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The Schedule Is Changing (Again): Flow Generative Scheduling for Project Management

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说明

The schedule is never done. Plans change and schedules needs to adapt. Project scope, deadlines, and resource availability are all constraints that impact a schedule. These constraints often change throughout a project's lifecycle, and production teams need to be capable of making swift adjustments to keep their projects moving forward. On large-scale productions with thousands of tasks, making these changes can be a massive undertaking. Generative Scheduling is a tool that facilitates large-scale schedule iteration, pulling production schedules from Autodesk Flow Production Tracking. In this session, we'll look at how to use Generative Scheduling, use constraints to iterate on and optimize a schedule, create hypothetical scheduling scenarios, and use resource shaping to refine schedules. Simplify your production scheduling workflow by enabling production teams to quickly iterate and plan against ever-changing project requirements with this easy-to-use tool.

主要学习内容

  • Learn how to use constraints to iterate on and optimize a production schedule.
  • Learn how to create scheduling scenarios to plan for constraint changes, such as changes to resource availability and deadlines.
  • Learn how to use resource shaping to refine a schedule for specific resource classes to better optimize resource usage.

讲师

  • Jessica Parsons
    With over six years of experience in production management across the media and entertainment industry, Jessica Parsons has worked on projects ranging from visual effects post-production and episodic animation to video games and virtual reality films. Jessica is on a mission to to simplify and streamline daily production tracking practices. Jessica currently works as a Technical Account Specialist for Flow Production Tracking at Autodesk, based out of Montreal.
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      Transcript

      JESSICA PARSONS: Hi, everyone. I'm excited to be here today to be talking to you about Flow Generative Scheduling. First a little about me. My name is Jessica Parsons, and I currently work as a Technical Account Specialist for Flow Production Tracking with Autodesk. I'm currently based out of Montreal. And my role is to support product adoption and develop training resources with the goal of making sure that anyone who tries to use Flow Production Tracking is able to use it successfully and has a positive experience doing so.

      My background is in production management, primarily for visual effects, post-production, animated series, and independent games. Before I get into Flow Generative Scheduling, I want to introduce Flow Production Tracking for anyone who is unfamiliar with the product because I will be speaking a little bit about it today. So Flow Production Tracking is Autodesk production management software. It's heavily used in media and entertainment across film, TV, advertising, and games, but it's also becoming more common to see it used across automotive design and manufacturing.

      You can use Flow Production Tracking to setup, track, and schedule every step of a production, from tracking task deadlines and progress, managing teams and tracking productivity, resourcing projects, and sharing and reviewing media. Managing lots of project data can be complex, so centralizing data tracking is an essential part in optimizing the production process so that teams can be agile and react quickly to changes.

      You want your data to be organized and connected, accessible from anywhere, trackable by anyone, and insightful to those who rely on it to make decisions. This is where Flow Production Tracking is designed to consolidate the number of tools you're using into just one. The idea is to plan, schedule, and track from the same place. So you might be wondering where Flow Generative Scheduling fits into all of this.

      If you've ever had to put together a project schedule, how many times have you had to change your plans from what you initially thought? Early in my career, I admit I was a bit naive about scheduling. I'd say things like. The schedule is done. And be so sure that it was. But I don't think that the schedule has ever really been done, at least not until the project is over. Plans are always changing, and that's just the reality of production.

      What we need is a way to adapt our schedules when changes need to happen. Sure, we can update our schedules manually, but on large-scale m or any project with a lot of connecting parts, this can be a really time consuming task. We all know this, especially for something is going to change again. So that's where Flow Generative Scheduling comes in. Flow Generative Scheduling is a new tool that works alongside Flow Production Tracking.

      It can quickly generate level schedules using the task information from your Flow Prediction Tracking site. Task data, including task dependencies, duration, pipeline steps, and department will get pulled from your site into a playground. From your playground, you'll be able to create different scenarios and use constraints, priorities, and resource shaping to level your different scenarios. When you have a scenario that you're happy with, you can send it back to Flow Production Tracking and apply it as your schedule.

      Your tasks don't even need to be scheduled in the first place to use the tool. Generative scheduling can actually generate the initial schedule for you. So what I want to show you today is how to use generative scheduling. I'm going to start by showing the round-trip process from Flow Production Tracking. Next, I'll talk about using constraints and priorities to iterate on your schedule. Then, I'll cover creating different scheduling scenarios. And finally, I'll look at refining the schedule even further with resource shaping.

      So let's start with the round-trip process. First, I'm going to open one of my Flow Production Tracking sites and show you a project that I'd like to schedule. Here I am on my site. And I have a project called Luna. This project is a visual effects film project with sequences and shots. And each shot has a series of tasks that need to be completed. In order for you to use Flow Generative Scheduling, there's a few requirements that your tasks need to meet.

      First, each task needs to have a duration. This is the estimate of how long each task will take. Next, each task needs to have a pipeline step. In Flow Production Tracking, pipeline steps are linked to departments, and so are people. So this is how generative scheduling will know your resource utilization. Finally, your tasks need dependencies. There are lots of different ways dependencies can be set up in Flow Production Tracking, but essentially, dependencies tell Generative Scheduling which tasks need to be completed before others.

      Generative Scheduling will use this information to schedule all of your tasks in the right order. So we have duration, pipeline step, and dependency. These tasks look good. They all have the information that's required, but what they don't have is dates. And so that's where we want to use Flow Generative Scheduling. Now, let's make a schedule. I'm going to move forward along the following premise that I'm going to start work on Luna on November 1, and I want it to be finished around March 30.

      So to get started, you're going to navigate to Flow Generative Scheduling through the app's dropdown menu on your Flow Production Tracking site. You can control access to a lot of features in Flow Production Tracking through permission roles. So access to the app can be restricted if you want it to be. With Generative Scheduling open, the first thing you want to do is make sure that you're connected to the correct Flow Production Tracking site.

      You're going to do this by using the Connection Setup tool, which you can find in the top right-hand corner of the screen under the Admin menu. From the Connection Setup tool, you'll be prompted for your Flow Production Tracking site URL and login. So you'll enter those and select Connect. Once you get confirmation that your site is connected, it'll look like this. You can start bringing in task data from your site. Now, here, I'm already connected to the correct site, so I can go ahead and close this.

      But if I wasn't connected to the correct site or I wanted to be connected to a different site, I would just select Disconnect and log-in to the other site. Now, the task data you bring into Flow Generative Scheduling is going to be created as a playground. A playground is a sandbox in which you will create your schedule scenarios. Each playground is a snapshot of the schedule from the time it was pulled as opposed to being a live production data.

      And all of your playgrounds will be visible from the home page. Here, you can see I have a lot of different playgrounds, and I can access any of them. For now, we want to create a new playground for the Luna project. So I can go ahead and select Create New Playground. Next, you'll be prompted for a data source. I won't talk about this today, but you do have the option to work with Open Schedule Format, or OSF.

      However, I want to work from my Flow Production Tracking site, so I'm going to select Use Schedule Data for Flow Production Tracking and select Next. Now, we'll be prompted to choose a project from your Flow Production Tracking site. I'm going to choose Luna and hit Next. Next, you'll configure the playground by choosing a name and description to identify it. And you'll choose a date from which you want your schedule to start.

      I'll go ahead and choose November 1 because that's when I want the schedule to start from when I want to start working on this particular project. Now, you can hit Next, review the details, and select Create Playground. Now, without doing anything except importing task data, you've got a schedule. All you did was tell the tool when you wanted your schedule to start from. And with information about how long each task should take, what kind of resources are required for each task, and what tasks are dependent on others, all data that came from Flow Production Tracking, Flow Generative Scheduling has created an as-soon-as-possible version of the schedule.

      Now, this is a great start, but it could be even better. Generative Scheduling can help you create a level schedule much faster than you could do by hand. I'll cover this in detail in the next section, but I'm going to go ahead and add a finish-no-later-than constraint on the project of March 30, which is an internal deadline. I actually don't need to finish this project until November of next year, but let's be super optimistic and set it to the end of March.

      Now, I can select Generate, which will run the solver on my data. Not only will generating the schedule help to better determine prospective schedule dates, but the solver will do it in a way that helps you avoid peaks and valleys in resource utilization without having to do all the time-consuming balancing of resources yourselves. OK, so now let's say you're happy with this schedule. To send your schedule to Flow Production Tracking, you're going to select the Export icon on the top right of the screen and choose Send to Flow Production Tracking and then hit Send Scenario.

      So once this process begins, it can't be canceled. The process can take several minutes, just depending on the size of the project. Last time I did this, it took me about 18 seconds. For some context, this project contains 10 sequences with a total of 990 shots and 5,451 individual tasks. So not too bad for 18 seconds. OK, so now that that's done and the scenario has been sent, you can go back to your Flow Production Tracking site to see what Flow Generative Scheduling has done.

      Taking a look at our tasks here, it doesn't look like anything has changed. We still don't have start or end dates. So what did Generative Scheduling do? When you send your new schedule to Flow Production Tracking, Flow Generative Scheduling didn't directly modify your existing schedule. Instead, the dates you just sent over will be added to a date field called Proposed Start Date, which had hidden, and I'm bringing it now.

      Now that the field is visible, we can see all of the dates from the scenario we just sent over from Generative Scheduling. This allows you to review the dates or even to change your mind before applying any kind of schedule. It essentially protects your live production schedule from accepting changes until you're ready for them. When you're ready to apply the new schedule, you can go ahead and select all of the tasks you would like to apply the new schedule to.

      Right Click and select Apply Proposed Start Date. This can take a few minutes to process, again, just depending on how many tasks you're updating at once. Now, when the Apply Proposed Start Date option is used, the value of the proposed start date is cleared. So you can see here that the Proposed Start Date field is now empty. The value of the Proposed Start Date field replaces any existing value in the Start Date field.

      So again, you can see that the date that was in the Proposed Start Date field has been transferred over to the Start Date field. And the value of the Due Date field is updated automatically based on the task duration. This is the way Flow Production Tracking works. If there is a task with a duration of five days and a start date of November 1, then the end date would be November 5. We just add 5 days to whatever day we're starting on.

      And as an additional note, Flow Production Tracking also has the ability to set up work schedules. So it's smart enough to know that November 2 and 3 are actually a weekend where nobody will be working. So if the task starts on November 1, the duration is five days, and the second and third are non-working days because that's a weekend, then the end date will be November 7 instead of November 5.

      Project work schedules will import to Generative Scheduling when you create a playground. So when you're working on your schedule, the weekends or non-working days will be taken into consideration. You can actually see this here, because I've set up Wednesdays to be a non-working day. So the Gantt chart is displaying gray columns over Saturday, Sunday, and Wednesday. And the Task Start and Due Dates have taken those non-working days into consideration.

      So that's it. I just added dates to a schedule with 5,451 tasks from scratch in less than 15 minutes, plus a couple of minutes of talking. It's as easy as that. So now, let's talk about using constraints and priorities to iterate on your schedule. A constraint is a time-based limitation used to describe when work can or should occur. All activities in Flow Generative Scheduling can have constraints. An activity in Flow Generative Scheduling is a task milestone or summary, such as a shot, asset, or sequence.

      So let's apply a constraint. To easily apply a constraint, you're going to start by opening your playground. So I'll open the Luna playground. Next, you can make sure the Schedule tab is open. The Schedule tab shows us all the activities we're scheduling, details about them, and displays everything in a Gantt chart. So you've opened up the Schedule tab. Now, you'll select an activity. So in this case, I'll select a shot.

      Your project's activities will be displayed in the same hierarchy that they exist in Flow Production Tracking. So here, I have a project with sequences. Each sequence contains shots, and each shot contains a series of tasks, and I can see that reflected in my hierarchy. Now, go over to the Activity Options, which are the four icons on the right-hand side of the screen. The Information tab at the top shows you general information, such as activity type, tags, and categories.

      The Controls icon displays information about the constraints and priority for an activity. The Dependencies tab displays upstream and downstream dependencies, both local and external. Internal dependencies are within the same summary. So for example, tasks within the same shot that are dependent on each other are local dependencies. External dependencies are across different summaries. So an example of this on a film project would be a task on a shot that is dependent on a task on an asset.

      And then you have the Calendar tab, which displays the standard working days for the activity, along with any work day exceptions. So this is what I was talking about earlier when I mentioned work schedules from Flow Production Tracking. OK, so I just showed you four activity options. Right now, because we want to work with constraints, we want to open the Controls tab. Right now, I still have a task selected, so I'll go ahead and select the shot.

      Now in the Controls tab, under Basic Constraints, you can select, Add a Constraint, and choose a constraint from the list. When you hit the Generate button, the newly set constraints will be taken into consideration in the output schedule. Now, constraints can be used to enforce that work must start as soon or as late as possible, start or finish on a specific date, start no earlier or later than a specific date, and finish no earlier or later than a specific date.

      The available constraints will depend on the activity and also other constraints that have already been applied. Here, if I select a shot, I get a lot less options than if I select a task within that shot. By setting constraints, you can make sure certain aspects of your schedule get prioritized. So let's test this out with our current example here. Let's say you're making a movie, and you have a few sequences you need completed by a certain date. So you can select a sequence and open the Controls tab, select Add a Constraint, choose Finish No Later Than, and choose a date.

      Now, some of these dates are going to be red. That's because they're infeasible. What the red is telling us is that, based on the amount of time each task in the sequence is going to take, there's just no way that all the work in this sequence can be completed by these dates. You can, however, choose any one of the black dates and you'll be good. Now, I talked about using constraints as a way of setting priorities on your schedule, but you can actually set a priority value.

      You can think of constraints like hard goals or requirements and priorities more like soft goals or nice to have. Maybe you have lots of shots to complete, but you'd like one done sooner than later. The client isn't asking for it sooner, but you want to get it out of the way, maybe because of the types of resources it will use or maybe its level of complexity or something like that. Whatever the reason, you can give your activities, in this case shots, a priority number, which will make Flow Generative Scheduling try to schedule the shots relative to other priorities.

      But if it doesn't work within the various constraints or hard requirements you've set, then it'll do what it can within the limits of those constraints. So you can select a shot and give it a priority value. You can choose any value between minus 1,000 and plus 1,000. The numbers are just relative to each other. So if you planned on using lots of priorities, you could jump by tens or hundreds, whatever works for you. Let's assign a priority of 1,000.

      On the next shot, we can set a priority of 900. On the next, we can do 800. And we'll leave the rest at 0, which is the default value. Now, when we generate our schedule, an attempt will be made to schedule these to be completed ahead of the other shots. And we can already see that reflected in the schedule in the Gantt chart. So now, what happens if you want to create different scenarios?

      You might, you probably will, find yourself in a situation where you want to explore a few different options for your schedule. Within your playground, you can create as many scenarios as you want. You can create a new scenario from scratch that uses your initially imported data, or just go ahead and duplicate a scenario that you want to make a few tweaks too to create a variation or alternative version of a schedule.

      I'm going to go ahead and create a new scenario so you can see what it's like to compare them. To create a new scenario, you can go over to the Scenarios tab and choose the New button. You can give the scenario a different name to differentiate it, a description, and hit Create. To clarify the difference here between duplicating a scenario versus creating a new one, creating a new scenario will use your originally imported data, the scheduling data that was imported at the time the playground was created, which means you will also be able to choose a new schedule from date.

      So this is great if you want to plan for scenarios with different start dates. Duplicating a scenario will duplicate the data in a scenario you've already been refining. So any constraints or priorities that you set will get copied over. And whatever schedule from date you set originally will also be maintained. I'm going to start fresh with a new scenario so that you can see it better comparison between the two scenarios since we've already made a few edits on our initial scenario.

      Now, before we compare these two scenarios, I want you to notice that each scenario has a version number. When you duplicate a scenario or create a new scenario, this is version 1 of that particular scenario. So you can see with the new scenario I just created, it's a V1. When you select Generate, the scenario will version up. So your scenarios start on V1, and every time you hit Generate, you're creating a new version of that scenario.

      So the version number is really just a marker of how many times you've hit Generate on the particular scenario. We've hit the Generate button twice on this first scenario, so it's V3. The icon to the left of each scenario will indicate if the latest changes to the scenario have been generated or not. A green icon means the latest edits have been generated. If I go ahead and make an edit on this new scenario, the orange icon means that the scenario has been edited, but that the latest edits have not been generated.

      OK, so let's go back to comparing scenarios. We've got two scenarios in this playground. And you can easily switch between them to compare the schedules and see how the dates and resource utilization stack up over time based on the various constraints and priorities you've set. The easiest way to visualize the comparison is actually from the Resources tab. The Resources tab shows us resource utilization over time.

      The resources overview graph is displayed at the top of the Resources tab and is a visual representation of your resourcing needs over time. You can choose to display the overview graph as stacked stream or list, and it can be styled to be smooth, linear, or stepped, whatever your preference is. Right now, beneath the overview graph, you can see the resource table. The table displays information about each resource class, including total resources, total tasks, and the planned start and finish for that resource class.

      Which fields are displayed can be toggled on and off from the Column Display Menu. With a Resource class selected from the overview graph or from the resource table, all of the resource class details will appear. So for example, here, I selected Animation. Now, I can see details about the resource utilization for animation. To the left, the detail graph displays resource utilization over time. Planned usage and ideal usage are both visible.

      Ideal usage is the theoretical ideal utilization, while planned usage is the actual utilization of a particular resource class. So it might be ideal to have a static number of artists over the course of a project. And Flow Generative Scheduling will attempt to achieve the ideal usage for a resource class. But this is not always possible to do while respecting the constraints that have been specified for the schedule.

      While the ideal utilization of a resource class might be a static number, reality will usually differ and there will be variations in the planned usage of a resource class over the course of a schedule. As an example, maybe your ideal usage is to have 10 animators working on a project for the week, but the reality of the schedule dictates that planned usage would be five people on Monday, eight people on Tuesday, and 10 people on Wednesday, just due to when the upstream dependencies will actually be ready for animators to start on tasks.

      So all that to say that you can choose on your graphs if you want to display the ideal or planned usage. Beneath the detail graph, you can see information about the selected resource class, so in this case, animation, including the total tasks and duration, the effort days based on an eight-hour work day, planned max and ideal max resources, and the max deviation, average deviation from the ideal.

      Now, to the right in the Detail panel, you can edit and view more information about activities that are a part of the resource class on display. And I'm going to get into this more in the next section. Before I do that, remember that we created two scenarios. The cool thing with the overview graph is that you can more easily visualize the differences in resource utilization over time between different scenarios than you can from the Gantt chart.

      In the Schedule tab, you're looking at the schedule of individual activities, while in the Resources tab, you're looking at the resource usage across the entire timeline of the project. So let's go ahead and look at these two scenarios. And you can see the differences in resource utilization between them. In the baseline scenario, I can see a project end at the end of March and a relatively level utilization of resources across that time.

      In the second scenario, which we haven't generated yet, an as-soon-as-possible version of the schedule is created, which has the project ending mid-December, with a big spike in resources at the beginning of the project. So we can see this quickly just by flipping between these two scenarios. So we talked about using constraints and priorities to iterate on your schedule and working across different scenarios. So now, I want to look at the other way you can refine your schedule, which is through resource shaping.

      Now, all resources in Flow Generative Scheduling can be shaped. For each resource class, resource shaping allows you to adjust start and end dates, add minimum resources, add easing in and out of resources, and set the total capacity. To shape your resources, you will work with the detailed graph and the Edit tab underneath the overview. Right off the bat, I see a big problem. Remember that this project contains over 5,000 tasks that need to be completed, and I know this project is, for my team at least, about a year's worth of work.

      But when this schedule was generated, I set a finish-no-later-than constraint of March 30. To complete this project by the end of March, several hundred resources have been allocated. And since I know I have a small team, this schedule is just not going to work for me. So before resource shaping, you can set constraints on your project to make sure the timeline makes sense. You can go to the Schedule tab and edit the finish-no-later-than constraint we set earlier, and choose a date in the future.

      So I'll choose November 1, giving a year for this project, which, if you remember, was my real due date to begin with. And now, I'll select Generate. When I jump back over to the Resources tab, I can see my resource utilization is much lower and spread out over a much longer period of time. This is better for me. Now, I can start shaping my resources. All right, so what if I have an entire department that I know will need to start late?

      Let's say you're working on a film, and it's your compositing team that won't be able to start until a certain date. Here, you can go select your resource class, so I'll choose compositing. Now, you can change the earliest start date to when that team will be available. My project starts November 1, and I won't have any compositing resources until January 1. So to set this up under the Edit tab, I'll change the earliest start date from November 5 to January 1.

      Now, you might notice that there's a lot of grayed out dates, including the date that I need. Earlier, I set up a finish-no-later-than constraint on the ATH sequence. If I go over to the Schedule tab, you can see the constraint is set to December 27. So going back to our earliest start date, what the gray shows is that based on the constraints that have been set on this project, the compositing team can't start any later than December 19 if we're going to hit that December 27 deadline.

      Shaping happens within the confines of the constraints that have been set. If I go back to the Schedule tab, I remove the constraint on the sequence and go back to edit the date, the limitation is gone. And now, I can choose January 1. Scheduling is always a give and take between deadlines and resource availability. If that constraint I set isn't realistic or even a real deadline, I can remove it. If it is a real deadline, then Generative Scheduling will help me to avoid making impossible scenarios where those deadlines can't be met.

      So how else can I shape my resources? You can choose to set a minimum number of resources for a resource class. For example, let's check out the layout team. I may want to maintain a minimum number of one layout artist, so I have one person on my team at all times. In this case, I can put one under Minimum Resources. We can also quite literally shape our resources using the Ease In-Out toggle to turn on the gradual increase and decrease of resources.

      You can drag the peak start and finish around and see how the easing in and out is reflected. When you hit Generate, you'll see that Generative Scheduling is going to try to match the resource utilization you've shaped. In this case, we're talking 1 to 2 resources, so we're not seeing a huge difference. But of course, with a larger team, this visual will be more noticeable if your team has a maximum number of people, you can also enter a number in the Capacity field to indicate the max number of resources.

      Now, Flow Generative Scheduling will do its best to work with that number. However, it will prioritize the constraints that have been set. If you have one month to complete this project, but you have three months worth of work to do, and you have a capacity of one person, something's got to give. But by applying capacity, you can see visually that, hey, maybe you need to look at hiring or finding more resources within your company or even changing some of your project start or end dates.

      Here, I'll set a capacity limit of two layout artists and move around the points of my peak usage to see how I can optimize my resource utilization. You can generate the schedule throughout this process to see how utilization changes. This department really only needs two people anyways. Let's try setting capacity limits with another resource class. So here, I've selected the lighting department, and I'll do the same thing. I'll set a capacity limit of 8 and hit Generate.

      And now, I can see the resource class. Let's see what it does. So it never really goes above that number except at the very end of the project. Just like with the earliest start date, if the resource utilization was going above the capacity number, this would have to do with constraints that you've already set. So if your project has certain deadlines, but you try to limit the capacity of a resource to less than what's needed to achieve that deadline, the constraints will override the capacity limitation for those periods of the project where both just aren't possible.

      So it's really that simple. You can generate a schedule as many times as you need. Each time, the schedule will vary slightly. And when you're happy with it, you can send it back to Flow Production Tracking and apply the dates. All right. So we've looked at the round-trip process from Flow Production Tracking. We've looked at using constraints and priorities, setting up scheduling scenarios, and resource shaping.

      Now, the example we've been running through is a brand new project that had a bunch of tasks that I was free to schedule in whatever way I wanted. What would you do if you have a project in progress that you need to update? Let's go ahead and create a playground for a project that's already in progress, started last month, and has a few more months of work still to be done. First, I'll go to my home page and select Create New Playground.

      I'll choose to use scheduled data from Flow Production Tracking. I'll choose my project. In this case, it's Lowlands. And I'll hit Next. I'll give the playground a name and description. Now, I'll set the schedule from date, and I'll select Keep Assign Dates for Tasks that Begin Before my New Date. So this means that anything that was already completed or any tasks that were started but not yet finished, they won't be rescheduled.

      It's just everything that hasn't started yet or anything without dates that will be scheduled. This project started mid-August, but we need to take a hiatus for reshoots that are happening. We're not sure yet how many shots will be impacted, so we're going to go ahead and pause any work that hasn't been started yet. So the schedule from date will be November 1, which is about when I think my client will be ready to start work again.

      Now, I can go ahead and add constraints and priorities. So I'm going to select the project, add a finish-no-later-than constraint of December 20. I know once the client is ready to start this project, I need to get it done quickly. I know the FLC sequence is priority for the client, so I'll set a start-as-soon-as-possible constraint on the entire sequence. FLC-10 is a priority shot within that sequence. That will be a key shot that will impact the work done in the surrounding shots, so I'm going to give it a priority of 100.

      I've generated the schedule. And now, I can look at my resource utilization in the Resources tab. I'm going to flip through each of my resources and ease resources in and out and shift the peaks of resource utilization a little. You'll see as I work that the original dates are maintained. Locked activities happen when a schedule is imported with activities that start in the past. Any activities that are done will be locked and won't be editable.

      They'll display, as you can see on the left hand of the screen here, with diagonal lines, which will show in the Gantt chart and in the overview graphs. When you're happy with the schedule, you can send it back to Flow Production Tracking. So I'm going to go ahead, send to Flow Production Tracking, Send Scenario. Give it a few seconds to complete. Now, when you open Flow Production Tracking, you'll see the new dates in the proposed start date field.

      But for the tasks that were already completed, you'll see that the dates are the same, that there's no change, which is what we asked Generative Scheduling to do. Now, we can apply the new proposed start dates and the schedule will get updated. But again, everything that has start dates in the past or had end dates in the past will be respected. Before I finish, I wanted to bring up the generative part of Flow Generative Scheduling.

      And more specifically, I wanted to talk about how this tool uses your data. Flow Generative Scheduling creates a unique Artificial Intelligence, or AI, model for each run of the solver, i.e. for each click of the Generate button. The model is derived only from the data set that is imported and does not utilize any models trained on or derived from any data from other users or third parties. Similarly, any data that's imported into Flow Generative Scheduling is not used in the training of any other AI models.

      You don't need to worry about your personal data or schedules being used in training or worry about the quality of the training material of the AI used because it doesn't use any. As for how it actually works, that is a topic for another presentation and definitely a more technical one for which I'm not qualified to begin explaining. So I won't get into that today. So to conclude this presentation, project plans are always changing.

      We need a way to adapt our schedules when changes need to happen, which they will. With Flow Generative Scheduling, you can quickly generate level schedules using the task information from your Flow Production Tracking site, create different scenarios to plan for project changes, and prepare for hypotheticals, apply constraints and priorities to your schedule to ensure that what matters the most to you happens first, and use resource shaping to balance resourcing across your different scenarios to avoid peaks and valleys in your resource utilization.

      I hope this class has been able to give you some insight on what Flow Generative Scheduling can do to help you quickly generate and iterate on your project schedules and manage the ever-changing reality of the schedule changing again. Thank you.

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      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。

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      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。

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      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。

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      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

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      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

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      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。