to them.

    And this is the same the project of the UCSC Theater project in 2022. It'll be turnkey ready fall 2023. So you can see the back there, the Torrey Pines Living and Learning Neighborhood campus project. So that's 1 million gross square foot and back there, and a 1 million gross square foot in the foreground here. And I was able to work on this over a period of several years. It's a real remarkable opportunity to have a chance to do a big project, integrated the best of ability, to take a lot of lessons learn. And I mean, believe me, this is the tip of the iceberg of the lessons learned for these projects because there's so much happening. There's so much you can learn from.

    And then in a very short amount of time, less than a year, do the next project. Very similar and apply a lot of the great abilities you can with the project team, and the owner was able to step up and give us everything they needed, and trusted us to deliver. So this is a wonderful opportunity to show what's possible when you work together.

    So let's recap and talk about what we learned today. Key takeaways for data success. Talk early and often about data deliverables and outcomes for the owner. Again, if you don't think they're gonna listen, or there's no scope, talking never killed anybody. Talk early and often, and show off a few things, get people's imagination running. You never know. This might evolve to a bigger opportunity.

    If the owner doesn't have a plan, but is interested, work with them to make one. Roadmaps, mapping, show them what's possible. Work solutions to your platforms. Don't let any platform or operations dictate to you what's possible. Figure out what you want to do, like I did in my mapping process, and how to get there. And make it very clear to people how it's going to happen.

    Connect your data sources together. Don't have silos. There's no excuse for that anymore. Everything is cloud enabled. Everything is easier to access than ever before. Have an easy to communicate roadmap, get the most value out of a project by communicating to your entire team what you're going to do. And that could be your digital scope, it could be any scope. Highly recommend how to use communication documents so you're not just guessing in your mind what's going to happen. That can lead you to interesting directions.

    Make sure you have dedicated points of contact. I had counterpoints of myself with every party I worked with, so that was easy to facilitate communication, especially when the owner was able to provide their own counterpoint for data and VDC. And don't let perfect be the enemy of the good. As you saw on the first part of the example we had here, and all the other topics discussed about, we live in an imperfect environment. So don't wait for things to be perfect, just continuously evolve. That's the name of the game. Do the best you can every step of the way.

    Here are some resources in this talk. You can take a pause and look at these. There's lots of great content out here for how to use data in BIM. And special shout out to friends and co-workers I worked with-- associates-- Gautam, Natalia, Luis Vickie, Cindy, Ali, Nash, Bridget, and many more. I learned a lot from these people. They're awesome people. I wouldn't be able to draw some of this cool stuff if it wasn't for them and their knowledge and their dedication. You guys are the real MVPs. Always good to have a shout out.

    But next time if you want to get in touch with me, I'm Tadeh Hakopian. I'm available everywhere. I love Dynamo too. Thank you so much for attending this presentation about digital deliverables for the owner. There's a whole world out there. And thank you for attending my session of Autodesk University. I really appreciate it. Any questions, feel free to reach out to me.

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    쿠기 기본 설정

    오토데스크는 고객의 개인 정보와 최상의 경험을 중요시합니다. 오토데스크는 정보를 사용자화하고 응용프로그램을 만들기 위해 고객의 본 사이트 사용에 관한 데이터를 수집합니다.

    오토데스크에서 고객의 데이터를 수집하고 사용하도록 허용하시겠습니까?

    오토데스크에서 사용하는타사 서비스개인정보 처리방침 정책을 자세히 알아보십시오.

    반드시 필요 - 사이트가 제대로 작동하고 사용자에게 서비스를 원활하게 제공하기 위해 필수적임

    이 쿠키는 오토데스크에서 사용자 기본 설정 또는 로그인 정보를 저장하거나, 사용자 요청에 응답하거나, 장바구니의 품목을 처리하기 위해 필요합니다.

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

    이 쿠키는 오토데스크가 보다 향상된 기능을 제공하고 사용자에게 맞는 정보를 제공할 수 있게 해 줍니다. 사용자에게 맞는 정보 및 환경을 제공하기 위해 오토데스크 또는 서비스를 제공하는 협력업체에서 이 쿠키를 설정할 수 있습니다. 이 쿠키를 허용하지 않을 경우 이러한 서비스 중 일부 또는 전체를 이용하지 못하게 될 수 있습니다.

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

    이 쿠키는 사용자와 관련성이 높은 광고를 표시하고 그 효과를 추적하기 위해 사용자 활동 및 관심 사항에 대한 데이터를 수집합니다. 이렇게 데이터를 수집함으로써 사용자의 관심 사항에 더 적합한 광고를 표시할 수 있습니다. 이 쿠키를 허용하지 않을 경우 관심 분야에 해당되지 않는 광고가 표시될 수 있습니다.

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    타사 서비스

    각 범주에서 오토데스크가 사용하는 타사 서비스와 온라인에서 고객으로부터 수집하는 데이터를 사용하는 방식에 대해 자세히 알아보십시오.

    icon-svg-hide-thick

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    반드시 필요 - 사이트가 제대로 작동하고 사용자에게 서비스를 원활하게 제공하기 위해 필수적임

    Qualtrics
    오토데스크는 고객에게 더욱 시의적절하며 관련 있는 이메일 컨텐츠를 제공하기 위해 Qualtrics를 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. Qualtrics 개인정보취급방침
    Akamai mPulse
    오토데스크 사이트에서 고객의 행동에 관한 데이터를 수집하기 위해 Akamai mPulse를 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. Akamai mPulse 개인정보취급방침
    Digital River
    오토데스크 사이트에서 고객의 행동에 관한 데이터를 수집하기 위해 Digital River를 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. Digital River 개인정보취급방침
    Dynatrace
    오토데스크 사이트에서 고객의 행동에 관한 데이터를 수집하기 위해 Dynatrace를 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. Dynatrace 개인정보취급방침
    Khoros
    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.