from around the globe it's thecube with digital coverage of exascale day made possible by hewlett packard enterprise welcome everyone to the cube celebration of exascale day ben bennett is here he's an hpc strategist and evangelist at hewlett-packard enterprise ben welcome good to see you good to see you too son hey well let's evangelize exascale a little bit you know what's exciting you uh in regards to the coming of exoskilled computing um well there's a couple of things really uh for me historically i've worked in super computing for many years and i have seen the coming of several milestones from you know actually i'm old enough to remember gigaflops uh coming through and teraflops and petaflops exascale is has been harder than many of us anticipated many years ago the sheer amount of technology that has been required to deliver machines of this performance has been has been us utterly staggering but the exascale era brings with it real solutions it gives us opportunities to do things that we've not been able to do before if you look at some of the the most powerful computers around today they've they've really helped with um the pandemic kovid but we're still you know orders of magnitude away from being able to design drugs in situ test them in memory and release them to the public you know we still have lots and lots of lab work to do and exascale machines are going to help with that we are going to be able to to do more um which ultimately will will aid humanity and they used to be called the grand challenges and i still think of them as that i still think of these challenges for scientists that exascale class machines will be able to help but also i'm a realist is that in 10 20 30 years time you know i should be able to look back at this hopefully touch wood look back at it and look at much faster machines and say do you remember the days when we thought exascale was faster yeah well you mentioned the pandemic and you know the present united states was tweeting this morning that he was upset that you know the the fda in the u.s is not allowing the the vaccine to proceed as fast as you'd like it in fact it the fda is loosening some of its uh restrictions and i wonder if you know high performance computing in part is helping with the simulations and maybe predicting because a lot of this is about probabilities um and concerns is is is that work that is going on today or are you saying that that exascale actually you know would be what we need to accelerate that what's the role of hpc that you see today in regards to sort of solving for that vaccine and any other sort of pandemic related drugs so so first a disclaimer i am not a geneticist i am not a biochemist um my son is he tries to explain it to me and it tends to go in one ear and out the other um um i just merely build the machines he uses so we're sort of even on that front um if you read if you had read the press there was a lot of people offering up systems and computational resources for scientists a lot of the work that has been done understanding the mechanisms of covid19 um have been you know uncovered by the use of very very powerful computers would exascale have helped well clearly the faster the computers the more simulations we can do i think if you look back historically no vaccine has come to fruition as fast ever under modern rules okay admittedly the first vaccine was you know edward jenner sat quietly um you know smearing a few people and hoping it worked um i think we're slightly beyond that the fda has rules and regulations for a reason and we you don't have to go back far in our history to understand the nature of uh drugs that work for 99 of the population you know and i think exascale widely available exoscale and much faster computers are going to assist with that imagine having a genetic map of very large numbers of people on the earth and being able to test your drug against that breadth of person and you know that 99 of the time it works fine under fda rules you could never sell it you could never do that but if you're confident in your testing if you can demonstrate that you can keep the one percent away for whom that drug doesn't work bingo you now have a drug for the majority of the people and so many drugs that have so many benefits are not released and drugs are expensive because they fail at the last few moments you know the more testing you can do the more testing in memory the better it's going to be for everybody uh personally are we at a point where we still need human trials yes do we still need due diligence yes um we're not there yet exascale is you know it's coming it's not there yet yeah well to your point the faster the computer the more simulations and the higher the the chance that we're actually going to going to going to get it right and maybe compress that time to market but talk about some of the problems that you're working on uh and and the challenges for you know for example with the uk government and maybe maybe others that you can you can share with us help us understand kind of what you're hoping to accomplish so um within the united kingdom there was a report published um for the um for the uk research institute i think it's the uk research institute it might be epsrc however it's the body of people responsible for funding um science and there was a case a science case done for exascale i'm not a scientist um a lot of the work that was in this documentation said that a number of things that can be done today aren't good enough that we need to look further out we need to look at machines that will do much more there's been a program funded called asimov and this is a sort of a commercial problem that the uk government is working with rolls royce and they're trying to research how you build a full engine model and by full engine model i mean one that takes into account both the flow of gases through it and how those flow of gases and temperatures change the physical dynamics of the engine and of course as you change the physical dynamics of the engine you change the flow so you need a closely coupled model as air travel becomes more and more under the microscope we need to make sure that the air travel we do is as efficient as possible and currently there aren't supercomputers that have the performance one of the things i'm going to be doing as part of this sequence of conversations is i'm going to be having an in detailed uh sorry an in-depth but it will be very detailed an in-depth conversation with professor mark parsons from the edinburgh parallel computing center he's the director there and the dean of research at edinburgh university and i'm going to be talking to him about the azimoth program and and mark's experience as the person responsible for looking at exascale within the uk to try and determine what are the sort of science problems that we can solve as we move into the exoscale era and what that means for humanity what are the benefits for humans yeah and that's what i wanted to ask you about the the rolls-royce example that you gave it wasn't i if i understood it wasn't so much safety as it was you said efficiency and so that's that's what fuel consumption um it's it's partly fuel consumption it is of course safety there is a um there is a very specific test called an extreme event or the fan blade off what happens is they build an engine and they put it in a cowling and then they run the engine at full speed and then they literally explode uh they fire off a little explosive and they fire a fan belt uh a fan blade off to make sure that it doesn't go through the cowling and the reason they do that is there has been in the past uh a uh a failure of a fan blade and it came through the cowling and came into the aircraft depressurized the aircraft i think somebody was killed as a result of that and the aircraft went down i don't think it was a total loss one death being one too many but as a result you now have to build a jet engine instrument it balance the blades put an explosive in it and then blow the fan blade off now you only really want to do that once it's like car crash testing you want to build a model of the car you want to demonstrate with the dummy that it is safe you don't want to have to build lots of cars and keep going back to the drawing board so you do it in computers memory right we're okay with cars we have computational power to resolve to the level to determine whether or not the accident would hurt a human being still a long way to go to make them more efficient uh new materials how you can get away with lighter structures but we haven't got there with aircraft yet i mean we can build a simulation and we can do that and we can be pretty sure we're right um we still need to build an engine which costs in excess of 10 million dollars and blow the fan blade off it so okay so you're talking about some pretty complex simulations obviously what are some of the the barriers and and the breakthroughs that are kind of required you know to to do some of these things that you're talking about that exascale is going to enable i mean presumably there are obviously technical barriers but maybe you can shed some light on that well some of them are very prosaic so for example power exoscale machines consume a lot of power um so you have to be able to design systems that consume less power and that goes into making sure they're cooled efficiently if you use water can you reuse the water i mean the if you take a laptop and sit it on your lap and you type away for four hours you'll notice it gets quite warm um an exascale computer is going to generate a lot more heat several megawatts actually um and it sounds prosaic but it's actually very important to people you've got to make sure that the systems can be cooled and that we can power them yeah so there's that another issue is the software the software models how do you take a software model and distribute the data over many tens of thousands of nodes how do you do that efficiently if you look at you know gigaflop machines they had hundreds of nodes and each node had effectively a processor a core a thread of application we're looking at many many tens of thousands of nodes cores parallel threads running how do you make that efficient so is the software ready i think the majority of people will tell you that it's the software that's the problem not the hardware of course my friends in hardware would tell you ah software is easy it's the hardware that's the problem i think for the universities and the users the challenge is going to be the software i think um it's going to have to evolve you you're just you want to look at your machine and you just want to be able to dump work onto it easily we're not there yet not by a long stretch of the imagination yeah consequently you know we one of the things that we're doing is that we have a lot of centers of excellence is we will provide well i hate say the word provide we we sell super computers and once the machine has gone in we work very closely with the establishments create centers of excellence to get the best out of the machines to improve the software um and if a machine's expensive you want to get the most out of it that you can you don't just want to run a synthetic benchmark and say look i'm the fastest supercomputer on the planet you know your users who want access to it are the people that really decide how useful it is and the work they get out of it yeah the economics is definitely a factor in fact the fastest supercomputer in the planet but you can't if you can't afford to use it what good is it uh you mentioned power uh and then the flip side of that coin is of course cooling you can reduce the power consumption but but how challenging is it to cool these systems um it's an engineering problem yeah we we have you know uh data centers in iceland where it gets um you know it doesn't get too warm we have a big air cooled data center in in the united kingdom where it never gets above 30 degrees centigrade so if you put in water at 40 degrees centigrade and it comes out at 50 degrees centigrade you can cool it by just pumping it round the air you know just putting it outside the building because the building will you know never gets above 30 so it'll easily drop it back to 40 to enable you to put it back into the machine um right other ways to do it um you know is to take the heat and use it commercially there's a there's a lovely story of they take the hot water out of the supercomputer in the nordics um and then they pump it into a brewery to keep the mash tuns warm you know that's that's the sort of engineering i can get behind yeah indeed that's a great application talk a little bit more about your conversation with professor parsons maybe we could double click into that what are some of the things that you're going to you're going to probe there what are you hoping to learn so i think some of the things that that are going to be interesting to uncover is just the breadth of science that can be uh that could take advantage of exascale you know there are there are many things going on that uh that people hear about you know we people are interested in um you know the nobel prize they might have no idea what it means but the nobel prize for physics was awarded um to do with research into black holes you know fascinating and truly insightful physics um could it benefit from exascale i have no idea uh i i really don't um you know one of the most profound pieces of knowledge in in the last few hundred years has been the theory of relativity you know an austrian patent clerk wrote e equals m c squared on the back of an envelope and and voila i i don't believe any form of exascale computing would have helped him get there any faster right that's maybe flippant but i think the point is is that there are areas in terms of weather prediction climate prediction drug discovery um material knowledge engineering uh problems that are going to be unlocked with the use of exascale class systems we are going to be able to provide more tools more insight [Music] and that's the purpose of computing you know it's not that it's not the data that that comes out and it's the insight we get from it yeah i often say data is plentiful insights are not um ben you're a bit of an industry historian so i've got to ask you you mentioned you mentioned mentioned gigaflop gigaflops before which i think goes back to the early 1970s uh but the history actually the 80s is it the 80s okay well the history of computing goes back even before that you know yes i thought i thought seymour cray was you know kind of father of super computing but perhaps you have another point of view as to the origination of high performance computing [Music] oh yes this is um this is this is one for all my colleagues globally um you know arguably he says getting ready to be attacked from all sides arguably you know um computing uh the parallel work and the research done during the war by alan turing is the father of high performance computing i think one of the problems we have is that so much of that work was classified so much of that work was kept away from commercial people that commercial computing evolved without that knowledge i uh i have done in in in a previous life i have done some work for the british science museum and i have had the great pleasure in walking through the the british science museum archives um to look at how computing has evolved from things like the the pascaline from blaise pascal you know napier's bones the babbage's machines uh to to look all the way through the analog machines you know what conrad zeus was doing on a desktop um i think i think what's important is it doesn't matter where you are is that it is the problem that drives the technology and it's having the problems that requires the you know the human race to look at solutions and be these kicks started by you know the terrible problem that the us has with its nuclear stockpile stewardship now you've invented them how do you keep them safe originally done through the ascii program that's driven a lot of computational advances ultimately it's our quest for knowledge that drives these machines and i think as long as we are interested as long as we want to find things out there will always be advances in computing to meet that need yeah and you know it was a great conversation uh you're a brilliant guest i i love this this this talk and uh and of course as the saying goes success has many fathers so there's probably a few polish mathematicians that would stake a claim in the uh the original enigma project as well i think i think they drove the algorithm i think the problem is is that the work of tommy flowers is the person who took the algorithms and the work that um that was being done and actually had to build the poor machine he's the guy that actually had to sit there and go how do i turn this into a machine that does that and and so you know people always remember touring very few people remember tommy flowers who actually had to turn the great work um into a working machine yeah super computer team sport well ben it's great to have you on thanks so much for your perspectives best of luck with your conversation with professor parsons we'll be looking forward to that and uh and thanks so much for coming on thecube a complete pleasure thank you and thank you everybody for watching this is dave vellante we're celebrating exascale day you're watching the cube [Music]

>>long from Las Vegas. It's the Q covering a ws re invent 2019. Brought to you by Amazon Web service is and in along with its ecosystem partners. >>Welcome back to the Cube. We are in Las Vegas, Lisa Martin with John Wall's. I'm very excited that we're kind of color coordinated >>way. Didn't compare notes to begin with, but certainly the pink thing. It's worth it if >>you like. You complete me. >>Oh, thank you. Really, Joe, I don't hear that very often. My wife says that >>you tell that we're at the end of day one of the coverage of A W s three in bed. Good day, though. Yes, it has been very excited. We have a couple of guests joining us for our final segment on this. Please welcome. We have Bill Gerard CTO of Digital Transformation and Scale solutions at Intel Bill, welcome to our show. >>Thank you very much. Happy to be here >>And one of our friends. That's no stranger to the Cube. One of our former host, Bobby Allyn, the CEO of Cloud Generate. Bobby. >>Thank you. Thank you for having us. >>Guys, here we are. This there has not been a lull in the background noise all day. Not reinvent day one. But Bobby want to start with you. Talk to her audience about cloud genera. Who are you guys? What do you do? And what's different about what you're delivering? >>One of the first things is different about Claude Generous where we're located. So we're in Charlotte, which I call Silicon South. So we're kind of representing the East Coast, and we're a company that focuses, focuses on helping with workload, placement and transformation. So where you don't know whether something should go on from off grim. If you put it in Amazon, which service's should have consumed licensing models? Pricing models way help you make data driven decisions, right? So you're not just going based on opinion, you're going based on fact. >>And that's challenging because, you know, in the as, as John Ferrier would say, No Cloud Wanda Otto, which was compute network storage, it was the easy I shouldn't say easy, but the lift and shit applications that enterprises do are these workloads should go to the cloud. Now we have you know what's left over, and that's challenging for organization. Some of the legacy once can't move. How do you help from a Consul Tatum's down point that customers evaluate workloads? What data are they running? What the value that data has and if they are able to move some of those more challenging applications. >>So part of the framework for us, Lisa, is we want to make sure we understand what people are willing and able to change right, because sometimes it's not just about lower costs. Sometimes it's about agility, flexibility, deploying a different region. So what we often start with his wit is better look like you would assist us with life for your organization. And so then, based on that, we analyze the applications with an objective, data driven framework and then make sure the apse land where they're supposed to go. We're not selling any skewer product. We're selling advice to give you inside about what you should do, >>Bobby, I think. And maybe Bill to you could chime in here on this. If you give people a choice, What does this look like? What you know, What do you want? I don't want to do anything right. I want to stay put, right? But that obviously that's not an option, But you I'm sure you do get pushed back quite a bit from these almost the legacy mindset. And we've talked a lot about this whole transformation versus transition. Some people don't want to go, period. So how do you cajole them? Persuade them bring them along on this journey? Because it's gonna be a long trip. Yeah, I think you gotta pack a lunch. >>It's a good point. I think what we've seen, most of them have data experience that this is a tried and elements didn't get the results that they expected. This is where you know, the partnership that we have with call General. Really? You know that data driven, intelligent, based planning is super important, right? We want to really fundamentally health organizations move the right workloads, make sure they get the right results and not have to redo it. Right? And so part of that, you know, move when you're either past scars or not used to what you're doing. Give him the data and the information to be able to do that intelligently and make that as fast as they can. And you know, at the right, you know, experience in performance from a capability perspective. >>So so many businesses these days, if they're not legacy if they're not looking in the rear view mirror, what is the side mirror site? Objects are closer than they appear, even for Amazon. Right? For all of these companies, there are smaller organizations that might be born in a cloud compared to the legacy two words. And if they're not looking at, we have to transform from the top down digitally, truly transform. Their business may not be here in a year or two, so the choice and I think they need to pack a lunch and a hip flask for this because it's quite the journey. But I'm curious with the opportunity that cloud provides. When you have these consultation conversations, what are This? Could be so transformative not just to a business, but to a do an entire industry. Bill talked to us from your perspective about some of the things that you've seen and how this next generation of cloud with a I machine learning, for example, can can really transfer like what's the next industry that you think is prime to be really flipped upside down? >>Well, the good news is I think most of the industries in the segment that we talked to have realized they need to some level of transformation. So doing the business as usual really isn't an option to really grow and drive in the future. But I do think the next evolution really does center on what's happening in a I and analytics. Whether it's, you know, moving manufacturing from video based defect detection, supply chain integrity. You know what's happening from a retail was really the first in that evolution, but we see it in health care in Federal Data Center modernization, and it's really moving at a faster pace and adopting those cloud technologies wherever they needed, both in their data center in the public, cloud out of the edge. And we'll start to see a real shift from really consolidation in tow. Large hyper converts, data centers to distributed computing where everything again. And that's where we're excited about the work we're doing with the Amazon, the work we're doing with Eyes V partners to be at the capability where they need it, but I think it will be really the next. Evolution of service is everywhere. >>Never talk us through an example or use case of a customer that you're working with, a cloud genera with intel and and a W S. What does that trifecta look like for, say, a retailer or financial service is organization >>so that that looks like this? ELISA. When we when we talk about workload placement, we think that most companies look at that as a single question. It's at least a five fold question. Right there is the venue. There's the service. There's the configuration, the licensing model and the pricing model. You need to look at all five of those things. So even if you decided on a DBS is your strategic partner, we're not done yet. So we have a very large financialservices customer that I can't name publicly. But we've collaborated with them to analyze tens of thousands of workloads, some that go best off from some that go best on for him. And they need guidance and coaching on things like, Are you paying for redhead twice your pay for licensing on him? Are you also paying for that in the cloud? There are things that maybe should be running an RT s database as a service. Here's your opportunity to cut down on labor and shift some of the relationships tohave, toe re index and databases is not glamorous or differential to value for your business. Let's take advantage of what a TBS does well and make this better for your company. One of the things that I want to kind of introduce to piggyback on your question. We lean on people process technology as kind of the three, the three legged horse in the Enterprise. I want to change that people process product or people process problem. We're falling in love with the tech and getting lazy. Technology should be almost ubiquitous or under the covers to make a product better or to solve a problem for the customer. >>Well, maybe on that, I mean automation concern to come in and make a big play here because we're taking all these new tasks if you could automate them that you free your people, your developers to do their thing right. So you raise an interesting point on that about being lazy and relying on things. But yet you do want off put our offload some of these nasty not to free up that creativity and free up the people to do what they're supposed to be doing. It's a delicate balance, though, isn't it? It is. It is. This >>is where I think the data driven, you know, informed decisions important. We did a lot of research with Cloud Jenner and our customers, and there's really four key technical characteristics when evaluating workload. The 1st 1 of course, is the size of the data. Where is the created words They use Words that consumed the 2nd 1? Is the performance right? Either performance not only to other systems around it or the end user, but the performance of the infrastructure. What do you need out of the capability? The level of integration with other systems? And then, of course, security. We hear that time and again, right? Regulatory needs. What are we having from top secret data to company sensitive data? Really Getting that type of information to drive those workload placement decision becomes at the forefront of that on getting, you know, using cloud gender to help understand the number of interfaces in and out the sides of the data. The performance utilization of the system's really helps customers understand how to move the right workload. What's involved and then how to put that in the right eight of us instance, and use the right ideas capabilities, >>and you and you both have hit on something here because the complexity of this decision, because it's multi dimensional, you talked about the five points a little bit ago. Now you talked about four other factors. Sue, this is not a static environment, No, and to me that as you're making a decision, that point is what's very difficult for, I would assume for the people that you're interfacing with on the company level. Yes, because it's a moving target for them, right? They just it's it's dynamic and changing your data flows exponentially. Increasing capabilities are changing. How do you keep them from just breaking down? >>I don't want to jump in on that, because again, I'm going to repeat this again. That my thesis is often technology is the easy part. We need to have conversations about what we want to do. And so I had a conversation earlier today. Think of Amazon like a chef. They could make anything I want, but I need to decide what I want to eat. If I'm a vegan and he wants steak. That's not Amazons fault. If they can't cook something, that's a mismatch of a bad conversation. We need to communicate. So what I'm finding is a lot of executives are worried about this. There were Then you're going to give me the right the wrong answer to the right question. The reality is you may have the wrong question. First of all right, the question is usually further upstream, so the worry that you're gonna give me the wrong answer to the right question. But often you need to worry that you're getting your starting with the wrong question. You're gonna get the right answer asked the right question first. And then you got a chance to get to the final destination. But >>and then he in this multi cloud world that many organizations live in, mostly not My strategy could be by Emma A could be bi developer preference for different solutions. A lot of Serios air telling us we've inherited a lot of this multi cloud and technical debt. Exactly. So does not just compound the problem because to your point, I mean you think of one way we hear so many different stats about the number of clouds that on average enterprises using is like 5 to 9. That whole world. That's a reality for organizations. So in terms of how the business can be transformed by what you guys are doing together, it seems like there's a tremendous opportunity there. But to your point, Bobby, where do you start? How do you help them understand what? That right first question is at the executive level so that those four technical points that Bill talked about Tek thee you know, the executive staff is all on board with Yes, this is the question we're asking then will understand it. The technology is right. Sold >>it. It's got to start with, Really? What? The company's business imperatives, right? It can't start with an I t objective. It's it's Are we moving into new markets? Do we need thio deploy capabilities faster? Are we doing a digital customer experience? Transformation? Are we deploying new factories, new products into new regions, and so really the first areas? What's the core company strategy, imperatives of the business objectives? And >>then how >>does I t really help them achieve that? In some cases, it may be we have to shift and reduce our data center footprints way have to move capabilities to where we have a new region. Deployments, right? We've got to get him over to Europe. We don't have capabilities in Europe. We're going to Asia. I've got a mobile sales force now where I need to get that customer, meet the customer where they're doing, you know, in the retail store, and >>that >>really then leads quite simply, too. What are the capabilities that we have in house that we're using? >>How are >>they being utilized? And he's using them, and then how do we get them to where they need to be? Some cases accost, imperative. Some cases and agility, Time to market and another's and we're seeing this more often is really what are the new sets of technologies? A. I service is training in forgetting that we're not experience to do and set up, and we don't want to spend the time to go train our infrastructure teams on the technology. So we'll put our data scientists in there figuring out the right set of workloads, the right set of technology, that we can then transform and move our applications to utilize it really starts, I think with the business conversation, or what's the key inflection point that they're experiencing? >>And have you seen that change in the last few years that now it's where you know, cloud not cloud. What goes on Cloud was an I t conversation to your point, Bill. And then the CEO got involved in a little bit later. But now we're we're seeing and hearing the CEO has got to be involved from a business imperative perspective. >>Share some data, right? Uh, so, you know, a couple of years ago, everybody was pursuing cloud largely for cost. Agility started to become primary, and that's still very important. A lot of the internal enterprise data modernizations were essentially stalled a bit because they were trying to figure how much do we move to the the public cloud, right. We want to take advantage of those modern service is at that time, we did a lot of research with our partners. He was roughly 56% of enterprise workload for in their own data center. You know, the rest of them Republic Cloud. And then we saw really the work, the intelligent workload discussion that says we've had some false starts. Organizations now really consistently realize they need both, you know, their own infrastructure and public cloud, and we've actually seen on increase of infrastructure modernization. While they're moving more and more stuff to the cloud, they're actually growing there on centre. It's now roughly 59% on Prem today for that same business, and that's largely because they're using more. Cloud service is that they're also even using Maur on premise, and they're realizing it's a balance and not stalling one or starving one and then committing to the other the committing to both and really just growing the business where it needs to go. >>Strategic reasons. All right? >>Yes, well, there should be four strategic reasons. There aren't always back to your question about which question asked. One of the questions I often ask is, What do you think the benefits will be if you go to cloud? And part of what happens is is not a cloud capability? Problem is an expectation problem. You're not gonna put your GOP system in the cloud and dropped 30% costs in a month, and so that's where we need to have a conversation on, You know, let's iterating on what this is actually gonna look like. Let's evolve the organization. Let's change our thinking. And then the other part of this and this were clouded or an intel come in. Let's model with simulation looks like. So we're gonna take those legacy work clothes unless model containers. Let's model Micro Service is so before you have to invest in transformation to may not make sense. Let's see what the outcome's look like through simulation through a through M l and understand. Where does it make sense to apply? The resource is, you know, to double click on that solution that will help the business. >>I was gonna finish my last question, Bobby, with you saying, Why, Cloud General? But I think you just answered that. So last question for you, though, from from an expectation perspective, give me one of your favorite examples of customer whatever kind of industry there and that you've come in and helped them really level, set their expectations and kick that door wide open. >>That's tough, many >>to choose from. >>Yeah, let me let me try to tackle that one quickly. Store's computer databases. Those are all things that people look at I think what people are struggling with the most in terms of kind of expectations is what they're willing and able to change. So this is kind of what I leave on. Bill and I talked about this earlier today. A product is good, a plan is better. A partnership is best. Because with the enterprises of saying is, we're overwhelmed. Either fix it for me or get in there with me and do it right. Be in this together. So what we've learned is it's not about were close applications. It's all kind of the same. We need help. We're overwhelmed. I want a partner in telling Claude Juncker the get in this thing with me. Help me figure this out because I told you this cloud is at best a teenager. They just learned how to drive is very capable, but it needs some guard rails. >>I love that. Thanks you guys So much for explaining with Johnny what you guys are doing together and how you're really flipping the model for what customers need to be evaluated and what they need to be asking. We appreciate your time. >>Thank you for having us >>our pleasure. Thank you. for John Wall's I'm Lisa Martin. You've been watching the Cube at Reinvent 19 from Vegas. Wants to go tomorrow.

>>Live from Las Vegas. It's the cube covering UI path forward Americas 2019 brought to you by UI path. Welcome >>back everyone to the cubes live coverage of UI path forward. I'm your host, Rebecca Knight, coasting alongside of Dave Volante. We have two guests for the segment. We have Chris career. He is the senior director of service delivery at century link. Thanks so much for coming on the show. And Kumar, he is the client partner at Infosys. Thank you so much for joining us. So show G I'm going to start with you. We're hearing so much about this automation first era and when you are partnering with a company, we hear that automation first requires this real mindset shift. So I'm wondering if you could walk us through the process of when you are partnering with a company and you are saying we will help you add more automation to your work processes. How do you do it? How do you get the company to sort of adopt that mindset shift? >>So it is basically changing the mindset of the individual contributor. So the first thing is how do we make them adapt? Those changes into the organization and making sure that the learning experience and the Cuban experience are getting tased, are adapting by the individual contributor. That is more important for Infosys as a client partner to Centrelink. We are always striving for. >>So Chris, maybe talk a little about your role. Your title is, has service delivery in it. What does that, what does that mean? So we're, we're of course we're a telecommunications providers, so of course we sell our products, we have an extensive product portfolio. Uh, once it's sold, we have to fulfill those products. And that's what our service delivery comes in. Uh, everything from order entry all the way through to activation and delivery to the customer of the final solution of whatever it is they purchase from us. All right, let's get into it. So we just had Gardner on, they were saying, Hey, you know, there's a, there's a lot of things that can be cleaned up, cleaned up in there, >> a lot of things in there. Um, if you think about technology today, telecommunications, especially as a, as a industry, um, it's an industry of aggregation at this point. >>And it has been for a number of years. So with aggregation you, you end up with is um, I use kind of a phrase where we have an aim over the front door and that's the name of how we do business. Uh, that's, that's becomes a brand behind the front door. We're still operating as many of those individual companies still. So we're trying to stitch together in the background, the various networks, delivery options, products, et cetera, in a seamless way for our customers. So to do that, of course using automation becomes a very powerful tool for us right now to do everything that we would have to stitch together with human glue. Um, that's something that we have to deal with on a day in and day out basis. An area of the I focus on is ordering. I'm ordering in our space is highly manual. You're doing a lot of transcription, so to give sales the right tools so they can sell a, you give them a very elegant front end of the house. >>And many of the discussions we've had today, uh, have centered around the front of the house, looks very elegant and very smooth. And the back of the house is where a lot of the stitch together work happens. And that's where that automation comes into play. So partnering with somebody like a shadier, uh, trying to get onto the front end of how do we smooth those things out internally. Um, we're an operations organization. What we are always challenged with is how do we provide the service and product to our customers at an efficient price point. Um, people is a, is a margin drag at the end of the day. Um, but also we want our folks to be doing things that are more interesting. Uh, which is what automation is really about is that digital transformation and how do you transform your employees with you. Uh, and I'm definitely in an area where I have an opportunity there. >>And so that is, that is, that is what you, I've had this really selling, it's this idea that here are your, your employees who are doing these mundane tasks, these dreariness, this Drudge drudgery. And we are giving them an opportunity to do more of the creative work to use their brains. And more interesting and compelling ways. Shoji I mean is, is that the value props, I mean, how much are customers buying into that? I mean, is that, and is that immediate? Is it immediately clear to them, Oh, since I don't have to do that type of data entry anymore, I can now do this. I mean, is it obvious how you'll spend your, the rest of your time? >>So it is more about the analyzing the, what is happened in the history and making sure that how their data can be used and put it into the AI and making sure that how the automations can be revealed through that. That is a way to, you know, out of power we are making as a journey in central link as well, like in, along with the, the other telco organizations we are doing here. So specifically that is what, yea and automation we are specifically into making sure that how the customers can take advantage of the practice using the tools, like a UI path. >>So where's your expertise? automation, RPA, telecommunications, ordering, all of the above. So my ex >>is telecommunication. I have been with the telecommunication companies for about 25 years now. I'm majorly going through the raw from >>push button telephones to the era now it is standing up to fighting. So that's my, uh, expedience. You sound like an old man. Yeah. So Chris, when you do a business case for doing in RPA, I mean, I know a lot of CFOs and where's the hard dollars? You know, where are we going to save money? Well, we're going to, we're going to shift people from here to here and they going to do more productive work. Where's my hard dollars? Did you go through that or is it so blatantly where the potential >>is? Talk about the business case. It's not always a blatantly obvious, right? So when I'm building a business case, there's a number of things as an operations leader that I have to focus on, right? I own budget for my organization. So at the end of the day, I own making sure that I hit my budget targets for the business businesses. Always you're finding those, um, based on our opportunities in the marketplace, so forth. But I also have a lot of people that work for me. So part of the bigger area for me, and it's an area that I've spent a lot of time with consultants like shot to you on, is how do I transform my workforce? How do I bring them with me? How do I make it less scary for my employees? Because the first reaction, human reaction to employees who have been doing a function for so long, we heard it today about the cognitive changes, opening up your brain path, so on and so forth. >>Um, and the first reaction to them is going to be that shortest path to, Oh my God, I'm gonna lose my job and I have to then become a salesperson in addition to operations leader in addition to a budget manager to say, no, this is an opportunity for you to do something more interesting. You have that 20 years of experience in the industry. I want to use that knowledge in a different way. I want to open up some doors and career paths for you. Uh, so for me it's interesting and trying to break a sedentary workforce into a more dynamic workforce to initiate them into the digital age. When I write a business case, mostly what I'm looking at is very some of the it classical things. How do I save those dollars? What's my payback? What's my return on investment? More and more in the automation space, we're thinking much more customer first employee experience first. >>How do I provide the customer a better experience? How do I provide an employee a better experience? So the business cases have become a little bit more challenging, uh, cause you're also have offering some soft benefits, which is our employee experiences is a really big deal. Our customer's experience is going to be how we differentiate ourselves, uh, could be in the difference between the next sale and not making the next sale. So those have to get factored into the business cases and it becomes a bit, uh, art and science on how to quantify that. So there's a lot to unpack there. I want to start with kind of the, the, the sentiment of, Hey, I'm gonna lose my job. How did you deal with that, uh, with your team? Is it carrot stick combination so they can try it. I think a lot of it is first listening. >>Um, at least my style as a leader is to listen to what my people are saying first and then address it with as many facts as I possibly can. Right. Um, most folks think emotion first. Um, and, and you can end up in an adversarial type of situation there where you really don't want to be in an adversarial situation with your employees. You want your employees to support the change, the transformation that, that shift into a digital space. So for me, I have to listen to a lot first. And depending on who I'm listening to, I'm getting a very different story. I have employees from millennials to baby boomers. So as a result, each one of them were coming from a very different place, a carrot versus stick. Interesting concept because from a carrot perspective, the companies getting the care that the employee may not necessarily see that at first where we're saying, Hey, we want you to do more interesting work. >>But to them, they feel it. It's more of a stick at first. Uh, so it's interesting. Um, in my space it's been a, I've consulted with, with other folks, I've talked to a lot of my peer leaders, um, seeking a lot of advice on how do we navigate this cause we're cutting a new path as leaders. Um, I'm more akin to a baby boomer and a Jenner in, you know, a gen X type of a person. That's who I came up under an industry. So I have to temper my own thinking. Um, so it's interesting because for instance, I looked at my people managers and maybe it's a little bit more stick with my people managers where it's very much of a, gives me ideas. How do we crowdsource that, that information, our employees are going to be the best source of our, of our ideas for automating. >>What do we automate? How do we automate the things that they really disliked doing first? Right? So you're kind of giving them a carrot with, you're giving them a little bit of quick wins. We've heard about that today as well. Um, but then it becomes a matter of what about the individual contributor developer, right? How do I take somebody today who hasn't maybe been retooled from a career perspective in many, many years and give them the ability to say, no, you're not a programmer but you can automate things and UI path gives us some of those tools to do that with the purveyors of RPA would ha would tell you that people actually love it because it's taking away that undifferentiated heavy lifting. Once they get a taste for it and they can do other things, frees up time. Having said that, they may be really good at entering data into a form. >>They may not be good at doing other strategic things, so there's gotta be some kind of retraining exercise to. My question is, are you seeing either specifically at century link or broadly in the industry some kind of notion of gain share? In other words, if you're going to save this much time slash money and your business case, we'll give you back a portion, I don't know, 30% 50% whatever, so that you can retrain people. You can actually advance their careers. So you see you having conversations like that or is it actually where I think we're having conversations akin to that. Not necessarily have that conversation. Um, conversations that I'm having are more of the nature of, you know, chicken and the egg kind of a thing. When it comes automation, you're under budgetary pressures. How do you take out your employee, retool them and train them on how to automate something using UI pads, tool suite, um, and then re-invest that same knowledge, right? >>Because if you automate something, you free up somebody else you can train to do more automation. Um, a lot of our, our employees who are first adopters, if you will, the willing hands that are going up. Some are millennials, some are many other generations. Um, but it's, it's been there very interesting because it's very powerful for those who have learned the tools and is very powerful and a peer to peer solicitation of, look what I can do for you. We've been complaining about this manual step for 20 years. How come it, we're still having to do it. So it the becomes a bit of a self fulfilling prophecy, right? You get those who evangelize it based on learning the new technology and then they train into their peers. Um, retooling employees is something that you brought up or at least that's what a little bit of what I heard. >>Um, you know, many areas, Hey, I've been doing data entry for a long time. What else am I good at? And a lot of that just becomes creativity. Who else? Who do you interact with the most? Who are the employees or who are the customers, who are the sales organizations, et cetera, where you end up, they know your name, they're going to call you because you know that answer. Well guess what? You're a knowledge base for them. And that often becomes where I ended up retooling and re shifting employees. They see new opportunities that they never seen before. One of the most interesting things I think I hear constantly is I never expected to be in sales, uh, from an operations type of person. They always think of a salesman as that salesperson kind of personality. And they don't see themselves in it, but they never think of themselves as sales support, which is that, that's what they end up becoming. Um, and they always were to begin with. They just never thought of themselves that way. So we're moving a lot more of my customers or my employees, if you will, closer to the customer than they ever saw in themselves. And RPA is enabling that. So that's, that's kind of a, a knowledge revolution. It's a self actualization change. It becomes a skill add that they never thought they had. Um, they're all interesting concepts, but they all, you know, I'm learning something new every day as a leader. >>Well, and you're bringing up so many interesting points that, that what this revolution actually means for people's careers. I mean, the really the re rebooting of work and really changing how we spend our time at the office and changing what we do during the course of our day is shadier. I mean he, he, Chris has been talking about how people are now closer to the customer and therefore the human, the soft skills are becoming increasingly important. So how are you helping companies think through those challenges to make sure that their people do have the appropriate skills? And as Chris said, it can be the difference of not making a sale versus making a sale. >>So it is about, uh, it's about learning. Learning can make, uh, the people transform as well as the company's transformed. So while we are adopting technology, we needed to ensure that how do we ensure the learning platforms are brought in to ensure the, that is part of their curriculum. Like what we have done in four school or colleges in the organization, make it live enterprise for the every organization to move into a live organization. It is always about learning. So what emphasis does is about, it's about the knowledge, what we carry. So we have created platforms like legs for internal to our organization. And wingspan is an AR is an external customized version for all of our external customers that is plugging into all the transformation programs. What we do to ensure that the learning is Paladin for the transformation, why you are path, you look it up. >>There's um, um, we have looked at, looked at others and I think in my career you're always going to have multiple partners. Um, so when it comes to the UI path, it's one of those UI path invested very early. You know, they wanted to be that partner. I think today part of the message we heard, uh, from some of the UI path executives were that, uh, we want to be humble. Um, and therefore it's not always about, Hey, how do I win this dollar so much as I, how do I educate on technology? Um, and how do we help you transform and pull you forward to a certain degree. Um, so I think UI path has a lot of, um, very human possibilities and human traits and how it, it educates its clients. >>Judge generally just a question as a, as a buyer and a practitioner, if you have a choice between best of breed, um, and you know, a suite, right? Let's say, I don't know if you're an ERP customer, but some ERP vendor all of a sudden bolts, you know, RPA on to their solution. How do you decide the convenience of Oh yeah. All in one versus the best of breed? >>Um, I think it depends on the size of your firm because throughout my career I've seen many different answers to the same question. Um, shadier is probably had a relationship with me for a number of years, uh, in various forms if you will, as a consultant and a partner. Um, what he often hears from me is both I'm gonna do both. Um, because some way I'm going to learn something from each of those engagements. So more often than not, the answer is you do a lot. You do both. You don't just pick a single partner. Um, the smaller you are, the more likely you are to do a single partner. The larger you are, the less likely you are to do a single partner. Diversity is a good thing. And so was competition >>where it's still live by Chris shot. Thank you so much for coming on the Kiva. Great conversation. That's going. Sorry. I'm Rebecca Knight for Dave Volante. Stay tuned for more of the cubes live coverage of UI path forward.