AU Class
AU Class
class - AU

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

共享此课程
在视频、演示文稿幻灯片和讲义中搜索关键字:

说明

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!

主要学习内容

  • 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.

讲师

  • Tadeh Hakopian 的头像
    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.
Video Player is loading.
Current Time 0:00
Duration 52:22
Loaded: 0.32%
Stream Type LIVE
Remaining Time 52:22
 
1x
  • Chapters
  • descriptions off, selected
  • en (Main), selected
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.

______
icon-svg-close-thick

Cookie 首选项

您的隐私对我们非常重要,为您提供出色的体验是我们的责任。为了帮助自定义信息和构建应用程序,我们会收集有关您如何使用此站点的数据。

我们是否可以收集并使用您的数据?

详细了解我们使用的第三方服务以及我们的隐私声明

绝对必要 – 我们的网站正常运行并为您提供服务所必需的

通过这些 Cookie,我们可以记录您的偏好或登录信息,响应您的请求或完成购物车中物品或服务的订购。

改善您的体验 – 使我们能够为您展示与您相关的内容

通过这些 Cookie,我们可以提供增强的功能和个性化服务。可能由我们或第三方提供商进行设置,我们会利用其服务为您提供定制的信息和体验。如果您不允许使用这些 Cookie,可能会无法使用某些或全部服务。

定制您的广告 – 允许我们为您提供针对性的广告

这些 Cookie 会根据您的活动和兴趣收集有关您的数据,以便向您显示相关广告并跟踪其效果。通过收集这些数据,我们可以更有针对性地向您显示与您的兴趣相关的广告。如果您不允许使用这些 Cookie,您看到的广告将缺乏针对性。

icon-svg-close-thick

第三方服务

详细了解每个类别中我们所用的第三方服务,以及我们如何使用所收集的与您的网络活动相关的数据。

icon-svg-hide-thick

icon-svg-show-thick

绝对必要 – 我们的网站正常运行并为您提供服务所必需的

Qualtrics
我们通过 Qualtrics 借助调查或联机表单获得您的反馈。您可能会被随机选定参与某项调查,或者您可以主动向我们提供反馈。填写调查之前,我们将收集数据以更好地了解您所执行的操作。这有助于我们解决您可能遇到的问题。. Qualtrics 隐私政策
Akamai mPulse
我们通过 Akamai mPulse 收集与您在我们站点中的活动相关的数据。这可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID、您的 Autodesk ID。我们使用此数据来衡量我们站点的性能并评估联机体验的难易程度,以便我们改进相关功能。此外,我们还将使用高级分析方法来优化电子邮件体验、客户支持体验和销售体验。. Akamai mPulse 隐私政策
Digital River
我们通过 Digital River 收集与您在我们站点中的活动相关的数据。这可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID、您的 Autodesk ID。我们使用此数据来衡量我们站点的性能并评估联机体验的难易程度,以便我们改进相关功能。此外,我们还将使用高级分析方法来优化电子邮件体验、客户支持体验和销售体验。. Digital River 隐私政策
Dynatrace
我们通过 Dynatrace 收集与您在我们站点中的活动相关的数据。这可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID、您的 Autodesk ID。我们使用此数据来衡量我们站点的性能并评估联机体验的难易程度,以便我们改进相关功能。此外,我们还将使用高级分析方法来优化电子邮件体验、客户支持体验和销售体验。. Dynatrace 隐私政策
Khoros
我们通过 Khoros 收集与您在我们站点中的活动相关的数据。这可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID、您的 Autodesk ID。我们使用此数据来衡量我们站点的性能并评估联机体验的难易程度,以便我们改进相关功能。此外,我们还将使用高级分析方法来优化电子邮件体验、客户支持体验和销售体验。. Khoros 隐私政策
Launch Darkly
我们通过 Launch Darkly 收集与您在我们站点中的活动相关的数据。这可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID、您的 Autodesk ID。我们使用此数据来衡量我们站点的性能并评估联机体验的难易程度,以便我们改进相关功能。此外,我们还将使用高级分析方法来优化电子邮件体验、客户支持体验和销售体验。. Launch Darkly 隐私政策
New Relic
我们通过 New Relic 收集与您在我们站点中的活动相关的数据。这可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID、您的 Autodesk ID。我们使用此数据来衡量我们站点的性能并评估联机体验的难易程度,以便我们改进相关功能。此外,我们还将使用高级分析方法来优化电子邮件体验、客户支持体验和销售体验。. New Relic 隐私政策
Salesforce Live Agent
我们通过 Salesforce Live Agent 收集与您在我们站点中的活动相关的数据。这可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID、您的 Autodesk ID。我们使用此数据来衡量我们站点的性能并评估联机体验的难易程度,以便我们改进相关功能。此外,我们还将使用高级分析方法来优化电子邮件体验、客户支持体验和销售体验。. Salesforce Live Agent 隐私政策
Wistia
我们通过 Wistia 收集与您在我们站点中的活动相关的数据。这可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID、您的 Autodesk ID。我们使用此数据来衡量我们站点的性能并评估联机体验的难易程度,以便我们改进相关功能。此外,我们还将使用高级分析方法来优化电子邮件体验、客户支持体验和销售体验。. Wistia 隐私政策
Tealium
我们通过 Tealium 收集与您在我们站点中的活动相关的数据。这可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。我们使用此数据来衡量我们站点的性能并评估联机体验的难易程度,以便我们改进相关功能。此外,我们还将使用高级分析方法来优化电子邮件体验、客户支持体验和销售体验。. Tealium 隐私政策
Upsellit
我们通过 Upsellit 收集与您在我们站点中的活动相关的数据。这可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。我们使用此数据来衡量我们站点的性能并评估联机体验的难易程度,以便我们改进相关功能。此外,我们还将使用高级分析方法来优化电子邮件体验、客户支持体验和销售体验。. Upsellit 隐私政策
CJ Affiliates
我们通过 CJ Affiliates 收集与您在我们站点中的活动相关的数据。这可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。我们使用此数据来衡量我们站点的性能并评估联机体验的难易程度,以便我们改进相关功能。此外,我们还将使用高级分析方法来优化电子邮件体验、客户支持体验和销售体验。. CJ Affiliates 隐私政策
Commission Factory
我们通过 Commission Factory 收集与您在我们站点中的活动相关的数据。这可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。我们使用此数据来衡量我们站点的性能并评估联机体验的难易程度,以便我们改进相关功能。此外,我们还将使用高级分析方法来优化电子邮件体验、客户支持体验和销售体验。. Commission Factory 隐私政策
Google Analytics (Strictly Necessary)
我们通过 Google Analytics (Strictly Necessary) 收集与您在我们站点中的活动相关的数据。这可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID、您的 Autodesk ID。我们使用此数据来衡量我们站点的性能并评估联机体验的难易程度,以便我们改进相关功能。此外,我们还将使用高级分析方法来优化电子邮件体验、客户支持体验和销售体验。. Google Analytics (Strictly Necessary) 隐私政策
Typepad Stats
我们通过 Typepad Stats 收集与您在我们站点中的活动相关的数据。这可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID、您的 Autodesk ID。我们使用此数据来衡量我们站点的性能并评估联机体验的难易程度,以便我们改进相关功能。此外,我们还将使用高级分析方法来优化电子邮件体验、客户支持体验和销售体验。. Typepad Stats 隐私政策
Geo Targetly
我们使用 Geo Targetly 将网站访问者引导至最合适的网页并/或根据他们的位置提供量身定制的内容。 Geo Targetly 使用网站访问者的 IP 地址确定访问者设备的大致位置。 这有助于确保访问者以其(最有可能的)本地语言浏览内容。Geo Targetly 隐私政策
SpeedCurve
我们使用 SpeedCurve 来监控和衡量您的网站体验的性能,具体因素为网页加载时间以及后续元素(如图像、脚本和文本)的响应能力。SpeedCurve 隐私政策
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

icon-svg-hide-thick

icon-svg-show-thick

改善您的体验 – 使我们能够为您展示与您相关的内容

Google Optimize
我们通过 Google Optimize 测试站点上的新功能并自定义您对这些功能的体验。为此,我们将收集与您在站点中的活动相关的数据。此数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID、您的 Autodesk ID 等。根据功能测试,您可能会体验不同版本的站点;或者,根据访问者属性,您可能会查看个性化内容。. Google Optimize 隐私政策
ClickTale
我们通过 ClickTale 更好地了解您可能会在站点的哪些方面遇到困难。我们通过会话记录来帮助了解您与站点的交互方式,包括页面上的各种元素。将隐藏可能会识别个人身份的信息,而不会收集此信息。. ClickTale 隐私政策
OneSignal
我们通过 OneSignal 在 OneSignal 提供支持的站点上投放数字广告。根据 OneSignal 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 OneSignal 收集的与您相关的数据相整合。我们利用发送给 OneSignal 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. OneSignal 隐私政策
Optimizely
我们通过 Optimizely 测试站点上的新功能并自定义您对这些功能的体验。为此,我们将收集与您在站点中的活动相关的数据。此数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID、您的 Autodesk ID 等。根据功能测试,您可能会体验不同版本的站点;或者,根据访问者属性,您可能会查看个性化内容。. Optimizely 隐私政策
Amplitude
我们通过 Amplitude 测试站点上的新功能并自定义您对这些功能的体验。为此,我们将收集与您在站点中的活动相关的数据。此数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID、您的 Autodesk ID 等。根据功能测试,您可能会体验不同版本的站点;或者,根据访问者属性,您可能会查看个性化内容。. Amplitude 隐私政策
Snowplow
我们通过 Snowplow 收集与您在我们站点中的活动相关的数据。这可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID、您的 Autodesk ID。我们使用此数据来衡量我们站点的性能并评估联机体验的难易程度,以便我们改进相关功能。此外,我们还将使用高级分析方法来优化电子邮件体验、客户支持体验和销售体验。. Snowplow 隐私政策
UserVoice
我们通过 UserVoice 收集与您在我们站点中的活动相关的数据。这可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID、您的 Autodesk ID。我们使用此数据来衡量我们站点的性能并评估联机体验的难易程度,以便我们改进相关功能。此外,我们还将使用高级分析方法来优化电子邮件体验、客户支持体验和销售体验。. UserVoice 隐私政策
Clearbit
Clearbit 允许实时数据扩充,为客户提供个性化且相关的体验。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。Clearbit 隐私政策
YouTube
YouTube 是一个视频共享平台,允许用户在我们的网站上查看和共享嵌入视频。YouTube 提供关于视频性能的观看指标。 YouTube 隐私政策

icon-svg-hide-thick

icon-svg-show-thick

定制您的广告 – 允许我们为您提供针对性的广告

Adobe Analytics
我们通过 Adobe Analytics 收集与您在我们站点中的活动相关的数据。这可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID、您的 Autodesk ID。我们使用此数据来衡量我们站点的性能并评估联机体验的难易程度,以便我们改进相关功能。此外,我们还将使用高级分析方法来优化电子邮件体验、客户支持体验和销售体验。. Adobe Analytics 隐私政策
Google Analytics (Web Analytics)
我们通过 Google Analytics (Web Analytics) 收集与您在我们站点中的活动相关的数据。这可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。我们使用此数据来衡量我们站点的性能并评估联机体验的难易程度,以便我们改进相关功能。此外,我们还将使用高级分析方法来优化电子邮件体验、客户支持体验和销售体验。. Google Analytics (Web Analytics) 隐私政策
AdWords
我们通过 AdWords 在 AdWords 提供支持的站点上投放数字广告。根据 AdWords 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 AdWords 收集的与您相关的数据相整合。我们利用发送给 AdWords 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. AdWords 隐私政策
Marketo
我们通过 Marketo 更及时地向您发送相关电子邮件内容。为此,我们收集与以下各项相关的数据:您的网络活动,您对我们所发送电子邮件的响应。收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID、电子邮件打开率、单击的链接等。我们可能会将此数据与从其他信息源收集的数据相整合,以根据高级分析处理方法向您提供改进的销售体验或客户服务体验以及更相关的内容。. Marketo 隐私政策
Doubleclick
我们通过 Doubleclick 在 Doubleclick 提供支持的站点上投放数字广告。根据 Doubleclick 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 Doubleclick 收集的与您相关的数据相整合。我们利用发送给 Doubleclick 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. Doubleclick 隐私政策
HubSpot
我们通过 HubSpot 更及时地向您发送相关电子邮件内容。为此,我们收集与以下各项相关的数据:您的网络活动,您对我们所发送电子邮件的响应。收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID、电子邮件打开率、单击的链接等。. HubSpot 隐私政策
Twitter
我们通过 Twitter 在 Twitter 提供支持的站点上投放数字广告。根据 Twitter 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 Twitter 收集的与您相关的数据相整合。我们利用发送给 Twitter 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. Twitter 隐私政策
Facebook
我们通过 Facebook 在 Facebook 提供支持的站点上投放数字广告。根据 Facebook 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 Facebook 收集的与您相关的数据相整合。我们利用发送给 Facebook 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. Facebook 隐私政策
LinkedIn
我们通过 LinkedIn 在 LinkedIn 提供支持的站点上投放数字广告。根据 LinkedIn 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 LinkedIn 收集的与您相关的数据相整合。我们利用发送给 LinkedIn 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. LinkedIn 隐私政策
Yahoo! Japan
我们通过 Yahoo! Japan 在 Yahoo! Japan 提供支持的站点上投放数字广告。根据 Yahoo! Japan 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 Yahoo! Japan 收集的与您相关的数据相整合。我们利用发送给 Yahoo! Japan 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. Yahoo! Japan 隐私政策
Naver
我们通过 Naver 在 Naver 提供支持的站点上投放数字广告。根据 Naver 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 Naver 收集的与您相关的数据相整合。我们利用发送给 Naver 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. Naver 隐私政策
Quantcast
我们通过 Quantcast 在 Quantcast 提供支持的站点上投放数字广告。根据 Quantcast 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 Quantcast 收集的与您相关的数据相整合。我们利用发送给 Quantcast 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. Quantcast 隐私政策
Call Tracking
我们通过 Call Tracking 为推广活动提供专属的电话号码。从而,使您可以更快地联系我们的支持人员并帮助我们更精确地评估我们的表现。我们可能会通过提供的电话号码收集与您在站点中的活动相关的数据。. Call Tracking 隐私政策
Wunderkind
我们通过 Wunderkind 在 Wunderkind 提供支持的站点上投放数字广告。根据 Wunderkind 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 Wunderkind 收集的与您相关的数据相整合。我们利用发送给 Wunderkind 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. Wunderkind 隐私政策
ADC Media
我们通过 ADC Media 在 ADC Media 提供支持的站点上投放数字广告。根据 ADC Media 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 ADC Media 收集的与您相关的数据相整合。我们利用发送给 ADC Media 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. ADC Media 隐私政策
AgrantSEM
我们通过 AgrantSEM 在 AgrantSEM 提供支持的站点上投放数字广告。根据 AgrantSEM 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 AgrantSEM 收集的与您相关的数据相整合。我们利用发送给 AgrantSEM 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. AgrantSEM 隐私政策
Bidtellect
我们通过 Bidtellect 在 Bidtellect 提供支持的站点上投放数字广告。根据 Bidtellect 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 Bidtellect 收集的与您相关的数据相整合。我们利用发送给 Bidtellect 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. Bidtellect 隐私政策
Bing
我们通过 Bing 在 Bing 提供支持的站点上投放数字广告。根据 Bing 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 Bing 收集的与您相关的数据相整合。我们利用发送给 Bing 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. Bing 隐私政策
G2Crowd
我们通过 G2Crowd 在 G2Crowd 提供支持的站点上投放数字广告。根据 G2Crowd 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 G2Crowd 收集的与您相关的数据相整合。我们利用发送给 G2Crowd 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. G2Crowd 隐私政策
NMPI Display
我们通过 NMPI Display 在 NMPI Display 提供支持的站点上投放数字广告。根据 NMPI Display 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 NMPI Display 收集的与您相关的数据相整合。我们利用发送给 NMPI Display 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. NMPI Display 隐私政策
VK
我们通过 VK 在 VK 提供支持的站点上投放数字广告。根据 VK 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 VK 收集的与您相关的数据相整合。我们利用发送给 VK 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. VK 隐私政策
Adobe Target
我们通过 Adobe Target 测试站点上的新功能并自定义您对这些功能的体验。为此,我们将收集与您在站点中的活动相关的数据。此数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID、您的 Autodesk ID 等。根据功能测试,您可能会体验不同版本的站点;或者,根据访问者属性,您可能会查看个性化内容。. Adobe Target 隐私政策
Google Analytics (Advertising)
我们通过 Google Analytics (Advertising) 在 Google Analytics (Advertising) 提供支持的站点上投放数字广告。根据 Google Analytics (Advertising) 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 Google Analytics (Advertising) 收集的与您相关的数据相整合。我们利用发送给 Google Analytics (Advertising) 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. Google Analytics (Advertising) 隐私政策
Trendkite
我们通过 Trendkite 在 Trendkite 提供支持的站点上投放数字广告。根据 Trendkite 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 Trendkite 收集的与您相关的数据相整合。我们利用发送给 Trendkite 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. Trendkite 隐私政策
Hotjar
我们通过 Hotjar 在 Hotjar 提供支持的站点上投放数字广告。根据 Hotjar 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 Hotjar 收集的与您相关的数据相整合。我们利用发送给 Hotjar 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. Hotjar 隐私政策
6 Sense
我们通过 6 Sense 在 6 Sense 提供支持的站点上投放数字广告。根据 6 Sense 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 6 Sense 收集的与您相关的数据相整合。我们利用发送给 6 Sense 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. 6 Sense 隐私政策
Terminus
我们通过 Terminus 在 Terminus 提供支持的站点上投放数字广告。根据 Terminus 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 Terminus 收集的与您相关的数据相整合。我们利用发送给 Terminus 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. Terminus 隐私政策
StackAdapt
我们通过 StackAdapt 在 StackAdapt 提供支持的站点上投放数字广告。根据 StackAdapt 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 StackAdapt 收集的与您相关的数据相整合。我们利用发送给 StackAdapt 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. StackAdapt 隐私政策
The Trade Desk
我们通过 The Trade Desk 在 The Trade Desk 提供支持的站点上投放数字广告。根据 The Trade Desk 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 The Trade Desk 收集的与您相关的数据相整合。我们利用发送给 The Trade Desk 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. The Trade Desk 隐私政策
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

是否确定要简化联机体验?

我们希望您能够从我们这里获得良好体验。对于上一屏幕中的类别,如果选择“是”,我们将收集并使用您的数据以自定义您的体验并为您构建更好的应用程序。您可以访问我们的“隐私声明”,根据需要更改您的设置。

个性化您的体验,选择由您来做。

我们重视隐私权。我们收集的数据可以帮助我们了解您对我们产品的使用情况、您可能感兴趣的信息以及我们可以在哪些方面做出改善以使您与 Autodesk 的沟通更为顺畅。

我们是否可以收集并使用您的数据,从而为您打造个性化的体验?

通过管理您在此站点的隐私设置来了解个性化体验的好处,或访问我们的隐私声明详细了解您的可用选项。