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Digital Transformation into action:Saipem Platform for AWP

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Description

Learn more about how Saipem has been working to create integrations that support Advanced Work Packaging implementations at any scale, realizing the “new possible”. Advanced Work Packaging methodology supports the work on an EPC project, from initial planning throughout detail design to construction execution; such methodology encompasses the overall process flow of all the detailed work packages (construction, engineering and installation). Saipem will give practical examples of their AWP implementation and how they have used Autodesk Forge development platform to solve their challenges. This session will show how a data-centric solution can integrate data coming from a variety of legacy systems, presenting opportunities never experienced before to the users. With this new solution they have access to a large variety of data from a single source of truth and the ability to access information from different point of views.

Key Learnings

  • Identify the importance of bringing data at the center to realize the new possible
  • Envision improvements for your daily activities, with a session intended to give you “food for thoughts”
  • Integrate legacy systems in a single platform
  • Implement Advanced Work Packaging in your business

Speakers

  • Avatar for Stefano Cartocci
    Stefano Cartocci
    For more than 20 years, I worked in Oil & Gas Industry following the use and development of Engineering software, starting as a CAD user and now as worldwide coordinator for Business Application and Italy IT Coordinator at Saipem Offshore Engineering & Construction Division. During the last, six years joined the IT Department as project and program manager for IT innovation projects. Currently i 'm also involved in Digital Transformation program as IT Coordinator for the Division and Digital Office Lead in smartworking project. During my career i was able to prove my best capabilities and able to succeed in reaching all the project targets showing strong skill set especially for team working and decision-making.
  • Avatar for Luca Bazzocchi
    Luca Bazzocchi
    Consulting Services Senior Manager and proud Autodesker since 2008! Team leader, always excited to meet dynamic and creative thinkers, I am enthusiastic about shaping innovative solutions. I received his Computer Science bachelor's degree from University of Genova, Italy. Also started to work with Forge in the early days, and have been working with the platform for the past 7 years.
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Transcript

STEFANO CARTOCCI: Good afternoon, and good to be here to Autodesk University to everybody. I'm Stefano Cartocci from Saipem Engineering and Construction OFFShore in Italy. And I'm here with my friend Luca from Autodesk. We are here to introduce you to our integrated solution for the adoption of advanced work packaging methodology.

Just hear the agenda of this panel. First of all, we will have a brief introduction on our speaker's bio. Then we will have an establishment moment, where I will bore you with an overview of what Saipem is, what its business is, and Saipem approach to digital transformation. Then we will get you to the point, right to the point, by showing you our solution, and finally, how will we see the future in front of us. And let me say, we'll give you some suggestion.

A brief introduction identifying the key objective of our introversion. First of all, we would like to underline the key role of data-centric approach and the democratization of data. And it is the importance of allowing everyone involved in business process to have the so-called single source of truth.

I know that you have already listened. This is a buzzword, the single source of truth. But it is really what is really meaningful in a data platform, meaning that having this single source of truth always you have access to the greatest and latest data and allowing what is really a data driven decision.

Then we want to add light to the integration that we have done to the legacy system, already news, and the introduction of a collaboratory platform that is based upon everything, allowing a data driven approach to the decision making process for our managers. Then we will show you a possible approach to the advanced work packaging, or at least how Saipem has intended a collaborative platform for AWP.

At the end, we would like to share our experience in the hope of providing you with insights for the development of your own process and the solution of your own problems. We want to think that at this panel would be the starting point for your brainstorming session on this focus.

But now let us introduce ourselves. My name, as I told you, is Stefano Cartocci. And I've been part of Saipem for about 17 years. And at the beginning, I was part of the engineering department as a 3D modeler. And then I moved to the IT department, where today I hold the position of Data Management and Application Management for the OFFShore E&C division. Luca, if you want to introduce yourself.

LUCA BAZZOCCHI: Thank you very much, Stefano. Hi, all. First of all, let me welcome all of you at this AU class. My name is Luca Bazzocchi. And I am a proud Autodesker since 2008 working in a global consulting delivery practice and covering the role of Consulting Service Manager and Principal Solution Architect.

My main goal is to support our customer during their digital transformation journey. And Saipem is an Autodesk customer I've been working with since 2015, so for almost half my Autodesk life. Today I'm here to co-present this session with Stefano and to introduce you to the Saipem Advanced Work Packaging platform. We worked together in the past few months.

STEFANO CARTOCCI: So now we can have the instructional moment. And we could also introduce Saipem. Who is Saipem? Saipem is a global solution provider. At Saipem, we are present in more than 70 countries with more than 35,000 employees, and we cover from almost 122 different nationalities with our employees.

Saipem is leader in engineering and drilling activities and in the completion of great projects in the energy infrastructure sector. Saipem is competitive with a distinctive skill, competence, and high tech asset. And it is capable of identifying and developing multiple solutions. Saipem is organized, basically, in five different divisions, each one focused on specific market segments and specific business.

As you can see also from the slide, we have the XSIGHT, which is the project definition services. Then we have the two divisions that are focused on engineering and construction, the offshore engineering construction and onshore engineering construction, and then, at the same way, the two drilling divisions.

In Saipem, I am part of the offshore division. And we are focused, basically, on delivering great projects above and under the sea. From the conventional activities such as you can imagine in a PCI project, the four platforms, we are now moving to the green industry. So we are developing some installation in for the [INAUDIBLE] turbine in the sea.

And then we are also proud to our new sectors, our new market that is the development of highly innovative ROV for maintenance and management of sub-sea field. The ROV, it is basically a little submarine that is driven from a remote position.

As a contractor, we base our job basically on project. And for this reason, we have, as always, a lot of problems because we have a project from our client, and then so we have to be strongly compliant with the client needs. We need to follow the specification. We need to follow the rules. But in the same time, we are trying to perform at the best our project as we are used to do, so following our own methodology and our own standards.

So we have to keep the balance between these two things. So we have to keep the scales in balance. And to do these things, what we typically do is we rely on three basic pillars. The strategic pillar for us are sustainable business, health and safety for our employees, and innovation. We strongly believe that innovation will help us in facing these problems and in upgrading at the best our project execution.

For this reason, we find in a moment where we have to start what we call a journey to digital transformation. This journey started in 2019 with larger backscatter initiative typically related to single process and without an orchestration, without a holistic view on the problem, without let me say, something that was on the top that can manage this. And typically, there are few resources purely dedicated to this digital transformation.

At this point, the Saipem have a strong ambition and decide to move in a different way, define to move in a better way, let me say, and define and decide to define a clear digital roadmap, decide to identify key technology, and especially to speed up cultural change.

Probably cultural change is the fundamental step that all the company has to face, speaking of a digital transformation. And it's also a point where a company has to be really, really focused, especially the incumbent company that have great difficulty in to start the cultural change, in changing their point of view, their way of working. And for this reason, the possibility to have an external partner that could help both in methodology and technology definition, it is really important.

In 2020, we decided to move from a scatter initiative, from a journey to a real digital transformation program. This digital transformation program was composed by several clusters of activities focused on different areas of the company. And among those activities, there is one which is the so-called EPC integration model that is really focused on project development, on solving the problem that we typically have with our client in our projects.

So basically, we want to create a simple and unique place where integrating the existing digital tools that we already have and developing the missing pieces to achieve a cross divisional. We are in division. We are splitted, in fact, in division. So we need something to be really holistic and to be really on top of everything to achieve cross divisional business benefit.

This benefit could be an improved collaboration during the project execution, cost reduction, and minimize the errors, and maximize the efficiency and especially a new way of working with the real time monitoring.

Beside the digital transformation journey, or we can consider also a sort of spin off to it, Saipem decided to invest in development of AWP methodology to focus on maintain a construction based approach to keep the management of the supply chain and to have the management of the construction activity, a better management of the construction activity, also have the possibility to take advantage of a 3D and 4D dimensional simulation for the project itself.

Knowing that the interest of the APC industry and oil and gas especially toward the AWP methodology, it is really increasing. And some experts told us that there is the possibility to increase in productivity of 25% and 10% in cost reduction data. I'm speaking about billions. It is a huge amount of money.

So at this point, we have a strategy, we have a methodology, and then what? What do we need more than this? We could easily say that now you need only the technology. You need only the tool. You need only the software to do this, to put everything on this software, and you can start and do this.

Anyone of you that are involved in digital transformation activities in developing or implementing a solution in an incumbent or in a big company knows that is not so easy and especially knows that is not everything about technology. And I have what I called my sensei, which is the head of the APC integration department, Mr. Luca Ursini, that usually said something to us, which is basically this. Don't wait for the technology to come to you.

Luca means that even the coolest technology cannot solve your problem without the human integration, without the human user of this technology, without the human element. A technology must be contextualized within the current business cases and be usable by end user. A technology must help and facilitate as many people as possible.

And with this data in mind, we decided to move to agile methodology for the developing, and we use a multidisciplinary team that was not all only related to digitalization and IT, but also with the business users.

How we want to develop this tool, how we want to develop this solution, we create this solution, we design this solution based on three main layers. This is a schematic, and things are really, really much more complex than this. But we can focus, for example, on the first layers. The first is the integration layer. It is the integration with all our legacy system, the systems that we normally use and effectively use during the development of our project.

For example, we can see that we have a Primavera P6 for the scheduling department. We have an ERP. We have SAP. We have all our engineering systems, and especially we have the 3D model. 3D model typically are imposed by our client. It is not a software by our choice. So we have a portfolio of two, three capability in different 3D modeling software.

And so we have the need to integrate all this type. We need to have the possibility to be seamless in the using of 3D model tools. Then what we have, document management system. We have a document management system to be integrated for sure. Then we have the fabrication and completion systems.

But then, as always, there are other sources, our scattered sources, our unstructured sources, and then, for sure, Excel files. Excel advice cannot be avoided for sure. So basically, integrating instead of replacing these tools in a much bigger solution gives us savings in money, savings in time, and also help us to accelerate the time to market towards our internet client.

The middle layer represents-- and me, as Data Manager, are really proud of this-- represents the real heart of the solution. And it is the data platform. Here in the data platform, we have the storage of the data. Data have to pass several quality checks and then have to be aggregated for different use cases and prepare for the top layer.

The top layer, it is the collaboration and visualization layer, where data are analyzed and become the most important bricks for the creation of a real data driven decision making process. Here in the collaboration layer, we have also the possibility of 3D and 4D visualization. We have simulation, and we are sure that all these simulation of this analysis rely on a data platform, on a data that is, let me say, compliant with all the quality that we need.

So fundamental in all this integration that we have done in our integration approach was the help of Autodesk. And I leave Luca to present the consulting services that very much help us in this.

LUCA BAZZOCCHI: Thank you, Stefano. Here we are. Let's now have a look at the Autodesk consulting transformation services. After working on many, many transformational initiatives, we have become a trusted advisor for the market leading companies, such as Saipem.

We are helping them break boundaries between the design and make process across converging industries and even within their own organization to deliver real meaningful changes. It is this relationship that inspired transformation services, which can be seen as a faster, easier, and more flexible way to get access to the full breadth of our consulting.

So let's see a little bit more in details what those services are meant to be. Instead of focusing on individual unconnected projects, we have found that more valuable relationship will focus on their sum. What does it mean? That means that we have seen that the wind technology is approached programmatically, such as an initiative. It has the power to drive the cultural and organizational shifts needed for successful transformation.

And on top of this, there are few characteristics that these relationships tend to have. And those are holistic, agile, and innovative. Let me stop here just one second. We have heard already during this presentation Stefano mentioned those terms. This is extremely important because this is a proof that Autodesk and Saipem's strategy are aligned, which is a key to success.

Having said that, let's understand what we mean. While the typical project relationships are focused on a single technology solution, transformational relationships take a more holistic approach. We focus on business goals, rather than on technology only. So technology, as Stefano said, it's a key. It's important. We cannot forget or decouple completely from technology.

But the starting point, the driver, is not the technology, are the business goal, the company strategies, and so on. While the project relationship are focused on fixed scope and specifications, transformational services are much more agile than that. We know that everything can change on a dime, corporate strategy, economics, project requirements.

We have experienced these in the past couple of years. Our way of working, our way of living completely changed. And we need to be ready to adapt ourselves to those changes and to adopt them as well. That is why an agile approach is much more productive and will bring us to more results than something which is a little bit more static.

And last but not least, the latter characteristic is the innovation. Probably if I ask you what do you mean by innovation, each one of you will give me a slightly different answer. I can tell you that to me, innovation means-- innovating means challenging the status quo of things, means thinking out of the box with the aim to fulfill our and our customers' goals in the best way possible.

And the next slide will represent a poster with a list of those transformational services that we, as Autodesk consulting, are delivering. Transformational services are mainly made by advisory and implementation services.

We can see and think to advisory as all that is a kind of assessment study, feasibility studies, or proof of concept, validation of the plans, assessment of the to be status, and identifying the to be status of your roadmap and of your environment, while the implementation services are more the practical side of things, where we go in action and apply everything that we found out in the advisory and developer solution, or configure things, or provide training, and so on. With that, Stefano, let's back to you.

STEFANO CARTOCCI: Thanks. So let's start with an overview of the solution. So the solution has to work together with the methodology and to increase our capability of integrated planning of the project phases, taking care, for example, for materials for drawing data and the link between, then has to give us the possibility of managing the construction work front by connecting later with the supply chain.

So we need where are materials, where are drawings, if we have it on the yard or not, and giving it to managers the real time visibility and forecasting to allow decision making activities. Then what we have to do is to improve our construction monitoring during the execution phase. All this could be possible because we are using a common and reliable data platform. So now Luca will go deep into some aspect of this solution.

LUCA BAZZOCCHI: Absolutely. So let me set up the scene upfront. So the solution we present, and the videos you will see assumes that the AWP structure is already in place. But most of all, what we are going to see is based on a real project and uses real data. That's true, even if in one cases, and I will underline it, we had to manipulate a little bit data to create a specific use case for demo purposes only.

As an anticipation on what you are going to see, with this solution, we want to support the team within an integrated planning along all and any project phase, giving the possibility to assess the detailed set of data, depending by what each user is really interested to analyze and to dive into.

The main benefits we expected from these are the increased consistency in work package definition, the reduce in misalignment in EPC planning, and improve execution.

So we are going now to see a short video. But before starting it, just with a second's difference, sorry, just to think at this light that Stefano presented a few minutes ago. When you see the three layers that are composing our solution.

At this stage, we are moving from the integration layer up to the collaboration one, where information coming from the data lake are presented in a complete dashboard that integrates Power BI dashboards, 3D models stored in 360, and all the data coming from the legacy system Stefano mentioned upfront.

We will start having a quick look at the solution it looks like. On the right side, we do have Power BI dashboard. It can be any business intelligence tool. But we are using, in this case, Power BI. And on the left, we have the 3D model alluded in the [INAUDIBLE]. As you can see, we have initially only a pipeline system. But you can load multiple model.

We decided to organize model by discipline, so that the user can see a unique model, which is an aggregation of, in this case, the three models containing pipeline, structure, and other elements. As you can see, everything is themed accordingly to the donut in the middle in Power BI. On the left, we also have a Gantt, where we can see all the status of the CWPs that still aligned with all the data coming from Power BI.

Filtering, by CWP, we can see everything changing and updating. So the driver of the solution are the data that we see in the Power BI dashboard. We filter by [INAUDIBLE] packages. We have specific results on the left side of the solution. Moreover, everything is fully integrated, so clicking on the box in the Gantt will focus on elements in the model accordingly.

We move now to the second tab of the Power BI dashboard. We were on the AWP progress before. Now we are in the CWP overview. And so we have to focus on the first donuts on the left in the dashboard. As you can see, what's more, everything is fully aligned to what we see in the dashboard. We have in progress elements and not available elements. And that's exactly what we see in the model. And as we will see shortly in the Gantt as well.

As I said, everything is fully integrated. What does it mean? That any action you perform in one area, in one portion of your solution, has an effect on the other part. So if we select a not feasible elements, again, we only see a theme, not feasible elements in the model. And we see only then not feasible CWP in the Gantt, same thing if we click Main Progress. Let's now go back to see both elements.

And one important thing is that we can see here the construction working package, but below them, we have another object, which are called smart objects. What are those smart objects or SMOs? Saipem had the need to introduce a new dimension, a dimension below the CWP as the packaging of materials, including the tagging, the coding, and the full visibility of the relevant supply chain. That is not defined in the AWP, but it's extremely important.

Here now, we are seeing the 4D simulation that Stefano mentioned earlier on. So we see now week by week the progress on the construction site. And here are the data that we manipulated, as I anticipated. As you can see, you can view that there are structures that have not been erected while the pipelines that they are supposed to hold are already completed.

And the last functionalities that we want to show you in this video is the side by side for the animation comparison. This is very important because you can make a real comparison on the 4D visualization for the animation of two different plans, the one on the left, which is the baseline, and the one on the right, which, in this case is the actual. More than this can be done because we can also upload different what-if scenario.

Next slide, Stefano. This is the video we already saw. Thank you. In this slide, we are focusing on the second set of capabilities of the solution that we want to underline today. Those capabilities focus on the advanced status visibility of materials as the result of very complex logic applied by the work front analysis.

Work front analysis is a predictive analysis based on material availability related to the construction scaling, so material and plan. This is the key. With such capability, the solution allows the possibility to intercept potential issues related to materials, planning, and preparation.

We can now highlight the benefits that we expect, as we did before. Here, again, we expect a reduce of disruption and improvement in information visibility, of construction visibility, and the reduction time and effort required in root cause analysis.

We have now another video to present you with this second set of capabilities, which-- here we are-- which are focusing on the Workfront analysis and materials. We are now in the third tab, so the WFA materials. All the functionality we have seen before are still valid here. We are just only focusing on a different set of data, those that are coming from the Workfront analysis calculation.

So we see the model, as we saw before, themed accordingly. What we see different in this case, also in the Gantt, is that the bar R can have multicolors. That's why because below the smart object, we are introduced to another level of details, which is the material.

And for each material, we have different levels of availability. They can be available, or later, or even not yet ordered. In this case, the bars represent a multi course because they want to show us not all the materials are available for that specific smart object for that specific construction work package. All views are still driven by the data in Power BI. In this case, we selected something that is late.

And as you can see, all the Gantt information, now you know already about the 3D model, only show the data of not available material for that specific CWP that we have selected. Good. Going back, there are a few other things to discuss. And again, one is, again, the possibility to analyze different scenarios.

This time it's not based on the data coming from [INAUDIBLE], but the data that are gained in the result of the analysis. So we have the best case and conservative scenario for the waterfront analysis. And selecting one of the two, we have a different presentation of data.

I hope really that this was of interest for you and help understanding how Saipem and which steps Saipem took in fixing their digital transformation journey towards the adoption of advanced work packaging. And with that, I will hand over again to Stefano for our final thoughts.

STEFANO CARTOCCI: Thank you, Luca, great as always. And so our final thoughts, our final thoughts are that despite the COVID implication that forced us to a total remote collaboration and development, and after a couple of months of users, some business testing, and the platform has provided to be solid and user-friendly, and that this will allow us to schedule production for September 2021.

Moreover, we are working on a continuous improvement. We are adding pieces, even with the help of Autodesk. And what we need to create, to implement new cases, new use cases, to add the potential integration, and we hope to present you live at the AU 2022. Now we are at the end of this phase of the project, and there is only one or two things that we want to suggest to you.

This is something that in our idea it is mandatory when we implement a solution like this, which are, one, it is the strong commitment and a cultural change. We need to be really committed. We need that the business users and the management are really committed on this. And

Then what we can tell you is that also a solid partnership with trusted advisor are needed to support this journey to implement these things. So now, let me thank you for the attention, and let me tell you, thank you again. Luca.

LUCA BAZZOCCHI: Thanks a lot for your participation. Stay safe, and really, I hope to see you soon in person. Thanks a lot.

STEFANO CARTOCCI: Goodbye.

LUCA BAZZOCCHI: Bye.

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We use Typepad Stats to collect data about your behaviour on our sites. This may include pages you’ve visited. We use this data to measure our site performance and evaluate the ease of your online experience, so we can enhance our platform to provide the most relevant content. This allows us to enhance your overall user experience. Typepad Stats Privacy Policy
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We use Geo Targetly to direct website visitors to the most appropriate web page and/or serve tailored content based on their location. Geo Targetly uses the IP address of a website visitor to determine the approximate location of the visitor’s device. This helps ensure that the visitor views content in their (most likely) local language.Geo Targetly Privacy Policy
SpeedCurve
We use SpeedCurve to monitor and measure the performance of your website experience by measuring web page load times as well as the responsiveness of subsequent elements such as images, scripts, and text.SpeedCurve Privacy Policy
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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Improve your experience – allows us to show you what is relevant to you

Google Optimize
We use Google Optimize to test new features on our sites and customize your experience of these features. To do this, we collect behavioral data while you’re on our sites. This data may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, your IP address or device ID, your Autodesk ID, and others. You may experience a different version of our sites based on feature testing, or view personalized content based on your visitor attributes. Google Optimize Privacy Policy
ClickTale
We use ClickTale to better understand where you may encounter difficulties with our sites. We use session recording to help us see how you interact with our sites, including any elements on our pages. Your Personally Identifiable Information is masked and is not collected. ClickTale Privacy Policy
OneSignal
We use OneSignal to deploy digital advertising on sites supported by OneSignal. Ads are based on both OneSignal 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 OneSignal has collected from you. We use the data that we provide to OneSignal to better customize your digital advertising experience and present you with more relevant ads. OneSignal Privacy Policy
Optimizely
We use Optimizely to test new features on our sites and customize your experience of these features. To do this, we collect behavioral data while you’re on our sites. This data may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, your IP address or device ID, your Autodesk ID, and others. You may experience a different version of our sites based on feature testing, or view personalized content based on your visitor attributes. Optimizely Privacy Policy
Amplitude
We use Amplitude to test new features on our sites and customize your experience of these features. To do this, we collect behavioral data while you’re on our sites. This data may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, your IP address or device ID, your Autodesk ID, and others. You may experience a different version of our sites based on feature testing, or view personalized content based on your visitor attributes. Amplitude Privacy Policy
Snowplow
We use Snowplow to collect data about your behavior on our sites. This may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, your IP address or device ID, and your Autodesk ID. We use this data to measure our site performance and evaluate the ease of your online experience, so we can enhance our features. We also use advanced analytics methods to optimize your experience with email, customer support, and sales. Snowplow Privacy Policy
UserVoice
We use UserVoice to collect data about your behaviour on our sites. This may include pages you’ve visited. We use this data to measure our site performance and evaluate the ease of your online experience, so we can enhance our platform to provide the most relevant content. This allows us to enhance your overall user experience. UserVoice Privacy Policy
Clearbit
Clearbit allows real-time data enrichment to provide a personalized and relevant experience to our customers. 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.Clearbit Privacy Policy
YouTube
YouTube is a video sharing platform which allows users to view and share embedded videos on our websites. YouTube provides viewership metrics on video performance. YouTube Privacy Policy

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Customize your advertising – permits us to offer targeted advertising to you

Adobe Analytics
We use Adobe Analytics to collect data about your behavior on our sites. This may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, your IP address or device ID, and your Autodesk ID. We use this data to measure our site performance and evaluate the ease of your online experience, so we can enhance our features. We also use advanced analytics methods to optimize your experience with email, customer support, and sales. Adobe Analytics Privacy Policy
Google Analytics (Web Analytics)
We use Google Analytics (Web Analytics) to collect data about your behavior on our sites. This 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. We use this data to measure our site performance and evaluate the ease of your online experience, so we can enhance our features. We also use advanced analytics methods to optimize your experience with email, customer support, and sales. Google Analytics (Web Analytics) Privacy Policy
AdWords
We use AdWords to deploy digital advertising on sites supported by AdWords. Ads are based on both AdWords 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 AdWords has collected from you. We use the data that we provide to AdWords to better customize your digital advertising experience and present you with more relevant ads. AdWords Privacy Policy
Marketo
We use Marketo to send you more timely and relevant email content. To do this, we collect data about your online behavior and your interaction with the emails we send. Data collected may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, your IP address or device ID, email open rates, links clicked, and others. We may combine this data with data collected from other sources to offer you improved sales or customer service experiences, as well as more relevant content based on advanced analytics processing. Marketo Privacy Policy
Doubleclick
We use Doubleclick to deploy digital advertising on sites supported by Doubleclick. Ads are based on both Doubleclick 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 Doubleclick has collected from you. We use the data that we provide to Doubleclick to better customize your digital advertising experience and present you with more relevant ads. Doubleclick Privacy Policy
HubSpot
We use HubSpot to send you more timely and relevant email content. To do this, we collect data about your online behavior and your interaction with the emails we send. Data collected may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, your IP address or device ID, email open rates, links clicked, and others. HubSpot Privacy Policy
Twitter
We use Twitter to deploy digital advertising on sites supported by Twitter. Ads are based on both Twitter 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 Twitter has collected from you. We use the data that we provide to Twitter to better customize your digital advertising experience and present you with more relevant ads. Twitter Privacy Policy
Facebook
We use Facebook to deploy digital advertising on sites supported by Facebook. Ads are based on both Facebook 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 Facebook has collected from you. We use the data that we provide to Facebook to better customize your digital advertising experience and present you with more relevant ads. Facebook Privacy Policy
LinkedIn
We use LinkedIn to deploy digital advertising on sites supported by LinkedIn. Ads are based on both LinkedIn 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 LinkedIn has collected from you. We use the data that we provide to LinkedIn to better customize your digital advertising experience and present you with more relevant ads. LinkedIn Privacy Policy
Yahoo! Japan
We use Yahoo! Japan to deploy digital advertising on sites supported by Yahoo! Japan. Ads are based on both Yahoo! Japan 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 Yahoo! Japan has collected from you. We use the data that we provide to Yahoo! Japan to better customize your digital advertising experience and present you with more relevant ads. Yahoo! Japan Privacy Policy
Naver
We use Naver to deploy digital advertising on sites supported by Naver. Ads are based on both Naver 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 Naver has collected from you. We use the data that we provide to Naver to better customize your digital advertising experience and present you with more relevant ads. Naver Privacy Policy
Quantcast
We use Quantcast to deploy digital advertising on sites supported by Quantcast. Ads are based on both Quantcast 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 Quantcast has collected from you. We use the data that we provide to Quantcast to better customize your digital advertising experience and present you with more relevant ads. Quantcast Privacy Policy
Call Tracking
We use Call Tracking to provide customized phone numbers for our campaigns. This gives you faster access to our agents and helps us more accurately evaluate our performance. We may collect data about your behavior on our sites based on the phone number provided. Call Tracking Privacy Policy
Wunderkind
We use Wunderkind to deploy digital advertising on sites supported by Wunderkind. Ads are based on both Wunderkind 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 Wunderkind has collected from you. We use the data that we provide to Wunderkind to better customize your digital advertising experience and present you with more relevant ads. Wunderkind Privacy Policy
ADC Media
We use ADC Media to deploy digital advertising on sites supported by ADC Media. Ads are based on both ADC Media 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 ADC Media has collected from you. We use the data that we provide to ADC Media to better customize your digital advertising experience and present you with more relevant ads. ADC Media Privacy Policy
AgrantSEM
We use AgrantSEM to deploy digital advertising on sites supported by AgrantSEM. Ads are based on both AgrantSEM 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 AgrantSEM has collected from you. We use the data that we provide to AgrantSEM to better customize your digital advertising experience and present you with more relevant ads. AgrantSEM Privacy Policy
Bidtellect
We use Bidtellect to deploy digital advertising on sites supported by Bidtellect. Ads are based on both Bidtellect 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 Bidtellect has collected from you. We use the data that we provide to Bidtellect to better customize your digital advertising experience and present you with more relevant ads. Bidtellect Privacy Policy
Bing
We use Bing to deploy digital advertising on sites supported by Bing. Ads are based on both Bing 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 Bing has collected from you. We use the data that we provide to Bing to better customize your digital advertising experience and present you with more relevant ads. Bing Privacy Policy
G2Crowd
We use G2Crowd to deploy digital advertising on sites supported by G2Crowd. Ads are based on both G2Crowd 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 G2Crowd has collected from you. We use the data that we provide to G2Crowd to better customize your digital advertising experience and present you with more relevant ads. G2Crowd Privacy Policy
NMPI Display
We use NMPI Display to deploy digital advertising on sites supported by NMPI Display. Ads are based on both NMPI Display 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 NMPI Display has collected from you. We use the data that we provide to NMPI Display to better customize your digital advertising experience and present you with more relevant ads. NMPI Display Privacy Policy
VK
We use VK to deploy digital advertising on sites supported by VK. Ads are based on both VK 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 VK has collected from you. We use the data that we provide to VK to better customize your digital advertising experience and present you with more relevant ads. VK Privacy Policy
Adobe Target
We use Adobe Target to test new features on our sites and customize your experience of these features. To do this, we collect behavioral data while you’re on our sites. This data may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, your IP address or device ID, your Autodesk ID, and others. You may experience a different version of our sites based on feature testing, or view personalized content based on your visitor attributes. Adobe Target Privacy Policy
Google Analytics (Advertising)
We use Google Analytics (Advertising) to deploy digital advertising on sites supported by Google Analytics (Advertising). Ads are based on both Google Analytics (Advertising) 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 Google Analytics (Advertising) has collected from you. We use the data that we provide to Google Analytics (Advertising) to better customize your digital advertising experience and present you with more relevant ads. Google Analytics (Advertising) Privacy Policy
Trendkite
We use Trendkite to deploy digital advertising on sites supported by Trendkite. Ads are based on both Trendkite 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 Trendkite has collected from you. We use the data that we provide to Trendkite to better customize your digital advertising experience and present you with more relevant ads. Trendkite Privacy Policy
Hotjar
We use Hotjar to deploy digital advertising on sites supported by Hotjar. Ads are based on both Hotjar 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 Hotjar has collected from you. We use the data that we provide to Hotjar to better customize your digital advertising experience and present you with more relevant ads. Hotjar Privacy Policy
6 Sense
We use 6 Sense to deploy digital advertising on sites supported by 6 Sense. Ads are based on both 6 Sense 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 6 Sense has collected from you. We use the data that we provide to 6 Sense to better customize your digital advertising experience and present you with more relevant ads. 6 Sense Privacy Policy
Terminus
We use Terminus to deploy digital advertising on sites supported by Terminus. Ads are based on both Terminus 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 Terminus has collected from you. We use the data that we provide to Terminus to better customize your digital advertising experience and present you with more relevant ads. Terminus Privacy Policy
StackAdapt
We use StackAdapt to deploy digital advertising on sites supported by StackAdapt. Ads are based on both StackAdapt 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 StackAdapt has collected from you. We use the data that we provide to StackAdapt to better customize your digital advertising experience and present you with more relevant ads. StackAdapt Privacy Policy
The Trade Desk
We use The Trade Desk to deploy digital advertising on sites supported by The Trade Desk. Ads are based on both The Trade Desk 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 The Trade Desk has collected from you. We use the data that we provide to The Trade Desk to better customize your digital advertising experience and present you with more relevant ads. The Trade Desk Privacy Policy
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

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