Adobe Inc. (ADBE) Earnings Call Transcript & Summary

Hi, everyone. Welcome to the first panel of the last day of HCTS about ensuring the end-to-end IT stack to improve the overall customer experience. It's been a fantastic few weeks as we're trying to really focus on what's going on with the cloud and hosting and digital transformation as a whole. And in a world where disruption and digital transformation experience is really changing the face of customer experiences, I'm really glad that we're here to talk about this whole end-to-end approach. And I'm being joined by a wonderful panelist, and we're really going to talk about what's happening and how we can elevate the importance of an agile IT infrastructure focused on data-driven initiatives and the state of digital transformation as we try to improve customer experiences from the core to the edge and really capitalize on the innovation that's available in the industry. So what I would love to do at this point, though, is I am Sheryl Kingstone, your host for today, pretty much for -- the Head of Customer Experience and Commerce Research as an industry analyst at 451 Research. But I'm going to let my colleagues here, the participants of the panel, sponsors, to introduce themselves and give themselves a key round of the background. And so when we really take a look at where we're trying to go today, the participants that are here, and here are our panelists. So take it away, I would love it. Patrick, why don't you start?

Hey. Good morning. Good afternoon for some folks. But my name is Patrick West. I am the DX Global Lead for Adobe looking after Publicis Group, and I want to just thank everybody for having me here today. And as I think about customer experience, the main problem or the main challenge that we're trying to solve here is to be able to deliver these experiences really seamlessly. And it's not easy to do, and the ability for us to do this collectively is critically important.

And Vish, why don't you go next?

Thank you. Good morning and good afternoon, everyone. My name is Vishnu Indugula, Vish, from Publicis Sapient. Been at Sapient for a very, very long time. And I started as a technologist and moved into a role where I oversee all of marketing technologies for the group that we work on. And just as Patrick said, I think that a key thing that we're doing is really connecting, as Sheryl said, the core to the front. And transformation just doesn't happen at the [indiscernible] of what a consumer sees. We think it's actually important to actually change the whole stack, right, everything that we call as the backstage and the front stage to be able to deliver those experiences. Excited to be here. And hopefully, we can share some good material for everyone to consider as they go through these journeys.

Absolutely. And Jim, that would be great if you could go next. Yes.

Thank you, Sheryl. So Jim Gannon here. I support global accounts and service providers at Pure Storage. A few quick facts about Pure, based at Mountain view, California. We've been in Gartner's Magic Quadrant for primary storage 6 years in a row. We've got a Net Promoter score of 85, which puts us in the top 1% of all B2B companies. And the reason I bring that up is because the formula that we've been working on has been solving 2 problems that many of our customers are all struggling with. First is, have you reduced the cost and the complexity of managing data volumes that seem to be growing exponentially day by day, week by week? And the second is, how do you take advantage of all of the advancements in AI, ML, et cetera, by unlocking the value of data that currently sits across multiple silos? So those are the problems that we've been solving for customers, and I'm looking forward to today's discussion.

And Michael.

Great. Thanks for having me. My name is Michael Cucchi. I'm Vice President of Product and Partner Marketing at PagerDuty. I'm very excited to be here. I feel like the challenges that you're focusing in on at this conference are really primary goals of ours at PagerDuty. For us, we're focused on enabling the future of work, which is obviously about delivering those digital experiences and business-critical services for digital enterprises. I think as companies are trying to transition and mature, they need the ability to kind of provide very, very high levels of visibility across very, very complex organizational infrastructure from both a people perspective and a technology perspective. And I know you've been very focused on cloud migration and digital transformation. And generally, that means doing that in multiple places and multiple environments, where you are today and where you're trying to get to. So PagerDuty is really focused on pulling in tons of data from a multitude of sources and then using machine learning and AI to help companies move from being reactive and kind of always on their heels as they're taking on these new challenges, new levels of complexity and noise and try to help them move to being predictive and proactive. And then very specific to your world, we're trying to do that all the way out to the customer through customer service. So I'm very excited. I think it's going to be a great chat today.

And we have a very well-rounded set of conversation topics. And so as those of you who attended the opening keynote, the whole data-driven experience economy, I talked about the power of 3, right? So we talk about digital transformation and cloud deployments and analytics and how important that is to the overall customer experience, and so what we're going to hear is trying to talk about all 3 of those in a very hopefully dynamic discussion. And so when we talk about data-driven and digital transformation and strategies in COVID, especially as it relates to digitizing that customer experiences, businesses are really rapidly embracing this disruption, but it's changing the technology stacks, and it's changing distributed teams, and we all have to work together to delight these customers.

So the first question I have is for Patrick. What have you really seen as those top pivots that companies are really trying to accomplish over the last 6 months?

Yes, great question. I think that the -- overall, as COVID has helped compress almost the road map that they're already on, right, so there's a lot of organizations out there that are already on this road map, and it really exposed some of the shortcomings that needed -- that wanted them or made them necessarily move forward. So one of the big things that we're seeing is that data, right? So the taking of different data silos within organizations and then being able to put them together to understand what's truly happening across the business, not just from a marketing perspective or from a CX perspective, but across the entire business. And so those are the big things that I'm seeing or that's one of the big things that I'm seeing across based on COVID. I think the other piece that I think I'd add there is that most organizations are trying to just cope with, hey, we weren't prepared for this and having to figure out how do we quickly pivot to be able to accelerate and continue to keep business continuity moving forward. We've seen that in travel hospitality. We've seen that in financial services, retail. A lot of verticals out there are struggling with accelerating that road map.

Yes. And Jim, the question is very simple as it is. So when you really see the COVID changes and priorities, where are you seeing investments within your customers?

Yes, I would say a similar theme. No one was quite prepared for this shift to shelter-in-place. And the first noticeable impact was customer shifting budget from previously approved items into how do we get a remote workforce setup. And most companies had anticipated anywhere from 20% to 30% of their employees being remote. In one fell swoop, that became 100%. So there's a fair amount of investment in remote workforce solutions, virtual desktops, et cetera. The second impact was more of a lagging effect, and that was as shelter-in-place put pressure on top line, it exacerbated some of the profitability challenges that a lot of customers were increasingly struggling with. Less top line means you have expenses that are running potentially outpacing sales, and so that acute pressure is causing people to do things to accelerate digital transformation, consolidation, et cetera. So that was the second primary takeaway, is a renewed interest in any type of investments that can help improve operational efficiency. The third trend that has emerged, and think about the first comment I made, as people moved and accelerated capital budgets towards remote workforce, it drained the swamp per se. And with less money to invest in the projects that were scheduled, a lot of customers are now asking us for consumption models that allows them to bring on the infrastructure to support a project without having the capital outlay. So those are 3 noticeable impacts to our customers as a result of shelter-in-place.

Yes, absolutely, because the world is really shifting today. And Michael, when we talk about the cost of the businesses and the downtime and those bad experiences, they go viral. And so can you really talk about the business value and hopefully avoiding some of those digital experiences in the downtime and potentially how we can even measure this?

Absolutely. I definitely agree with Patrick and jim that what COVID and the pandemic did was really accelerate and accentuate transitions that were at times already in process, but they became business-critical and business-vital that companies could make that transition. I think Patrick talked a lot about how the interaction with our customers became digital, and Jim kind of highlighted that the interaction with each other at the business became digital. So the whole company had to kind of shift to interacting with their customer really 100% digitally, maybe 90% digitally where they used to maintain multiple channels of interaction. And then if something -- as far as running real-time operations at the company, you weren't tapping your neighbor on the shoulder over a cubicle, right? You're having digital interactions with your coworkers to solve problems. That acceleration also and kind of the rush to provide really innovative experiences to those customers and move those workloads into the cloud, it causes a lot of change, and contemporary applications are rapidly changing and made up of really complex stacks these days. What we observed on our platform during that time was literally a 40% increase in the number of incidents, right? We have 500,000 users, 13,000 customers on our cloud platform. So we can watch these trends and take away a lot in terms of what's happening across the globe and also how that's impacting customer experience and costing businesses. So we had this 38% increase. There was a ton more noise being generated. Jim talked about this, the exact same staff. Nobody was getting injected with a whole bunch of money to solve these problems or make this transition. So the same people had to solve a lot more challenging problem in 2 places with a lot more noise. For us, we really felt this was a place to leverage machine learning in a big way to cut through that noise to make sure that human beings get involved when it's critical they get involved, but that they're not getting inadvertently disturbed or interrupted from their work because there's just noise occurring. So I think that's the first thing. From a cost perspective, I think what used to cost a company $100,000 a minute in terms of a downtime impact to their business, because of the shift of how much of the business is flowing through that channel now, you're looking at about a 5x, 10x increase in the impact on the business when that service goes down. So it's harder to do your job. It's much more important that you get your job done in these new ways with -- to interact with your customers and keep your business relevant. And then when something goes wrong, you're really hurting your company. And as you're trying to change a business and change a technical approach, and you mentioned DevOps, change a human development and human delivery process, it really becomes kind of a perfect storm. And so one of the things we did very quickly is we moved our technology to be able to be delivered into these digital interaction places, chat ops locations. Wherever the enterprise was doing the work, we had to get our information and get the control of these services into their hands because having multiple interfaces up is just not going to work. And we, as I mentioned, stepped up our machine learning and our data science algorithms to drive that noise down, and we actually -- we achieved a 65% reduction in that noise. So the noise went up 40%, and our cloud platform was able to basically cut through that using machine learning and return 65% of a benefit. When things go wrong, humans may need to be involved, and I think we potentially can touch on this later. But when possible, that new noise, you should try to automate as much of it as possible so that, that limited staff you have is fully leveraged.

Yes, it's a good point. And Vish, when we talk about the end-to-end experience, when we're talking about going from core to edge and the whole stack, I think your company -- you mentioned it in the opening, one of the questions I have for you was what of those lessons learned when we're talking about the end-to-end approach, especially as it relates to digital transformation and the changes in COVID.

So I think, as I mentioned, the first thing is we've been doing digital for a long time, right, almost in our entire existence of 30 years, right from the start of when the Internet boom started, we've been doing a lot of these things. So for us, I think that creating the customer experience part of it was just native to how we did our business. I think that there's 2 key things that I will say that we've started seeing a shift in trend, right? One is I would call agility, right? CX, customer experience, whether you call it service or just the ability for our consumers to interact on the digital properties, is almost table stakes at this point, right? Like if you don't have a good customer experience, you don't have a good fast performing site, nobody is going to be there. And that trend was there even before COVID hit, right? But I think that the biggest thing that businesses are starting to realize is the need for agility, more and more -- becoming more and more important. And I think in a lot of the cases, what happens is some of the backstage or what happens outside of the marketing platforms that actually inform and drive that, they're not as nimble as they need to be. So we're seeing a huge shift in modernizing, making them more efficient from an agility perspective to actually be able to serve and work at the speed of what the consumers actually expect from businesses. So that's a big shift that we're seeing. And I think going hand-in-hand with that is what used to be traditional IT infrastructure projects or where we say, "Oh, you know what, this is not as important an application for now, right, because it didn't serve a customer need. We'll think about the migration to cloud down the line or deprioritize it. It's looked as an IT investment." I think that more and more, because all of these things are now intertwined, right, in driving the customer experience, those are starting to get priority. And I think Jim kind of mentioned that there's a shift of what was approved projects to what was not approved projects, how do you actually make that prioritization, I think there's a lot of upheaval in how you think about and prioritize that to drive those customer experience. So those are the key things that we're seeing as a trend. And like I said, I think the steel thread in all of this is that consumer experiences are not driven by just the -- by everything. They have to be driven by everything within the organization, right, everything that happens within the 4 walls and the things that happen outside those 4 walls.

Absolutely. I mean if you were able to listen to the keynote that we had, it really was the differences between digitally-driven organizations and their ability to accelerate the plans that they had in place for digital transformation, along with things like shift to digital delivery of the customer experience, information security practices, the ability to automate business processes and also cloud-native technologies, have really accelerated that or been newly introduced. I compared to the research we have is once that were delayed, there was 2 to 4x less likely to even have any of this in play. And so as we shift and talk about what it really takes, a lot of it is also being data-driven. We heard you earlier. You mentioned all about the analytics and the data-driven, but let's just take a deeper dive in that because when I look at my data, and I think digitally-driven organizations having a data-driven strategy, there's a 2x difference between ones that are digitally delayed. Again, we have a persona and anyone can react to me and I can go over this. But 50% that have formal strategies to be more data-driven are usually more advanced. They're setting themselves up for success, and it's why it's so important in data-driven experience economy. So I really want to talk about this. And one of the things has to do with the data and the shift to unstructured data. And Jim, it's really important. I've been talking about the world of unstructured data. But how are we dealing with this? What are the key drivers that Pure Storage is seeing? Because it's so massive. I mean we're really trying to harness the power of this data, and a lot of businesses are struggling.

Yes. I mean you're spot on. There is a tectonic shift, to say the least, taking place between block and traditional structured data into unstructured. And in fact, the bulk of the data today that's being generated is unstructured. So whether it's e-mail, text files, video files, social media or the applications running today to support machine learning, AI, that's resulting in a massive acceleration of unstructured data. One of the analysts is predicting that in the next 5 years, we will create roughly 130 zettabytes of data globally, 130 zettabytes. I don't know how many zeros that is. It's massive. Now interestingly, 80% of that will be unstructured. And another interesting anecdote is that 30% of that data will be used in real time. So that has a couple of implications for customers as well as service providers that are supporting those customers. On the one hand, you need to figure out how am I going to store these massive troves of data. And on the other hand, how do I create a scalable platform that will provide ultra-fast performance and availability to support the need for real-time processing of the data? And most customers today are struggling because they do have legacy environments. But as compute gets faster and as the algorithms get more sophisticated, the choke point can become the storage platform. Now let me give you an example. We have a customer in Berkeley, California, Bright Labs. Some people may know them because they were the home to Apache Spark, but they have these genomic analytic runs. Now before we met with them, it was taking them 4 days to complete a genomic analytic run. And they had a 64 node Apache Spark cluster with 2,400 cores, hundreds of local disks. So this was a massive compute -- parallel compute environment, but it was taking them 4 days to complete a run. They were able to take advantage of our block our FlashBlade technology, which is an ultrafast scale-out object storage platform, and they reduced the genomic run from 4 days to 2 hours. So they saw a 48x improvement in the run. And most importantly, the data scientists were able to make faster decisions. And as most people know who have invested in the data science team, these are high-priced individuals on the market, and you don't want them sitting idle. So that's one of the big drivers that we're seeing in the growth of unstructured data, the need to make sure that you have a next-generation platform, think compute network storage to combine with the algorithms, to support the real-time need of processing the data and the ability to store it.

Yes. I absolutely agree. And Patrick, when we talk about that customer experience market and Adobe and the digital experience and embracing those customer data platforms, a lot of it that the industry is moving forward to is about combining the structured and unstructured data to improve the customer experience and digital delivery. And I know you have a lot of experience trying to bring it all together. What are customers trying to do there?

Well, they're trying to bring together structured and unstructured, but I think it's what's relevant, what's relevant to a profile inside of a CDP then how do you activate that profile in a more real-time fashion, and so that's really how it's starting to come together. Part of that is the ability to resolve identity in the context of a CDP. That's where you start to see the power of: how am I delivering the right message? How am I delivering it at the right time. And is the content that I'm pulling in order to deliver to my customers, is it relevant? So all of those pieces of data, so all the clicks and the videos and the interactions and the -- it all builds upon itself in that context of a profile. And that's really what we're seeing a lot of our customers do, is to identify what that is. But if you think of the context of transformation, you have people, process, technology and data, data is the only one piece of it, right? So -- and technology is only one piece of it. So if you're not supplying the processes and the people to be able to deliver on it, you're only getting really halfway there. And so technology and data is only partway there, and the ability to market against and having an understanding of why the data is relevant in a marketing context becomes critically important.

Yes, absolutely. And some of the research I'm coming out with this year really is about putting a little bit more clarity of what we really need on these customer data platforms and how they're really evolving into what I call customer intelligence platforms. And actually, one of the questions we had earlier that I just got had to do with industries and digital transformation. And Vish, one of the questions we actually wanted to ask you was, what's going on with the industries? And where are you seeing some of this change as it relates to these data-driven experiences and really leveraging different capabilities there?

Yes. And I think that you actually hit the nail on the head, right? I mean it's not just about customer information platforms. It's about customer intelligence platforms, right? I think data is not equal to information, and information is not equal to intelligence. And just the amount of data that is being created, they -- you have to bring out the nuggets out of that data to actually engage from a customer perspective. Now as far as industries go, I think that everyone's been making a huge shift towards this, but I think that there is pockets in every industry where they're doing well. But I think that generally, most of the industry still haven't tapped the entire potential of where they can go with some of these data-driven experiences. I think travel and hospitality, as an example, has done a really good job. Retail, although I think that a lot of the data and the experience is skewed by the likes of Amazon and the big players and what they're doing from an innovation perspective, so I think retail generally seems to have a higher level of data intelligence inherent in the industry. But I also think that some of the other industries such as CPG, they all have a lot of potential to grow, right? And even financial services, it would be interesting because they're really good at the servicing of customers. But how much of it is experience-driven and engaging from a customer perspective, there's actually a lot of room for them to take advantage of that. So I think that -- and as we go through this COVID and whatever comes on the other side of this, the engagement is going to get even more fractured from a customer perspective. And like you said, it needs to move from data to information to intelligence very, very quickly if you are to capture the customers and their attention going forward.

Yes. And it really does take all different types of data. And you're right, I mean, even B2B organizations, I'm seeing invest in this. They need different types of data as it relates to retail, and financial services has a long way to go, even though they were pretty early adopters of technologies right from the beginning. And Michael, what kinds of data are really required to ensure these digital experiences can go uninterrupted? So what are we doing to make sure we're using the data and optimizing those experiences?

Sure. I think it's really interesting. Each one of our panelists brought up a point that kind of resonated with me. I think that Patrick and Vishnu, you're talking about doing this to engage customers and give customers more delight and more innovative experiences. Our world is about collecting that data and ensuring that operations teams and DevOp teams and customer service teams have that same type of insight surface to them from massive amounts of data so that those services and those engaging sites and applications never go down, right? So for us, it's about collecting as much data as possible from as many places as possible because for us, it's about correlating to identify and predict when something may be toppling or a customer's experience may be degrading. And then I think I really liked what Patrick said about it being a different -- it's not just a technology problem, right? So we need data from the very difficult technology stack. We have to understand data from the changes because as I mentioned earlier, you've got a ton of changes happening on these applications, and applications made of microservices have such dynamic states that we have to keep track of. So you need a lot of data from technology and from that stack, but you really also have to understand the human beings and who's the right people to contact, how to contact them, how their dependencies are and in order to solve these problems really rapid if they do pop up. So massive amounts of data. And then I really like what Jim said, which is you can't just have all this data and have these insights, you actually need to be able to inject it in real time. And Patrick and Vishnu are about that injecting it in for a customer experience. We're about making sure that in real time, an operations team or a DevOps team member gets the information they need in time to solve the problem or in time to actually solve the -- remove the problem before it occurs. So I think that's a really big deal. It's about pulling all that together and then building a real-time process for a company so that they're able to actually get predictive. I mentioned this a little bit earlier, but I think it's relevant here, which is then there's this powerful capability around understanding human processes and repetitive human processes and automating them where possible. And so we use data also to identify incidents or issues that are potentially automatable. And we can suggest to a company, "Hey, if you start automating this, by the time a human being is interrupted, you may have already solved the problem." And so we're trying to move from hours of engagement and orchestration and response and resolution and drive that down to seconds or minutes or potentially do it before anyone is impacted or any human being is needed. But you can't do that with just automation alone and data alone. You really have to create this virtuous cycle with your operations teams and with your DevOps teams so that they're involved and that you're doing it responsibly. And then ultimately, your end user is the one that benefits. So one of the nice things about this automation thing, again, just to connect it to our world here today, you can give that type of control out to a customer service rep. So when -- first of all, when something is happening on the application or on the service, a customer service team can be proactively notified and potentially proactively contact specific user groups or VIP users, for example. And then if an issue is occurring, we really believe in letting the customer service team also have control and act as what we call an incident commander or a case commander so that they can also fire off some of this automation to try and solve problems themselves or even escalate a problem, right? Like the people that know what's hurting the business most is the customer service team that's connected with our, ultimately, most important users, right? So that's kind of how our world at PagerDuty is about data and pulling it together. I think it is a combination of what we all heard, but our goal is delivering that to real-time operations teams supporting digital businesses.

Absolutely. And we are here at a cloud conference about cloud transformation, and the whole data side of it is absolutely essential. But as we shift to the cloud, one of the things I also had said in the earlier keynote had to be around the cloud as an important digital maturity enabler. So we do have a maturity model that talks about being able to shift from mostly on-premise infrastructure all the way through this multi-cloud scalable way of working. And we see differences between digitally driven and digitally delayed. So a lot of digitally-driven organizations are much more advanced using more cloud applications and allowing more of that multi-cloud initiative as compared to digitally delayed that are mostly on the on-premise side of it. And so Jim, when we talk about cloud and the data, and can we put it in context? What are some good strategies to unlock data mobility and understand how we're going to shift from this current on-premise into this hybrid cloud environment? How can you just do it? Because a lot of times, we're concerned about security. So what's holding a lot of some of these more conservative businesses back?

Yes. I mean you're spot on. It's a great question. It's a dilemma that's challenging a lot of customers. If we think about the audience, it's a mix of both commercial and enterprise customers, who, in all likelihood, are running packaged applications on-premises that are built on silos and support projects. And then the other hand, you have the public cloud providers that are running web scale applications that typically leverage pads. In a perfect world, people have the ability to leverage multiple cloud environments, whether it's on-premises, private cloud or a hyperscaler or service provider. And so that creates a number of challenges, both in terms of the architecture of the applications, how those applications are managed and then also how they're consumed. So we see a couple of best practices emerging from our customers to help support their journey towards a multi-cloud strategy, first of which is containers and microservices. Customers are now moving beyond the pilot phase, and they're looking to scale containers because it does enable the apps and the data to be portable between an on-premise environment and a cloud service provider. The second trend that we tend to see emerging has to do with API-first architectures. It's a lot easier to design to manage an application to support an on-premises or a public cloud platform if it's an API-first environment or an architecture that you're designing around. And then finally, because we're talking about mobility, people have to beef up their networks. And so we're seeing a lot of investments in the network stack to ensure that it's capable of handling the movement of data between data center locations that are typically geographically dispersed. And then as you appropriately mentioned, you solve one problem, right, by taking advantage of cloud, but you tend to introduce another. In the minute everyone moved into a remote workforce world, that created an increased need to secure data that was now running outside of the 4 walls of the data center. Likewise, as people move from an on-premises to a multi-cloud world, there's also new concerns raised about security. So what we tend to see from our customers today are a few things. First of all, the data has got to be encrypted, whether it's at rest or it's in transmission to a cloud provider. Now the second is identity and access management controls. Being able to not only establish identity and access management but automate it is becoming a critical imperative for organizations that want to be able to scale cost effectively. The other thing that we tend to see are cryptographic protocols and the importance of making sure whether it's SSL or TSL, you've got to have a secure transmission of the data over the network. And then the last thing that we tend to see is SSH network protocols for data communication between unsecured locations. So those tend to be top of mind for most of the customers that we're talking to that are looking to enable a hybrid cloud environment.

Yes. It's a very complicated move. And it really is why this conference is so approachable for companies because they really are trying to understand how are they going to take this shift. And so Michael, when shifting to the cloud, can you really continue to operate as you did from a premises base? What are you seeing around operating differently in the cloud? And if it is, how are we going to make the change?

Sure. Great question. Patrick pointed this out at the beginning, but this is not a brand-new technology or methodology for delivering computing, right? The truth is, it's kind of hard to move to a cloud architecture and model, and there's headwinds as you try to transfer into that model. And we've touched on a bit of why that happens. And Jim mentioned microservice architecture. So now your application is built up of tens and hundreds of microservices. What those microservices are, are a by-product of the innovation that occurs in an agile organization with distributed development teams. So DevOps is about enabling these teams to roll new innovation out into their application very quickly and very -- without dependence against each other. So that's where this change rate picks up. So in a cloud environment, it's -- the state of your application is always changing, and who's responsible for each component of that stack is really tough to figure out. We believe that the answer here is something that can span both legacy and your future cloud and hybrid cloud, to Jim's point, world, which is something called service ownership. And our solution, our cloud platform is built around a service orientation approach. What that is, is we identify the business-critical service. Then there's all the complexity behind that: the individuals that build it, the changes that have occurred recently to it, the microservices that it's made up of, where those are hosted, how the network and the infrastructure that supports it is delivering. But all of that complexity has to be massively simplified very, very quickly. And so we believe the answer is through service ownership. And I mentioned these distributed teams. You have to be able to be rapidly deployed and implemented. You have to be self-service because these teams are very iterative and working very quickly and independently, as I mentioned. And then you have the central requirements of an enterprise that -- you mentioned security, Jim. You need to have control over this. It has to be secure. It has to be compliant. It has to be scalable. And those things are really tough to achieve when you have such a distributed innovation cycle happening at the organization. So for us, we take a service ownership approach, and then we can use machine learning to, again, go through all those data sets and understand the human beings, very rapidly connect those components that are dependent. And whether it's in the cloud or not, we can kind of homogenize that view of your business services. And again, whether you're a CEO or a DevOps team or a central IT team or a customer service representative, you really want to see a single source of real-time truth, right? When something is going wrong, it really doesn't matter if it's in the cloud or in the data center. If a customer is impacted, then your business is impacted, and it's a critical priority for you to solve the problem. So we take an approach that focuses in on critical business services, and then the platform that we built handles all that complexity for you so that you're really managing your business as opposed to managing 2 infrastructures, if you will.

Yes, absolutely. And it really is all about managing that business because we're here to improve the overall customer experience. And I don't know if people know this, but Patrick, Adobe actually was one of the early companies that really did navigate that transition to the cloud, not only with your own products, but your company as a whole. And so you're also very close to delivering on those digital experience with all the different solutions that you're bringing there. So how does cloud help the businesses that you work with really embrace that change that needed to happen?

Yes. It's a good question. I mean I think the overarching thing that I'm seeing in accounts or in some of these customers is what do I need. What do we need today? And then how can I accelerate time to market or speed to market based on the innovations that they're trying to create around customer experience. And so whether it's deploying a new app, whether it's deploying a new website, whether it's deploying microsize, whatever it might be from however they're collecting their data and then moving that back into a CDC to then run the cycle again. I think the big thing for Adobe has been one of the things that we've done with our experience platform, which is our version of a CDP is the ability to have it be open and extensible, API-driven. It's almost like bring your own stuff. And so whether it means data, whether it means algorithms, whether it means -- whatever it is that you need in order to stitch together a profile, that allows you to market better. And I think from a cloud perspective, we wouldn't be able to do that as a on-prem example. So I think the customers themselves are requiring organizations to move to a cloud. And I think if you look at financial, they're trying to figure out what data do I need in that cloud environment, what data do I not need in that cloud environment. And that's really where I think the organizations, whether it be financial services or retail or any other vertical, is really trying to pinpoint what type of cloud environment do I need versus what's a nice effect. And I think we're seeing that across the board in most of most of these effects across a lot of the verticals.

Yes. Absolutely. Great work. And we're coming to a close. So Vish, you get the last question. And I'm going to kind of talk about it from an end-to-end approach. So in my opinion, as you know, it really is about pulling it all together. It can't just be about that pretty digital experience later. It's not just to have data for data's sake. It really is about that end-to-end future that everyone's trying to see. And so using cloud and data and digital transformation, where do you see the future laying as you work with a lot of your companies?

So I think that there's 2 interesting things. And most of the panelists have called out elements of it, right? I think that cloud is not a new thing. We've been on this journey for at least half of the decade, right? I think that there's a huge shift in understanding that it's not just about taking an application and putting it into one of the many clouds that exist today. There's got to be a strategy that you need to think about around how you're affecting the business as a whole, right? And the customers play a huge part of the business, right? So it's about -- in my opinion, it's at least about 3 things, right? What is the priority of the kinds of applications and data that you need to move to the cloud? Similar to what Patrick said. Then the second part is once you've made that rationalization, how do you actually restructure that to move it into a cloud? There's no point in just taking a monolithic application and putting it back on the cloud because it's going to be just as inefficient, right? So you need the right technologies, IT modernization strategy to actually be able to move that into the cloud. And the third part of it is that even the clouds as they're maturing, MI and -- ML and AI, and those things become quite ubiquitous in the cloud and increasing the computing, how do you actually take advantage of that so that you're not manually processing zettabytes of data, as Jim called it. I have to figure out how zettabyte -- what it is to start with. But how do you actually efficiently process that? So I think that you actually need somebody to lead you through those kinds of strategies to be able to be efficient when you move to the cloud, right?

Yes. Absolutely. I think we've had a fabulous discussion. I want to thank the panelists and the sponsors and all my collaborators here through the session. We have other sessions coming up today. I've got my colleague, Jordan, going further on commerce. And then we have another session on doubling down specifically on the data, and I'm going to talk specifically also around customer intelligence platforms as the next-generation CDP there. So at this point, I want to thank the participants for coming. Continue to show up later today and really look forward to hearing from you throughout the year and into 2021. So thank you very much.

You're welcome, Sheryl.

Thank you.

Thank you.

Thank you.