>> Live from Las Vegas, it's theCUBE covering AWS re:Invent 2018. Brought to you by Amazon Web Services, Intel, and their ecosystem partners. >> Well, good afternoon, or good evening, if you're watching us back on the East Coast right now. We are live here at AWS re:Invent in Las Vegas along with Justin Warren, I'm John Walls. We're now joined by Anthony Brooks-Williams, who's the CEO of HVR. >> Thanks for having me here today. >> Thanks for being here with us today, and Paul Specketer, who's the Enterprise Data Architect at SUEZ. Paul, good afternoon to you. >> Good afternoon. >> All right so let's just first off, tell us a little bit about your respective companies and why you're here together, and why you're here at the show? Anthony if you will. >> Sure absolutely. So at HVR, we provide the most efficient way for companies to move their data, in particular to the cloud and at scale, and that they have the peace of mind that when they move their data that it's accurate, and we give them insights on the data that we move. So we do that for companies such as SUEZ, enable them to get their data into S3, into Redshift, and so they can make decisions on the freshest data. >> All right, go on Paul. >> So yeah, we're formally GE, and SUEZ acquired our company. So now we're standing up an entire data platform, all the applications are coming over to AWS. So in the past year, we've had to stand up for Redshift cluster, the full ETL backbone behind that, and including the replication from our ERP system into that environment. So we're going live with that in the next coming months. So that's why we're here. We use HVR to move our data around before the ETL process. >> Anthony, you mentioned that if customers want to make decisions on the latest, the freshest data. >> Yeah. >> So what are the kinds of analysis, and what are the kinds of the decisions that customers are trying to make here? >> Sure, obviously it depends on the customer themselves. >> Clearly yeah. >> If it's a big e-commerce vendor, someone like that or where are certain products selling at a certain region based on a certain weather pattern or something like that. Our ability to capture that at a store level, and moving that back so they know how to fulfill the warehouses or what stock is out there, that enables them to run a more profitable business. Whether it be someone like that or Paul's previous company, someone like GE from an aviation perspective to transportation. It's what's happening in the environment in the systems. So giving them the ability to move that data, move it at volume, and just make good business decisions. Even the main use case for us is consolidated reporting. Consolidated reporting along some of those financials as well. So the exact level, board level are making decisions on their business with the freshest numbers that are sitting in front of them at that time. >> Paul, what are some of the key ways that HVR will be able to help you in designing that system that can support the needs of those customers? What are some of the key things where you've got there is when actually we really the help of someone like HVR to help us to do that. >> Long ago, we had database triggers, and we had some programs that we had to write to capture changes. That all goes away when you do log based data replication. So for us, we changed that whole strategy and we said, you know what, just take everything from the ERP. Move it up into the cloud. Then from there, move it where you need to, process the ETL, and shift it around. So for us, it's just the first goal is take everything as is, get it up into the cloud as the replicated data set. Then from there, we do our ETL processing. We watch that, or we view that in Tableau. So for us, what I'm building allows us to close our books in one to two days. As when we were in GE, we're driving towards a one-day close. Now that we're in SUEZ, we're doing a hard close every month. So we're trying to drive that time down as low as possible. You've got people sitting around waiting for the report to look right. So the more we can do to drive that time down, the more people get their weekends back. >> Right, right, yeah. >> People like weekends. >> Yeah all right, so you talked about accuracy. >> Yep >> You talked about volume. >> Yep. >> All right, so obviously you got a lot more data coming through. >> Yeah. >> The need to keep it a mart. What about speed and latency? I mean how of a concern is that for you? Because you got this bigger funnel that you need all the time. >> Absolutely, and especially in today's world of the cloud, and moving data across wide area networks. So that's whereby the technique that we use, the CDC, the change data capture, where you're reading those transaction logs. You're only capturing the changes, and moving those across the network. Then our technology, we have some proprietary techniques we do around compression that further magnifies that bandwidth. So you're magnifying the bandwidth. You're able to move a large volume of data more efficiently, and the latency certainly comes in to them as well. So built into the product, we have a feature around the data accuracy perspective. So that no matter what the source or target system is, they know their data is absolutely accurate. And then tied to that is a product that we released recently is around insights. That's telling them the statistics on the data that we're moving. We've gathered that and now we now showing that published into the customers, largely because customers like Paul, that were doing this themselves, we provided the statistics on the data, and they were having a front-end on top of that. We've not taken that to the broader market. So that's showing them exactly things like latency. So they'll be able to drill in, and go that graph or that line is red or it's thicker, and it's telling them the latency. We should probably do something about that. What's the bottleneck there? So it's all coming together now. Particularly in this cloudy world of moving this data. >> So Paul, can you give us an example then of what Anthony has just talked about? How in real life, of how this happened for you that with that kind of reporting, that you saw whatever hiccup there was in the system if you will, that it identified that and solved that problem for you. >> As far as the short cycle close, I had a hard time hearing you actually. >> Yeah, from the statistics, I was talking about when we were moving the data, and how you were collecting stats on that data that moved already, that's enabled you, particularly from a latency perspective of the volume you can move. If there's an issue with it, what do you do with that. >> So one of the challenges we always have was when you go through a long cycle replication, and you've been doing it for months, and I ask you the question. Are you sure you got every change? Do you know? So that's we never know but now with increases in the Redshift cluster performance, with the DC2 clusters, increases in the performance of Redshift or of HVR in moving that data in, our strategy now is to not doubt the data ever. We just refresh it every month, right before it close. We refresh the data. It takes us like four hours to move two terabytes into Redshift. So why not? That changes your approach when you don't have to stress out about the data being accurate, week in, week out. Every quarter right before it closes, you're getting a fresh copy. So that really changed my life. It's being able to know going into close, before the finance guys look at it, that the data is perfect. >> So now that you've had that issue or that concern taken away, and you don't have to worry about it anymore, has that open up new possibilities in like I can now attempt to do these things, which I would have loved to, like I thought about it, but like I don't have time. We have these other constraints. So with those constraints gone, what are you now able to do? >> What we're going to look at now is instead of doing ETL inside of the Redshift cluster, we're going to take that out. Because we actually do about three quarter of the space in our cluster is used for ETL. So we're going to carve that out, maybe do it in S3, we're not sure. As soon as we do that, we'll be down to like a four-node Redshift cluster. That'll save a lot of money. So that for us-- >> Big savings. >> Yeah. >> Now that we're in the cloud, the next push is how do we optimize it? How do we take advantages of cloud native services that we never had access to before? >> Right. >> Yeah. >> So that's what's on my horizon. It's looking at that and saying what can I do in the next year? >> All right, we're seeing massive growth in data across. We've had many conversations so far today about data being generated from IoT devices at the edge. We're having to process it in more places because we're just physically moving this data around. It's such a huge problem. It's why you exist. >> Yep. >> So what do you see customers deal? When they're trying to deal with this issue, this data is not going to get smaller. There's going to be more and more of this data. So how are you helping customers to grapple with this issue about well, where should we move the data? Should we move all of it into the cloud? Is that the only direction that it should be moved? Or you're able to help them say, you know what we want to move some of it to here. We'll place some other data over there. We can help you move it around no matter where it needs to go. >> Certainly, so we're obviously agnostic to where they want to move their data. Well, given the years of experience that we have, and the people we have in the company, we certainly are able to lend that seasoned advice to them of where we think an efficient place will be to move that data. Certainly within the technology of HVR, it's very efficient at capturing data once, and then sending it to many. >> Right. >> That's how we really set ourselves apart from a complexity of we're being modular and flexible of capturing that data, feed on the cusp where they need to. We can send to capture one, send to multiple target systems. So they could go and say, I'm going to put the bulk of this feed into S3. I'm going to take a bit of that, and put it into Redshift. So it gives them that flexibility to do that. So obviously with us, some of our skilled architects that we have in the field, are able to make them, not just go and sell a product, actually help them with a solution. We're out there selling software but we're making sure that we're delivering customers with a total solution. Because I think we look back on yesteryear, and some of the data lags, you know the stats from Gartner, 70% of those projects failed. It was just, I'm going to take it all and put it in there. Well why, how? I think it's planning those well together, and sort of the defacto data lag we've seen out today is seven out of 10 times in something like S3. So take the architecture, take the technology, take the people, and help them go execute on their plan, and just lend some of that advice along the process to them. >> That sounds like something that would add a lot of value. >> Yeah. >> You put it there because you could. >> Absolutely. >> That's why. >> Why, 'cause we can. >> It was a small improvement, it was a good place to put it. >> It fits. >> I might not look at it for a long time. >> It was cheap, and it was clear. >> Put it on top there, right. >> Absolutely. >> Gentlemen, thank you for being with us. We appreciate the time. >> Thank you for the time. >> Paul, we're really happy you have your weekends back. Thank goodness on that, excellent. >> Absolutely. >> Thank you. >> Back with more, here from AWS re:Invent, pardon me, from Las Vegas. We're live at the Sands. We'll wrap up in just a moment. (enlightening music)

>> Narrator: From around the globe, it's the CUBE with digital coverage of IBM Think 2021, brought to you by IBM. >> Welcome back to IBM Think 2021, the virtual edition. This is the CUBEs, continuous, deep dive coverage of the people, processes and technologies that are really changing our world. Right now, we're going to talk about modernization and what's beyond with Jamie Thomas, general manager, strategy and development, IBM Enterprise Security. Jamie, always a pleasure. Great to see you again. Thanks for coming on. >> It's great to see you, Dave. And thanks for having me on the CUBE is always a pleasure. >> Yeah, it is our pleasure. And listen, we've been hearing a lot about IBM is focused on hybrid cloud, Arvind Krishna says we must win the architectural battle for hybrid cloud. I love that. We've been hearing a lot about AI. And I wonder if you could talk about IBM Systems and how it plays into that strategy? >> Sure, well, it's a great time to have this discussion Dave. As you all know, IBM Systems Technology is used widely around the world, by many, many 1000s of clients in the context of our IBM System Z, our power systems and storage. And what we have seen is really an uptake of monetization around those workloads, if you will, driven by hybrid cloud, the hybrid cloud agenda, as well as an uptake of Red Hat OpenShift, as a vehicle for this modernization. So it's pretty exciting stuff, what we see as many clients taking advantage of OpenShift on Linux, to really modernize these environments, and then stay close, if you will, to that systems of record database and the transactions associated with it. So they're seeing a definite performance advantage to taking advantage of OpenShift. And it's really fascinating to see the things that they're doing. So if you look at financial services, for instance, there's a lot of focus on risk analytics. So things like fraud, anti money laundering, mortgage risk, types of applications being done in this context, when you look at our retail industry clients, you see also a lot of customer centricity solutions, if you will, being deployed on OpenShift. And once again, having Linux close to those traditional LPARs of AIX, I-Series, or in the context of z/OS. So those are some of the things we see happening. And it's quite real. >> Now, you didn't mention power, but I want to come back and ask you about power. Because a few weeks ago, we were prompted to dig in a little bit with the when Arvind was on with Pat Kessinger at Intel and talking about the relationship you guys have. And so we dug in a little bit, we thought originally, we said, oh, it's about quantum. But we dug in. And we realized that the POWER10 is actually the best out there and the highest performance in terms of disaggregating memory. And we see that as a future architecture for systems and actually really quite excited about it about the potential that brings not only to build beyond system on a chip and system on a package, but to start doing interesting things at the Edge. You know, what do you what's going on with power? >> Well, of course, when I talked about OpenShift, we're doing OpenShift on power Linux, as well as Z Linux, but you're exactly right in the context for a POWER10 processor. We couldn't be more we're so excited about this processor. First of all, it's our first delivery with our partner Samsung with a seven nanometer form factor. The processor itself has only 18 billion transistors. So it's got a few transistors there. But one of the cool inventions, if you will, that we have created is this expansive memory region as part of this design point, which we call memory inception, it gives us the ability to reach memory across servers, up to two petabytes of memory. Aside from that, this processor has generational improvements and core and thread performance, improved energy efficiency. And all of this, Dave is going to give us a lot of opportunity with new workloads, particularly around artificial intelligence and inferencing around artificial intelligence. I mean, that's going to be that's another critical innovation that we see here in this POWER10 processor. >> Yeah, processor performance is just exploding. We're blowing away the historical norms. I think many people don't realize that. Let's talk about some of the key announcements that you've made in quantum last time we spoke on the qubit for last year, I think we did a deeper dive on quantum. You've made some announcements around hardware and software roadmaps. Give us the update on quantum please. >> Well, there is so much that has happened since we last spoke on the quantum landscape. And the key thing that we focused on in the last six months is really an articulation of our roadmaps, so the roadmap around hardware, the roadmap around software, and we've also done quite a bit of ecosystem development. So in terms of the roadmap around hardware, we put ourselves out there we've said we were going to get to over 1000 qubit machine and in 2023, so that's our milestone. And we've got a number of steps we've outlined along that way, of course, we have to make progress, frankly, every six months in terms of innovating around the processor, the electronics and the fridge associated with these machines. So lots of exciting innovation across the board. We've also published a software roadmap, where we're articulating how we improve a circuit execution speeds. So we hope, our plan to show shortly a 100 times improvement in circuit execution speeds. And as we go forward in the future, we're modifying our Qiskit programming model to not only allow a easily easy use by all types of developers, but to improve the fidelity of the entire machine, if you will. So all of our innovations go hand in hand, our hardware roadmap, our software roadmap, are all very critical in driving the technical outcomes that we think are so important for quantum to become a reality. We've deployed, I would say, in our quantum cloud over, you know, over 20 machines over time, we never quite identify the precise number because frankly, as we put up a new generation machine, we often retire when it's older. So we're constantly updating them out there, and every machine that comes on online, and that cloud, in fact, represents a sea change and hardware and a sea change in software. So they're all the latest and greatest that our clients can have access to. >> That's key, the developer angle you got redshift running on quantum yet? >> Okay, I mean, that's a really good question, you know, as part of that software roadmap in terms of the evolution and the speed of that circuit execution is really this interesting marriage between classical processing and quantum processing and bring those closer together. And in the context of our classical operations that are interfacing with that quantum processor, we're taking advantage of OpenShift, running on that classical machine to achieve that. And once again, if, as you can imagine, that'll give us a lot of flexibility in terms of where that classical machine resides and how we continue the evolution the great marriage, I think that's going to that will exist that does exist and will exist between classical computing and quantum computing. >> I'm glad I asked it was kind of tongue in cheek. But that's a key thread to the ecosystem, which is critical to obviously, you know, such a new technology. How are you thinking about the ecosystem evolution? >> Well, the ecosystem here for quantum is infinitely important. We started day one, on this journey with free access to our systems for that reason, because we wanted to create easy entry for anyone that really wanted to participate in this quantum journey. And I can tell you, it really fascinates everyone, from high school students, to college students, to those that are PhDs. But during this journey, we have reached over 300,000 unique users, we have now over 500,000 unique downloads of our Qiskit programming model. But to really achieve that is his back plane by this ongoing educational thrust that we have. So we've created an open source textbook, around Qiskit that allows organizations around the world to take advantage of it from a curriculum perspective. We have over 200 organizations that are using our open source textbook. Last year, when we realized we couldn't do our in person programming camps, which were so exciting around the world, you can imagine doing an in person programming camp and South Africa and Asia and all those things we did in 2019. Well, we had just like you all, we had to go completely virtual, right. And we thought that we would have a few 100 people sign up for our summer school, we had over 4000 people sign up for our summer school. And so one of the things we had to do is really pedal fast to be able to support that many students in this summer school that kind of grew out of our proportions. The neat thing was once again, seeing all the kids and students around the world taking advantage of this and learning about quantum computing. And then I guess that the end of last year, Dave, to really top this off, we did something really fundamentally important. And we set up a quantum center for historically black colleges and universities, with Howard University being the anchor of this quantum center. And we're serving 23 HBCUs now, to be able to reach a new set of students, if you will, with STEM technologies, and most importantly, with quantum. And I find, you know, the neat thing about quantum is is very interdisciplinary. So we have quantum physicist, we have electrical engineers, we have engineers on the team, we have computer scientists, we have people with biology and chemistry and financial services backgrounds. So I'm pretty excited about the reach that we have with quantum into HBCUs and even beyond right I think we can do some we can have some phenomenal results and help a lot of people on this journey to quantum and you know, obviously help ourselves but help these students as well. >> What do you see in people do with quantum and maybe some of the use cases. I mean you mentioned there's sort of a connection to traditional workloads, but obviously some new territory what's exciting out there? >> Well, there's been a really a number of use cases that I think are top of mind right now. So one of the most interesting to me has been one that showed us a few months ago that we talked about in the press actually a few months ago, which is with Exxon Mobil. And they really started looking at logistics in the context of Maritime shipping, using quantum. And if you think of logistics, logistics are really, really complicated. Logistics in the face of a pandemic are even more complicated and logistics when things like the Suez Canal shuts down, are even more complicated. So think about, you know, when the Suez Canal shut down, it's kind of like the equivalent of several major airports around the world shutting down and then you have to reroute all the traffic, and that traffic and maritime shipping is has to be very precise, has to be planned the stops are plan, the routes are plan. And the interest that ExxonMobil has had in this journey is not just more effective logistics, but how do they get natural gas shipped around the world more effectively, because their goal is to bring energy to organizations into countries while reducing CO2 emissions. So they have a very grand vision that they're trying to accomplish. And this logistics operation is just one of many, then we can think of logistics, though being a being applicable to anyone that has a supply chain. So to other shipping organizations, not just Maritime shipping. And a lot of the optimization logic that we're learning from that set of work also applies to financial services. So if we look at optimization, around portfolio pricing, and everything, a lot of the similar characteristics will also go be applicable to the financial services industry. So that's one big example. And I guess our latest partnership that we announced with some fanfare, about two weeks ago, was with the Cleveland Clinic, and we're doing a special discovery acceleration activity with the Cleveland Clinic, which starts prominently with artificial intelligence, looking at chemistry and genomics, and improve speed around machine learning for all of the the critical healthcare operations that the Cleveland Clinic has embarked on but as part of that journey, they like many clients are evolving from artificial intelligence, and then learning how they can apply quantum as an accelerator in the future. And so they also indicated that they will buy the first commercial on premise quantum computer for their operations and place that in Ohio, in the the the years to come. So it's a pretty exciting relationship. These relationships show the power of the combination, once again, of classical computing, using that intelligently to solve very difficult problems. And then taking advantage of quantum for what it can uniquely do in a lot of these use cases. >> That's great description, because it is a strong connection to things that we do today. It's just going to do them better, but then it's going to open up a whole new set of opportunities. Everybody wants to know, when, you know, it's all over the place. Because some people say, oh, not for decades, other people say I think it's going to be sooner than you think. What are you guys saying about timeframe? >> We're certainly determined to make it sooner than later. Our roadmaps if you note go through 2023. And we think the 2023 is going to will be a pivotal year for us in terms of delivery around those roadmaps. But it's these kind of use cases and this intense working with these clients, 'cause when they work with us, they're giving us feedback on everything that we've done, how does this programming model really help me solve these problems? What do we need to do differently? In the case of Exxon Mobil, they've given us a lot of really great feedback on how we can better fine tune all elements of the system to improve that system. It's really allowed us to chart a course for how we think about the programming model in particular in the context of users. Just last week, in fact, we announced some new machine learning applications, which these applications are really to allow artificial intelligence users and programmers to get take advantage of quantum without being a quantum physicist or expert, right. So it's really an encapsulation of a composable elements so that they can start to use, using an interface allows them to access through PyTorch into the quantum computer, take advantage of some of the things we're doing around neural networks and things like that, once again, without having to be experts in quantum. So I think those are the kind of things we're learning how to do better, fundamentally through this co-creation and development with our quantum network. And our quantum network now is over 140 unique organizations and those are commercial, academic, national laboratories and startups that we're working with. >> The picture started become more clear, we're seeing emerging AI applications, a lot of work today in AI is in modeling. Over time, it's going to shift toward inference and real time and practical applications. Everybody talks about Moore's law being dead. Well, in fact, the yes, I guess, technically speaking, but the premise or the outcome of Moore's law is actually accelerating, we're seeing processor performance, quadrupling every two years now, when you include the GPU along with the CPU, the DSPs, the accelerators. And so that's going to take us through this decade, and then then quantum is going to power us, you know, well beyond who can even predict that. It's a very, very exciting time. Jamie, I always love talking to you. Thank you so much for coming back on the CUBE. >> Well, I appreciate the time. And I think you're exactly right, Dave, you know, we talked about POWER10, just for a few minutes there. But one of the things we've done in POWER10, as well as we've embedded AI into every core that processor, so you reduce that latency, we've got a 10 to 20 times improvement over the last generation in terms of artificial intelligence, you think about the evolution of a classical machine like that state of the art, and then combine that with quantum and what we can do in the future, I think is a really exciting time to be in computing. And I really appreciate your time today to have this dialogue with you. >> Yeah, it's always fun and it's of national importance as well. Jamie Thomas, thanks so much. This is Dave Vellante with the CUBE keep it right there our continuous coverage of IBM Think 2021 will be right back. (gentle music) (bright music)

>> From around the globe, it's theCUBE with digital coverage of IBM Think 2021, brought to you by IBM. >> Welcome to theCUBE's coverage of IBM Think 2021. I'm Lisa Martin. Terrance Wampler joins me next, General Manager at Workday Financial Management at Workday. Terrance, welcome to theCUBE. >> Well thank you for having me. It's great to be here, I appreciate it. >> Nice that we can still do these events virtually even though we were quite socially distance. So the last year has brought lots of changes, one of them being IBM Think and theCUBE being virtual, but I'm curious to get your perspectives and your observations. We've seen many finance organizations have to rapidly pivot and accelerate their digital transformation making it a priority. What are some of the key priorities that you've seen that the C-suite, the CFO are dealing with? >> Yeah, well, I think what's happening is what we've seen are new ways to work and using remote access, having to do mobile technologies. What's happening is that's actually driving more risk for companies. And so as companies get more risk that's driving the needs to have more scrutiny on those business processes and that's forcing them to want to accelerate what they're doing in terms of a digital transformation, other stuff like that. It's also forcing them to think more about the data they have and the information they have looking forward and how they're doing planning and how they can do planning in terms of bringing people back to work, in terms of new business models, in terms of what may be next, in terms of opportunity for them or even doing catastrophe planning as they work through this stuff. And as they start to look at that, they're really thinking about how to make their business profit and much more agile. And so it's kind of a complicated thread that you start to pull as people start to change how things work. >> Yeah, that risk is a big factor and that pivot was so quick for so many businesses where suddenly so many of us, and so many of us are still remote. I'm curious what some of the things are though that you're hearing with respect to organizations looking to start opening things back up and bringing some of their folks back on campus. >> Yeah, it's a very interesting dilemma because what's happening is people have learned how to work remotely now. And so they're trying to figure out how they're going to bring people back to be more collaborative. But at the end of the day the first and most important thing they've learned is that especially for a finance function, they no longer want to be transaction operators. What they want to start doing is pushing that work to more automated tools, to have that be done for them and try to promote themselves to be more like analysts or even advisors to the business or even a partner to the business. And as they go through that evolution what they're really trying to do is unlock all of the potential of the people they have, of the processes they have and of the data they have. So it has really made companies do, is look at everything in its entirety and want to change all of it, but they have to go at different paces. >> Definitely, talk to me about what Workday and IBM are doing together to help customers tackle these challenges, adjust their priorities and accelerate that transformation. >> Yeah, certainly. So one of the things that we've done is gotten together and created this go to market strategy called Enterprise Finance. And what enterprise finance does is it really tries to meet the customer wherever they are. So while all of these customers are looking to accelerate their digital transformation they come from very different places, right? And their journey to that transformation is going to be very different. And that means that some of them are going to want to be able to do a full transformation right away and do it globally and make a big change because they've just been hit very hard by this and they see it as an opportunity to grow. And others are going to come from a very complex environment and that complex environment could include complicated manufacturing components in their solution. And they need to look at something like just a corporate finance layer that has kind of an integrated planning solution and consolidation, close capabilities for them to be able to run their business and be a little bit more agile at the top line. >> So a spectrum of you said meeting them where they are. There's a lot of customers in different places. I'm curious what some of the things are that you've observed over the last year, that really are kind of unique ways that finance leaders are approaching this new way of working. >> Yeah, so there's probably two examples I can give you. One is a generic example where we have customers that have participated in merger or acquisition activity over the past year, as it happens to be or customers that have even spun up new divisions with new business models, trying to introduce new services or think about things that they can take advantage of or even shifting away from old this months that have been impacted by what's happening. And as they do that, they will look to do a transformation around finance in that function only or for that subsidiary or for that division. And so that's probably the first example. The second example that I'll give you is companies having to do something they never thought they would do before. I'll give you a simple example. We have a large number of insurance companies here in the United States as customers. And we all probably got our rebate check from the insurance company for our automobiles, right? So what happened is most of the large insurance companies identified that, hey, we actually don't have much risk because people aren't driving and they're paying us these big premiums. And so the insurance regulatory bodies put pressure on those insurance companies. So they had to figure out it business process model and a mechanism by which to go out, forecast what the premium reduction should be, what the business should look like, what that risk should be, do all of that planning and then think about it for their future actually and all the old stuff and then figure out a process by which to get those rebates delivered out to customers. So there's interesting things like that happening in process. And if somebody wasn't running a remote system that didn't have good agility, they wouldn't be able to make that quick pivot and get us all those rebate checks that we were so happy to have. >> Yes, very happy to have that. It sounds like that was done in a pretty fast turnaround time. So I imagine you're also dealing with customers who have sort of a TBD time schedule where there's still so much dynamics going on in the market today. >> Well, that's exactly right. I mean, because you're looking at different business models in different industries, I picked insurance there, but you can pick other extremes like how are retailers reopening? What are they thinking? You can look at hospitality places, how are they going to reopen? How are they going to generate revenue? How are they going to do planning? How are they going to account for things, right? So it's a range. So what's happened is everybody's looked at this as it's now an opportunity to not think in terms of years or even longer range plans. It's really an opportunity to be much more agile and think about being able to dynamically move in quarters or half year kind of increments. >> Yeah, we've been having a lot of conversations about how that time table has shifted and it's getting smaller and smaller because there's been so much flux and so much change that these organizations are really figuring out how do we actually shift and not just organizationally, but culturally as well to be able to adapt to these changes, that can be pretty sudden and pretty significant. I am curious too, Workday has historically focused its financial management solutions on really very much people intensive industries but you do have customers that are outside of that in the services. You talked about insurance getting value from Workday. Talk to me about some of those other expansion of opportunities there are in the more services oriented industries. >> No, that makes a lot of sense. And so I'll call it product based industries but you can think about it as manufacturing your other components, but is people that have systems around product. And while they might have complex supply chains that Workday isn't able to support for them right now they are looking at doing either that corporate transformation layer or they're looking at a solution we have around the Accounting Center. What Accounting Center allows them to do is bring in high volume of data from those source transaction systems and then generate accounting from it. But it gives them the ability to mix that operational data with that accounting data to do exactly what you're describing, be able to pivot more quickly and do more planning because they have a better foundation from their data accuracy and the consistency of that data. So they may be running multiple ERP systems and as they're running those they can bring that data together through Accounting Center kind of in a federated way and get better insight into what they need to do to plan more rapidly to roll things out. So they can kind of keep that execution system of record system, and then they can basically promote this to more of a operational, planning and analysis type function. >> Have you noticed in your conversations with customers the financial management changing in terms of being elevated up to the C-suite or a board level conversation with businesses now suddenly being very laser focused on understanding that reducing risk. Did any of that change and shift in terms of visibility in the last year? >> Yes it did. And the primary reason is because finance has always been the stewards of that information, and they curate the data, they do all of that work and then other people take it and do analysis. The finance department has taken more control of not only being the curator of that information but also being the team that does more of the analysis and has engaged more with corporate strategy or the chief revenue officers and trying to bring forward the ability to do analysis and have a voice in terms of what are the business models we should be doing, what are the strategic growth initiatives we should be doing? How should we be looking at running the business? Not just doing a finance function but really doing that advisory role. And it really has become because the data is so important to make those decisions, everyone wants these data driven decisions. And they are the curator of that data or the steward of that data. So they've kind of helped promote themselves to do that. >> What are some of the things that if you look out into your crystal ball for the rest of 2021, what are some of the things that you think we're going to see in some of the key industries that are working hard to return retail, manufacturing, the supply chain. We just had that big traffic jam in the Suez Canal, and a lot of challenges there. What are some of the things that you think are opportunities that we're going to see unfolding this year? >> Yeah, so I think it's going to be first, around getting back to work. So it's back to office stuff, which we'll start on the HR side, but it's going to lead to facility costs. It's going to lead to worker safety stuff and reporting, and it's going to lead to how you manage a healthcare or other tracking of things, is going to lead to how you engage with customers remotely. It's going to be a number of factors that are related to how do we transition back into real life? Because what we've started to see is in different parts of the country or the world even, parts of retail open up but we haven't seen mass return to lots of offices like here in the United States. And I think that will drive a lot of different processes in terms of about how people do working shifts, how they do meetings, how they do analysis, and there will be a desire then to have those business processes automated, right? The results of the transaction that comes from that, et cetera. >> That's a good point that you bring up that there's so many things that I hadn't really considered in terms of what it's going to take for businesses to return and have folks come back to campus. The extrovert in me just wants to go back but you bring up a great point and there's so many other facets that they had to deal with rapidly last year that have to be reconsidered. And so it makes sense that automation is something that they're looking at as coming in and really helping to automate certain processes to help reduce risk, reduce costs. Last question for you, Terrance, where can customers go if they are looking to get back on the track? How could they engage IBM and Workday together to help transform? >> Yeah, so the best and easiest way is we have some joint blogs that we've worked together, but first there's this CUBE. And then there is the joint blogs that we've worked together to talk about Enterprise Finance and how we're going to market. And then Enterprise Finance talks about the spectrum of a full finance transformation to a division to a corporate layer. >> Excellent, and I did see your blog. It sounds like you've been very busy in the last year which is excellent. But thanks so much Terrance for coming by and sharing with us all the dynamics that are going on in financial management and beyond, and the acceleration of elements of transformation that organizations have to look at now. It's very interesting. We appreciate your time. >> Yeah, thank you for having me. >> For Terrance Wampler, I'm Lisa Martin. You're watching theCUBE. (bright ambient music)

(bright music) >> Narrator: From around the globe, it's the CUBE with digital coverage of IBM Think 2021, brought to you by IBM. >> Welcome back to IBM Think 2021, the virtual edition. This is the CUBEs, continuous, deep dive coverage of the people, processes and technologies that are really changing our world. Right now, we're going to talk about modernization and what's beyond with Jamie Thomas, general manager, strategy and development, IBM Enterprise Security. Jamie, always a pleasure. Great to see you again. Thanks for coming on. >> It's great to see you, Dave. And thanks for having me on the CUBE is always a pleasure. >> Yeah, it is our pleasure. And listen, we've been hearing a lot about IBM is focused on hybrid cloud, Arvind Krishna says we must win the architectural battle for hybrid cloud. I love that. We've been hearing a lot about AI. And I wonder if you could talk about IBM Systems and how it plays into that strategy? >> Sure, well, it's a great time to have this discussion Dave. As you all know, IBM Systems Technology is used widely around the world, by many, many 1000s of clients in the context of our IBM System Z, our power systems and storage. And what we have seen is really an uptake of monetization around those workloads, if you will, driven by hybrid cloud, the hybrid cloud agenda, as well as an uptake of Red Hat OpenShift, as a vehicle for this modernization. So it's pretty exciting stuff, what we see as many clients taking advantage of OpenShift on Linux, to really modernize these environments, and then stay close, if you will, to that systems of record database and the transactions associated with it. So they're seeing a definite performance advantage to taking advantage of OpenShift. And it's really fascinating to see the things that they're doing. So if you look at financial services, for instance, there's a lot of focus on risk analytics. So things like fraud, anti money laundering, mortgage risk, types of applications being done in this context, when you look at our retail industry clients, you see also a lot of customer centricity solutions, if you will, being deployed on OpenShift. And once again, having Linux close to those traditional LPARs of AIX, I-Series, or in the context of z/OS. So those are some of the things we see happening. And it's quite real. >> Now, you didn't mention power, but I want to come back and ask you about power. Because a few weeks ago, we were prompted to dig in a little bit with the when Arvind was on with Pat Kessinger at Intel and talking about the relationship you guys have. And so we dug in a little bit, we thought originally, we said, oh, it's about quantum. But we dug in. And we realized that the POWER10 is actually the best out there and the highest performance in terms of disaggregating memory. And we see that as a future architecture for systems and actually really quite excited about it about the potential that brings not only to build beyond system on a chip and system on a package, but to start doing interesting things at the Edge. You know, what do you what's going on with power? >> Well, of course, when I talked about OpenShift, we're doing OpenShift on power Linux, as well as Z Linux, but you're exactly right in the context for a POWER10 processor. We couldn't be more we're so excited about this processor. First of all, it's our first delivery with our partner Samsung with a seven nanometer form factor. The processor itself has only 18 billion transistors. So it's got a few transistors there. But one of the cool inventions, if you will, that we have created is this expansive memory region as part of this design point, which we call memory inception, it gives us the ability to reach memory across servers, up to two petabytes of memory. Aside from that, this processor has generational improvements and core and thread performance, improved energy efficiency. And all of this, Dave is going to give us a lot of opportunity with new workloads, particularly around artificial intelligence and inferencing around artificial intelligence. I mean, that's going to be that's another critical innovation that we see here in this POWER10 processor. >> Yeah, processor performance is just exploding. We're blowing away the historical norms. I think many people don't realize that. Let's talk about some of the key announcements that you've made in quantum last time we spoke on the qubit for last year, I think we did a deeper dive on quantum. You've made some announcements around hardware and software roadmaps. Give us the update on quantum please. >> Well, there is so much that has happened since we last spoke on the quantum landscape. And the key thing that we focused on in the last six months is really an articulation of our roadmaps, so the roadmap around hardware, the roadmap around software, and we've also done quite a bit of ecosystem development. So in terms of the roadmap around hardware, we put ourselves out there we've said we were going to get to over 1000 qubit machine and in 2023, so that's our milestone. And we've got a number of steps we've outlined along that way, of course, we have to make progress, frankly, every six months in terms of innovating around the processor, the electronics and the fridge associated with these machines. So lots of exciting innovation across the board. We've also published a software roadmap, where we're articulating how we improve a circuit execution speeds. So we hope, our plan to show shortly a 100 times improvement in circuit execution speeds. And as we go forward in the future, we're modifying our Qiskit programming model to not only allow a easily easy use by all types of developers, but to improve the fidelity of the entire machine, if you will. So all of our innovations go hand in hand, our hardware roadmap, our software roadmap, are all very critical in driving the technical outcomes that we think are so important for quantum to become a reality. We've deployed, I would say, in our quantum cloud over, you know, over 20 machines over time, we never quite identify the precise number because frankly, as we put up a new generation machine, we often retire when it's older. So we're constantly updating them out there, and every machine that comes on online, and that cloud, in fact, represents a sea change and hardware and a sea change in software. So they're all the latest and greatest that our clients can have access to. >> That's key, the developer angle you got redshift running on quantum yet? >> Okay, I mean, that's a really good question, you know, as part of that software roadmap in terms of the evolution and the speed of that circuit execution is really this interesting marriage between classical processing and quantum processing and bring those closer together. And in the context of our classical operations that are interfacing with that quantum processor, we're taking advantage of OpenShift, running on that classical machine to achieve that. And once again, if, as you can imagine, that'll give us a lot of flexibility in terms of where that classical machine resides and how we continue the evolution the great marriage, I think that's going to that will exist that does exist and will exist between classical computing and quantum computing. >> I'm glad I asked it was kind of tongue in cheek. But that's a key thread to the ecosystem, which is critical to obviously, you know, such a new technology. How are you thinking about the ecosystem evolution? >> Well, the ecosystem here for quantum is infinitely important. We started day one, on this journey with free access to our systems for that reason, because we wanted to create easy entry for anyone that really wanted to participate in this quantum journey. And I can tell you, it really fascinates everyone, from high school students, to college students, to those that are PhDs. But during this journey, we have reached over 300,000 unique users, we have now over 500,000 unique downloads of our Qiskit programming model. But to really achieve that is his back plane by this ongoing educational thrust that we have. So we've created an open source textbook, around Qiskit that allows organizations around the world to take advantage of it from a curriculum perspective. We have over 200 organizations that are using our open source textbook. Last year, when we realized we couldn't do our in person programming camps, which were so exciting around the world, you can imagine doing an in person programming camp and South Africa and Asia and all those things we did in 2019. Well, we had just like you all, we had to go completely virtual, right. And we thought that we would have a few 100 people sign up for our summer school, we had over 4000 people sign up for our summer school. And so one of the things we had to do is really pedal fast to be able to support that many students in this summer school that kind of grew out of our proportions. The neat thing was once again, seeing all the kids and students around the world taking advantage of this and learning about quantum computing. And then I guess that the end of last year, Dave, to really top this off, we did something really fundamentally important. And we set up a quantum center for historically black colleges and universities, with Howard University being the anchor of this quantum center. And we're serving 23 HBCUs now, to be able to reach a new set of students, if you will, with STEM technologies, and most importantly, with quantum. And I find, you know, the neat thing about quantum is is very interdisciplinary. So we have quantum physicist, we have electrical engineers, we have engineers on the team, we have computer scientists, we have people with biology and chemistry and financial services backgrounds. So I'm pretty excited about the reach that we have with quantum into HBCUs and even beyond right I think we can do some we can have some phenomenal results and help a lot of people on this journey to quantum and you know, obviously help ourselves but help these students as well. >> What do you see in people do with quantum and maybe some of the use cases. I mean you mentioned there's sort of a connection to traditional workloads, but obviously some new territory what's exciting out there? >> Well, there's been a really a number of use cases that I think are top of mind right now. So one of the most interesting to me has been one that showed us a few months ago that we talked about in the press actually a few months ago, which is with Exxon Mobil. And they really started looking at logistics in the context of Maritime shipping, using quantum. And if you think of logistics, logistics are really, really complicated. Logistics in the face of a pandemic are even more complicated and logistics when things like the Suez Canal shuts down, are even more complicated. So think about, you know, when the Suez Canal shut down, it's kind of like the equivalent of several major airports around the world shutting down and then you have to reroute all the traffic, and that traffic and maritime shipping is has to be very precise, has to be planned the stops are plan, the routes are plan. And the interest that ExxonMobil has had in this journey is not just more effective logistics, but how do they get natural gas shipped around the world more effectively, because their goal is to bring energy to organizations into countries while reducing CO2 emissions. So they have a very grand vision that they're trying to accomplish. And this logistics operation is just one of many, then we can think of logistics, though being a being applicable to anyone that has a supply chain. So to other shipping organizations, not just Maritime shipping. And a lot of the optimization logic that we're learning from that set of work also applies to financial services. So if we look at optimization, around portfolio pricing, and everything, a lot of the similar characteristics will also go be applicable to the financial services industry. So that's one big example. And I guess our latest partnership that we announced with some fanfare, about two weeks ago, was with the Cleveland Clinic, and we're doing a special discovery acceleration activity with the Cleveland Clinic, which starts prominently with artificial intelligence, looking at chemistry and genomics, and improve speed around machine learning for all of the the critical healthcare operations that the Cleveland Clinic has embarked on but as part of that journey, they like many clients are evolving from artificial intelligence, and then learning how they can apply quantum as an accelerator in the future. And so they also indicated that they will buy the first commercial on premise quantum computer for their operations and place that in Ohio, in the the the years to come. So it's a pretty exciting relationship. These relationships show the power of the combination, once again, of classical computing, using that intelligently to solve very difficult problems. And then taking advantage of quantum for what it can uniquely do in a lot of these use cases. >> That's great description, because it is a strong connection to things that we do today. It's just going to do them better, but then it's going to open up a whole new set of opportunities. Everybody wants to know, when, you know, it's all over the place. Because some people say, oh, not for decades, other people say I think it's going to be sooner than you think. What are you guys saying about timeframe? >> We're certainly determined to make it sooner than later. Our roadmaps if you note go through 2023. And we think the 2023 is going to will be a pivotal year for us in terms of delivery around those roadmaps. But it's these kind of use cases and this intense working with these clients, 'cause when they work with us, they're giving us feedback on everything that we've done, how does this programming model really help me solve these problems? What do we need to do differently? In the case of Exxon Mobil, they've given us a lot of really great feedback on how we can better fine tune all elements of the system to improve that system. It's really allowed us to chart a course for how we think about the programming model in particular in the context of users. Just last week, in fact, we announced some new machine learning applications, which these applications are really to allow artificial intelligence users and programmers to get take advantage of quantum without being a quantum physicist or expert, right. So it's really an encapsulation of a composable elements so that they can start to use, using an interface allows them to access through PyTorch into the quantum computer, take advantage of some of the things we're doing around neural networks and things like that, once again, without having to be experts in quantum. So I think those are the kind of things we're learning how to do better, fundamentally through this co-creation and development with our quantum network. And our quantum network now is over 140 unique organizations and those are commercial, academic, national laboratories and startups that we're working with. >> The picture started become more clear, we're seeing emerging AI applications, a lot of work today in AI is in modeling. Over time, it's going to shift toward inference and real time and practical applications. Everybody talks about Moore's law being dead. Well, in fact, the yes, I guess, technically speaking, but the premise or the outcome of Moore's law is actually accelerating, we're seeing processor performance, quadrupling every two years now, when you include the GPU along with the CPU, the DSPs, the accelerators. And so that's going to take us through this decade, and then then quantum is going to power us, you know, well beyond who can even predict that. It's a very, very exciting time. Jamie, I always love talking to you. Thank you so much for coming back on the CUBE. >> Well, I appreciate the time. And I think you're exactly right, Dave, you know, we talked about POWER10, just for a few minutes there. But one of the things we've done in POWER10, as well as we've embedded AI into every core that processor, so you reduce that latency, we've got a 10 to 20 times improvement over the last generation in terms of artificial intelligence, you think about the evolution of a classical machine like that state of the art, and then combine that with quantum and what we can do in the future, I think is a really exciting time to be in computing. And I really appreciate your time today to have this dialogue with you. >> Yeah, it's always fun and it's of national importance as well. Jamie Thomas, thanks so much. This is Dave Vellante with the CUBE keep it right there our continuous coverage of IBM Think 2021 will be right back. (gentle music) (bright music)

>>from around the globe. It's the cube >>With digital coverage of IBM think 2021 brought to you by IBM. Welcome to the cubes coverage of IBM Think 2021. I'm lisa martin. Terrence WAmpler joins me next General manager at Workday financial management at workday Terrance. Welcome to the cube. >>Well thank you for having me. It's great to be here. I appreciate it. >>Nice that we can still do these events virtually even though we are quite socially distance. So the last year has brought lots of changes. One of them being at B. M. Thinking the cube being virtual. I'm curious to get your perspectives and your observations. We've seen many finance organizations have to rapidly pivot and accelerate their digital transformation making it a priority. What are some of the key priorities that you've seen that the C suite the CFO are dealing with? >>Yeah. Well I think what's happening is what we've seen our new ways to work and using remote access, having to do mobile technologies. What's happening is that's actually driving more risk for companies. And so as companies get more risk that's driving the needs to have more scrutiny on those business processes and that's forcing them to want to accelerate what they're doing in terms of the digital transformation, other stuff like that. It's also forcing them to think more about the data they have and the information they have looking forward and how they're doing planning and how they can do planning in terms of bringing people back to work in terms of new business models, in terms of what may be next, in terms of opportunity for them or even doing catastrophe planning as they, as they work through this stuff and as they start to look at that they're really thinking about how to make their business process and much more agile. And so it's kind of a complicated thread that you start to pull as people start to change how things work. >>Yeah, that risk is a big factor in that pivot was so quick for so many businesses where suddenly so many of us and so many of us are still remote. I'm curious what some of the things are though that you're hearing with respect to organizations looking to start opening things back up and bringing some of the folks back on campus. >>Yeah, it's a very interesting dilemma because what's happening is people have learned how to work remotely now and so they're trying to figure out how they're going to bring people back to be more collaborative. But at the end of the day, the first and most important thing they've learned is that especially for a finance function, they no longer want to be transaction operators. What they want to start doing is pushing that work to more automated tools to have that be done for them and try to promote themselves to be more like analysts or even advisors to the business or even a partner to the business. And as they go through that evolution, what they're really trying to do is unlock all of the potential of the people they have of the processes they have and if the data they have. So what is really made companies do is look at everything in its entirety and want to change all of it. But they have to go at different paces, >>definitely talk to me about what worked and IBM are doing together to help customers tackle these challenges, adjust their priorities and accelerate that transformation. >>Yeah, certainly. So one of the things that we've done is gotten together and created this go to market strategy called enterprise finance and what enterprise finance does is it really tries to meet the customer where they are. So while all of these customers are looking to accelerate their digital transformation, they come from very different places, right? And their journey to that transformation is going to be very different and that means that some of them are going to want to be able to do a full transformation right away and do it globally and make a big change because they've just been hit very hard by this or they see it as an opportunity to grow and others are going to come from a very complex environment. And that complex environment could include complicated manufacturing components in their solution. And they need to look at something like just a corporate finance layer that has kind of an integrated planning solution, consolidation, close capabilities for them to be able to run their business and be a little bit more agile at the top line. >>So a spectrum of of use of meeting them where they are. There's a lot of customers in different places. I'm curious what some of the things are that you've observed over the last year, that really are kind of unique ways that finance leaders are approaching this, this new way of working. >>Yeah, so there's probably two examples I can give you. One is a generic example where we have customers that have participated in merger or acquisition activity over the past year as it happens to be. Or customers that have even spun up new divisions with new business models trying to introduce new services or think about things that they can take advantage of or even shifting away from all this months that have been impact by what's happening And as they do that they will look to do a transformation around finance in that function only or for that subsidiary or for that division. And so that's probably the first example. The second example that I'll give you is companies having to do something they never thought they would do before. I'll give you a simple example. We have a large number of insurance companies here in the United States as customers and we all probably got our rebate check from the insurance company for automobiles. Right? So what happened is most of the large insurance companies identified that, hey, we actually don't have much risk because people aren't driving and they're paying us these big premiums. And so the insurance regulatory bodies put pressure on those insurance companies. So they had to figure out a business process model, any mechanism by which to go out forecast what the premium reduction should be, what the business should look like, what that risk should be, do all of that planning and then think about it for their future, actually, really old stuff and then figure out a process by which to get those rebates delivered out to customers. So there's interesting things like that happening in process. And if somebody wasn't running a remote system that didn't have good agility, they wouldn't be able to make that quick pivot and get us all those rebate checks that we were so happy to have. >>Yes, very happy to have that. It sounds like that was done in a pretty, pretty fast turnaround time. So imagine you're also dealing with customers who have sort of a TBD time schedule where there's still so much dynamics going on in the market today. >>Well, that's exactly right. I mean because you're looking at different business models in different industries. I picked insurance there, but you can pick other extremes like how are retailers reopening? What are they thinking? You can look at hospitality places, how are they going to reopen? How are they going to generate revenue? How are they going to do planning, How are they going to account for things? Right. So it's a range. So what's happened is everybody has looked at this as it's now an opportunity to not think in terms of years or even longer range plans, it's really an opportunity to be much more agile and think about being able to dynamically move in quarters or half, half year. Kind of, >>we've been having a lot of conversations about how that timetable has shifted and it's getting smaller and smaller because there's been so much flux and so much change that these organizations are really figuring out, how do we actually shift? Um and not just organizations but culturally as well to be able to adapt to these changes. That can be pretty sudden and pretty significant. I am curious to workday has historically focused its financial management solutions on really very much people intensive industries, but you do have customers that are outside of that and the services you talked about insurance getting value from work. They talk to me about um some of those other expansion of opportunities there are in the more services oriented industries. >>That makes a lot of sense. And so I'll call it product based industries but you can think about it as manufacturing or other components, but it's people that have systems around product and while they might have complex supply chains that Workday isn't able to support for them right now, they are looking at doing either that corporate transformation layer or they're looking at a solution we have around the county center. What accounting center allows them to do is bring in high volume of data from those source transaction systems and then generate accounting from it. But it gives them the ability to mix that operational data with that accounting data to do exactly what you're describing. Be able to pivot more quickly and do more planning because they have a better foundation from their data accuracy than the consistency of that data. So they may be running multiple E. R. P. Systems and as they're running those they can bring that data together through accounting center kind of a Federated way and get better insight into what they need to do to plan more rapidly to roll things out so they can kind of keep that execution system of record system and then they can basically promote this to more of operational planning and analysis type. >>Have you noticed in your conversations with customers? The financial management changing in terms of being elevated up to the C suite or a board level conversation with businesses. Now suddenly being very laser focused on understanding that reducing risk and did that any of that change and shift in terms of visibility in the last year? >>Yes it did. And the primary reason is because finance has always been the stewards of that information. They curate the data, they do all of that word and then other people take it and do analysis. The Finance department has taken more control of not only being the curator of that information but also being the team that does more of the analysis and has engaged more with corporate strategy or the chief revenue officers trying to bring forward the ability to do analysis and have a voice in terms of what are the business models we should be doing? What are the strategic growth initiatives we should be doing? How should we be looking at running the business, not just doing a finance function, but really doing that advisory role. And it really has become because the data is so important to make those decisions. Everyone wants these data german decisions and they are the curator of that data or the steward of that data. So they kind of helped promote themselves to do. >>What are some of the things that if you look out into your crystal ball for the rest of 2021, but are some of the things that you can that you think we're going to see in some of the key industries that are, that are working hard to return retail, manufacturing, the supply chain. We just had that big traffic jam in the Suez Canal and a lot of challenges there. What are some of the things that you think are opportunities that we're gonna see unfolding this year? >>Yeah, so I think it's going to be first around getting back to work, so it's back to office stuff which will start on the HR side, but it's going to lead to facility costs. It's going to lead to, you know, work or safety stuff and reporting, it's going to lead to how you manage health care or other tracking of things is going to lead to how you engage with customers remotely. It's going to be a number of factors that are related to how do we transition back into real life? Because what we started to see is in different parts of the country or the world, even parts of retail open up. But we haven't seen mass return to lots of offices like here in the United States. And I think that will drive a lot of different processes in terms of about how people do working shifts, how they do meetings, how they do analysis. And there will be a desire then to have those business processes automated the results of the transaction that comes from that, etc. >>That's a good point that you bring up that there's so many things that I hadn't really considered in terms of what it's going to take for businesses to return and have folks come back to campus. The extroverted me just wants to go back but you bring up a great point. There's so many other facets that they had to deal with rapidly last year. They have to be reconsidered. And so it makes sense that automation is something that they're looking at is coming in and really helping to automate certain processes to help reduce risk, reduce costs. Last question for you Terrence. Working customers go if they are looking to get back on the track, how can they engage IBM and workday together to help transform. >>Yeah. So the the best and easiest way is we have some joint blogs that we've worked together but first there's this cube and then there is the joint blogs that we've worked together to talk about enterprise finance and how we're going to market and that enterprise finance talks about the spectrum of a full finance transformation to a division to a corporate layer. >>Excellent. And I did see your blog. It sounds like you've been very busy in the last year which is excellent but thanks so much Terrence for coming by and sharing with us all the dynamics that are going on in financial management and beyond and the the acceleration of elements of transformation that organizations have to look at now. It's very interesting. We appreciate your time. >>No, thank you for having me >>for Terrence Wobbler. I'm lisa martin. You're watching the cube. >>Mhm.

>>from around the globe. It's the cube >>with digital coverage >>of IBM Think >>2021 >>brought to you by IBM. >>Welcome to the cubes coverage of IBM Think 2021. I'm lisa martin. Terrence Wobbler joins me next General manager at workday financial management at workday Terrance. Welcome to the cube. >>Well thank you for having me. It's great to be here. I appreciate it. >>Nice that we can still do these events virtually even though we are quite socially distance. So the last year has brought lots of changes. One of them being IBM think and the cube being virtual. I'm curious to get your perspectives and your observations. We've seen many finance organizations have to rapidly pivot and accelerate their digital transformation making it a priority. What are some of the key priorities that you've seen that the C suite the CFO are dealing with? >>Yeah. Well I think what's happening is what we've seen our new ways to work and using remote access, having to do mobile technologies. What's happening is that's actually driving more risk for companies. And so as companies get more risk that's driving the needs to have more scrutiny on those business processes and that's forcing them to want to accelerate what they're doing in terms of the digital transformation, other stuff like that. It's also forcing them to think more about the data they have and the information they have looking forward and how they're doing planning and how they can do planning in terms of bringing people back to work in terms of new business models, in terms of what may be next, in terms of opportunity for them or even doing catastrophe planning as they, as they work through this stuff and as they start to look at that they're really thinking about how to make their business process and much more agile. And so it's kind of a complicated thread that you start to pull as people start to change how things work. >>Yeah, that risk is a big factor in that pivot was so quick for so many businesses where suddenly so many of us and so many of us are still remote. I'm curious what some of the things are though that you're hearing with respect to organizations looking to start opening things back up and bringing some of the folks back on campus. >>Yeah, it's a very interesting dilemma because what's happening is people have learned how to work remotely now and so they're trying to figure out how they're going to bring people back to be more collaborative. But at the end of the day, the first and most important thing they've learned is that especially for a finance function, they no longer want to be transaction operators. What they want to start doing is pushing that work to more automated tools to have that be done for them and try to promote themselves to be more like analysts or even advisors to the business or even a partner to the business. And as they go through that evolution, what they're really trying to do is unlock all of the potential of the people they have of the processes they have and if the data they have. So what is really made companies do is look at everything in its entirety and want to change all of it. But they have to go at different paces, >>definitely talk to me about what worked and IBM are doing together to help customers tackle these challenges, adjust their priorities and accelerate that transformation. >>Yeah, certainly. So one of the things that we've done is gotten together and created this go to market strategy called enterprise finance and what enterprise finance does is it really tries to meet the customer where they are. So while all of these customers are looking to accelerate their digital transformation, they come from very different places, right? And their journey to that transformation is going to be very different and that means that some of them are going to want to be able to do a full transformation right away and do it globally and make a big change because they've just been hit very hard by this or they see it as an opportunity to grow and others are going to come from a very complex environment. And that complex environment could include complicated manufacturing components in their solution. And they need to look at something like just a corporate finance layer that has kind of an integrated planning solution, consolidation, closed capabilities for them to be able to run their business and be a little bit more agile top one. >>So a spectrum of of use of meeting them where they are. There's a lot of customers in different places. I'm curious what some of the things are that you've observed over the last year, that really are kind of unique ways that finance leaders are approaching this, this new way of working. >>Yeah, So there's probably two examples I can give you. One is a generic example where we have customers that have participated in merger or acquisition activity over the past year as it happens to be. Or customers that have even spun up new divisions with new business models trying to introduce new services or think about things that they can take advantage of or even shifting away from all of this must have been impact by what's happening and as they do that they will look to do a transformation around finance in that function only or for that subsidiary or for that division. And so that's probably the first example, The second example that I'll give you is companies having to do something they never thought they would do before. I'll give you a simple example. We have a large number of insurance companies here in the United States as customers and we all probably got our rebate check from the insurance company for automobiles. Right? So what happened is most of the large insurance companies identified that, hey, we actually don't have much risk because people aren't driving and they're paying us these big premiums. And so the insurance regulatory bodies put pressure on those insurance companies. So they had to figure out a business process model any mechanism by which to go out forecast what the premium reduction should be, what the business should look like, what that risk should be. Do all of that planning and then think about it for their future, actually, really old stuff and then figure out a process by which to get those rebates delivered out to customers. So there's interesting things like that happening in process. And if somebody wasn't running a remote system that didn't have good agility, they wouldn't be able to make that quick pivot and get us all those rebate checks that we were so happy to have. >>Yes, very happy to have that. It sounds like that was done in a pretty, pretty fast turnaround time. So imagine you're also dealing with customers who have sort of a TBD time schedule where there's still so much dynamics going on in the market today. >>Well, that's exactly right. I mean, because you're looking at different business models in different industries. I picked insurance there, but you can pick other extremes like how are retailers reopening? What are they thinking? You can look at hospitality places, how are they going to reopen? How are they going to generate revenue? How are they going to do planning? How are they going to account for things? Right. So it's a range. So what's happened is everybody has looked at this as it's now an opportunity to not think in terms of years or even longer range plans. It's really an opportunity to be much more agile and think about being able to dynamically move in quarters or half, half year. Kind of, >>we've been having a lot of conversations about how that timetable has shifted and it's getting smaller and smaller because there's been so much flux and so much change that these organizations are really figuring out, how do we actually shift? Um and not just organizations, but culturally as well to be able to adapt to these changes that can be pretty sudden and pretty significant. I am curious to workday has historically focused its financial management solutions on really very much people intensive industries, but you do have customers that are outside of that in the services, You talked about insurance, getting value from work. They talk to me about um some of those other expansion of opportunities there are in the more services oriented industries. >>That makes a lot of sense and so I'll call it product based industries but you can think about it as manufacturing or other components but it's people that have systems around product and while they might have complex supply chains that Workday isn't able to support for them right now, they are looking at doing either that corporate transformation layer or they're looking at a solution we have around the counting centre. What accounting center allows them to do is bring in high volume of data from those source transaction systems and then generate accounting from it. But it gives them the ability to mix that operational data with that accounting data to do exactly what you're describing. Be able to pivot more quickly and do more planning because they have a better foundation from their data accuracy than the consistency of that data. So they may be running multiple E. R. P. Systems and as they're running those they can bring that data together through accounting center kind of in a Federated way and get better insight into what they need to do to plan more rapidly to roll things out so they can kind of keep that execution system of record system and then they can basically promote this to more of operational planning and analysis type function. >>Have you noticed in your conversations with customers, the financial management changing in terms of being elevated up to the C suite or a board level conversation with businesses. Now suddenly being very laser focused on understanding that reducing risk and did that any of that change and shift in terms of visibility in the last year? >>Yes it did. And the primary reason is because finance has always been the stewards of that information. They curate the data, they do all of that word and then other people take it and do analysis. The Finance department has taken more control of not only being the curator of that information but also being the team that does more of the analysis and has engaged more with corporate strategy or the Chief revenue officers trying to bring forward the ability to do analysis and have a voice in terms of what are the business models we should be doing? What are the strategic growth initiatives we should be doing? How should we be looking at running the business, not just doing a finance function, but really doing that advisory role. And it really has become because the data is so important to make those decisions. Everyone wants these data driven decisions and they are the curator of that data or the steward of that data. So they kind of helped promote themselves to do that. >>What are some of the things that if you look out into your crystal ball for the rest of 2021? But are some of the things that you can that you think we're going to see in some of the key industries that are that are working hard to return retail, manufacturing, the supply chain. We just had that big traffic jam in the Suez Canal and a lot of challenges there. What are some of the things that you think are opportunities that we're going to see unfolding this year? >>Yeah, so I think it's going to be first around getting back to work, so it's back to office stuff which will start on the HR side, but it's going to lead to facility costs. It's going to lead to, you know, worker safety stuff and reporting, it's going to lead to how you manage health care or other tracking of things. It's going to lead to how you engage with customers remotely. It's going to be a number of factors that are related to how do we transition back into real life? Because what we started to see is in different parts of the country or the world, even parts of retail open up. But we haven't seen mass return to lots of offices like here in the United States. And I think that will drive a lot of different processes in terms of about how people do working shifts, how they do meetings, how they do analysis. And there will be a desire then to have those business processes automated the results of the transaction that comes from that, etc. >>That's a good point that you bring up that there's so many things that I hadn't really considered in terms of what it's going to take for businesses to return and have folks come back to campus. The extroverted just wants to go back. But you bring up a great point. There's so many other facets that they had to deal with rapidly last year. They have to be reconsidered. And so it makes sense that automation, it's something that they're looking at is coming in and really helping to automate certain processes to help reduce risk, reduce costs. Last question for you terrence. Working customers go if they are looking to get back on the track, how can they engage IBM and work together to help transform. >>Yeah. So the the best and easiest way is we have some joint blogs that we've worked together but first there's this cube and then there is the joint blogs that we've worked together to talk about enterprise finance and how we're going to market and that enterprise finance talks about the spectrum of a full finance transformation to a division to a corporate layer. >>Excellent. And I did see your blog. It sounds like you've been very busy in the last year which is excellent but thanks so much Terrence for coming by and sharing with us all the dynamics that are going on in financial management and beyond and the the acceleration of elements of transformation that organizations have to look at now. It's very interesting. We appreciate your time. >>No, thank you for having me >>for terrence Wobbler. I'm lisa martin. You're watching the cube.

>> From our studios in the heart of Silicon Valley, Palo Alto, California. This is a CUBE Conversation. >> Hello everyone, welcome to this special CUBE Conversation here in Palo Alto California, theCUBE headquarters. I'm John Furrier, host of theCUBE. We're here with Dheeraj Pandey CEO and Founder of Nutanix. Great guest, been with us for 10 years. Was on the cube in 2010 when we first started doing theCUBE coverage of events was at VMworld, Dheeraj, great to see you. >> Pleasure. >> Thanks for coming in. >> Thank you. >> You've had such a great journey. I've been so impressed with you as an entrepreneur, the hustle, the early days when you were misunderstood to the growth and going public and continuing to compete. Congratulations to you and your team. It's been great. >> Thank you, no, it's been a journey and it's going to continue to be a journey. >> A lot of competitive pressure. A lot of cloud happening, a lot of server dynamics in the marketplace with On-Premise now getting validated as a part of this multi-cloud hybrid equation, certainly not going away, but still growth of the cloud has been huge. What's the big focus, 'cause you have your Nutanix Next conference coming up in May. I'll be there with theCUBE, what's the focus, what is the theme of the event? What's the big focus? >> Yeah, no, in fact we complete 10 years this September, so it's a decade since the beginning of time for Nutanix. And we are focusing on the things that we're good at. We are good at what I call the three D's. So it's a three D view of the company. The first D's data, we are really good at data. And we're doubling down on data. We're very good at design, we've done a very good job of simplification making elegant consumer grade and taking clicks away rather than things taking months, how can it be done in seconds and hours, and we're very good at delivery, you know, the third D being delivery, you know, it's not just delivery of our software through all different form factors and our appliance and software and subscription and other servers, but also customer support, customer success, which has really endeared us to our customers. So if you think about what this conference is all about, obviously it's about the customers and as the power of social proof, the fact that they learn from each other and we learn from them. But it's really about reinforcing the three D's. Data, design, and delivery. >> And the theme is invisible clouds. Period, visible IT, invisible cloud, so I'm assuming that's, make that, abstract that away, multi-cloud in there, probably a theme. Visible IT, that's supposed to be invisible too, but what does that mean? I get the invisible cloud 'cause you want to make it seamless, multi-cloud, hybrid cloud. But what's visible IT, how do those words play? What's the play on words there? >> Yeah, I mean, you know, we, first of all the word invisible is really powerful and we use it a lot and it's very unique to Nutanix, you know, not everybody uses the word invisible as much as we do, but the idea is that machines should become invisible. Software and systems and tools and those things should become invisible. And then humans should become visible and by the way, there's this really good antithesis, sort of the polar opposites of machines versus humans that goes on in many other walks of life, I mean zero trust when it comes to security. Machines should not trust each other. But full trust, when people need to trust people. So when it's an organization of people you need to be the opposite of zero trust. Same thing is true for invisible machines invisible clouds with visible people visible careers and I think what's happening is that as the cloud hype cycle actually matures, CIOs are talking about cloud cloud cloud, but the grassroots is basically saying like do you even know the legacy apps of the last 20 years? Do you understand the challenges of what we call the laws of the land? Data compliance and regulations, laws of physics which is the gravity of data and the gravity of people and operations and laws of economics, owning and renting. So I think what's happening is that the cloud revolution is really being dug like a Eurotunnel, from two sides. Top down from C-level people are saying let's go transform ourselves to the cloud. And we are helping the grassroots really go and translate that, say look, this is only possible by doing these things because we have to be respectful of data sovereignty, data gravity, and applications and the economics of that. So, in really helping the CIOs build trust with the grassroots. As opposed to-- So essentially, you're operational as a cloud 'cause I can hear. We've interviewed a lot of CXOs on theCUBE as you know, take that hill, go to the cloud, move everything to the cloud. Wait a minute, we got, we're closing a pin. So to make sense of that vision, it's got to be operationalized, that's kind of what you're getting at. >> Absolutely, absolutely. And then finally there's a, I mean look what happens in computing, we make things smaller all the time, you know, we started with mainframes and we ended up with serverless. And along the way we had obviously Unix and x86 and container, VMs and containers and so on. Same thing with personal computing. We started with desktops and we ended up with wearables. So the fact that there's a billion dollar data center is the new mainframe. The fact that there's going to be a big cloud data center only two places in a big country is actually quite the antithesis of computing, we have to make cloud be everywhere and make it about software. To operationalizing the cloud and making it into a half a trillion dollar market will be about software. >> This whole mainframe is in the cloud or mainframe distributing computing. Software industry kind of come back in vogue. It doesn't go away, it's all the same game. It's just distributed out around in different formats, that's kind of what's going on here. >> Absolutely, I mean go back in time to distribution. Apple was a vertically integrated stack. So how does Microsoft come and really compete against Apple, they said look PC is about software, they said look PC's not about hardware, it's about software and the market becomes 10 times larger because they really bring in other partners who make money with the Windows Operating System. >> That's just more enabling. There's more demand, there's more growth. >> Absolutely, and the same thing happens again 15 years later with iOS versus Android. So Apple says smartphone is about vertically integrated stack, and Google comes and says no, to make the market 10 times larger, Android is about software. And then other handset manufacturers come and make money, so cloud is at this juncture where to take it beyond, 50, 60 billion dollars to half a trillion dollars, it has to be about software. >> Dheeraj, one of the things that I'm impressed with with you as an entrepreneur and your team is you fit the profile of the classic big idea. Be different, have good product leadership and pick a way that's going to have a big, totally adjustable market. You did that and you didn't waver, so I reviewed your analyst meeting from Wikibon and involved third party analysts. A hundred billion dollar addressable market. So big market, check, private cloud trend which you called early and Stu Miniman also called that on Wikibon is not going away, you have a stack for that. Large customer base, you have what 12 thousand customers plus and growing. Great revenue, strong revenue, and you got refreshes coming because the technology continues to shift in the wave that you're on. So, congratulations, that's good health meters. But there's now competitive pressure. The genie's out of the bottle. People know what you're doing. They figured it out and they're going to try to compete with you. This economy of scale that you have there's economy of scales others have specifically Dell, Dell EMC, VMware have been highly competitive with you. How are you responding to that and what's the landscape look like? >> Yeah, look, we've always been about disrupting ourselves, and that's the way we've actually grown our company. Very contrarian way of thinking about it but if we go back in time four, five years ago we're an appliance company, and we said we're going to do an OEM relationship with Dell and then Lenovo and others. All of a sudden people started competing with yourself, and for us it was like the more we compete with ourselves the better it is, today I think if you think about where the company's real response to any competition is to really compete with ourselves. I typically don't get wavered or changed by what's out there, we don't compete with anybody else, if we can keep competing with ourselves and get better in solving our customers and those three D's I talked about being even deeper in data, that VMware can't even touch us on simply because they have to compete with EMC on that and I don't know whether they actually have the gumption to do that, we do actually. We have to be better at design. Make the control plane even simpler. Understand what it means to virtualize the cloud. And get better at delivery, so if we can keep getting better in the three D's and we can keep competing with ourselves. We just did a really good announcement at HPE where we're going to compete with ourselves one more time because-- >> Talk about that announcement 'cause I think this is different. So HPE bought Nimble Storage so they already got the storage piece. They've got tons of servers, they also compete with Dell, what's your position with HPE, what's the announcement? What's the partnership? >> Yeah, so we're going to do a two-way relationship where we're going to be able to our sellers can quote HP servers and their sellers can actually quote our operating system. We have this rainbow which we call core essentials enterprise, Nutanix Core which is about hyper-convergence. Modernize your infrastructure. Nutanix Essential which is how we build a private cloud, and then Nutanix Enterprise which is really about navigating and simplifying the multi-cloud journey of the customer. And HP's going to take this stack to its customers. Again, we started to compete with ourselves because our appliance business was not based on HP, but now it will. Similarly, they will compete with themselves. And that's how companies transform themselves. When they compete with themselves rather than somebody else. >> And it's always the old expression, eat your own before your competition does. That's a cannibalization, kind of MBA concept. You guys are aggressive on that. You don't mind doing that and taking that risk. >> No, in fact if you don't do it, someone else will. It's better to do it in the controlled way ourselves. >> Got great, great management styles. So let's talk about, you mentioned control plane earlier, you have a quote on your deck that says, that I reviewed, it says control plane matters, this speaks to some of the product leadership. What does that actually mean, the control plane message, 'cause we hear this a lot come up in multi-cloud hybrid, and certainly within the data conversation around data control planes, control planes. For you guys, what does that mean? Control plane matters? >> Well if you take back like 10 years ago. We were very bold and audacious. We were the only company to say look we will not be building a tab in vCenter. Contrarian, highly contrarian. Most people said you'll lose a lot of deals because you are not adjunct to vCenter. You're not a tab in vCenter, every hardware renderer was really bending over backwards to please VMware because that was the only way to the heart of the virtualization administrator. We took a very different stance. Prism was the control plane, they said if you do a really good job at Prism make it a distributed scale out platform. Make it consumer grade one click delight. Then customers will actually look at this as a very powerful thing, and then we virtualized the hypervisor. So Prism was a multi hypervisor platform. It worked for Vmware, it worked for Hyper-V and it worked for Nutanix AHV. So over time, we just kept doing more of it. So now we have a control plane for multi-cloud. We were saying look, the world does need an automation orchestration engine. That is multi-cloud come is that thing for us. We've taken Prism to the next level with Prism Pro which is about ML and AI and what does it mean to really do operations management and capacity planning and security and analytics. So, we've doubled down on design which is the second D that I talked about with these control planes and going forward and as you see us getting to multi-cloud desktop delivery, we acquired a company almost a year ago, which is really about a cloud native desktop delivery solution where, now the control plane of desktops could belong in the cloud but the desktop itself could be running on prem. And that's a very powerful concept that you can have these cloud enabled cloud holstered cloud serviced control planes but the data place could actually be anywhere. It could be running-- This is the invisible cloud concept you're talking about. Absolutely, yeah. In fact the fact that the controller could be running anywhere, and the thing it controls could be running someplace else. >> The question, that's great stuff and that's great product leadership and again, invisible cloud, people don't want to deal with multiple code bases They want to have seamless operations. So with that I got to ask you your cloud positioning because every enterprise now because it's from the top end. Now it's top comparative, what's the cloud positioning because we now see on premise, super important a-du-is-ca outpost. The data's going to reside on premise in the cloud, it's all going to move around. What is the cloud positioning that you talk to your customers about when they say hey, we like Nutanix but we got to go to cloud, what's the positioning? >> Well our positioning is that cloud has to be about software. It has to seep everywhere, it has to be injected everywhere, our software should run no just on prim but in an AWS bare metal. There's a bare metal service and our software should run there. There will be an Azure bare metal. We already run in GCP metal so our software can run on top of GCP as well. Of course it is on prem and we are already working on our own disaster recovery as a service, desktop as a service where we become the service provider for many of these hybrid services that customers actually need from us. So cloud is about ubiquity, it's about portability, I mean the strength of any software company is portability. If we can make ourselves available in every server, every hypervisor, and every cloud, I think we've done a very good job. >> My final question I want to ask you is when you go to your event coming up invisible clouds, visible IT, you got to give the customer the 20 mile stare. You got to show 'em the 20 mile vision and the bridge to the future that they want to cross with you, that's the main value every company has to do as CEO. What is that story, what's the pitch to the customer saying we've got you covered today as you're organically building that operational cloud path, but I really want to know that I have a partner for the next generation, what's that story that you tell them? >> Yeah, I mean, even as I said before. Any big project, whether it's Panama Canal Suez Canal, Eurotunnel, you have to dig it from both sides and then you eventually shake hands and it becomes a historic picture, which is what we've known about the way the English side and the French side met. I think the way CIOs are talking about the cloud, the way grassroots is perceiving more of the cloud as you called it operationalizing. I think we really have to do it from both sides. And we really don't talk about the three D's. Data, we've done so well in data. We've done so well in design, we've done so well in delivery, and then at times we've actually screwed up like in the last two, three, four years, we might have gotten more complicated, we might have gotten more complex, so we go and even ask for forgiveness and open ourselves up, talk about the evaluability of the company and people like that, they didn't want to connect to an auto machine, but they wanted to connect to humans on this other side. As a business, we are not machines. We're actually humans, and that's what resonates in the conference. >> Dheeraj, thanks for coming in and sharing your insight, great to see you again, congratulations on the business performance, we'll see you at Nutanix Next in May, May 7th, thanks for coming in. >> Thank you, my pleasure. >> I'm John Furrier here in Palo Alto for CUBE Conversation, thanks for watching. (jazz music)