(upbeat music) (logo shimmers) >> Good afternoon everyone, and welcome back to AWS re Invent 2022. We are live here from the show floor in Las Vegas, Nevada, we're theCUBE, my name is Savannah Peterson, joined by John Furrier, John, are you excited for the next segment? >> I love the innovation story, this next segment's going to be really interesting, an example of ecosystem innovation in action, it'll be great. >> Yeah, our next guests are actually award-winning, I am very excited about that, please welcome Alan and Becky from IBM. Thank you both so much for being here, how's the show going for ya? Becky you got a, just a platinum smile, I'm going to go to you first, how's the show so far? >> No, it's going great. There's lots of buzz, lots of excitement this year, of course, three times the number of people, but it's fantastic. >> Three times the number of people- >> (indistinct) for last year. >> That is so exciting, so what is that... Do you know what the total is then? >> I think it's over 55,000. >> Ooh, loving that. >> John: A lot. >> It's a lot, you can tell by the hallways- >> Becky: It's a lot. >> John: It's crowded, right. >> Yeah, you can tell by just the energy and the, honestly the heat in here right now is pretty good. Alan, how are you feeling on the show floor this year? >> Awesome, awesome, we're meeting a lot of partners, talking to a lot of clients. We're really kind of showing them what the new IBM, AWS relationship is all about, so, beautiful time to be here. >> Well Alan, why don't you tell us what that partnership is about, to start us off? >> Sure, sure. So the partnership started with the relationship in our consulting services, and Becky's going to talk more about that, right? And it grew, this year it grew into the IBM software realm where we signed an agreement with AWS around May timeframe this year. >> I love it, so, like you said, you're just getting started- >> Just getting started. >> This is the beginning of something magic. >> We're just scratching the surface with this right? >> Savannah: Yeah. >> But it represents a huge move for IBM to meet our clients where they are, right? Meet 'em where they are with IBM technology, enterprise technology they're used to, but with the look and feel and usage model that they're used to with AWS. >> Absolutely and so to build on that, you know, we're really excited to be an AWS Premier Consulting Partner. We've had this relationship for a little over five years with AWS, I'd say it's really gone up a notch over the last year or two as we've been working more and more closely, doubling down on our investments, doubling down on our certifications, we've got over 15,000 people certified now, almost 16,000 actually- >> Savannah: Wow. >> 14 competencies, 16 service deliveries and counting. We cover a mass of information and services from Data Analytics, IoT, AI, all the way to Modernization, SAP, Security Services, right. So it's pretty comprehensive relationship, but in addition to the fantastic clients that we both share, we're doing some really great things around joint industry solutions, which I'll talk about in a few minutes and some of those are being launched at the conference this year, so that's even better. But the most exciting thing to me right now is that we just found out that we won the Global Innovator Partner of the Year award, and a LATAM Partner of the Year award. >> Savannah: Wow. >> John: That's (indistinct) >> So, super excited for IBM Consulting to win this, we're honored and it's just a great, exciting part to the conference. >> The news coming out of this event, we know tomorrow's going to be the big keynote for the new Head of the ecosystem, Ruba. We're hearing that it's going to be all about the ecosystem, enabling value creation, enabling new kinds of solutions. We heard from the CEO of AWS, this nextGen environment's upon us, it's very solution-oriented- >> Becky: Absolutely. >> A lot of technology, it's not an either or, it's an and equation, this is a huge new shift, I won't say shift, a continuation for AWS, and you guys, we've been covering, so you got the and situation going on... Innovation solutions and innovation technology and customers can choose, build a foundation or have it out of the box. What's your reaction to that? Do you think it's going to go well for AWS and IBM? >> I think it fits well into our partnership, right? The the thing you mentioned that I gravitate to the most is the customer gets to choose and the thing that's been most amazing about the partnership, both of these companies are maniacally focused on the customer, right? And so we've seen that come about as we work on ways the customer to access our technology, consume the technology, right? We've sold software on-prem to customers before, right, now we're going to be selling SaaS on AWS because we had customers that were on AWS, we're making it so that they can more easily purchase it by being in the marketplace, making it so they can draw down their committed spin with AWS, their customers like that a lot- [John] Yeah. >> Right. We've even gone further to enable our distributor network and our resellers, 'cause a lot of our customers have those relationships, so they can buy through them. And recently we've enabled the customer to leverage their EDP, their committed spend with AWS against IBM's ELA and structure, right, so you kind of get a double commit value from a customer point of view, so the amazing part is just been all about the customers. >> Well, that's interesting, you got the technology relationship with AWS, you mentioned how they're engaging with the software consumption in marketplace, licensed deals, there's all kinds of new business model innovations on top of the consumption and building. Then you got the consulting piece, which is again, a big part of, Adam calls it "Business transformation," which is the result of digital transformation. So digital transformation is the process, the outcome is the business transformation, that's kind of where it all kind of connects. Becky, what's your thoughts on the Amazon consulting relationships? Obviously the awards are great but- >> They are, no- >> What's the next step? Where does it go from here? >> I think the best way for me to describe it is to give you some rapid flyer client examples, you know, real customer stories and I think that's where it really, rubber meets the road, right? So one of the most recent examples are IBM CEO Arvind Krishna, in his three key results actually mentioned one of our big clients with AWS which is the Department of Veterans Affairs in the US and is an AI solution that's helped automate claims processing. So the veterans are trying to get their benefits, they submit the claims, snail mail, phone calls, you know, some in person, some over email- >> Savannah: Oh, it gives me all the feels hearing you talk about this- >> It's a process that used to take 25 to 30 days depending on the complexity of the claims, we've gotten it down with AWS down to within 24 hours we can get the veterans what they need really quickly so, I mean, that's just huge. And it's an exciting story that includes data analytics, AI and automation, so that's just one example. You know, we've got examples around SAP where we've developed a next generation SAP for HANA Platform for Phillips Carbon Black hosted on AWS, right? For them, it created an integrated, scalable, digital business, that cut out a hundred percent the capital cost from on-prem solutions. We've got security solutions around architectures for telecommunications advisors and of course we have lots of examples of migration and modernization and moving workloads using Red Hat to do that. So there's a lot of great client examples, so to me, this is the heart of what we do, like you said, both companies are really focused on clients, Amazon's customer-obsessed, and doing what we can for our clients together is where we get the impact. >> Yeah, that's one of the things that, it sounds kind of cliche, "Oh we're going to work backwards from the customer," I know Amazon says that, they do, you guys are also very customer-focused but the customers are changing. So I'd love to get your reaction because we're now in that cloud 2.0, I call that 2.0 or you got the Amazon Classic, my word, and then Next Gen Cloud coming, the customers are different, they're transforming because IT's not a department anymore, it's in the DevOps pipeline. The developers are driving a lot of IT but security and on DataOps, it's the structural change happening at the customer, how do you guys see that at IBM? I know we cover a lot of Red Hat and Arvind talks to us all the time, meeting the customer where they are, where are they? Where are the customers? Can you share your perspective on where they are? >> It's an astute observation, right, the customer is changing. We have both of those sets of customers, right, we still have the traditional customer, our relationship with Central IT, right, and driving governance and all of those things. But the folks that are innovating many times they're in the line of business, they're discovering solutions, they're building new things. And so we need our offerings to be available to them. We need them to understand how to use them and be convenient for these guys and take them through that process. So that change in the customer is one that we are embracing by making our offerings easy to consume, easy to use, and easy to build into solutions and then easy to parlay into what central IT needs to do for governance, compliance, and these types of things, it's becoming our new bread and butter. >> And what's really cool is- >> Is that easy button- >> We've been talking about- >> It's the easy button. >> The easy button a lot on the show this week and if you just, you just described it it's exactly what people want, go on Becky. >> Sorry about that, I was going to say, the cool part is that we're co-creating these things with our clients. So we're using things like the Amazon Working Backward that you just mentioned.` We're using the IBM garage methodology to get innovative to do design working, design thinking workshops, and think about where is that end user?, Where is that stakeholder? Where are they, they thinking, feeling, doing, saying how do we make the easier? How do we get the easy button for them so that they can have the right solutions for their businesses. We work mostly with lines of business in my part of the organization, and they're hungry for that. >> You know, we had a quote on theCUBE yesterday, Savannah remember one of our guests said, you know, back in the, you know, 1990s or two 2000s, if you had four production apps, it was considered complex >> Savannah: Yeah. >> You know, now you got hundreds of workloads, thousands of workloads, so, you know, this end-to-end vision that we heard that's playing out is getting more complex, but the easy button is where these abstraction layers and technology could come in. So it's getting more complex because there's more stuff but it's getting easier because- >> Savannah: What is the magnitude? >> You can make it easier. This is a dynamic, share your thoughts on that. >> It's getting more complex because our clients need to move faster, right, they need to be more agile, right, so not only are there thousands of applications there are hundreds of thousands microservices that are composing those applications. So they need capabilities that help them not just build but govern that structure and put the right compliance over that structure. So this relationship- >> Savannah: Lines of governance, yeah- >> This relationship we built with AWS is in our key areas, it's a strategic move, not a small thing for us, it covers things like automation and integration where you need to build that way. It covers things like data and AI where you need to do the analytics, even things like sustainability where we're totally aligned with what AWS is talking about and trying to do, right, so it's really a good match made there. >> John: It really sounds awesome. >> Yeah, it's clear. I want to dig in a little bit, I love the term, and I saw it in my, it stuck out to me in the notes right away, getting ready for you all, "maniacal", maniacal about the customer, maniacal about the community, I think that's really clear when we're talking about 24 days to 24 hours, like the veteran example that you gave right there, which I genuinely felt in my heart. These are the types of collaborations that really impact people's lives, tell me about some of the other trends or maybe a couple other examples you might have because I think sometimes when our head's in the clouds, we talk a lot about the tech and the functionality, we forget it's touching every single person walking around us, probably in a different way right now than we may even be aware- >> I think one of the things that's been, and our clients have been asking us for, is to help coming into this new era, right, so we've come out of a pandemic where a lot of them had to do some really, really basic quick decisions. Okay, "Contact Center, everyone work from home now." Okay, how do we do that? Okay, so we cobbled something together, now we're back, so what do we do? How do we create digital transformation around that so that we are going forward in a really positive way that works for our clients or for our contact center reps who are maybe used to working from home now versus what our clients need, the response times they need, and AWS has all the technology that we're working with like Amazon Connect to be able to pull those things together with some of our software like Watson Assistant. So those types of solutions are coming together out of that need and now we're moving into the trend where economy's getting tougher, right? More cost cutting potentially is coming, right, better efficiencies, how do we leverage our solutions and help our clients and customers do that? So I think that's what the customer obsession's about, is making sure we really understand where their pain points are, and not just solve them but maybe get rid of 'em. >> John: Yeah, great one. >> Yeah. And not developing in a silo, I mean, it's a classic subway problem, you got to be communicating with your community if you want to continue to serve them. And IBM's been serving their community for a very long time, which is super impressive, do you think they're ready for the challenge? >> Let's do it. >> So we have a new thing on theCUBE. >> Becky: Oh boy. >> We didn't warn you about this, but here we go. Although you told, Alan, you've mentioned you're feeling very cool with the microphone on, so I feel like, I'm going to put you in the hot seat first on this one. Not that I don't think Becky's going to smash it, but I feel like you're channeling the power of the microphone. New challenges, treat it like a 32nd Instagram reel-style story, a hot take, your thought leadership, money clip, you know, this is your moment. What is the biggest takeaway, most important thing happening at the show this year? >> Most important thing happening at the show? Well, I'm glad you mentioned it that way, because earlier you said we may have to sing (presenters and guests all laughing) >> So this is much better than- >> That's actually part of the close. >> John: Hey, hey. >> Don't worry, don't worry, I haven't forgotten that, it's your Instagram reel, go. (Savannah laughs) >> Original audio happening here on theCUBE, courtesy of Alan and IBM, I am so here for it. >> So what my takeaway and what I would like for the audience to take away, out of this conversation especially, but even broadly, the IBM AWS relationship is really like a landmark type of relationship, right? It's one of the biggest that we've established on both sides, right- >> Savannah: It seems huge, okay you are too monolith in the world of companies, like, yeah- >> Becky: Totally. >> It's huge. And it represents a strategic change on both sides, right? With that customer- >> Savannah: Fundamentally- >> In the middle right? >> Savannah: Yeah. >> So we're seeing things like, you know, AWS is working with us to make sure we're building products the way that a AWS client likes to consume them, right, so that we have the right integration, so they get that right look and feel, but they still get the enterprise level capabilities they're used to from IBM, right? So the big takeaway I like for people to take, is this is a new IBM, it's a new AWS and IBM relationship, and so expect more of that goodness, more of those new things coming out of it. [John] Excellent, wow. >> That was great, well done, you nailed it. and you're going to finish with some acapella, right? (Alan laughs) >> You got a pitch pipe ready? (everyone laughs) >> All right Becky, what about you? Give us your hot take. >> Well, so for me, the biggest takeaway is just the way this relationship has grown so much, so, like you said, it's the new IBM it's the new AWS, we were here last year, we had some good things, this year we're back at the show with joint solutions, have been jointly funded and co-created by AWS and IBM. This is huge, this is a really big opportunity and a really big deal that these two companies have come together, identified joint customer needs and we're going after 'em together and we're putting 'em in the booth. >> Savannah: So cool. And there's things like smart edge for welding solutions that are out there. >> Savannah: Yes. >> You know, I talked about, and it's, you know you wouldn't think, "Okay, well what's that?" There's a lot to that, a lot of saving when you look at how you do welding and if you apply things like visual AI and auditory AI to make sure a weld is good. I mean, I think these are, these things are cool, I geek out on these things- >> John: Every vertical. >> I'm geeking out with you right now, just geeking- >> Yeah, yeah, yeah, so- >> Every vertical is infected. >> They are and it's so impactful to have AWS just in lockstep with us, doing these solutions, it's so different from, you know, you kind of create something that you think your customers like and then you put it out there. >> Yeah, versus this moment. >> Yeah, they're better together. >> It's strategic partnership- >> It's truly a strategic partnership. and we're really bringing that this year to reinvent and so I'm super excited about that. >> Congratulations. >> Wow, well, congratulations again on your awards, on your new partnership, I can't wait to hear, I mean, we're seven months in, eight months in to this this SaaS side of the partnership, can't wait to see what we're going to be talking about next year when we have you back on theCUBE. >> I know. >> and maybe again in between now and then. Alan, Becky, thank you both so much for being here, this was truly a joy and I'm sure you gave folks a taste of the new IBM, practicing what you preach. >> John: Great momentum. >> And I'm just, I'm so impressed with the two companies collaborating, for those of us OGs in tech, the big companies never collaborated before- >> Yeah. >> John: Yeah. Joint, co-created solutions. >> And you have friction between products and everything else. I mean's it's really, co-collaboration is, it's a big theme for us at all the shows we've been doing this year but it's just nice to see it in practice too, it's an entirely different thing, so well done. >> Well it's what gets me out of the bed in the morning. >> All right, congratulations. >> Very clearly, your energy is contagious and I love it and yeah, this has been great. Thank all of you at home or at work or on the International Space Station or wherever you might be tuning in from today for joining us, here in Las Vegas at AWS re Invent where we are live from the show floor, wall-to-wall coverage for three days with John Furrier. My name is Savannah Peterson, we're theCUBE, the source for high tech coverage. (cheerful upbeat music)

>>Good evening everyone and welcome back to Sparkly Sin City, Las Vegas, Nevada, where we are here with the cube covering AWS Reinvent for the 10th year in a row. John Furrier has been here for all 10. John, we are in our last session of day one. How does it compare? >>I just graduated high school 10 years ago. It's exciting to be, here's been a long time. We've gotten a lot older. My >>Got your brain is complex. You've been a lot in there. So fast. >>Graduated eight in high school. You know how it's No. All good. This is what's going on. This next segment, wrapping up day one, which is like the the kickoff. The Mondays great year. I mean Tuesdays coming tomorrow big days. The announcements are all around the kind of next gen and you're starting to see partnering and integration is a huge part of this next wave cuz API's at the cloud, next gen cloud's gonna be deep engineering integration and you're gonna start to see business relationships and business transformation scale a horizontally, not only across applications but companies. This has been going on for a while, covering it. This next segment is gonna be one of those things that we're gonna look at as something that's gonna happen more and more on >>Yeah, I think so. It's what we've been talking about all day. Without further ado, I would like to welcome our very exciting guest for this final segment, trust from single store. Thank you for being here. And we also have him on from IBM Data and ai. Y'all are partners. Been partners for about a year. I'm gonna go out on a limb only because their legacy and suspect that a few people, a few more people might know what IBM does versus what a single store does. So why don't you just give us a little bit of background so everybody knows what's going on. >>Yeah, so single store is a relational database. It's a foundational relational systems, but the thing that we do the best is what we call us realtime analytics. So we have these systems that are legacy, which which do operations or analytics. And if you wanted to bring them together, like most of the applications want to, it's really a big hassle. You have to build an ETL pipeline, you'd have to duplicate the data. It's really faulty systems all over the place and you won't get the insights really quickly. Single store is trying to solve that problem elegantly by having an architecture that brings both operational and analytics in one place. >>Brilliant. >>You guys had a big funding now expanding men. Sequel, single store databases, 46 billion again, databases. We've been saying this in the queue for 12 years have been great and recently not one database will rule the world. We know that. That's, everyone knows that databases, data code, cloud scale, this is the convergence now of all that coming together where data, this reinvent is the theme. Everyone will be talking about end to end data, new kinds of specialized services, faster performance, new kinds of application development. This is the big part of why you guys are working together. Explain the relationship, how you guys are partnering and engineering together. >>Yeah, absolutely. I think so ibm, right? I think we are mainly into hybrid cloud and ai and one of the things we are looking at is expanding our ecosystem, right? Because we have gaps and as opposed to building everything organically, we want to partner with the likes of single store, which have unique capabilities that complement what we have. Because at the end of the day, customers are looking for an end to end solution that's also business problems. And they are very good at real time data analytics and hit staff, right? Because we have transactional databases, analytical databases, data lakes, but head staff is a gap that we currently have. And by partnering with them we can essentially address the needs of our customers and also what we plan to do is try to integrate our products and solutions with that so that when we can deliver a solution to our customers, >>This is why I was saying earlier, I think this is a a tell sign of what's coming from a lot of use cases where people are partnering right now you got the clouds, a bunch of building blocks. If you put it together yourself, you can build a durable system, very stable if you want out of the box solution, you can get that pre-built, but you really can't optimize. It breaks, you gotta replace it. High level engineering systems together is a little bit different, not just buying something out of the box. You guys are working together. This is kind of an end to end dynamic that we're gonna hear a lot more about at reinvent from the CEO ofs. But you guys are doing it across companies, not just with aws. Can you guys share this new engineering business model use case? Do you agree with what I'm saying? Do you think that's No, exactly. Do you think John's crazy, crazy? I mean I all discourse, you got out of the box, engineer it yourself, but then now you're, when people do joint engineering project, right? They're different. Yeah, >>Yeah. No, I mean, you know, I think our partnership is a, is a testament to what you just said, right? When you think about how to achieve realtime insights, the data comes into the system and, and the customers and new applications want insights as soon as the data comes into the system. So what we have done is basically build an architecture that enables that we have our own storage and query engine indexing, et cetera. And so we've innovated in our indexing in our database engine, but we wanna go further than that. We wanna be able to exploit the innovation that's happening at ibm. A very good example is, for instance, we have a native connector with Cognos, their BI dashboards right? To reason data very natively. So we build a hyper efficient system that moves the data very efficiently. A very other good example is embedded ai. >>So IBM of course has built AI chip and they have basically advanced quite a bit into the embedded ai, custom ai. So what we have done is, is as a true marriage between the engineering teams here, we make sure that the data in single store can natively exploit that kind of goodness. So we have taken their libraries. So if you have have data in single store, like let's imagine if you have Twitter data, if you wanna do sentiment analysis, you don't have to move the data out model, drain the model outside, et cetera. We just have the pre-built embedded AI libraries already. So it's a, it's a pure engineering manage there that kind of opens up a lot more insights than just simple analytics and >>Cost by the way too. Moving data around >>Another big theme. Yeah. >>And latency and speed is everything about single store and you know, it couldn't have happened without this kind of a partnership. >>So you've been at IBM for almost two decades, don't look it, but at nearly 17 years in how has, and maybe it hasn't, so feel free to educate us. How has, how has IBM's approach to AI and ML evolved as well as looking to involve partnerships in the ecosystem as a, as a collaborative raise the water level together force? >>Yeah, absolutely. So I think when we initially started ai, right? I think we are, if you recollect Watson was the forefront of ai. We started the whole journey. I think our focus was more on end solutions, both horizontal and vertical. Watson Health, which is more vertically focused. We were also looking at Watson Assistant and Watson Discovery, which were more horizontally focused. I think it it, that whole strategy of the world period of time. Now we are trying to be more open. For example, this whole embedable AI that CICE was talking about. Yeah, it's essentially making the guts of our AI libraries, making them available for partners and ISVs to build their own applications and solutions. We've been using it historically within our own products the past few years, but now we are making it available. So that, how >>Big of a shift is that? Do, do you think we're seeing a more open and collaborative ecosystem in the space in general? >>Absolutely. Because I mean if you think about it, in my opinion, everybody is moving towards AI and that's the future. And you have two option. Either you build it on your own, which is gonna require significant amount of time, effort, investment, research, or you partner with the likes of ibm, which has been doing it for a while, right? And it has the ability to scale to the requirements of all the enterprises and partners. So you have that option and some companies are picking to do it on their own, but I believe that there's a huge amount of opportunity where people are looking to partner and source what's already available as opposed to investing from the scratch >>Classic buy versus build analysis for them to figure out, yeah, to get into the game >>And, and, and why reinvent the wheel when we're all trying to do things at, at not just scale but orders of magnitude faster and and more efficiently than we were before. It, it makes sense to share, but it's, it is, it does feel like a bit of a shift almost paradigm shift in, in the culture of competition versus how we're gonna creatively solve these problems. There's room for a lot of players here, I think. And yeah, it's, I don't >>Know, it's really, I wanted to ask if you don't mind me jumping in on that. So, okay, I get that people buy a bill I'm gonna use existing or build my own. The decision point on that is, to your point about the path of getting the path of AI is do I have the core competency skills, gap's a big issue. So, okay, the cube, if you had ai, we'd take it cuz we don't have any AI engineers around yet to build out on all the linguistic data we have. So we might use your ai but I might say this to then and we want to have a core competency. How do companies get that core competency going while using and partnering with, with ai? What you guys, what do you guys see as a way for them to get going? Because I think some people probably want to have core competency of >>Ai. Yeah, so I think, again, I think I, I wanna distinguish between a solution which requires core competency. You need expertise on the use case and you need expertise on your industry vertical and your customers versus the foundational components of ai, which are like, which are agnostic to the core competency, right? Because you take the foundational piece and then you further train it and define it for your specific use case. So we are not saying that we are experts in all the industry verticals. What we are good at is like foundational components, which is what we wanna provide. Got it. >>Yeah, that's the hard deep yes. Heavy lift. >>Yeah. And I can, I can give a color to that question from our perspective, right? When we think about what is our core competency, it's about databases, right? But there's a, some biotic relationship between data and ai, you know, they sort of like really move each other, right? You >>Need, they kind of can't have one without the other. You can, >>Right? And so the, the question is how do we make sure that we expand that, that that relationship where our customers can operationalize their AI applications closer to the data, not move the data somewhere else and do the modeling and then training somewhere else and dealing with multiple systems, et cetera. And this is where this kind of a cross engineering relationship helps. >>Awesome. Awesome. Great. And then I think companies are gonna want to have that baseline foundation and then start hiring in learning. It's like driving the car. You get the keys when you're ready to go. >>Yeah, >>Yeah. Think I'll give you a simple example, right? >>I want that turnkey lifestyle. We all do. Yeah, >>Yeah. Let me, let me just give you a quick analogy, right? For example, you can, you can basically make the engines and the car on your own or you can source the engine and you can make the car. So it's, it's basically an option that you can decide. The same thing with airplanes as well, right? Whether you wanna make the whole thing or whether you wanna source from someone who is already good at doing that piece, right? So that's, >>Or even create a new alloy for that matter. I mean you can take it all the way down in that analogy, >>Right? Is there a structural change and how companies are laying out their architecture in this modern era as we start to see this next let gen cloud emerge, teams, security teams becoming much more focused data teams. Its building into the DevOps into the developer pipeline, seeing that trend. What do you guys see in the modern data stack kind of evolution? Is there a data solutions architect coming? Do they exist yet? Is that what we're gonna see? Is it data as code automation? How do you guys see this landscape of the evolving persona? >>I mean if you look at the modern data stack as it is defined today, it is too detailed, it's too OSes and there are way too many layers, right? There are at least five different layers. You gotta have like a storage you replicate to do real time insights and then there's a query layer, visualization and then ai, right? So you have too many ETL pipelines in between, too many services, too many choke points, too many failures, >>Right? Etl, that's the dirty three letter word. >>Say no to ETL >>Adam Celeste, that's his quote, not mine. We hear that. >>Yeah. I mean there are different names to it. They don't call it etl, we call it replication, whatnot. But the point is hassle >>Data is getting more hassle. More >>Hassle. Yeah. The data is ultimately getting replicated in the modern data stack, right? And that's kind of one of our thesis at single store, which is that you'd have to converge not hyper specialize and conversation and convergence is possible in certain areas, right? When you think about operational analytics as two different aspects of the data pipeline, it is possible to bring them together. And we have done it, we have a lot of proof points to it, our customer stories speak to it and that is one area of convergence. We need to see more of it. The relationship with IBM is sort of another step of convergence wherein the, the final phases, the operation analytics is coming together and can we take analytics visualization with reports and dashboards and AI together. This is where Cognos and embedded AI comes into together, right? So we believe in single store, which is really conversions >>One single path. >>A shocking, a shocking tie >>Back there. So, so obviously, you know one of the things we love to joke about in the cube cuz we like to goof on the old enterprise is they solve complexity by adding more complexity. That's old. Old thinking. The new thinking is put it under the covers, abstract the way the complexities and make it easier. That's right. So how do you guys see that? Because this end to end story is not getting less complicated. It's actually, I believe increasing and complication complexity. However there's opportunities doing >>It >>More faster to put it under the covers or put it under the hood. What do you guys think about the how, how this new complexity gets managed or in this new data world we're gonna be coming in? >>Yeah, so I think you're absolutely right. It's the world is becoming more complex, technology is becoming more complex and I think there is a real need and it's not just from coming from us, it's also coming from the customers to simplify things. So our approach around AI is exactly that because we are essentially providing libraries, just like you have Python libraries, there are libraries now you have AI libraries that you can go infuse and embed deeply within applications and solutions. So it becomes integrated and simplistic for the customer point of view. From a user point of view, it's, it's very simple to consume, right? So that's what we are doing and I think single store is doing that with data, simplifying data and we are trying to do that with the rest of the portfolio, specifically ai. >>It's no wonder there's a lot of synergy between the two companies. John, do you think they're ready for the Instagram >>Challenge? Yes, they're ready. Uhoh >>Think they're ready. So we're doing a bit of a challenge. A little 32nd off the cuff. What's the most important takeaway? This could be your, think of it as your thought leadership sound bite from AWS >>2023 on Instagram reel. I'm scrolling. That's the Instagram, it's >>Your moment to stand out. Yeah, exactly. Stress. You look like you're ready to rock. Let's go for it. You've got that smile, I'm gonna let you go. Oh >>Goodness. You know, there is, there's this quote from astrophysics, space moves matter, a matter tells space how to curve. They have that kind of a relationship. I see the same between AI and data, right? They need to move together. And so AI is possible only with right data and, and data is meaningless without good insights through ai. They really have that kind of relationship and you would see a lot more of that happening in the future. The future of data and AI are combined and that's gonna happen. Accelerate a lot faster. >>Sures, well done. Wow. Thank you. I am very impressed. It's tough hacks to follow. You ready for it though? Let's go. Absolutely. >>Yeah. So just, just to add what is said, right, I think there's a quote from Rob Thomas, one of our leaders at ibm. There's no AI without ia. Essentially there's no AI without information architecture, which essentially data. But I wanna add one more thing. There's a lot of buzz around ai. I mean we are talking about simplicity here. AI in my opinion is three things and three things only. Either you use AI to predict future for forecasting, use AI to automate things. It could be simple, mundane task, it would be complex tasks depending on how exactly you want to use it. And third is to optimize. So predict, automate, optimize. Anything else is buzz. >>Okay. >>Brilliantly said. Honestly, I think you both probably hit the 32nd time mark that we gave you there. And the enthusiasm loved your hunger on that. You were born ready for that kind of pitch. I think they both nailed it for the, >>They nailed it. Nailed it. Well done. >>I I think that about sums it up for us. One last closing note and opportunity for you. You have a V 8.0 product coming out soon, December 13th if I'm not mistaken. You wanna give us a quick 15 second preview of that? >>Super excited about this. This is one of the, one of our major releases. So we are evolving the system on multiple dimensions on enterprise and governance and programmability. So there are certain features that some of our customers are aware of. We have made huge performance gains in our JSON access. We made it easy for people to consume, blossom on OnPrem and hybrid architectures. There are multiple other things that we're gonna put out on, on our site. So it's coming out on December 13th. It's, it's a major next phase of our >>System. And real quick, wasm is the web assembly moment. Correct. And the new >>About, we have pioneers in that we, we be wasm inside the engine. So you could run complex modules that are written in, could be C, could be rushed, could be Python. Instead of writing the the sequel and SQL as a store procedure, you could now run those modules inside. I >>Wanted to get that out there because at coupon we covered that >>Savannah Bay hot topic. Like, >>Like a blanket. We covered it like a blanket. >>Wow. >>On that glowing note, Dre, thank you so much for being here with us on the show. We hope to have both single store and IBM back on plenty more times in the future. Thank all of you for tuning in to our coverage here from Las Vegas in Nevada at AWS Reinvent 2022 with John Furrier. My name is Savannah Peterson. You're watching the Cube, the leader in high tech coverage. We'll see you tomorrow.

>>Good morning live from Chicago. It's the cube on the floor at Ansible Fast 2022. This is day two of our wall to wall coverage. Lisa Martin here with John Furrier. John, we're gonna be talking next in the segment with two alumni about what Red Hat and IBM are doing to give Ansible users AI superpowers. As one of our alumni guests said, just off the keynote stage, we're nearing an inflection point in ai. >>The power of AI with Ansible is really gonna be an innovative, I think an inflection point for a long time because Ansible does such great things. This segment's gonna explore that innovation, bringing AI and making people more productive and more importantly, you know, this whole low code, no code, kind of right in the sweet spot of the skills gap. So should be a great segment. >>Great segment. Please welcome back two of our alumni. Perry is here, the Chief scientist, IBM Research and IBM Fellow. And Tom Anderson joins us once again, VP and general manager at Red Hat. Gentlemen, great to have you on the program. We're gonna have you back. >>Thank you for having >>Us and thanks for joining us. Fresh off the keynote stage. Really enjoyed your keynote this morning. Very exciting news. You have a project called Project Wisdom. We're talking about this inflection point in ai. Tell the audience, the viewers, what is Project Wisdom And Wisdom differs from intelligence. How >>I think Project Wisdom is really about, as I said, sort of combining two major forces that are in many ways disrupting and, and really constructing many a aspects of our society, which are software and AI together. Yeah. And I truly believe it's gonna result in a se shift on how not just enterprises, but society carries forefront. And as I said, intelligence is, is, I would argue at least artificial intelligence is more, in some ways mechanical, if I may say it, it's about algorithms, it's about data, it's about compute. Wisdom is all about what is truly important to bring out. It's not just about when you bring out a, a insight, when you bring out a decision to be able to explain that decision as well. It's almost like humans have wisdom. Machines have intelligence and, and it's about project wisdom. That's why we called it wisdom. >>Because it is about being a, a assistant augmenting humans. Just like be there with the humans and, and almost think of it as behave and interact with them as another colleague will versus intelligence, which is, you know, as I said, more mechanical is about data. Computer algorithms crunch together and, and we wanna bring the power of project wisdom and artificial intelligence to developers to, as you said, close the skills gap to be able to really make them more productive and have wisdom for Ansible be their assistant. Yeah. To be able to get things for them that they would find many ways mundane, many ways hard to find and again, be an assistant and augmented, >>You know, you know what's interesting, I want to get into the origin, how it all happened, but interesting IBM research, well known for the deep tech, big engineering. And you guys have been doing this for a long time, so congratulations. But it's interesting here at this event, even on stage here event, you're starting to see the automation come in. So the question comes up, scale. So what happens, IBM buys Red Hat, you go raid the, the raid, the ip, Trevor Treasure trove of ai. I mean this cuz this is kind of like bringing two killer apps together. The Ansible configuration automation layer with ai just kind of a, >>Yeah, it's an amazing relationship. I was gonna say marriage, but I don't wanna say marriage cause I may be >>Last. I didn't mean say raid the Treasure Trobe, but the kind of >>Like, oh my God. An amazing relationship where we bring all this expertise around automation, obviously around IP and application infrastructure automation and IBM research, Richie and his team bring this amazing capacity and experience around ai. Bring those two things together and applying AI to automation for our teams is so incredibly fantastic. I just can't contain my enthusiasm about it. And you could feel it in the keynote this morning that Richie was doing the energy in the room and when folks saw that, it's just amazing. >>The geeks are gonna love it for sure. But here I wanna get into the whole evolution. Computers on computers, remember the old days thinking machines was a company generations ago that I think they've sold or went outta business, but self-learning, learning machines, computers, programming, computers was actually on your slide you kind of piece out this next wave of AI and machine learning, starting with expert systems really kind of, I'm almost say static, but like okay programs. Yeah, yeah. And then now with machine learning and that big debate was unsupervised, supervised, which is not really perfect. Deep learning, which now explores some things, but now we're at another wave. Take, take us through the thought there explaining what this transition looks like and why. >>I think we are, as I said, we are really at an inflection point in the journey of ai. And if ai, I think it's fair to say data is the pain of ai without data, AI doesn't exist. But if I were to train AI with what is known as supervised learning or or data that is labeled, you are almost sort of limited because there are only so many people who have that expertise. And interestingly, they all have day jobs. So they're not just gonna sit around and label this for you. Some people may be available, but you know, this is not, again, as I as Tom said, we are really trying to apply it to some very sort of key domains which require subject matter expertise. This is not like labeling cats and dogs that everybody else in the board knows there are, the community's very large, but still the skills to go around are not that many. >>And I truly believe to apply AI to the, to the word of, you know, enterprises information technology automation, you have to have unsupervised learning and that's the only way to skate. Yeah. And these two trends really about, you know, information technology percolating across every enterprise and unsupervised learning, which is learning on this very large amount of data with of course know very large compute with some very powerful algorithms like transformer architectures and others which have been disrupting the, the domain of natural language as well are coming together with what I described as foundation models. Yeah. Which anybody who plays with it, you'll be blown away. That's literally blown away. >>And you call that self supervision at scale, which is kind of the foundation. So I have to ask you, cuz this comes up a lot with cloud, cloud scale, everyone tells horizontally scalable cloud, but vertically specialized applications where domain expertise and data plays. So the better the data, the better the self supervision, better the learning. But if it's horizontally scalable is a lot to learn. So how do you create that data ops where it's where the machines are gonna be peaked to maximize what's addressable, but what's also in the domain too, you gotta have that kind of diversity. Can you share your thoughts on that? >>Absolutely. So in, in the domain of foundation models, there are two main stages I would say. One is what I'll describe as pre-training, which is think of it as the, the machine in this particular case is knowledgeable about the domain of code in general. It knows syntax of Python, Java script know, go see Java and so, so on actually, and, and also Yammel as well, which is obviously one would argue is the domain of information technology. And once you get to that level, it's a, it's almost like having a developer who knows all of this but may not be an expert at Ansible just yet. He or she can be an expert at Ansible but is not there yet. That's what I'll call background knowledge. And also in the, in the case of foundation models, they are very adept at natural language as well. So they can connect natural language to code, but they are not yet expert at the domain of Ansible. >>Now there's something called, the second stage of learning is called fine tuning, which is about this data ops where I take data, which is sort of the SME data in this particular case. And it's curated. So this is not just generic data, you pick off GitHub, you don't know what exists out there. This is the data which is governed, which we know is of high quality as well. And you think of it as you specialize the generic AI with pre-trained AI with that data. And those two stages, including the governance of that data that goes into it results in this sort of really breakthrough technology that we've been calling Project Wisdom for. Our first application is Ansible, but just watch out that area. There are many more to come and, and we are gonna really, I'm really excited about this partnership with Red Hat because across IBM and research, I think where wherever we, if there is one place where we can find excited, open source, open developer community, it is Right. That's, >>Yeah. >>Tom, talk about the, the role of open source and Project Wisdom, the involvement of the community and maybe Richard, any feedback that you've gotten since coming off stage? I'm sure you were mobbed. >>Yeah, so for us this is, it's called Project Wisdom, not Product Wisdom. Right? Sorry. Right. And so, no, you didn't say that but I wanna just emphasize that it is a project and for us that is a key word in the upstream community that this is where we're inviting the community to jump on board with us and bring their expertise. All these people that are here will start to participate. They're excited in it. They'll bring their expertise and experience and that fine tuning of the model will just get better and better. So we're really excited about introducing this now and involving the community because it's super nuts. Everything that Red Hat does is around the community and this is no different. And so we're really excited about Project Wisdom. >>That's interesting. The project piece because if you see in today's world the innovation strategy before where we are now, go back to say 15 years ago it was of standard, it's gotta have standard bodies. You can still innovate and differentiate, but yet with open source and community, it's a blending of research and practitioners. I think that to me is a big story here is that what you guys are demonstrating is the combination of research and practitioners in the project. Yes. So how does this play out? Cuz this is kind of like how things are gonna get done in the cloud cuz Amazon's not gonna just standardize their stack at at higher level services, nor is Azure and they might get some plumbing commonalities below, but for Project Project Wisdom to be successful, they can, it doesn't need to have standards. If I get this right, if I can my on point here, what do you guys think about that? React to that? Yeah, >>So I definitely, I think standardization in terms of what we will call ML ops pipeline for models to be deployed and managed and operated. It's like models, like any other code, there's standardization on DevOps ops pipeline, there's standardization on machine learning pipeline. And these models will be deployed in the cloud because they need to scale. The only way to scale to, you know, thousands of users is through cloud. And there is, there are standard pipelines that we are working and architecting together with the Red Hat community leveraging open source packages. Yeah. Is really to, to help scale out the AI models of wisdom together. And another point I wanted to pick up on just what Tom said, I've been sort of in the area of productizing AI for for long now having experience with Watson as well. The only scenario where I've seen AI being successful is in this scenario where, what I describe as it meets the criteria of flywheel of ai. >>What do I mean by flywheel of ai? It cannot be some research people build a model. It may be wowing, but you roll it out and there's no feedback. Yeah, exactly. Okay. We are duh. So what actually, the only way the more people use these models, the more they give you feedback, the better it gets because it knows what is right and what is not right. It will never be right the first time. Actually, you know, the data it is trained on is a depiction of reality. Yeah. It is not a reality in itself. Yeah. The reality is a constantly moving target and the only way to make AI successful is to close that loop with the community. And that's why I just wanted to reemphasize the point on why community is that important >>Actually. And what's interesting Tom is this is a difference between standards bodies, old school and communities. Because developers are very efficient in their feedback. Yes. They jump to patterns that serve their needs, whether it's self-service or whatever. You can kind of see what's going on. Yeah. It's either working or not. Yeah, yeah, >>Yeah. We get immediate feedback from the community and we know real fast when something isn't working, when something is working, there are no problems with the flow of data between the members of the community and, and the developers themselves. So yeah, it's, I'm it's great. It's gonna be fantastic. The energy around Project Wisdom already. I bet. We're gonna go down to the Project Wisdom session, the breakout session, and I bet you the room will be overflowed. >>How do people get involved real quick? Get, get a take a minute to explain how I would get involved. I'm a community member. Yep. I'm watching this video, I'm intrigued. This has got me enthusiastic. How do I get more confident with this opportunity? >>So you go to, first of all, you go to red hat.com/project Wisdom and you register your interests and you wanna participate. We're gonna start growing this process, bringing people in, getting ready to make the service available to people to start using and to experiment with. Start getting their feedback. So this is the beginning of, of a journey. This isn't the, you know, this isn't the midpoint of a journey, this is the begin. You know, even though the work has been going on for a year, this is the beginning of the community journey now. And so we're gonna start working together through channels like Discord and whatnot to be able to exchange information and bring people in. >>What are some of the key use cases, maybe Richie are starting with you that, that you think maybe dream use cases that you think the community will help to really uncover as we're looking at Project Wisdom really helping in this transformation of ai. >>So if I focus on let's say Ansible itself, there are much wider use cases, but Ansible itself and you know, I, I would say I had not realized, I've been working on AI for Good for long, but I had not realized the excitement and the power of Ansible community itself. It's very large, it's very bottom sum, which I love actually. But as I went to lot of like CTOs and CIOs of lot of our customers as well, it was becoming clear the use cases of, you know, I've got thousand Ansible developers or IT or automation experts. They write code all the time. I don't know what all of this code is about. So the, the system administrators, managers, they're trying to figure out sort of how to organize all of this together and think of it as Google for finding all of these automation code automation content. >>And I'm very excited about not just the use cases that we demonstrated today, that is beginning of the journey, but to be able to help enterprises in finding the right code through natural language interfaces, generating the code, helping Del us debug their code as well. Giving them predictive insights into this may happen. Just watch out for it when you deploy this. Something like that happened before, just watch out for it as well. So I'm, I'm excited about the entire life cycle of IT automation, Not just about at the build time, but also at the time of deployment. At the time of management. This is just a start of a journey, but there are many exciting use cases abound for Ansible and beyond. >>It's gonna be great to watch this as it unfolds. Obviously just announcing this today. We thank you both so much for joining us on the program, talking about Project wisdom and, and sharing how the community can get involved. So you're gonna have to come back next year. We're gonna have to talk about what's going on. Cause I imagine with the excitement of the community and the volume of the community, this is just the tip of the iceberg. Absolutely. >>This is absolutely exactly. You're excited about. >>Excellent. And you should be. Congratulations. Thank, thanks again for joining us. We really appreciate your insights. Thank you. Thank >>You for having >>Us. For our guests and John Furrier, I'm Lisa Barton and you're watching The Cube Lie from Chicago at Ansible Fest 22. This is day two of wall to wall coverage on the cube. Stick around. Our next guest joins us in just a minute.

(upbeat music) >> Welcome back everyone to theCUBEs live coverage in San Francisco for VMware Explorer. I'm John Furrier with my host, Dave Vellante. Two sets, three days of wall to wall coverage. This is day two. We got a great guest, Scott Baker, CMO at IBM, VP of Infrastructure at IBM. Great to see you. Thanks for coming on. >> Hey, good to see you guys as well. It's always a pleasure. >> ()Good time last night at your event? >> Great time last night. >> It was really well-attended. IBM always has the best food so that was good and great props, magicians, and it was really a lot of fun, comedians. Good job. >> Yeah, I'm really glad you came on. One of the things we were chatting, before we came on camera was, how much changed. We've been covering IBM storage days, back on the Edge days, and they had the event. Storage is the center of all the conversations, cyber security- >> ()Right? >> ... But it's not just pure cyber. It's still important there. And just data and the role of multi-cloud and hybrid cloud and data and security are the two hottest areas, that I won't say unresolved, but are resolving themselves. And people are talking. It's the most highly discussed topics. >> Right. >> ()Those two areas. And it's just all on storage. >> Yeah, it sure does. And in fact, what I would even go so far as to say is, people are beginning to realize the importance that storage plays, as the data custodian for the organization. Right? Certainly you have humans that are involved in setting strategies, but ultimately whatever those policies are that get applied, have to be applied to a device that must act as a responsible custodian for the data it holds. >> So what's your role at IBM and the infrastructure team? Storage is one only one of the areas. >> ()Right. >> You're here at VMware Explore. What's going on here with IBM? Take us through what you're doing there at IBM, and then here at VMware. What's the conversations? >> Sure thing. I have the distinct pleasure to run both product marketing and strategy for our storage line. That's my primary focus, but I also have responsibility for the mainframe software, so the Z System line, as well as our Power server line, and our technical support organization, or at least the services side of our technical support organization. >> And one of the things that's going on here, lot of noise going on- >> Is that a bird flying around? >> Yeah >> We got fire trucks. What's changed? 'Cause right now with VMware, you're seeing what they're doing. They got the Platform, Under the Hood, Developer focus. It's still an OPS game. What's the relationship with VMware? What are you guys talking about here? What are some of the conversations you're having here in San Francisco? >> Right. Well, IBM has been a partner with VMware for at least the last 20 years. And VMware does, I think, a really good job about trying to create a working space for everyone to be an equal partner with them. It can be challenging too, if you want to sort of throw out your unique value to a customer. So one of the things that we've really been working on is, how do we partner much stronger? When we look at the customers that we support today, what they're looking for isn't just a solid product. They're looking for a solid ecosystem partnership. So we really lean in on that 20 years of partnership experience that we have with IBM. So one of the things that we announced was actually being one of the first VMware partners to bring both a technical innovation delivery mechanism, as well as technical services, alongside VMware technologies. I would say that was one of the first things that we really leaned in on, as we looked out at what customers are expecting from us. >> So I want to zoom out a little bit and talk about the industry. I've been following IBM since the early 1980s. It's trained in the mainframe market, and so we've seen, a lot of things you see come back to the mainframe, but we won't go there. But prior to Arvind coming on, it seemed like, okay, storage, infrastructure, yeah it's good business, and we'll let it throw off some margin. That's fine. But it's all about services and software. Okay, great. With Arvind, and obviously Red Hat, the whole focus shift to hybrid. We were talking, I think yesterday, about okay, where did we first hear hybrid? Obviously we heard that a lot from VMware. I heard it actually first, early on anyway, from IBM, talking hybrid. Some of the storage guys at the time. Okay, so now all of a sudden there's the realization that to make hybrid work, you need software and hardware working together. >> () Right. So it's now a much more fundamental part of the conversation. So when you look out, Scott, at the trends you're seeing in the market, when you talk to customers, what are you seeing and how is that informing your strategy, and how are you bringing together all the pieces? >> That's a really awesome question because it always depends on who, within the organization, you're speaking to. When you're inside the data center, when you're talking to the architects and the administrators, they understand the value in the necessity for a hybrid-cloud architecture. Something that's consistent. On The Edge, On-Prem, in the cloud. Something that allows them to expand the level of control that they have, without having to specialize on equipment and having to redo things as you move from one medium to the next. As you go upstack in that conversation, what I find really interesting is how leaders are beginning to realize that private cloud or on-prem, multi cloud, super cloud, whatever you call it, whatever's in the middle, those are just deployment mechanisms. What they're coming to understand is it's the applications and the data that's hybrid. And so what they're looking for IBM to deliver, and something that we've really invested in on the infrastructure side is, how do we create bidirectional application mobility? Making it easy for organizations, whether they're using containers, virtual machines, just bare metal, how do they move that data back and forth as they need to, and not just back and forth from on-prem to the cloud, but effectively, how do they go from cloud to cloud? >> Yeah. One of the things I noticed is your pin, says I love AI, with the I next to IBM and get all these (indistinct) in there. AI, remember the quote from IBM is, "You can't have AI without IA." Information architect. >> () Right. >> () Rob Thomas. >> Rob Thomas (indistinct) the sound bites. But that brings up the point about machine learning and some of these things that are coming down the like, how is your area devolving the smarts and the brains around leveraging the AI in the systems itself? We're hearing more and more softwares being coded into the hardware. You see Silicon advances. All this is kind of, not changing it, but bringing back the urgency of, hardware matters. >> That's right. >> () At the same time, it's still software too. >> That's right. So let's connect a couple of dots here. We talked a little bit about the importance of cyber resiliency, and let's talk about a little bit on how we use AI in that matter. So, if you look at the direct flash modules that are in the market today, or the SSDs that are in the market today, just standard-capacity drives. If you look at the flash core modules that IBM produces, we actually treat that as a computational storage offering, where you store the data, but it's got intelligence built into the processor, to offload some of the responsibilities of the controller head. The ability to do compression, single (indistinct), deduplication, you name it. But what if you can apply AI at the controller level, so that signals that are being derived by the flash core module itself, that look anomalous, can be handed up to an intelligence to say, "Hey, I'm all of a sudden getting encrypted rights from a host that I've never gotten encrypted rights for. Maybe this could be a problem." And then imagine if you connect that inferencing engine to the rest of the IBM portfolio, "Hey, Qradar. Hey IBM Guardian. What's going on on the network? Can we see some correlation here?" So what you're going to see IBM infrastructure continue to do is invest heavily into entropy and the ability to measure IO characteristics with respect to anomalous behavior and be able to report against that. And the trick here, because the array technically doesn't know if it's under attack or if the host just decided to turn on encryption, the trick here is using the IBM product relationships, and ecosystem relationships, to do correlation of data to determine what's actually happening, to reduce your false positives. >> And have that pattern of data too. It's all access to data too. Big time. >> That's right. >> And that innovation comes out of IBM R&D? Does it come out of the product group? Is it IBM research that then trickles its way in? Is it the storage innovation? Where's that come from? Where's that bubble up? That partnership? >> Well, I got to tell you, it doesn't take very long in this industry before your counterpart, your competitor, has a similar feature. Right? So we're always looking for, what's the next leg? What's the next advancement that we can make? We knew going into this process, that we had plenty of computational power that was untapped on the FPGA, the processor running on the flash core module. Right? So we thought, okay, well, what should we do next? And we thought, "Hey, why not just set this thing up to start watching IO patterns, do calculations, do trending, and report that back?" And what's great about what you brought up too, John, is that it doesn't stay on the box. We push that upstack through the AIOPS architecture. So if you're using Turbonomic, and you want to look applications stack down, to know if you've got threat potential, or your attack surface is open, you can make some changes there. If you want to look at it across your infrastructure landscape with a storage insight, you could do that. But our goal here is to begin to make the machine smarter and aware of impacts on the data, not just on the data they hold onto, but usage, to move it into the appropriate tier, different write activities or read activities or delete activities that could indicate malicious efforts that are underway, and then begin to start making more autonomous, how about managed autonomous responses? I don't want to turn this into a, oh, it's smart, just turn it on and walk away and it's good. I don't know that we'll ever get there just yet, but the important thing here is, what we're looking at is, how do we continually safeguard and protect that data? And how do we drive features in the box that remove more and more of the day to day responsibility from the administrative staff, who are technically hired really, to service and solve for bigger problems in the enterprise, not to be a specialist and have to manage one box at a time. >> Dave mentioned Arvind coming on, the new CEO of IBM, and the Red Hat acquisition and that change, I'd like to get your personal perspective, or industry perspective, so take your IBM-hat off for a second and put the Scott-experience-in-the-industry hat on, the transformation at the customer level right now is more robust, to use that word. I don't want to say chaotic, but it is chaotic. They say chaos in the cloud here at VM, a big part of their messaging, but it's changing the business model, how things are consumed. You're seeing new business models emerge. So IBM has this lot of storage old systems, you're transforming, the company's transforming. Customers are also transforming, so that's going to change how people market products. >> () Right. >> For example, we know that developers and DevOps love self-service. Why? Because they don't want to install it. Let me go faster. And they want to get rid of it, doesn't work. Storage is infrastructure and still software, so how do you see, in your mind's eye, with all your experience, the vision of how to market products that are super important, that are infrastructure products, that have to be put into play, for really new architectures that are going to transform businesses? It's not as easy as saying, "Oh, we're going to go to market and sell something." The old way. >> () Right. >> This shifting happening is, I don't think there's an answer yet, but I want to get your perspective on that. Customers want to hear the storage message, but it might not be speeds and fees. Maybe it is. Maybe it's not. Maybe it's solutions. Maybe it's security. There's multiple touch points now, that you're dealing with at IBM for the customer, without becoming just a storage thing or just- >> () Right. >> ... or just hardware. I mean, hardware does matter, but what's- >> Yeah, no, you're absolutely right, and I think what complicates that too is, if you look at the buying centers around a purchase decision, that's expanded as well, and so as you engage with a customer, you have to be sensitive to the message that you're telling, so that it touches the needs or the desires of the people that are all sitting around the table. Generally what we like to do when we step in and we engage, isn't so much to talk about the product. At some point, maybe later in the engagements, the importance of speeds, feeds, interconnectivity, et cetera, those do come up. Those are a part of the final decision, but early on it's really about outcomes. What outcomes are you delivering? This idea of being able to deliver, if you use the term zero trust or cyber-resilient storage capability as a part of a broader security architecture that you're putting into place, to help that organization, that certainly comes up. We also hear conversations with customers about, or requests from customers about, how do the parts of IBM themselves work together? Right? And I think a lot of that, again, continues to speak to what kind of outcome are you going to give to me? Here's a challenge that I have. How are you helping me overcome it? And that's a combination of IBM hardware, software, and the services side, where we really have an opportunity to stand out. But the thing that I would tell you, that's probably most important is, the engagement that we have up and down the stack in the market perspective, always starts with, what's the outcome that you're going to deliver for me? And then that drags with it the story that would be specific to the gear. >> Okay, so let's say I'm a customer, and I'm buying it to zero trust architecture, but it's going to be somewhat of a long term plan, but I have a tactical need. I'm really nervous about Ransomware, and I don't feel as though I'm prepared, and I want an outcome that protects me. What are you seeing? Are you seeing any patterns? I know it's going to vary, but are you seeing any patterns, in terms of best practice to protect me? >> Man, the first thing that we wanted to do at IBM is divorce ourselves from the company as we thought through this. And what I mean by that is, we wanted to do what's right, on day zero, for the customer. So we set back using the experience that we've been able to amass, going through various recovery operations, and helping customers get through a Ransomware attack. And we realized, "Hey. What we should offer is a free cyber resilience assessment." So we like to, from the storage side, we'd like to look at what we offer to the customer as following the NIST framework. And most vendors will really lean in hard on the response and the recovery side of that, as you should. But that means that there's four other steps that need to be addressed, and that free cyber-resilience assessment, it's a consultative engagement that we offer. What we're really looking at doing is helping you assess how vulnerable you are, how big is that attack surface? And coming out of that, we're going to give you a Vendor Agnostic Report that says here's your situation, here's your grade or your level of risk and vulnerability, and then here's a prioritized roadmap of where we would recommend that you go off and start solving to close up whatever the gaps or the risks are. Now you could say, "Hey, thanks, IBM. I appreciate that. I'm good with my storage vendor today. I'm going to go off and use it." Now, we may not get some kind of commission check. We may not sell the box. But what I do know is that you're going to walk away knowing the risks that you're in, and we're going to give you the recommendations to get started on closing those up. And that helps me sleep at night. >> That's a nice freebie. >> Yeah. >> Yeah, it really is, 'cause you guys got deep expertise in that area. So take advantage of that. >> Scott, great to have you on. Thanks for spending time out of your busy day. Final question, put a plug in for your group. What are you communicating to customers? Share with the audience here. You're here at VMware Explorer, the new rebranded- >> () Right? >> ... multi-cloud, hybrid cloud, steady state. There are three levels of transformation, virtualization, hybrid cloud, DevOps, now- >> Right? >> ... multi-cloud, so they're in chapter three of their journey- >> That's right. >> Really innovative company, like IBM, so put the plugin. What's going on in your world? Take a minute to explain what you want. >> Right on. So here we are at VMware Explorer, really excited to be here. We're showcasing two aspects of the IBM portfolio, all of the releases and announcements that we're making around the IBM cloud. In fact, you should come check out the product demonstration for the IBM Cloud Satellite. And I don't think they've coined it this, but I like to call it the VMware edition, because it has all of the VMware services and tools built into it, to make it easier to move your workloads around. We certainly have the infrastructure side on the storage, talking about how we can help organizations, not only accelerate their deployments in, let's say Tanzu or Containers, but even how we help them transform the application stack that's running on top of their virtualized environment in the most consistent and secure way possible. >> Multiple years of relationships with VMware. IBM, VMware together. Congratulations. >> () That's right. >> () Thanks for coming on. >> Hey, thanks (indistinct). Thank you very much. >> A lot more live coverage here at Moscone west. This is theCUBE. I'm John Furrier with Dave Vellante. Thanks for watching. Two more days of wall-to-wall coverage continuing here. Stay tuned. (soothing music)

>>Welcome to this exclusive discussion. IBM, the next three years of life sciences, innovation, precision medicine, advanced clinical data management and beyond. My name is Dave Volante from the Cuban today, we're going to take a deep dive into some of the most important trends impacting the life sciences industry in the next 60 minutes. Yeah, of course. We're going to hear how IBM is utilizing Watson and some really important in life impacting ways, but we'll also bring in real world perspectives from industry and the independent analyst view to better understand how technology and data are changing the nature of precision medicine. Now, the pandemic has created a new reality for everyone, but especially for life sciences companies, one where digital transformation is no longer an option, but a necessity. Now the upside is the events of the past 22 months have presented an accelerated opportunity for innovation technology and real world data are coming together and being applied to support life science, industry trends and improve drug discovery, clinical development, and treatment commercialization throughout the product life cycle cycle. Now I'd like to introduce our esteemed panel. Let me first introduce Lorraine Marshawn, who is general manager of life sciences at IBM Watson health. Lorraine leads the organization dedicated to improving clinical development research, showing greater treatment value in getting treatments to patients faster with differentiated solutions. Welcome Lorraine. Great to see you. >>Dr. Namita LeMay is the research vice-president of IDC, where she leads the life sciences R and D strategy and technology program, which provides research based advisory and consulting services as well as market analysis. The loan to meta thanks for joining us today. And our third panelist is Greg Cunningham. Who's the director of the RWE center of excellence at Eli Lilly and company. Welcome, Greg, you guys are doing some great work. Thanks for being here. Thanks >>Dave. >>Now today's panelists are very passionate about their work. If you'd like to ask them a question, please add it to the chat box located near the bottom of your screen, and we'll do our best to answer them all at the end of the panel. Let's get started. Okay, Greg, and then Lorraine and meta feel free to chime in after one of the game-changers that you're seeing, which are advancing precision medicine. And how do you see this evolving in 2022 and into the next decade? >>I'll give my answer from a life science research perspective. The game changer I see in advancing precision medicine is moving from doing research using kind of a single gene mutation or kind of a single to look at to doing this research using combinations of genes and the potential that this brings is to bring better drug targets forward, but also get the best product to a patient faster. Um, I can give, uh, an example how I see it playing out in the last decade. Non-oncology real-world evidence. We've seen an evolution in precision medicine as we've built out the patient record. Um, as we've done that, uh, the marketplace has evolved rapidly, uh, with, particularly for electronic medical record data and genomic data. And we were pretty happy to get our hands on electronic medical record data in the early days. And then later the genetic test results were combined with this data and we could do research looking at a single mutation leading to better patient outcomes. But I think where we're going to evolve in 2022 and beyond is with genetic testing, growing and oncology, providing us more data about that patient. More genes to look at, uh, researchers can look at groups of genes to analyze, to look at that complex combination of gene mutations. And I think it'll open the door for things like using artificial intelligence to help researchers plow through the complex number of permutations. When you think about all those genes you can look at in combination, right? Lorraine yes. Data and machine intelligence coming together, anything you would add. >>Yeah. Thank you very much. Well, I think that Greg's response really sets us up nicely, particularly when we think about the ability to utilize real-world data in the farm industry across a number of use cases from discovery to development to commercial, and, you know, in particular, I think with real world data and the comments that Greg just made about clinical EMR data linked with genetic or genomic data, a real area of interest in one that, uh, Watson health in particular is focused on the idea of being able to create a data exchange so that we can bring together claims clinical EMR data, genomics data, increasingly wearables and data directly from patients in order to create a digital health record that we like to call an intelligent patient health record that basically gives us the digital equivalent of a real life patient. And these can be used in use cases in randomized controlled clinical trials for synthetic control arms or natural history. They can be used in order to track patients' response to drugs and look at outcomes after they've been on various therapies as, as Greg is speaking to. And so I think that, you know, the promise of data and technology, the AI that we can apply on that is really helping us advance, getting therapies to market faster, with better information, lower sample sizes, and just a much more efficient way to do drug development and to track and monitor outcomes in patients. >>Great. Thank you for that now to meta, when I joined IDC many, many years ago, I really didn't know much about the industry that I was covering, but it's great to see you as a former practitioner now bringing in your views. What do you see as the big game-changers? >>So, um, I would, I would agree with what both Lorraine and Greg said. Um, but one thing that I'd just like to call out is that, you know, everyone's talking about big data, the volume of data is growing. It's growing exponentially actually about, I think 30% of data that exists today is healthcare data. And it's growing at a rate of 36%. That's huge, but then it's not just about the big, it's also about the broad, I think, um, you know, I think great points that, uh, Lorraine and Greg brought out that it's, it's not just specifically genomic data, it's multi omic data. And it's also about things like medical history, social determinants of health, behavioral data. Um, and why, because when you're talking about precision medicine and we know that we moved away from the, the terminology of personalized to position, because you want to talk about disease stratification and you can, it's really about convergence. >>Um, if you look at a recent JAMA paper in 2021, only 1% of EHS actually included genomic data. So you really need to have that ability to look at data holistically and IDC prediction is seeing that investments in AI to fuel in silico, silicone drug discovery will double by 20, 24, but how are you actually going to integrate all the different types of data? Just look at, for example, diabetes, you're on type two diabetes, 40 to 70% of it is genetically inherited and you have over 500 different, uh, genetic low side, which could be involved in playing into causing diabetes. So the earlier strategy, when you are looking at, you know, genetic risk scoring was really single trait. Now it's transitioning to multi rate. And when you say multi trade, you really need to get that integrated view that converging for you to, to be able to drive a precision medicine strategy. So to me, it's a very interesting contrast on one side, you're really trying to make it specific and focused towards an individual. And on the other side, you really have to go wider and bigger as well. >>Uh, great. I mean, the technology is enabling that convergence and the conditions are almost mandating it. Let's talk about some more about data that the data exchange and building an intelligent health record, as it relates to precision medicine, how will the interoperability of real-world data, you know, create that more cohesive picture for the, for the patient maybe Greg, you want to start, or anybody else wants to chime in? >>I think, um, the, the exciting thing from, from my perspective is the potential to gain access to data. You may be weren't aware of an exchange in implies that, uh, some kind of cataloging, so I can see, uh, maybe things that might, I just had no idea and, uh, bringing my own data and maybe linking data. These are concepts that I think are starting to take off in our field, but it, it really opens up those avenues to when you, you were talking about data, the robustness and richness volume isn't, uh, the only thing is Namita said, I think really getting to a rich high-quality data and, and an exchange offers a far bigger, uh, range for all of us to, to use, to get our work done. >>Yeah. And I think, um, just to chime, chime into that, uh, response from Greg, you know, what we hear increasingly, and it's pretty pervasive across the industry right now, because this ability to create an exchange or the intelligent, uh, patient health record, these are new ideas, you know, they're still rather nascent and it always is the operating model. Uh, that, that is the, uh, the difficult challenge here. And certainly that is the case. So we do have data in various silos. Uh, they're in patient claims, they're in electronic medical records, they might be in labs, images, genetic files on your smartphone. And so one of the challenges with this interoperability is being able to tap into these various sources of data, trying to identify quality data, as Greg has said, and the meta is underscoring as well. Uh, we've gotta be able to get to the depth of data that's really meaningful to us, but then we have to have technology that allows us to pull this data together. >>First of all, it has to be de-identified because of security and patient related needs. And then we've gotta be able to link it so that you can create that likeness in terms of the record, it has to be what we call cleaned or curated so that you get the noise and all the missing this out of it, that's a big step. And then it needs to be enriched, which means that the various components that are going to be meaningful, you know, again, are brought together so that you can create that cohort of patients, that individual patient record that now is useful in so many instances across farm, again, from development, all the way through commercial. So the idea of this exchange is to enable that exact process that I just described to have a, a place, a platform where various entities can bring their data in order to have it linked and integrated and cleaned and enriched so that they get something that is a package like a data package that they can actually use. >>And it's easy to plug into their, into their studies or into their use cases. And I think a really important component of this is that it's gotta be a place where various third parties can feel comfortable bringing their data together in order to match it with other third parties. That is a, a real value, uh, that the industry is increasingly saying would be important to them is, is the ability to bring in those third-party data sets and be able to link them and create these, these various data products. So that's really the idea of the data exchange is that you can benefit from accessing data, as Greg mentioned in catalogs that maybe are across these various silos so that you can do the kind of work that you need. And that we take a lot of the hard work out of it. I like to give an example. >>We spoke with one of our clients at one of the large pharma companies. And, uh, I think he expressed it very well. He said, what I'd like to do is have like a complete dataset of lupus. Lupus is an autoimmune condition. And I've just like to have like the quintessential lupus dataset that I can use to run any number of use cases across it. You know, whether it's looking at my phase one trial, whether it's selecting patients and enriching for later stage trials, whether it's understanding patient responses to different therapies as I designed my studies. And so, you know, this idea of adding in therapeutic area indication, specific data sets and being able to create that for the industry in the meta mentioned, being able to do that, for example, in diabetes, that's how pharma clients need to have their needs met is through taking the hard workout, bringing the data together, having it very therapeutically enriched so that they can use it very easily. >>Thank you for that detail and the meta. I mean, you can't do this with humans at scale in technology of all the things that Lorraine was talking about, the enrichment, the provenance, the quality, and of course, it's got to be governed. You've got to protect the privacy privacy humans just can't do all that at massive scale. Can it really tech that's where technology comes in? Doesn't it and automation. >>Absolutely. >>I, couldn't more, I think the biggest, you know, whether you talk about precision medicine or you talk about decentralized trials, I think there's been a lot of hype around these terms, but what is really important to remember is technology is the game changer and bringing all that data together is really going to be the key enabler. So multimodal data integration, looking at things like security or federated learning, or also when you're talking about leveraging AI, you're not talking about things like bias or other aspects around that are, are critical components that need to be addressed. I think the industry is, uh, it's partly, still trying to figure out the right use cases. So it's one part is getting together the data, but also getting together the right data. Um, I think data interoperability is going to be the absolute game changer for enabling this. Uh, but yes, um, absolutely. I can, I can really couldn't agree more with what Lorraine just said, that it's bringing all those different aspects of data together to really drive that precision medicine strategy. >>Excellent. Hey Greg, let's talk about protocols decentralized clinical trials. You know, they're not new to life silences, but, but the adoption of DCTs is of course sped up due to the pandemic we've had to make trade-offs obviously, and the risk is clearly worth it, but you're going to continue to be a primary approach as we enter 2022. What are the opportunities that you see to improve? How DCTs are designed and executed? >>I see a couple opportunities to improve in this area. The first is, uh, back to technology. The infrastructure around clinical trials has, has evolved over the years. Uh, but now you're talking about moving away from kind of site focus to the patient focus. Uh, so with that, you have to build out a new set of tools that would help. So for example, one would be novel trial, recruitment, and screening, you know, how do you, how do you find patients and how do you screen them to see if are they, are they really a fit for, for this protocol? Another example, uh, very important documents that we have to get is, uh, you know, the e-consent that someone's says, yes, I'm, well, I understand this study and I'm willing to do it, have to do that in a more remote way than, than we've done in the past. >>Um, the exciting area, I think, is the use of, uh, eco, uh, E-Pro where we capture data from the patient using apps, devices, sensors. And I think all of these capabilities will bring a new way of, of getting data faster, uh, in, in this kind of model. But the exciting thing from, uh, our perspective at Lily is it's going to bring more data about the patient from the patient, not just from the healthcare provider side, it's going to bring real data from these apps, devices and sensors. The second thing I think is using real-world data to identify patients, to also improve protocols. We run scenarios today, looking at what's the impact. If you change a cut point on a, a lab or a biomarker to see how that would affect, uh, potential enrollment of patients. So it, it definitely the real-world data can be used to, to make decisions, you know, how you improve these protocols. >>But the thing that we've been at the challenge we've been after that this probably offers the biggest is using real-world data to identify patients as we move away from large academic centers that we've used for years as our sites. Um, you can maybe get more patients who are from the rural areas of our countries or not near these large, uh, uh, academic centers. And we think it'll bring a little more diversity to the population, uh, who who's, uh, eligible, but also we have their data, so we can see if they really fit the criteria and the probability they are a fit for the trial is much higher than >>Right. Lorraine. I mean, your clients must be really pushing you to help them improve DCTs what are you seeing in the field? >>Yes, in fact, we just attended the inaugural meeting of the de-central trials research Alliance in, uh, in Boston about two weeks ago where, uh, all of the industry came together, pharma companies, uh, consulting vendors, just everyone who's been in this industry working to help define de-central trials and, um, think through what its potential is. Think through various models in order to enable it, because again, a nascent concept that I think COVID has spurred into action. Um, but it is important to take a look at the definition of DCT. I think there are those entities that describe it as accessing data directly from the patient. I think that is a component of it, but I think it's much broader than that. To me, it's about really looking at workflows and processes of bringing data in from various remote locations and enabling the whole ecosystem to work much more effectively along the data continuum. >>So a DCT is all around being able to make a site more effective, whether it's being able to administer a tele visit or the way that they're getting data into the electronic data captures. So I think we have to take a look at the, the workflows and the operating models for enabling de-central trials and a lot of what we're doing with our own technology. Greg mentioned the idea of electronic consent of being able to do electronic patient reported outcomes, other collection of data directly from the patient wearables tele-health. So these are all data acquisition, methodologies, and technologies that, that we are enabling in order to get the best of the data into the electronic data capture system. So edit can be put together and processed and submitted to the FDA for regulatory use for clinical trial type submission. So we're working on that. I think the other thing that's happening is the ability to be much more flexible and be able to have more cloud-based storage allows you to be much more inter-operable to allow API APIs in order to bring in the various types of data. >>So we're really looking at technology that can make us much more fluid and flexible and accommodating to all the ways that people live and work and manage their health, because we have to reflect that in the way we collect those data types. So that's a lot of what we're, what we're focused on. And in talking with our clients, we spend also a lot of time trying to understand along the, let's say de-central clinical trials continuum, you know, w where are they? And I know Namita is going to talk a little bit about research that they've done in terms of that adoption curve, but because COVID sort of forced us into being able to collect data in more remote fashion in order to allow some of these clinical trials to continue during COVID when a lot of them had to stop. What we want to make sure is that we understand and can codify some of those best practices and that we can help our clients enable that because the worst thing that would happen would be to have made some of that progress in that direction. >>But then when COVID is over to go back to the old ways of doing things and not bring some of those best practices forward, and we actually hear from some of our clients in the pharma industry, that they worry about that as well, because we don't yet have a system for operationalizing a de-central trial. And so we really have to think about the protocol it's designed, the indication, the types of patients, what makes sense to decentralize, what makes sense to still continue to collect data in a more traditional fashion. So we're spending a lot of time advising and consulting with our patients, as well as, I mean, with our clients, as well as CRS, um, on what the best model is in terms of their, their portfolio of studies. And I think that's a really important aspect of trying to accelerate the adoption is making sure that what we're doing is fit for purpose, just because you can use technology doesn't mean you should, it really still does require human beings to think about the problem and solve them in a very practical way. >>Great, thank you for that. Lorraine. I want to pick up on some things that Lorraine was just saying. And then back to what Greg was saying about, uh, uh, DCTs becoming more patient centric, you had a prediction or IDC, did I presume your fingerprints were on it? Uh, that by 20 25, 70 5% of trials will be patient-centric decentralized clinical trials, 90% will be hybrid. So maybe you could help us understand that relationship and what types of innovations are going to be needed to support that evolution of DCT. >>Thanks, Dave. Yeah. Um, you know, sorry, I, I certainly believe that, uh, you know, uh, Lorraine was pointing out of bringing up a very important point. It's about being able to continue what you have learned in over the past two years, I feel this, you know, it was not really a digital revolution. It was an attitude. The revolution that this industry underwent, um, technology existed just as clinical trials exist as drugs exist, but there was a proof of concept that technology works that this model is working. So I think that what, for example, telehealth, um, did for, for healthcare, you know, transition from, from care, anywhere care, anytime, anywhere, and even becoming predictive. That's what the decentralized clinical trials model is doing for clinical trials today. Great points again, that you have to really look at where it's being applied. You just can't randomly apply it across clinical trials. >>And this is where the industry is maturing the complexity. Um, you know, some people think decentralized trials are very simple. You just go and implement these centralized clinical trials, but it's not that simple as it it's being able to define, which are the right technologies for that specific, um, therapeutic area for that specific phase of the study. It's being also a very important point is bringing in the patient's voice into the process. Hey, I had my first telehealth visit sometime last year and I was absolutely thrilled about it. I said, no time wasted. I mean, everything's done in half an hour, but not all patients want that. Some want to consider going back and you, again, need to customize your de-centralized trials model to, to the, to the type of patient population, the demographics that you're dealing with. So there are multiple factors. Um, also stepping back, you know, Lorraine mentioned they're consulting with, uh, with their clients, advising them. >>And I think a lot of, um, a lot of companies are still evolving in their maturity in DCTs though. There's a lot of boys about it. Not everyone is very mature in it. So it's, I think it, one thing everyone's kind of agreeing with is yes, we want to do it, but it's really about how do we go about it? How do we make this a flexible and scalable modern model? How do we integrate the patient's voice into the process? What are the KPIs that we define the key performance indicators that we define? Do we have a playbook to implement this model to make it a scalable model? And, you know, finally, I think what organizations really need to look at is kind of developing a de-centralized mature maturity scoring model, so that I assess where I am today and use that playbook to define, how am I going to move down the line to me reach the next level of maturity. Those were some of my thoughts. Right? >>Excellent. And now remember you, if you have any questions, use the chat box below to submit those questions. We have some questions coming in from the audience. >>At one point to that, I think one common thread between the earlier discussion around precision medicine and around decentralized trials really is data interoperability. It is going to be a big game changer to, to enable both of these pieces. Sorry. Thanks, Dave. >>Yeah. Thank you. Yeah. So again, put your questions in the chat box. I'm actually going to go to one of the questions from the audience. I get some other questions as well, but when you think about all the new data types that are coming in from social media, omics wearables. So the question is with greater access to these new types of data, what trends are you seeing from pharma device as far as developing capabilities to effectively manage and analyze these novel data types? Is there anything that you guys are seeing, um, that you can share in terms of best practice or advice >>I'll offer up? One thing, I think the interoperability isn't quite there today. So, so what's that mean you can take some of those data sources. You mentioned, uh, some Omix data with, uh, some health claims data and it's the, we spend too much time and in our space putting data to gather the behind the scenes, I think the stat is 80% of the time is assembling the data 20% analyzing. And we've had conversations here at Lilly about how do we get to 80% of the time is doing analysis. And it really requires us to think, take a step back and think about when you create a, uh, a health record, you really have to be, have the same plugins so that, you know, data can be put together very easily, like Lorraine mentioned earlier. And that comes back to investing in as an industry and standards so that, you know, you have some of data standard, we all can agree upon. And then those plugs get a lot easier and we can spend our time figuring out how to make, uh, people's lives better with healthcare analysis versus putting data together, which is not a lot of fun behind the scenes. >>Other thoughts on, um, on, on how to take advantage of sort of novel data coming from things like devices in the nose that you guys are seeing. >>I could jump in there on your end. Did you want to go ahead? Okay. So, uh, I mean, I think there's huge value that's being seen, uh, in leveraging those multiple data types. I think one area you're seeing is the growth of prescription digital therapeutics and, um, using those to support, uh, you know, things like behavioral health issues and a lot of other critical conditions it's really taking you again, it is interlinking real-world data cause it's really taking you to the patient's home. Um, and it's, it's, there's a lot of patients in the city out here cause you can really monitor the patient real-time um, without the patient having coming, you know, coming and doing a site visit once in say four weeks or six weeks. So, um, I, and, uh, for example, uh, suicidal behavior and just to take an example, if you can predict well in advance, based on those behavioral parameters, that this is likely to trigger that, uh, the value of it is enormous. Um, again, I think, uh, Greg made a valid point about the industry still trying to deal with resolving the data interoperability issue. And there are so many players that are coming in the industry right now. There are really few that have the maturity and the capability to address these challenges and provide intelligence solutions. >>Yeah. Maybe I'll just, uh, go ahead and, uh, and chime into Nikita's last comment there. I think that's what we're seeing as well. And it's very common, you know, from an innovation standpoint that you have, uh, a nascent industry or a nascent innovation sort of situation that we have right now where it's very fragmented. You have a lot of small players, you have some larger entrenched players that have the capability, um, to help to solve the interoperability challenge, the standards challenge. I mean, I think IBM Watson health is certainly one of the entities that has that ability and is taking a stand in the industry, uh, in order to, to help lead in that way. Others are too. And, uh, but with, with all of the small companies that are trying to find interesting and creative ways to gather that data, it does create a very fragmented, uh, type of environment and ecosystem that we're in. >>And I think as we mature, as we do come forward with the KPIs, the operating models, um, because you know, the devil's in the detail in terms of the operating models, it's really exciting to talk these trends and think about the future state. But as Greg pointed out, if you're spending 80% of your time just under the hood, you know, trying to get the engine, all the spark plugs to line up, um, that's, that's just hard grunt work that has to be done. So I think that's where we need to be focused. And I think bringing all the data in from these disparate tools, you know, that's fine, we need, uh, a platform or the API APIs that can enable that. But I think as we, as we progress, we'll see more consolidation, uh, more standards coming into play, solving the interoperability types of challenges. >>And, um, so I think that's where we should, we should focus on what it's going to take and in three years to really codify this and make it, so it's a, it's a well hum humming machine. And, you know, I do know having also been in pharma that, uh, there's a very pilot oriented approach to this thing, which I think is really healthy. I think large pharma companies tend to place a lot of bets with different programs on different tools and technologies, to some extent to see what's gonna stick and, you know, kind of with an innovation mindset. And I think that's good. I think that's kind of part of the process of figuring out what is going to work and, and helping us when we get to that point of consolidating our model and the technologies going forward. So I think all of the efforts today are definitely driving us to something that feels much more codified in the next three to five years. >>Excellent. We have another question from the audience it's sort of related to the theme of this discussion, given the FDA's recent guidance on using claims and electronic health records, data to support regulatory decision-making what advancements do you think we can expect with regards to regulatory use of real-world data in the coming years? It's kind of a two-parter so maybe you guys can collaborate on this one. What role that, and then what role do you think industry plays in influencing innovation within the regulatory space? >>All right. Well, it looks like you've stumped the panel there. Uh, Dave, >>It's okay to take some time to think about it, right? You want me to repeat it? You guys, >>I, you know, I I'm sure that the group is going to chime into this. I, so the FDA has issued a guidance. Um, it's just, it's, it's exactly that the FDA issues guidances and says that, you know, it's aware and supportive of the fact that we need to be using real-world data. We need to create the interoperability, the standards, the ways to make sure that we can include it in regulatory submissions and the like, um, and, and I sort of think about it akin to the critical path initiative, probably, I don't know, 10 or 12 years ago in pharma, uh, when the FDA also embrace this idea of the critical path and being able to allow more in silico modeling of clinical trial, design and development. And it really took the industry a good 10 years, um, you know, before they were able to actually adopt and apply and take that sort of guidance or openness from the FDA and actually apply it in a way that started to influence the way clinical trials were designed or the in silico modeling. >>So I think the second part of the question is really important because while I think the FDA is saying, yes, we recognize it's important. Uh, we want to be able to encourage and support it. You know, when you look for example, at synthetic control arms, right? The use of real-world data in regulatory submissions over the last five or six years, all of the use cases have been in oncology. I think there've been about maybe somewhere between eight to 10 submissions. And I think only one actually was a successful submission, uh, in all those situations, the real-world data arm of that oncology trial that synthetic control arm was actually rejected by the FDA because of lack of completeness or, you know, equalness in terms of the data. So the FDA is not going to tell us how to do this. So I think the second part of the question, which is what's the role of industry, it's absolutely on industry in order to figure out exactly what we're talking about, how do we figure out the interoperability, how do we apply the standards? >>How do we ensure good quality data? How do we enrich it and create the cohort that is going to be equivalent to the patient in the real world, uh, in the end that would otherwise be in the clinical trial and how do we create something that the FDA can agree with? And we'll certainly we'll want to work with the FDA in order to figure out this model. And I think companies are already doing that, but I think that the onus is going to be on industry in order to figure out how you actually operationalize this and make it real. >>Excellent. Thank you. Um, question on what's the most common misconception that clinical research stakeholders with sites or participants, et cetera might have about DCTs? >>Um, I could jump in there. Right. So, sure. So, um, I think in terms of misconceptions, um, I think the communist misconceptions that sites are going away forever, which I do not think is really happening today. Then the second, second part of it is that, um, I think also the perspective that patients are potentially neglected because they're moving away. So we'll pay when I, when I, what I mean by that neglected, perhaps it was not the appropriate term, but the fact that, uh, will patients will, will, will patient engagement continue, will retention be strong since the patients are not interacting in person with the investigator quite as much. Um, so site retention and patient retention or engagement from both perspectives, I think remains a concern. Um, but actually if you look at, uh, look at, uh, assessments that have been done, I think patients are more than happy. >>Majority of the patients have been really happy about, about the new model. And in fact, sites are, seem to increase, have increased investments in technology by 50% to support this kind of a model. So, and the last thing is that, you know, decentralized trials is a great model and it can be applied to every possible clinical trial. And in another couple of weeks, the whole industry will be implementing only decentralized trials. I think we are far away from that. It's just not something that you would implement across every trial. And we discussed that already. So you have to find the right use cases for that. So I think those were some of the key misconceptions I'd say in the industry right now. Yeah. >>Yeah. And I would add that the misconception I hear the most about is, uh, the, the similar to what Namita said about the sites and healthcare professionals, not being involved to the level that they are today. Uh, when I mentioned earlier in our conversation about being excited about capturing more data, uh, from the patient that was always in context of, in addition to, you know, healthcare professional opinion, because I think both of them bring that enrichment and a broader perspective of that patient experience, whatever disease they're faced with. So I, I think some people think is just an all internet trial with just someone, uh, putting out there their own perspective. And, and it's, it's a combination of both to, to deliver a robust data set. >>Yeah. Maybe I'll just comment on, it reminds me of probably 10 or 15 years ago, maybe even more when, um, really remote monitoring was enabled, right? So you didn't have to have the study coordinator traveled to the investigative site in order to check the temperature of the freezer and make sure that patient records were being completed appropriately because they could have a remote visit and they could, they could send the data in a via electronic data and do the monitoring visit, you know, in real time, just the way we're having this kind of communication here. And there was just so much fear that you were going to replace or supplant the personal relationship between the sites between the study coordinators that you were going to, you know, have to supplant the role of the monitor, which was always a very important role in clinical trials. >>And I think people that really want to do embrace the technology and the advantages that it provided quickly saw that what it allowed was the monitor to do higher value work, you know, instead of going in and checking the temperature on a freezer, when they did have their visit, they were able to sit and have a quality discussion for example, about how patient recruitment was going or what was coming up in terms of the consent. And so it created a much more high touch, high quality type of interaction between the monitor and the investigative site. And I think we should be looking for the same advantages from DCT. We shouldn't fear it. We shouldn't think that it's going to supplant the site or the investigator or the relationship. It's our job to figure out where the technology fits and clinical sciences always got to be high touch combined with high-tech, but the high touch has to lead. And so getting that balance right? And so that's going to happen here as well. We will figure out other high value work, meaningful work for the site staff to do while they let the technology take care of the lower quality work, if you will, or the lower value work, >>That's not an, or it's an, and, and you're talking about the higher value work. And it, it leads me to something that Greg said earlier about the 80, 20, 80% is assembly. 20% is actually doing the analysis and that's not unique to, to, to life sciences, but, but sort of question is it's an organizational question in terms of how we think about data and how we approach data in the future. So Bamyan historically big data in life sciences in any industry really is required highly centralized and specialized teams to do things that the rain was talking about, the enrichment, the provenance, the data quality, the governance, the PR highly hyper specialized teams to do that. And they serve different constituencies. You know, not necessarily with that, with, with context, they're just kind of data people. Um, so they have responsibility for doing all those things. Greg, for instance, within literally, are you seeing a move to, to, to democratize data access? We've talked about data interoperability, part of that state of sharing, um, that kind of breaks that centralized hold, or is that just too far in the future? It's too risky in this industry? >>Uh, it's actually happening now. Uh, it's a great point. We, we try to classify what people can do. And, uh, the example would be you give someone who's less analytically qualified, uh, give them a dashboard, let them interact with the data, let them better understand, uh, what, what we're seeing out in the real world. Uh, there's a middle user, someone who you could give them, they can do some analysis with the tool. And the nice thing with that is you have some guardrails around that and you keep them in their lane, but it allows them to do some of their work without having to go ask those centralized experts that, that you mentioned their precious resources. And that's the third group is those, uh, highly analytical folks that can, can really deliver, uh, just value beyond. But when they're doing all those other things, uh, it really hinders them from doing what we've been talking about is the high value stuff. So we've, we've kind of split into those. We look at people using data in one of those three lanes and it, and it has helped I think, uh, us better not try to make a one fit solution for, for how we deliver data and analytic tools for people. Right. >>Okay. I mean, DCT hot topic with the, the, the audience here. Another question, um, what capabilities do sponsors and CRS need to develop in-house to pivot toward DCT? >>Should I jump in here? Yeah, I mean, um, I think, you know, when, when we speak about DCTs and when I speak with, uh, folks around in the industry, I, it takes me back to the days of risk-based monitoring. When it was first being implemented, it was a huge organizational change from the conventional monitoring models to centralize monitoring and risk-based monitoring, it needs a mental reset. It needs as Lorraine had pointed out a little while ago, restructuring workflows, re redefining processes. And I think that is one big piece. That is, I think the first piece, when, you know, when you're implementing a new model, I think organizational change management is a big piece of it because you are disturbing existing structures, existing methods. So getting that buy-in across the organization towards the new model, seeing what the value add in it. And where do you personally fit into that story? >>How do your workflows change, or how was your role impacted? I think without that this industry will struggle. So I see organizations, I think, first trying to work on that piece to build that in. And then of course, I also want to step back for the second to the, uh, to the point that you brought out about data democratization. And I think Greg Greg gave an excellent point, uh, input about how it's happening in the industry. But I would also say that the data democratization really empowerment of, of, of the stakeholders also includes the sites, the investigators. So what is the level of access to data that you know, that they have now, and is it, uh, as well as patients? So see increasingly more and more companies trying to provide access to patients finally, it's their data. So why shouldn't they have some insights to it, right. So access to patients and, uh, you know, the 80, 20 part of it. Uh, yes, he's absolutely right that, uh, we want to see that flip from, uh, 20%, um, you know, focusing on, on actually integrating the data 80% of analytics, but the real future will be coming in when actually the 20 and 18 has gone. And you actually have analysts the insights out on a silver platter. That's kind of wishful thinking, some of the industries is getting there in small pieces, but yeah, then that's just why I should, why we share >>Great points. >>And I think that we're, we're there in terms that like, I really appreciate the point around democratizing the data and giving the patient access ownership and control over their own data. I mean, you know, we see the health portals that are now available for patients to view their own records, images, and labs, and claims and EMR. We have blockchain technology, which is really critical here in terms of the patient, being able to pull all of their own data together, you know, in the blockchain and immutable record that they can own and control if they want to use that to transact clinical trial types of opportunities based on their data, they can, or other real world scenarios. But if they want to just manage their own data because they're traveling and if they're in a risky health situation, they've got their own record of their health, their health history, uh, which can avoid, you know, medical errors occurring. So, you know, even going beyond life sciences, I think this idea of democratizing data is just good for health. It's just good for people. And we definitely have the technology that can make it a reality. Now >>You're here. We have just about 10 minutes left and now of course, now all the questions are rolling in like crazy from the crowd. Would it be curious to know if there would be any comments from the panel on cost comparison analysis between traditional clinical trials in DCTs and how could the outcome effect the implementation of DCTs any sort of high-level framework you can share? >>I would say these are still early days to, to drive that analysis because I think many companies are, um, are still in the early stages of implementation. They've done a couple of trials. The other part of it that's important to keep in mind is, um, is for organizations it's, they're at a stage of, uh, of being on the learning curve. So when you're, you're calculating the cost efficiencies, if ideally you should have had two stakeholders involved, you could have potentially 20 stakeholders involved because everyone's trying to learn the process and see how it's going to be implemented. So, um, I don't think, and the third part of it, I think is organizations are still defining their KPIs. How do you measure it? What do you measure? So, um, and even still plugging in the pieces of technology that they need to fit in, who are they partnering with? >>What are the pieces of technology they're implementing? So I don't think there is a clear cut as answered at this stage. I think as you scale this model, the efficiencies will be seen. It's like any new technology or any new solution that's implemented in the first stages. It's always a little more complex and in fact sometimes costs extra. But as, as you start scaling it, as you establish your workflows, as you streamline it, the cost efficiencies will start becoming evident. That's why the industry is moving there. And I think that's how it turned out on the long run. >>Yeah. Just make it maybe out a comment. If you don't mind, the clinical trials are, have traditionally been costed are budgeted is on a per patient basis. And so, you know, based on the difficulty of the therapeutic area to recruit a rare oncology or neuromuscular disease, there's an average that it costs in order to find that patient and then execute the various procedures throughout the clinical trial on that patient. And so the difficulty of reaching the patient and then the complexity of the trial has led to what we might call a per patient stipend, which is just the metric that we use to sort of figure out what the average cost of a trial will be. So I think to point, we're going to have to see where the ability to adjust workflows, get to patients faster, collect data more easily in order to make the burden on the site, less onerous. I think once we start to see that work eases up because of technology, then I think we'll start to see those cost equations change. But I think right now the system isn't designed in order to really measure the economic benefit of de-central models. And I think we're going to have to sort of figure out what that looks like as we go along and since it's patient oriented right now, we'll have to say, well, you know, how does that work, ease up? And to those costs actually come down and then >>Just scale, it's going to be more, more clear as the media was saying, next question from the audiences, it's kind of a best fit question. You all have touched on this, but let me just ask it is what examples in which, in which phases suit DCT in its current form, be it fully DCT or hybrid models, none of our horses for courses question. >>Well, I think it's kind of, uh, it's, it's it's has its efficiencies, obviously on the later phases, then the absolute early phase trials, those are not the ideal models for DCTs I would say so. And again, the logic is also the fact that, you know, when you're, you're going into the later phase trials, the volume of number of patients is increasing considerably to the point that Lorraine brought up about access to the patients about patient selection. The fact, I think what one should look at is really the advantages that it brings in, in terms of, you know, patient access in terms of patient diversity, which is a big piece that, um, the cities are enabling. So, um, if you, if, if you, if you look at the spectrum of, of these advantages and, and just to step back for a moment, if you, if you're looking at costs, like you're looking at things like remote site monitoring, um, is, is a big, big plus, right? >>I mean, uh, site monitoring alone accounts for around a third of the trial costs. So there are so many pieces that fall in together. The challenge actually that comes when you're in defining DCTs and there are, as Rick pointed out multiple definitions of DCTs that are existing, uh, you know, in the industry right now, whether you're talking of what Detroit is doing, or you're talking about acro or Citi or others. But the point is it's a continuum, it's a continuum of different pieces that have been woven together. And so how do you decide which pieces you're plugging in and how does that impact the total cost or the solution that you're implementing? >>Great, thank you. Last question we have in the audience, excuse me. What changes have you seen? Are there others that you can share from the FDA EU APAC, regulators and supporting DCTs precision medicine for approval processes, anything you guys would highlight that we should be aware of? >>Um, I could quickly just add that. I think, um, I'm just publishing a report on de-centralized clinical trials should be published shortly, uh, perspective on that. But I would say that right now, um, there, there was a, in the FDA agenda, there was a plan for a decentralized clinical trials guidance, as far as I'm aware, one has not yet been published. There have been significant guidances that have been published both by email and by, uh, the FDA that, um, you know, around the implementation of clinical trials during the COVID pandemic, which incorporate various technology pieces, which support the DCD model. Um, but I, and again, I think one of the reasons why it's not easy to publish a well-defined guidance on that is because there are so many moving pieces in it. I think it's the Danish, uh, regulatory agency, which has per se published a guidance and revised it as well on decentralized clinical trials. >>Right. Okay. Uh, we're pretty much out of time, but I, I wonder Lorraine, if you could give us some, some final thoughts and bring us home things that we should be watching or how you see the future. >>Well, I think first of all, let me, let me thank the panel. Uh, we really appreciate Greg from Lily and the meta from IDC bringing their perspectives to this conversation. And, uh, I hope that the audience has enjoyed the, uh, the discussion that we've had around the future state of real world data as, as well as DCT. And I think, you know, some of the themes that we've talked about, number one, I think we have a vision and I think we have the right strategies in terms of the future promise of real-world data in any number of different applications. We certainly have talked about the promise of DCT to be more efficient, to get us closer to the patient. I think that what we have to focus on is how we come together as an industry to really work through these very vexing operational issues, because those are always the things that hang us up and whether it's clinical research or whether it's later stage, uh, applications of data. >>We, the healthcare system is still very fragmented, particularly in the us. Um, it's still very, state-based, uh, you know, different states can have different kinds of, uh, of, of cultures and geographic, uh, delineations. And so I think that, you know, figuring out a way that we can sort of harmonize and bring all of the data together, bring some of the models together. I think that's what you need to look to us to do both industry consulting organizations, such as IBM Watson health. And we are, you know, through DTRA and, and other, uh, consortia and different bodies. I think we're all identifying what the challenges are in terms of making this a reality and working systematically on those. >>It's always a pleasure to work with such great panelists. Thank you, Lorraine Marshawn, Dr. Namita LeMay, and Greg Cunningham really appreciate your participation today and your insights. The next three years of life sciences, innovation, precision medicine, advanced clinical data management and beyond has been brought to you by IBM in the cube. You're a global leader in high tech coverage. And while this discussion has concluded, the conversation continues. So please take a moment to answer a few questions about today's panel on behalf of the entire IBM life sciences team and the cube decks for your time and your feedback. And we'll see you next time.

>>Welcome back. You're watching the cubes coverage of AWS 2021. We're here in the Venetian, formerly the sands convention center in Las Vegas. My name is Dave Volante. Really excited to have Bob bright tell here. He's the director of SAP global alliances at IBM and Manu.. I'm going to try that again. Pro boxcar, is that correct? Rebecca Head of Linux and IBM alliances at AWS Manu. I'm sorry for bashing your name, but at least I got it right, guys. Great to see you. Thanks for coming on. >>And I'm actually now AWS partnership. I had SAP before, so it's great. I first, my first reinvest, >>I have a old DNA title. That's great. That's why I was asking you about Philly before you don't have the accent though. Bob, >>I'm not a Philly native, so cowboy >>Because you have the SAP connection there. IBM, AWS. It's like, whoa, what's going on here? >>Well, maybe I'll start and then have my new, my new, make some comments. And I'll just start by just, uh, we're real excited to be here. IBM's a diamond sponsor at, at re-invent and it's great to be in person and really appreciate AWS being able to put this event on this week and get us back in person. It really makes a difference. And I know there's a lot of people virtually as well, but, um, IBM and AWS have worked together for a number of years. Uh, maybe we could characterize it more opportunistically, um, prior, but in the last 12, 18 months, I think there's been a lot of developments that have really made us come together strategically as partners. I know we'll talk a little bit about red hat during the course of the conversation, but with IBM's >>You say opportunities like you mean in the field and the more strategic >>Relationship or strategic and with IBM's open hybrid cloud strategy. And, uh, with so many of our clients preferring AWS is their cloud. Um, we are working together now to meet clients where they're at to help them get the value of the cloud. And we're talking a little bit about coming out of the pandemic before this. Um, and one of the things that we're seeing with our clients that IBM is a lot of that low hanging fruit. The cloud was achieved, maybe the lift and shift or doing some SAS based applications, but now it's even more important to rapidly adopt hybrid cloud and cloud technologies to provide your business with flexible innovation transformation, all of those things. So that's why it has been important for us to, to partner with AWS strategically. Um, our clients are telling us that when they do move those heavier workloads to the cloud and do it in a hybrid model, they see about two and a half times the value. >>So with that, our partnership is multi-dimensional, we're doing a lot with IBM consulting. My new we'll talk a little bit about IBM software and red hat. Just one example, Dave, with IBM consulting, we now are up to almost 10,000 certifications and 10 plus AWS competencies. So that competency chart that shows we're knocking them all out on the, on the checkerboard there to get them to IBM consulting competencies. And we just had the energy one announced this week. So IBM consulting is in area software's big too. In my news, been helping us with that part of the partner. >>Well, it's, you know, to your point, you can't pick whatever cliche you want. You can't fight fashion. The trend is your friend. You have a lot of, a lot of people want to be on AWS. So rather than fighting, oh, we have our own cloud. No, you've got to meet customers where they are, right >>David, this is where this takes us. You know, the analogy we use between Bob and I, IBM boss spoke about IBM consulting, which we know has been a strategic partnership for the last two, two and a half years. I think I'm going to share the best kept secret in the cloud phase right now. IBM software and AWS now are working together. The analogy we use is IBM software and AWS. I like peanut butter and jelly better together. And over the last 12 months, the two companies have accelerated working together around three key dimensions. Number one, around product, number two around making sure our customers, joint customers successful. And number three, around building a robust ecosystem of partners. One thing that we have realized is just helping customers modernize. Migrate is challenging. And on the product side, now we have about 15 products on AWS marketplace. >>I think about trusty or verify insecurity, cloud Pak for data, uh, uh, Cognos data DataStage over the next 12 months, we plan to land all of the cloud packs. These are containerized version of IBM software on AWS and the marketplace. In addition, many of our customers are now using the managed red hat, OpenShift servers. We launched it earlier in April. This year, we are seeing tremendous customer feedback, tremendous, uh, growth there that is also informing that customers really like the open shirt model managed services one-click deployment. And so our goal is over the next 12 months, launched many more IBM software as a managed service offering. So that's kind of like what we're doing on the product side, on the customer success. A great example is somebody is helping a big oil and gas customers managed with this energy transition that we're working through. Um, Schlumberger software around simulation runs on OpenShift on Amazon in a hybrid environment, especially critical as we have a lot of oil and gas data that needs to have maybe sit on premises, uh, because of data residency requirements. >>I think the third piece is around building an ecosystem of partners for our red hat OpenShift services, which we launched April. We already have 30 partners that are helping customers not only to modernize, but to migrate on AWS. We know modernization is challenging, moving to containers is difficult. So we need this robust ecosystem of partners and Bob and I, and you know, the IBM and AWS team are investing heavily. We have cash credit to do financial incentives plus also technical content so that our customers so that our partners can help customers to be successful. Yeah, >>So the cloud packs are cool. That makes a lot of sense. And now the acquisition of red hat makes it easier. It's a catalyst gets IBM, much more closely aligned to developers and it makes it easier for things like cloud packs to be migrated to the cloud and being running cloud native. How did that acquisition affect from your standpoint menu and Bob I'd love your thoughts and your relationship. >>The red hat acquisition by IBM is a net positive red hat. And AWS have been working together for 14 years now. And we have tens of thousands of customers that are running mission critical workloads, such as SAP, Oracle databases. And there's a lot of trust that is engendered by working in the field for 14 years, uh, supporting mission critical customers, mission critical workloads. And so that relationship has provided a lot of tailwinds to our partnership with IBM software. I think a lot of the stuff we spoke about a lot of the progress you've made in the last six to eight to 12 months, a big function is that the trust that we have engendered working together with red hat. >>Yeah. I'll add Dave that, um, I, I agree with my new comments on the red hat. Red hat really is the epitome of openness right. Of open source software and the history that Manu described with AWS, there has been excellent adoption of red hat on AWS, red hat, enterprise Linux, and then most recently, um, red hat OpenShift on AWS. And just to give another example to the ecosystem point, just this morning, red hat with IBM, with a major ISV named Solonus announced that Solonus will be running one of their key, uh, applications and releasing it on Rossa on AWS. And all this means for our clients is faster adoption and acceleration and being able to innovate, um, in a hybrid way. So that's really the value that red hat is helping, um, to bring to the table in our cloud packs are available on open shift and rose as an option as well. So we're excited about the red hat partnership. It's really essential to our partnership into our, our hybrid cloud strategy. >>You mentioned up front, you know, happy that AWS decided to have this show. Of course, a lot of people watching online and you can get massive scale online, but there's nothing like the live event, you know, and when you make announcements at a live event, there's a little buzz going on and you get feedback. So are you making any hard news here? What, what announcements can you >>Share? Yeah, well, the one we had, um, on, um, uh, Solonus earlier with red hat and to do roasts on top of red hat was one and there's just an advance of, um, of re-invent. Um, we announced something in the data and AI space. So that's another big area of our partnership is data and AI. So we're in, we announced that in the oil industry and in the, um, uh, in that area that we are partnering together with AWS to be able to get insights on data so that we could get clean and reusable energy solutions out there. And there's so much untapped data. We know data is such an important resource, that that's an area that we're going to partner on with our cloud Pak for data on AWS. And of course underlying everything is open shifts. So that's one big announcement. We're also doing a lot in security for IBM and my news has been working closely with this. So my new, I, I know you're close to the integrations we're doing with AWS. So I'll let you comment maybe on some of the things in security. >>I mean, everybody's a security company these days, right? I mean, >>And then we continue to work and making sure that a lot of the IBM security products are integrating with our native services. So the customers have a seamless experience. And as he you'll see a lot of the same investments happening over 2022 as we grow the >>Partnership. So what like a QRadar or something like that >>Are, for example, integrating with security hub. That would be great example. >>I mean, it's the, it's the number one topic for CEO's that has been for a while and still will be okay. So give us a little roadmap, you know, maybe Bob, you could start, where do you want to see this relationship go? Um, what can we expect in the, in the coming 12 months? Yeah, well, >>Again, we're super excited about our partnership with AWS. I think we're just scratching the surface of how we're going to add value to our clients on this, on this hybrid cloud journey that they're all going through. And IBM, and this has been in our financial reports and in our earnings and everything, we're investing over a billion dollars in the ecosystem. And so partners like AWS are critical to provide that platform of growth for our clients and innovation for our clients. So all of the things that I talked about in money talked about today, whether it be our IBM consulting capabilities or our IBM software, our red hat, we're going to continue to invest. We talked about the red hat acquisition. IBM has made a few other acquisitions that help drive this partnership and drive value to our clients for adoption, from Instana to Turbonomic X, to some really innovative cloud consulting companies like Knorr cloud in towels. So we're going to continue to make investments. And I think we're just on the tip of the iceberg and we invite everybody at re-invent, either in person, which is exciting or virtually to learn more about our partnership and how we can help you and my new, any additional comments to that. >>Thanks, Bob V have a golden child hair with red hat OpenShift on Amazon. That'd be launched in April. We are seeing tremendous customer adoption. So we suspect that in next year, we'll continue to see solid adoption around red hat OpenShift. That VocaliD is also informing how customers want a more native experience for IBM software on AWS. And so we, um, we are targeting to, to launch many more IBM software in a native format on edema. So that would be the big team for next year. Uh, in addition, again, I'll call to action to our partner community. There's a huge opportunity to help our joint customers to modernize and migrate on AWS via both IBM, AWS are leaning in, we have cash credit to give financial incentives to partners, to help our customers, to migrate and modernize as well as we are also creating a lot of technical content that is not freely available so that a lot of our partners can start this. IBM focus on AWS practice >>Guys. Thanks so much for coming on the cube. Congratulations, and look at, you know, I often say the next 10 years is not going to be like the last 10 years. The cloud is expanding is a really good example. So thank you for your time. Appreciate your time. All right. You're watching the cube, the leader in high tech coverage at AWS reinvent 2021

(upbeat techno music) >> From around the globe, it's theCUBE. With digital coverage of Postgres Vision 2021. Brought to you by EBD. >> Hello everyone, this is David Vellante, for the CUBE. And we're here covering Postgres Vision 2021. The virtual version, thCUBE virtual, if you will. And welcome to our power-panel. Now in this session, we'll dig into database modernization. We want to better understand how and why customers are tapping open source to drive innovation. But at the same time, they've got to deliver the resiliency and enterprise capabilities that they're used to that are now necessary to support today's digital business requirements. And with me are three experts on these matters. Abdul Sheik, is Global CTO and President of Cintra. Young Il Cho, aka Charlie, is High Availability Cluster Sales Manager, at Daone CNS. And Alan Villalobos, is the Director of Development Partnerships, at IBM. Gentlemen, welcome to theCUBE. >> Thank you, Dave, nice to be here. >> Thank you, Dave. >> All right, let's talk trends and frame the problem. Abdul, I want to start with you? Cintra you're all about this topic. Accelerating innovation using EDB Postgres helping customers move to modern platforms. And doing so, you got to do it cost-effectively but what's driving these moves? What are the problems that you're seeing at the organizations that you serve? >> Oh, so let me quickly introduce, Abdul Sheik, CTO. I'll quickly introduce Cintra. So we are a multicloud and database architecture MSP. And we've been around for 25 plus years. Headquartered in New York and the UK. But as a global organization, we're serving our SMB customers as well as large enterprise customers. And the trends we're seeing certainly in this day and age is transformation and modernization. And what that means is, customers looking to get out of the legacy platforms, get out of the legacy data centers and really move towards a modern strategy with a lower cost base, while still retaining resiliency and freedom. Ultimately, in terms of where they're going. The key words that really I see driving this, number one is choice. They've been historically locked into vendors. With limited choice with a high cost base. So choice, freedom to choose in terms of what database technologies they apply to which workloads and certainly EDB and the work that has been done to closely marry what enterprise RD platforms offer with EDBs in a work that they've done in terms of filling those gaps and addressing where the resiliency monitoring performance and security requirements are, are certainly are required from an enterprise customer perspective. Choice is driving the move that we see and choice towards a lower cost platform that can be deployed anywhere. Both on-prem modernization customers are looking to retain on premise platforms or moving into any multi clouds whether it's an infrastructure cloud play or a platform cloud play. And certainly with EDBs offering in terms of, you know the latest cloud native offerings also very interesting. And lastly, aside from just cost and the freedom to choose where they deploy those platforms the SLA, the service level model where is the resiliency requirement where the which system is going to bronze, silver, gold? Which ones are the tier one revenue platform revenue generating platforms which are the lower, lower utility platforms. So a combination of choice, a combination of freedom to deploy anywhere and while still maintaining the resiliency and the service levels that the customers need to deliver to their businesses >> Abdul that was a beautiful setup. And, and we've got so much to talk about here because customers want to move from point A to point B but getting there and they, they need help. It's sometimes not trivial. So Charlie Daone is a consultancy. You've got a strong technical capabilities. What are you seeing in this space? You know, what are the major trends? Why are organizations considering that move? And what are some of the considerations there? >> Well, like in other country in South Korea or so our a lot of customers, banking's a manufacturing distributor. They are 90, over 90%. They are all are using Oracle DB and a rack system. But as the previous presenters pointed out, a lot of customers that are sick of the Oracle and they have to undergo the huge cost of a maintenance costs. They want to move away from this cost stress. And secondly, they can think about they're providing service to customer on their cloud base which is a private or the public. So we cannot imagine running on database, Oracle database running on the cloud the system that's not matches on this cloud. And first and second, and finally the customer what they want is the cost and they want to move away from the Oracle locking. They cannot be just a slave at Oracle for a long time and the premium for the new cloud the service for the customer. >> Great. Thank you for that. Oh, go ahead. Yeah. Did you have something else to add Charlie go ahead and please. >> No that's all. >> Okay, great. Yeah, Allen, welcome to theCUBE. You know, it's very interesting to us. IBM, you, you, of course, you're a big player in database. You have a lot of expertise here. And you partner with EDB, you're offering Postgres to customers, you know, what are you seeing? Charlie was talking about Oracle and RAC. I mean, the, the, the thing there is obviously, we talked about the maintenance costs but there's also a lot of high availability capabilities. That's something that IBM really understands well. Do you see this as largely a cloud migration trend? Is it more modernization? Interested in what's IBM's perspective on this? >> I think modernization is the right word. The points that the previous panelists brought up or are on point, right? You know, lower TCO or lower costs in general but that of agility and then availability for developers and data scientists as well. And then of course, you know, hybrid cloud, right? You know, you want to be able to deploy on prem or in the cloud, or both in a mixture of all of that. And I think, I think what ties it together is the customers are looking for insights, right? And, you know, especially in larger organizations there's a myriad of data sources that they're already working with. And, you know, we, you know we want to be able to play in that space. We want to give an offering that is based on Postgres and open source and be able to further what they're strong at at and kind of, you know on top of that, you know, a layer of, of of need that we see is, is seamless data governance across all of those different stores. >> All right, I'm going to go right to the heart of the hard problem here. So if, I mean, I want to, it's just that I want to get from point A to point B, I want to save money. I want to modernize, but if I'm the canary in the coal mine at the customer, I'm saying guys, migration scares me. How do I do that? What are the considerations? And what do I need to know that I don't know. So Abdul, maybe you could walk us through what are some of the concerns that customers have? How do you help mitigate those? Whether it's other application dependencies, you know freezing code, you know, getting, again from that point A to point B without risking my existing business processes how do you handle that? >> Yeah, certainly I think a customer needs to understand what the journey looks like to begin with. So we've actually developed our own methodology that we call Rocket Cloud, which is also part of our cloud modernization strategy that builds in and database modernization strategy built into it starts with an assessment in terms of current state discovery. Not all customers totally understand where they are today. So understanding where the database state is, you know where the risks lie what are the criticality of the various databases? What technologies are used, where we have RAC or we don't have RAC but we have data God, where we have encryption. And so on. That gives the customer a very good insight in terms of the current state, both commercially and technically that's a key point to understand how they're licensed today and what costs could be freed up to free the journey to effectively fund the journey. It's a big, big topic, but once we do that, we get an idea and we've actually developed a tool called rapid discovery. That's able to discover a largest stake without knowing the database list. We just put the scripts at the database servers themselves and it tells us exactly which databases are suited to be you know, effectively migrated to Postgres with in terms of the feature function usage in terms of how heavy they are, would store procedures in the database amount of business logic use of technologies like RAC data guard and how they convert over to to Postgres specifically. That ultimately gives us the ability to give that customer an assessment and that assessment in a short sharp few weeks and get the customer view of all of my hundreds of databases. Here are the subset of candidates for Postgres and specifically than we do the schemer advisor tool the actual assessment tool from EDB, which gives us a sense of how well the schema gets converted and how best to then also look at the stored procedure conversion as well. That gives the customer a full view of their architecture mapping their specific candidate databases and then a cost analysis in terms of what that migration looks like and how we migrate. We also run and maintain those platforms once we're on EDB. >> Thank you for that again, very clear but so you're not replacing, doing an organ transplant. You may, you're you're, you know, this is not I don't mean this as a pejorative, but you're kind of cherry picking those workloads that are appropriate for EDB and then moving those and then maybe, maybe through attrition or, you know over time, sun-setting those other, those other core pieces. >> Exactly. >> Charlie, let me ask you, so we talked about RAC, real application clusters, data guard. These are, you know kind of high profile Oracle capabilities. Can you, can you really replicate the kind of resiliency at lower costs with open source, with EDB Postgres and how do you do that? >> It's my turn? >> yes, please. >> Quite technically, again, I go on in depths and technically the RAC, RAC system is so-called is the best you know, best the tool to protect data and especially in the Unix system, but apart from the RAC by the some nice data replication solution we just stream the application and log shipping and something and then monitor Pam and, and EFM solution which is enterprise failover manager. So even though it be compared to Apple the Apple RAC versus with EDB solution, we can definitely say that RAC is more stable one, but after migration, whatever, we can overcome the, you know, drawbacks of the HA cluster system by providing the EDB tools. So whatever the customer feel that after a successful migration, utilizing the EDB high availability failable solution they can make of themselves at home. So that's, that's how we approach it with the customers. >> So, Alan, again, to me, IBM is fascinating here with your level of involvement because you're the, you guys are sort of historically the master of proprietary the mainframes, VCM, CICF, EB2, all that stuff. And then, you know IBM was the first I remember Steve Mills actually announced we're going to invest a billion dollars in open source with Linux. And that was a major industry milestone. And of course, the, the acquisition of red hat. So you've got now this open source mindset this open source culture. So we, you know, as it's all about recovery in, in database and enterprise database and all the acid properties in two phase commits, and we're talking about, you know the things that Charlie just talked about. So what's your perspective here? IBM knows a lot about this. How do you help customers get there? >> Yeah, well, I mean the main, the main thrust right now IBM has a offering called IBM cloud Pak for data which from here, which runs EDB, right? EDB, Postgres runs on top of cloud Pak for Data But the, you know I think going back to Abdul's points about, you know migrating whatever's needed and whatever can be migrated to Postgres and maybe migrating other things other places, we have data virtualization and autoSQL, right? So once you have migrated those parts of your database or those schemes that can be, having, you know a single point where you can query across them and by the way, being able to query across them you know, before, during and after migration as well. Right? So we're kind of have that seamless experience of layer of SQL. And now with autoSQL of spark SQL as well, as you're, as you're migrating and after is, I'd say, you know, key to this. >> What, what's the typical migration look like? I know I'm sorry, but it's a consultant question but thinking about the, you know, the average, in terms of timeframe, what are the teams look like? You know who are the stakeholders that I need to get involved? If I'm a customer to really make this a success? maybe Abdul, you could talk about that and Charlie and Alan can chime in. >> Well, I think, well, number one you knew the exact sponsors bought into it in terms of the business case, supporting the business case an architect has got a big picture understanding not only database technology but also infrastructure that they're coming from as well as the target cloud platforms and how you ensure that the infrastructure can deliver the performance. So the architect role is important, of course the core DBA that lives within the scope of the database understands the schema of the data model the business logic itself, and the application on it. That's key specifically around the application certification testing connectivity and the migration of the code. And specifically in terms of timeline just to touch on that quickly. I mean, in our experience so far and we're seeing the momentum really really take off the last 18 months, a small project with limited business logic within the database itself can we migrate it in a couple of months but typically with all the testing and rigor around that you typically say three months timeline a medium-sized complexity projects, a six month timeline and a large complex project could be anything from nine months and beyond, but it really comes down to how heavy the database is with business logic and the database and how much effort it will take to re-engineer effectively migrate that PLC code, business logic into EDB given the compatibility level between Oracle and EDB it's relatively certainly an easier path than any other target platform in terms of options. Yeah. Not perspective. That's certainly looks like the composition of a team and timeline >> Charlie or Alan, anything you guys would add. >> Yeah. So, so I think all those personas make sense. I think you might, on the consumer side of the consumer the consumer of the data side the data scientists often we see, you know during migrations and then obviously the dev ops, I think or any operations, right, have to be heavily involved. And then lastly, you know, you see more and more data steward role or data steward type persona, CDO office type type person coming in there make sure that, you know, whatever data governance that is already in place or wants to be in place after the migration is also part of the conversation. >> Why EDB? You know, there's a lot of databases out there you know, it's funny, I always say like, you know, 10, 15 years ago databases were kind of sort of a boring market, right? It was like, okay, you're going to work or whatever. And now it's exploded. You got open source databases, you got, you know not only sequel databases, you got graph databases you know, you get cloud databases, it's going crazy. Why EDB? You wonder if you guys could address that? >> Allan why don't you go first this time? I'll compliment your answers. >> Yeah. I mean, again, I think it goes back to, to the, the I guess varying needs and, and enterprises. Right. And I think that's, what's driven this explosion in databases, whether it's a document store like you're saying, or, or new types of RDBMS, the needs that we talked about at the beginning, like lower TCO, and the push to open source. But you know, the fact of the matter is that that yes, there is a myriad, an ecosystem of databases, pretty much any organization. And so, yeah, we want to tap into that. And why EDB? EDB has done a great job of taking Postgres and making it enterprise ready, you know, that's what they're, they're good at and that, you know fits very nicely with the IBM story obviously. And, and so, you know, and they've they've worked with us as well. They have an operator on, on the runs on red hat OpenShift. So that makes it portable as well but also part of the IBM cloud Pak for data story. And, and yeah, you know, we want to break down those silos. We realized that that need is there for all of these, you know, there's this ecosystem of databases. And so, you know, we're, we see our role as being that platform, whether it's red hat OpenShift, or IBM cloud Pak for data that, that unifies, and kind of gives you that single pane of glass across all of those sources. >> And Charlie, you're obviously all in, you've got EDB in your background. Why EDB for you? >> Before talking about EDB you asked about the previous question about how the migration was different from Oracle to EDB. We had a couple of success story in Korea telecom and some banking area, and it was easier. So EDB provide MTK tool as a people know but it was an appropriate, like a 90%. So we are the channel partner of the EDB for four years. So what we have done was to hire the Oracle expert. So we train Oracle export as as EDB expert at the same time so that they can approach customer and make it easy. So you have no worry about that. Just migrating EDB, Oracle to EDB. There is a no issue. Those telltales include all the tasks, you know Stratus test and trainee, and a POC that we there. So by investing that Oracle expert that we could overcome and persuade the customer to adopt EDB. So, why EDB? Simply I can say there, is there any database they can finally replaced Oracle in the world? Why is the, it's the interoperability between Oracle to EDB as the many experts pointed out there is no other DBE. They can, you know, 90, 90% in compatibility and intercooperability with EDB. That's why, of course, there's the somewhat, you know budget issues or maintenance issue cost the issue escape from Oracle lock-in. But I think the the number one reason was the interoperability and the compatibility with database itself, Oracle database. That was a reason, I guess >> Great Abdul we've talked about, we all know the, as is, you've got a high maintenance costs. You got a lot of tuning, and it's just a lot of complexity. What about the 2B maybe you could share with us sort of the outcome some of the outcomes you've seen what the business impact has been of some of these migrations? >> Sure. I mean, I'll give you a very simple example then just the idea of running Oracle on prem a lot of customer systems teams, for example will drive a virtualization VMware strategy. We know some of the challenges of running Oracle MBM where from a license perspective. So giving the business the ability where I want to go customer in the financial services market in New York, heavy virtualization strategy the ability for them to move away from Oracle on, you know expensive hardware on to Postgres EDB on virtualization just leverage existing skillsets, leveraging existing investment in terms of infrastructure, and also give them portability in AWS. The other clouds, you know, in terms of a migration. More from a business perspective as well, I would say about some of the Allan's points in terms of just freeing up the ability for data scientists and data consumers, to, you know, to consume some of that data from an Postgres perspective more accessibility spinning up environments quicker less latency in terms of the agility is another key word in terms of the tangible differences, the business, lower cost agility, and the freedom to deploy anywhere at the end of the day. Choices, I think the key word that we could come back to and knowing that we can do that to Charlie's point specifically around maintaining service levels. And as architects, we support some of the big, big names out there in terms of airlines, online, cosmetic retailers, financial services, trading applications, hedge funds, and they all want one thing as architect: for us to deliver that resiliency and stand behind them. And as the MSP we're accountable to ensure those systems are up and running and performing. So knowing that the EDB is provided the compatibility but also plugged the specific requirements around performance management, security availability that's fundamentally been key. >> [Dave I mean, having done a lot of TCO studies in this area, it's, it's it Oracle's different. You know, normally the biggest component of TCO is labor with Oracle. The biggest component of TCO is licensed and maintenance costs. So if you can virtualize and reduce those costs and of course, of course the Oracle will fight you and say we won't support it in a VMware environment. Of course, you know, they will, but, but you got to really, you got to battle. But, so here's my last question. So if I'm a customer in that state that you described you know, a lot of sort of Oracle sprawl a lot of databases out there, high maintenance costs, the whole lock-in thing. I got to choices. I, you know, a lot of choices out there. One is EDB. You guys have convinced me that you've got the expertise If I can partner with firms like yours, it's safer route. Okay, cool. My other choice is Oracle is going to, The Oracle sales reps is going to get me in a headlock and talk about exit data and how their Oracle cloud, and how it's, they've invested a lot there. And they have, and, I can pay by the drink all this sort of modern sort of discussion, you know, Oracle act like they invented it late to the game. And then here we are. So, so help me. What's the pitch as to, well, that's kind of compelling. It's maybe the safe bet they're there. They're working with my CIO, whatever. Why should I go with the open source route versus that route? It sounds kind of attractive to me, help me understand that each of you maybe take me through that. Abdul, why don't you start. >> Yeah. I'd say, you know, Oracle's being the defacto for so many years that people have just assumed and defaulted saying, high availability, RAC, DR. Data guard, you know, and I'll apply to any database need that I have. And at the end of the day customers have a three tier database requirement: the lowest, less critical, bronze level databases that really don't need RAC or a high availability, silver tier that are departmental solutions. That means some level of resiliency. And then you've got your gold revenue producing brand impact databases that are they're down. And certainly they won. You see no reason why the bronze and silver databases can be targeted towards EDB. Admittedly, we have some of our largest customers are running platforms, are running $5 million an hour e-commerce platform or airlines running large e-commerce platforms. And exit data certainly has a place. RAC has a place in those, in those scenarios. Were not saying that the EDB is a solution for everything in all scenarios, but apply the technology where it's appropriate where it's required and, you know, generally wherever Oracle has being the defacto and it's being applied across the estate, that's fundamentally what's changed. It doesn't have to be the only answer you have multiple choices now. EDB provides us with the ability to probably address, you know more than 50% of the databases' state, and comfortably cope with that and just apply that more expensive kind of gold tier one cost-based but also capability, you know from the highest requirements of performance and availability where it's appropriate. >> Yeah. Very pragmatic approach. Abdul, thank you for that. And Charlie. Charlie, what's your perspective? Give us your closing thoughts. >> Well, it has been, Oracle has been dominating in Asia in South Korea has market or over many years. So customers got tired of this, continuous spending money for the maintenance costs and there is no discount. There is no negotiation. So they want to move away from expensive stuff. And they were looking for a flexible platform with the easygoing and the high speed and performance open source database like a possibly as career. And now the EDB cannot replace a hundred percent of existing legacy worker, but 10%, 20% 50% as time goes on the trend that will continue. And it will be reaching some high point or replacing the existing Oracle system. And it can, it can also leading to good business chance to a channel partner and EDB steps and other related business in open source. >> Great. Thank you, Charlie and Allen, bring us home here. Give us your follow up >> I think my, co- panelists hit the nail on the head, right? It's a menu, right? That's as things become more diverse and as people make more choices and as everybody wants more agility, you have to provide, I mean, and so that, that's where that's coming in and I liked the way that Andul I kind of split it into gold silver and bronze. Yeah. And I think that that's where, we're going, right? I mean you should ask your developers right? Are your developers like pining to start up a new instance of Oracle every time you're starting a new project? Probably not reach for their Postgres right? And so, because of that, that's where this is coming from and that's not going to change. And, and yeah, that that ecosystem is going to continue to, to thrive. And there'll be lots of different flavors in the growing open source ecosystem. >> Yeah. I mean, open source absolutely is the underpinning you know, the, the bedrock of innovation, these days. Gentlemen, great power panel. Thanks so much for bringing your perspectives and best of luck in the future. >> Thank you, next time we'll try and match our backgrounds >> Next time. Well, we'll up our game. Okay. And thank you for watching everybody. This is Dave Volante for theCUBE. Stay tuned for more great coverage. Postgres vision, 21. Be right back. (upbeat techno music)

>>from >>around the globe. It's >>the cube >>with digital >>coverage of IBM >>Think 2021 >>brought to you by IBM. Welcome back to the cubes coverage of IBM Think 2021 virtual, I'm john for your host of the cube. We're here virtual again in real life soon is right around the corner but we got a great guest here, Cameron art managing director at A T and T for IBM. Cameron manages the A T and T global account for IBM camera. Great to see you. Thanks for coming on the cube. >>Thank you very much, john it's great to be >>Here. Uh, can almost imagine how complicated and big and large a TNT is with respect to IBM in the history and 18 very large company. What's the relationship with I B M and A T and T over the years? How has that evolved? And what, how do you approach that role as the managing director? >>Well, it's been fascinating. Um as you said, we've got to large complex companies but also to brand names that are synonymous for innovation, whether it be in in compute or technology or communications. But the most fascinating thing is if you look back at our relationship and this is two brands that have been around for well over 100 years. Our relationship actually has some fascinating backdrop to it. My favorite is in 1924, A T and T sent a picture of thomas Watson sr over a telephone wire to IBM and thomas Watson said they sent this over the telephone. We are united in a community of interest. They want to make it easier for businesses to transact as do I. We need to work together. And since then, there has been a number of advanced advances that both of us have driven collectively and individually. And it's been a it's been a long running and treasured relationship in the IBM company. >>It's such a storied relationship on both sides. I mean, the history is just amazing. They could do a whole History Channel segment on both 18 T N I B M. Uh but together, it's kind of the better together story, as you pointed out from that example, going back to sending a picture with the phone lines, like, oh my God, that's instagram on the internet um, happening. But how are they responding to the relationship now? I'll see with cloud, um Native exploding with the ability to get more access and you're seeing a lot more things evolved, more complexity is emerging. That needs to be abstracted away. You're seeing businesses saying, hey, I can do more with less, I can connect more more access. But then that also services more potential opportunities and challenges. How are you responding with a T and T? How are they responding to that dynamic with you guys? >>Yeah, I think it's fascinating because when I originally approached this relationship and I've been doing this for 12 months now, a little over 12 months and when I originally approach it as with anything else, many times, you're trying to enter something that is quite special and make it even better. And my approach at least initially with AT and T was very much one of, we're going to provide even better service. We're going to jointly grow together in the market and strengthen each of our businesses and we're gonna work for something broader than ourselves. And I'll get into a little more of the last point later. But those first two things from an A T T response perspective, and I think this is a common perspective among many clients is we'll see if your actions follow your words. And so it's been a process. We've gone through to understand that I'm a champion for A T and T inside of IBM and those interests that we share individually and collectively will be represented at the highest levels. And we will mature this relationship into one of not just kind of supply chain partners because we're very complementary to each other, but more ecosystem partners and my belief in my core. And you see this much with many of the business strategies that are out there. The ecosystem strategy, this sum is greater than the parts, it's not a zero sum game is something that's absolutely blooming in the market. >>Yeah, that ecosystem message is one of the things that's resonating and coming clearly out of IBM think 2021 this year and in the industry is seeing the success of network effects, ecosystem changes is the constant that's happening. Certainly the pandemic and now coming out of it, people want to have a growth strategy that's gonna be relevant, current and impactful. And you you pointed that out growth with each other is interesting. And you you shared some perspective on this just recently with an example of what is underway there where you heading with that? I mean talk more about this growth with each other because that really is an ecosystem dynamic. What is underway and where are you heading? >>It's a fascinating ecosystem dynamic and it's something that we've adopted wholeheartedly within AT and T in terms of not only how we work. So there are very basic examples examples like we, rather than answering our PS and responding to uh to requirements, we're co creating with our clients, we have multiple cloud garages going with a T and T. Where we identify outcomes that we believe could be possible and then we show and allow the client to experience the outcome of that rather than a power point slides. So there's this kind of base of how do you work with each other? But then much more broadly in the market, it didn't take long for us to realize that, you know, the addressable market, if if I were selling A T and T, everything I could ever sell them and at and T was selling IBM everything they could ever sell us. The addressable market is, let's say $10 billion. But the moment at which we pointed ourselves outside to the external market, we realize that that market opportunity expands by a factor of 20 or by a factor of 50, we have the opportunity to create unique value together. And I think that kind of comes from the core of how we work together. >>I'm also intrigued by your comments about working together for a greater purpose. You said you'd address that later. What do you mean by that? I mean that's a little bit very higher purpose. Um North Star and as you mentioned, you know, working together in the ecosystem that kind of seems tactical and strategic as well. But what's this greater purpose? What does that mean? >>Well, my belief and it's something I learned actually, as I got indoctrinated into the work that 18 T does the work that IBM does and how we do it. But we share many common purposes in terms of what we believe on the whole, in terms of progress in society. So for example, equality in the workplace. We hosted a women's day lunch and actually multiple women stays lunch days luncheons across the United States, where we had hundreds of female leaders from both IBM and AT and T. Collaborating together talking about how tips and tricks for how they continue to advance in the workplace. Another example is in equality and diversity and inclusion. Both A T and T and IBM have a strong commitment and if you'll see IBM just published, just published their diversity and inclusion study where we actually demonstrate here the numbers, here's our targets, here's where we want to get 18 T has exactly that same belief. Finally, in stem education for educating our future leaders in science and technology, engineering and math. Both 18 T and IBM for our future, need those skills showing up in the marketplace and Corey Anthony is just a quick spot for any of you would think cory cory Anthony who see it diversity and development Officer at AT and T is going to give a great presentation on A. T. N. T. S work in stem for younger generations. So there are many things that are, I would say societal on a broader purpose statement that we share a belief in together, >>that's awesome people and also people want to work on a team that's mission driven, has impact beyond just the profit and loss me, I love capitalism personally myself, I'm an entrepreneur but been there done that, but we're living in a cultural shift. Now we're starting to see a remote work. You're starting to see virtual teams, new use cases that have different expectations and experiences um, in the work place and also at home. So you know, with mobile that could be on the side of the soccer fields or you know, skiing or running or jogging and take a message to pull over to a chat, jump into an audio chat, listen to a podcast, engage. So we're all tethered now, this is exchanging the experiences and this is going to change the game for how you work together. >>100%. And by the way, we're all teller tethered hopefully through a T and T mobile connectivity devices, it was kind of amusing how much that has become a part of our lives and the core value, one of the core value propositions of AT and T is obviously connecting businesses to each other, but also consumers through their mobile brand, but also then to entertainment. I will say when I was in Augusta at the Masters, you know, people that have been there know that you're not allowed to have cell phones. It was amazing just in conversations how often whoever was I was having a conversation with and myself would say, well I'd like to look that up, hold on, can I get that statistic and and we we realized we're missing a big part of our of our lives in terms of communication. But those requirements of connecting people in new ways and in their homes were remotely actually only reinforce this shared value proposition of when you have the technology and you have it securely between our company IBM and A T and T. We play a massive part in that and it's something I'm quite proud of. >>You guys have a really interesting position there with the history of with the relationship and as you pointed out, A T and T has to be in the forefront of cutting edge user experience technology bringing. I mean, they are the edge. I mean they ultimately from base station down to the device to the person to the account you're talking about a real edge there, that's a person's consumer. Um They got to provide these new services. So I gotta ask you, you mentioned at the top of this interview that your goal is to provide even better service to a T and T. A pretty big pressure point for IBM. You know, you gotta deliver step up and their expectations must be high. Can you take us through perspectives on that kind of even better service when you've got a client that's on the cutting edge of having to deliver new kinds of things like better notifications. Smarter devices, Smarter software, more fault tolerant, highly available services. These are things that, you know, there's a lot of pressure take us through that what's it like? >>There is a lot of pressure, but there's a lot of consistency in terms of expectations and it's something that both of us understand very well and I would argue that it's probably the reason we work so well together, Both 18 T and IBM for years uh namely 50 hundreds of years have understood that if we're transacting for business, were transaction transacting on something that has to get done so on both sides of the equation. Not only do we push the edge of what can be done technically or for business, but we also understand the expectations of the business clients that are, it works every time and it works in every way I needed to. So for us, when we work together, I think that healthy balance of uh part musician, part engineer uh comes out very, very strongly in both teams, >>camera great insight and great to talk to you. I love to get the perspective on, you know, the kind of challenges and opportunities that you're um seizing at IBM with A T and T. Again, the history is amazing. Um the impact of the industry at both levels you mentioned Tom Watson senior than you got Junior. That in that generation just carries forward. You got that vibe back now with hybrid cloud. Arvin loves clouds. So, you know, you got a lot of things happening and it's really strong over at IBM and the theme this year generally is better together. So awesome, awesome work. Congratulations. >>Thank you very much. I will tell you, I don't want to I don't want to miss the opportunity to talk a bit about the future because from an A T and T and IBM perspective, we're doing a load of work around private five G or five G in general. This is something that provides an absolutely low latency, huge band with with a lot of actually characteristics from a business perspective that are manageable and it will enable. What I believe is another big wave in the technology and business industry, which is new business models very similar to that of the Internet. Originally, it allows with IBM technology and 18 T technology, they have something called multi access. Such compute these are absolutely blazing fast. Five G boxes that will be in not only businesses but universities, sports stadiums, you name that, you name it, changing the experience of how people consume technology or the benefits of technology, which I couldn't be more excited about >>awesome future ahead. Great. There's a big wave certainly away we've never seen before. Cameron, art managing Director at A T and T at IBM. Great insight. Thanks for sharing. Thanks for coming on. >>Thanks john >>Okay, Cube coverage of IBM think 2021. I'm John Ferrier. Thanks for watching. Mm. Mhm. Mhm.

>> From around the globe, It's theCUBE. With digital coverage of IBM Think 2021, brought to you by IBM. >> Hi, welcome back to theCUBE's coverage of IBM Think 2021 virtual. I'm John Furrier host of the CUBE. We got a great guest here. Brian Bouchard is the co-founder president and CEO of Alacrinet. Brian great to see you remoting in all the way from Puerto Rico to Palo Alto. >> That's right. >> Great to see you. >> Thanks for First of all, thanks John, for having me. I really appreciate the opportunity. >> Yeah, great to see you. Thanks for coming on. First of all, before we get into what you guys do and and how this all ties in to Think. What do you guys do at Alacrinet? Why the name? A it's good you're at the top of the list and alphabetically, but tell us the, the, the the secret behind the name and what you guys do. >> So, first of all Alacrinet is based on the root word alacrity which means a prompt and willing, a prompt a joyous prompt to, excuse me, to achieve a common goal. So we ultimately are a network of individuals with the traits of alacrity. So Alacrinet. So that's our name. >> Great. So what's your relationship with IBM and how you guys have been able to leverage the partnership program in the marketplace? Take us through the relationship. >> So, well, first of all Alacrinet is a platinum IBM business partner and it was awarded recently the 2020 IBM North American partner of the year award. And we were selected amongst 1600 other business partners across North America. We've been actually a consulting, an IT consulting company for almost 20 years now. And we were founded in 2002 in Palo Alto and we have focused specifically on cyber security since 2013. And then as part, go ahead. >> What are some of the things that you guys are working on? Because obviously, you know, the business is hot right now. Everyone's kind of looking at COVID saying we're going to double down on the most critical projects and no time for leisurely activities when it comes to IT. And cloud scale projects, you know mission critical stuff's happening what are you guys working on? >> So we're, we're focused on cybersecurity, our security services really compliment IBM's suite of security solutions and cover the full spectrum from our research and penetration testing, which helps identify vulnerabilities before a breach occurs. And we also have managed security services which helps prevent, detect and remediate attacks in real time. And then finally, we also have a security staffing division and a software resell division, which kind of rounds out the full amount of offerings that we have to provide protection for our clients. >> What are some of the biggest challenges you guys have as a business, and how's IBM helping you address those? >> Well, as you know, John, we all know the importance of cybersecurity in today's world, right? So it's increasing in both demand and importance and it's not expected to wane anytime soon. Cyber attacks are on the rise and there's no there's no expected end in sight to this. And in fact, just this week on 60 minutes, Jay Powell, the chairman of the federal reserve board he noted that cyber attacks were the number one threat to the stability of the US economy. Also this week, a public school in Buffalo New York was hacked with ransomware and the school you know, this, the school district is just contemplating you know, paying the ransom to the hackers. So there's literally thousands of these attacks happening every day, whether it's in local school district or a state government, or an enterprise even if you don't hear about them, they're happening In adding to the complexity that the cyber attackers pose is the complexity of the actual cybersecurity tools themselves. There isn't a single solution provider or a single technology, that can ensure a company's security. Our customers need to work with many different companies and disconnected tools and processes to build an individual strategy that can adequately protect their organizations. >> You know, I love this conversation whenever I talk to practitioners on cybersecurity, you know that first of all, they're super smart, usually cyber punks and they also have some kinds of eclectic backgrounds, but more importantly is that there's different approaches in terms of what you hear. Do you, do you put more if you add more firefighters, so to speak to put out the fires and solve the problems? Or do you spend your time preventing the fires from happening in the first place? You know, and you know, the buildings are burning down don't make fire fire, don't make wood make fire resistance, you know, more of a priority. So there's less fires needing firefighters So it's that balance. You throw more firefighters at the problem or do you make the supply or the material the business fireproof, what's your take on that? >> Yeah, well, it kind of works both ways. I mean, we've seen customers want it. They really want choice. They want to, in some cases they want to be the firefighter. And in some cases they want the firefighter to come in and solve their problems. So, the common problem set that we're seeing with our that our customers encounter is that they struggle one, with too many disparate tools. And then they also have too much data being collected by all these disparate tools. And then they have a lack of talent in their environment to manage their environments. So what we've done at Alacrinet is we've taken our cybersecurity practice and we've really specifically tailored our offerings to address these core challenges. So first, to address the too many disparate tools problem, we've been recommending that our clients look at security platforms like the IBM Cloud Pak for security the IBM Cloud Pak for security is built on a security platform that allows interoperability across various security tools using open standards. So our customers have been responding extremely positively to this approach and look at it as a way to future-proof their investments and begin taking advantage of interoperability with, and, tools integration. >> How about where you see your business going with this because, you know, there's not a shortage of need or demand How are you guys flexing with the market? What's the strategy? Are you going to use technology enablement? You're going to more human driven. Brian, how do you see your business unfolding? >> Well, actually really good. We're doing very well. I mean, obviously we made the, the top the business partner for IBM in 2020. They have some significant growth and a lot of interest. I think we really attack the market in a, in a with a good strategy which was to help defragment the market if you will. There's a lot of point solutions and a lot of point vendors that various, you know, they they spent specialized in one piece of the whole problem. And what we've decided to do is find them the highest priority list, every CSO and CIO has a tick list. So that how that, you know, first thing we need we need a SIM, we need an EDR, we need a managed service. We need, what's the third solution that we're doing? So we, we need some new talent in-house. So we actually have added that as well. So we added a security staffing division to help that piece of it as well. So to give you an idea of the cybersecurity market size it was valued at 150 billion in 2019 and that is expected to grow to 300 billion by 2027. And Alacrinet is well-positioned to consolidate the many fragmented aspects of the security marketplace and offer our customers more integrated and easier to manage solutions. And we will continue to help our customers select the best suite of solutions to address all types of cybersecurity, cybersecurity threats. >> You know, it's it's such a really important point you're making because you know, the tools just have piled up in the tool shed. I call it like that. It's like, it's like you don't even know what's in there anymore. And then you've got to support them. Then the world's changed. You get cloud native, the service areas increasing and then the CSOs are also challenged. Do I, how many CLAWs do I build on? Do I optimize my development teams for AWS or Azure? I mean, now that's kind of a factor. So, you have all this tooling going on they're building their own stuff they're building their own core competency. And yet the CSO still needs to be like maintaining kind of like a relevance list. That's almost like a a stock market for the for the products. You're providing that it sounds like you're providing that kind of service as well, right? >> Yeah, well, we, we distill all of the products that are out there. There's thousands of cybersecurity products out there in the marketplace and we kind of do all that distillation for the customer. We find using, you know, using a combination of things. We use Forrester and Gartner and all the market analysts to shortlist our proposed solutions that we offer customers. But then we also use our experience. And so since 2013, we've been deploying these solutions across organizations and corporations across America and we've, we've gained a large body of experience and we can take that experience and knowledge to our customers and help them, you know, make make some good decisions. So they don't have to, you know, make them go through the pitfalls that many companies do when selecting these types of solutions. >> Well congratulations, you've got a great business and you know, that's just a basic search making things easier for the CSO, more so they can be safe and secure in their environment. It's funny, you know, cyber warfare, you know the private companies have to fight their own battles got to build their own armies. Certainly the government's not helping them. And then they're confused even with how to handle all this stuff. So they need, they need your service. I'm just curious as this continues to unfold and you start to see much more of a holistic view, what's the IBM angle in here? How, why are you such a big partner of theirs? Is it because their customers are working with you they're bringing you into business? Is it because you have an affinity towards some of their products? What's the connection with IBM? >> All of the above. (chuckles) So I think it probably started with our affinity to IBM QRadar product. And we have, we have a lot of expertise in that and that solution. So that's, that's where it started. And then I think IBM's leadership in this space has been remarkable, really. So like what's happening now with the IBM Cloud Pak for security you know, building up a security platform to allow all these point solutions to work together. That's the roadmap we want to put our customers on because we believe that's the that's the future for this, this, this marketplace. >> Yeah. And the vision of hybrid cloud having that underpinning be with Red Hat it's a Linux kernel, model of all things >> Yeah. Super NetEase. >> Locked in >> It's portable, multiple, you can run it on Azure. IBM Cloud, AWS. It's portable. I mean, yeah, all this openness, as you probably know cyber security is really a laggard in the security in the information technology space as far as adopting open standards. And IBM is I think leading that charge and you'll be able to have a force multiplier with the open standards in this space. >> Open innovation with open source is incredible. I mean, if you, if, if if open source can embrace a common platform and build that kind of control plane and openness to allow thriving companies to just build out then you have an entire hybrid distributed architecture. >> Yeah. Well, I think companies want to use the best in breed. So when we, when we show these solutions to customers they want the best in breed. They always say, I don't, when it comes to security they don't want second best. They want the best it's out there because they're securing their crown jewels. So that makes sense. So the problem with, you know having all these different disparate solutions that are all top in their category none of them talk to each other. So we need to address that problem because without that being solved, this is just going to be more it's going to compound the complexity of the problems we solve day to day. >> Awesome. Congratulations, Brian, great story. You know entrepreneur built a great business over the years. I think the product's amazing. I think that's exactly what the market needs and just shows you what the ecosystem is all about. This is the power of the ecosystem. You know, a thousand flowers are blooming. You got a great product. IBM is helping as well. Good partnership, network effects built in and and still a lot more to do. Congratulations. >> Absolutely. >> Okay. >> Thank you very much >> Brian Bouchard >> Made my impression. I appreciate that >> Thanks for coming on theCUBE Appreciate it. I'm John Furrier with IBM thinks 2021 virtual coverage. Thanks for watching. (outro music plays)

>>from >>around the >>globe, it's the >>cube with digital >>coverage of IBM, >>Think 2021 >>brought to you by IBM. Welcome back to the cubes coverage of IBM Think 2021 virtual, I'm john for your host of the cube, had a great line up here talking sustainability. Kary musa ph d general manager of AI applications and block chains, career great to see you and wayne both the vice president of corporate environmental affairs and chief sustainability officer, among other things involved in the products around that. Wait and korean, great to see you. Thanks for coming on. >>Thank you for having us. >>Well, I'll start with you. What's driving? IBMS investment sustainability as a corporate initiative. We know IBM has been active, we've covered this many times, but there's more drivers now as IBM has more of a larger global scope and continues to do that with hybrid cloud, it's much more of a global landscape. What's driving today's investments in sustainability, >>you know, johN what drives IBM in this area has always been a longstanding, mature and deep seated belief in corporate responsibility. That's the bedrock foundation. So, you know, IBM is 100 10 year old company. We've always strived to be socially responsible, But what's not as well known is that for the last 50 years, IBM has truly regarded environmental sustainability is a strategic imperative. Okay, It's strategic because hey, environmental problems require a strategic fix. It's long term imperative because you have to be persistent with environmental problems, you don't necessarily solve them overnight. And it's imperative because business cannot succeed in a world of environmental degradation, that really is the main tenant of sustainable development. You can't have successful economies with environmental degradation, you can't solving environmental problems without successful economies. So, and IBM's case as a long standing company, We were advantaged because 50 years ago our ceo at the time, Tom Watson put in place the company's first policy for environmental, our stewardship and we've been at it ever since. And he did that in 1971 and that was just six months after the U. S. C. P. A. Was created. It was a year before the Stockholm Conference on the Environment. So we've been added for that long. Um in essence really it's about recognizing that good environmental management makes good business sense. It's about corporate responsibility and today it's the E of E. S. G. >>You know, wayne. That's a great call out, by the way, referencing thomas Watson that IBM legend. Um people who don't may not know the history, he was really ahead of its time and that was a lot of the culture they still see around today. So great to see that focus and great, great call out there. But I will ask though, as you guys evolved in today's modern error. How is that evolved in today's focus? Because you know, we see data centers, carbon footprint, global warming, you now have uh A I and analytics can measure everything. So I mean you can you can measure everything now. So as the world gets larger in the surface area of what is contributing to the sustainable equation is larger, what's the current IBM focus? >>So, you know, these days we continually look at all of the ways in which IBM s day to day business practices intersect with any matter of the environment, whether it's materials waste water or energy and climate. And IBM actually has 21 voluntary goals that drive us towards leadership. But today john as you know, uh the headline is really climate change and so we're squarely focused like many others on that. And that's an imperative. But let me say before I just before I briefly tell you our current goals, it's also important to have context as to where we have been because that helps people understand what we're doing today. And so again, climate change is a topic that the men and women of IBM have paid attention to for a long time. Yeah, I was think about it. It was back in 1992 that the U. S. C. P. A. Created something called Energy Star. People look at that and they say, well, what's that all about? Okay, that's all about climate change. Because the most environmentally friendly energy you can get is the energy that you don't really need to consume. IBM was one of eight companies that helped the U. S. C. P. A. Launched that program 1992. Today we're all disclosing C. 02 emissions. IBM began doing that in 1994. Okay. In 2007, 13 years ago, I'd be unpublished. Its position on climate change, calling for urgent action around the world. We supported the Paris agreement 2015. We reiterated that support in 2017 for the us to remain a partner. 2019, we became a founding member of Climate Leadership Council, which calls for a carbon tax and a carbon dividend. So that's all background context. Today, we're working on our third renewable electricity goal, our fifth greenhouse gas emissions reduction goal and we set a new goal to achieve net zero greenhouse gas emissions. Each of those three compels IBM to near term >>action. That's awesome wayne as corporate environmental affairs and chief sustainable, great vision and awesome work. Karim dr Karim use if I wanna. We leave you in here, you're the general manager. You you've got to make this work because of the corporate citizenship that IBM is displaying. Obviously world world class, we know that's been been well reported and known, but now it's a business model. People realize that it's good business to have sustainability, whether it's carbon neutral footprints and or intersecting and contributing for the world and their employees who want mission driven companies ai and Blockchain, that's your wheelhouse. This is like you're in the big wave, wow, this is happening, give us your view because you're commercializing this in real time. >>Yeah, look as you've already said and it's the way well articulated, this is a business imperative, right? Is key to all companies corporate strategies. So the first step when you think about operationalized in this is what we've been doing, is to really step back and kind of break this down into what we call five key needs or focus areas that we've understood that we work with our clients. Remember in this context, Wayne is indeed my clients as well. Right. And so when you think about it, the five needs, as we like to lay them out, we talk about the sustainability strategy first of all, how are you approaching it as you saw from Wayne, identifying your key goals and approaches right against that, you begin to get into various areas and dimensions. Climate risk management is becoming increasingly important, especially in asset heavy industries electrification, energy and emissions management, another key focus area where we can bring technology to bear resilient infrastructure and operations, sustainable supply chain, all of these kind of come together to really connect with our clients business operations and allows us to bring together the technologies and the context of ai Blockchain and the key business operations. We can support to kind of begin to address specific news cases in the context of those needs. >>You know, I've covered it in the past and written about and also talked about the cube about sustainability on the supply chain side with Blockchain, whether it's your tracking, you know, um you know, transport of goods with with Blockchain and making sure that that kind of leads your kind of philosophy works because this waste involved is also disruption to business a security issues. But when you really move into the Ai side, how does a company scale that Corinne? Because now, you know, I have to one operationalize it and then scale it. Okay, so that's transformed, innovate and scale. How do I take take me through the examples of how that works >>well, I think really key to that, and this is really key to our ethos, it's enabling ai for business by integrating ai directly into business operations and decision making. So it's not really how can I put this? We try to make it so that the client isn't fixating on trying to deploy ai, they're just leveraging Ai. So as you say, let's take some practical examples. You talked about sustainable supply chains and you know, the key needs around transparency and provenance. Right? So we have helped clients like a tear with their seafood network or the shrimp sustainability network, where there's a big focus on understanding where are things being sourced and how they're moving through the supply chain. We also have a responsible sourcing business network that's being used for cobalt in batteries as an example from mine to manufacturing and here our technologies are allowing us to essentially track, trace and prove the provenance Blockchain serves as kind of that key shared ledger to pull all this information together. But we're leveraging AI to begin to quickly assess based upon the data inputs, the actual state of inventory, how to connect dots across multiple suppliers and as you onboard them and off board them off the network. So that's how we begin to put A. I in action so that the client begins to fixate on the work and the decisions they need to make. Not the AI itself. Another quick example would be in the context of civil infrastructure. One of our clients son and Belt large, maximum client of ours, he uses maximum to really focus on the maintenance and sustainable maintenance of their bridges. Think about how much money is spent setting up to do bridge inspections right. When you think about how much they have to invest the stopping of the traffic that scaffolding. We have been leveraging AI to do things like visual inspection, actually fly drones, take pictures, assess those images to identify cracks and use that to route and prioritized work. Similar examples are occurring in energy and utilities focused on vegetation management where we're leveraging ai to analyse satellite imagery, weather data and bringing it together so that work can be optimally prior authorized and deployed um for our clients. >>It's interesting. One of the themes coming out of think that I'm observing is this notion of transformation is innovation and innovation is about scale. Right? So it's not just innovation for innovating sake. You can transform from whether it's bridge inspections to managing any other previous pre existing kind of legacy condition and bring that into a modern error and then scale it with data. This is a common theme. It applies to to your examples. Kareem, that's super valuable. Um how do you how do you tie that together with partnering? Because wayne you were talking about the corporate initiative, that's just IBM we learned certainly in cybersecurity and now these other areas like sustainability, it's a team sport, you have to work on a global footprint with other industries and other leaders. How was I being working across the industry to connect and work with other, either initiatives or companies or governments. >>Sure. And there have been john over the years and at present a number of diverse collaborations that we seek out and we participate in. But before I address that, I just want to amplify something Kareem said, because it's so important, as I look back at the environmental movement over the last 50 years, frankly, since the first earth day in 1970, I, you know, with the benefit of hindsight, I observed there have really been three different hair, It's in the very beginning, global societies had to enact laws to control pollution that was occurring. That was the late 60s 1970s, into the early 1980s and around the early 1980s through to the first part of this century, that era of let's get control of this sort of transformed, oh, how can we prevent stuff from happening given the way we've always done business and that area ran for a while. But now, thanks to technology and data and things like Blockchain and ai we all have the opportunity to move into this era of innovation, which differs from control in which differs from traditional prevention. Innovation is about changing the way you get the same thing done. And the reason that's enabled is because of the tools that you just spoke about with korean. So how do we socialize these opportunities? Well to your question, we interact with a variety of diverse teams, government, different business associations, NGos and Academia. Some examples. There's an organization named the Center for Climate and Energy Solutions, which IBM is a founding member of its Business Leadership Council. Its predecessor was the Q Centre on global climate change. We've been involved with that since 1998. That is a cross section of people from all these different constituencies who are looking for solutions to climate. Many Fortune 102000s in there were part of the green grid. The green grid is an organization of companies involved with data centers and it's constantly looking at how do you measure energy efficiency and data centers and what are best practices to reduce consumption of energy at data centers where a member of the renewable energy buyers alliance? Many Fortune 100 200 Zar in that trying to apply scale to procure more renewable electricity to actually come to our facilities I mentioned earlier were part of the Climate Leadership Council calling for a carbon tax were part of the United Nations Environment programs science policy business form that gets us involved with many ministers of environment from countries around the world. We recently joined the new MITt Climate and sustainability consortium. Mitt Premier Research University. Many key leaders are part of that. Looking at how academic research can supercharge this opportunity for innovation and then the last one, I'm just wrap up call for code. You may be familiar with IBM s involvement in call for code. Okay. The current challenge under Call for Code in 2021 calls for solutions targeted the climate change. So that's that's a diverse set of different constituents, different types of people. But we try to get involved with all of them because we learn and hopefully we contribute something along the way as well. >>Awesome Wayne. Thank you very much, Karim, the last 30 seconds we got here. How do companies partner with IBM if they want to connect in with the mission and the citizenship that you guys are doing? How do they bring that to their company real quick. Give us a quick overview. >>Well, you know, it's really quite simple. Many of these clients are already clients of ours were engaging with them in the marketplace today, right, trying to make sure we understand their needs, trying to ensure that we tune what we've got to offer both in terms of product and consulting services with our GPS brethren, you know, to meet their needs, linking that in as well to IBM being in what we like to turn clients zero. We're also applying these same technologies and capabilities to support IBM efforts. And so as they engage in all these associations, what IBM is doing, that also provides a way to really get started. It's really fixate on those five imperatives or needs are laid out, picked kind of a starting point and tie it to something that matters. That changes how you're doing something today. That's really the key. As far as uh we're concerned, >>Karim, we thank you for your time on sustainability. Great initiative. Congratulations on the continued mission. Going back to the early days of IBM and the Watson generation continuing out in the modern era. Congratulations and thanks for sharing. >>Thank you john. >>Okay. It's the cubes coverage. I'm sean for your host. Thanks for watching. Mhm. Mhm. Mhm.

(upbeat music) >> (Narrator) From around the globe, it's theCUBE. With digital coverage of IBM Think 2021. Brought to you by IBM. >> Hello, welcome back to theCUBE's coverage of IBM Think 2021 virtual. Soon we'll be back in person in real life, but this year again it's a virtual conference. I'm John Furrier, your host of the cube for more cube coverage. We've got a great guest here, Debbie Vavangas, Global Garage Lead for IBM Services. Global Garage, great program. Debbie, great to see you. Thanks for coming on theCUBE. >> Thanks for having me. >> So, we've covered the Garage a lot on theCUBE in the past, and a success, everyone loves the Garage. Things are born in the Garage, entrepreneurship, innovation, has been kind of categorically known for, kind of, the Garage startup. >> Absolutely. >> But also, it's become known for, really, agility, which has been a cloud phenomenon, DevOps. Now we're seeing dev SecOps as a big trend this year with hybrid cloud. So, I've got to ask you, how is Garage doing with the pandemic? Obviously, I can almost imagine people at home kind of disrupted from the office, but maybe more creativity, maybe more energy online? What's going on with the Garage? How has your transformation journey been with COVID? >> Well, John, COVID has been the leveler for us all, right? There isn't a person who hasn't had some challenge or some complexity to And that includes our clients. And I'm incredibly proud to be able to say that IBM Garage, because it is so digitally native, when the COVID pandemic has struck around the world every single one of our Garages was able to switch to being virtual without fail, without a single days lost productivity. And that's hugely beneficial to clients who are on an incredibly time-sensitive journey. And so, we've seen as a result of COVID actually there are a huge acceleration in Garages, for two reasons. So, number one, from a virtualization perspective, actually it's much easier when everybodies together in the same space. So everybody's together virtually in the same space, and we've seen, you know, acceleration in our velocity, in our collaboration, because everybody is really learning how to work in that same space. But two, because of the pandemic, because of the pressure on our client's needs to make decisions fast, know not guess, really be focused on their outcomes, not just doing stuff, the Garage really plays to that objective for them. And so we've seen a huge rise, you know, we've gone from in 2019 to just a few hundred garages, to finishing 2020 with over two and a half thousand garages. And it being embedded across services and with the goal of being the primary way our clients experience it. So COVID has been a big accelerator. >> Sorry, Debbie, can you repeat the numbers again? I just want to capture that, I missed that. >> Sure, sure. >> I did a double take on the numbers. (Debbie laughs) >> So then, we finished 2019 with just under 300 garages, and we finished 2020 with just over two and a half thousand. So, we've had a huge growth, and it isn't just the number of garages, it's the range of garages and what we're serving with our clients, and how we're collaborating with our clients, and the topics we're unpacking that has really broadened. >> Yeah, I mean I covered, and we've reported on the Garage on theCUBE and also on www.siliconangle.com in the past things and through your news coverage, but that's amazing growth. I got to believe the tailwind from COVID and just the energy around it has energized you. I want to get your thoughts on that because, you know, what we've reported on in the past has been about design thinking, human-centered design, all of those beautiful things that come with cloud-scale, right? You know, you're moving faster, you're innovating, and so that's been kind of there. But what you're getting at with this growth is, and with COVID has proven, and again, we've been pointing this out, you're seeing the pattern, it's clear. Companies are either retrenching, okay, which is refactoring, redesigning, doing those things to kind of get ready to come out of COVID with a growth strategy, and you're seeing other companies build net new innovations. So, they're building new capabilities, because COVID's shown them, kind of pulled back the curtain if you will on where the action is. So, this means there's two threads going on. You've got, "Okay, I've got to transform my business, and I got to refactor', or 'Hey, we got net new business models'. These are kind of two different things and not mutually exclusive. What's your comment on that? >> And I think that my comment on it is that is the sweet spot that Garage comes into its own, right? You mentioned lots of things in there. You talked about design thinking, and agility, and, you know, these other buzzwords that are used all the time, and Garage of course is synonymous with those. Of course, Garage uses the best design thinking, and AGILE practices, and all of those things that absolutely call to what we do. DevOps, even through down to DesignOps. You know, we have the whole range depending on what the client objective is. But, I think what is really happening now is that innovation being something separate is no longer how to accelerate your outcomes, and your business outcomes. Regardless of whether that is in refactoring and modernizing your existing estate, or diversifying, creating new ecosystems, new platforms, new offerings. Regardless of what that is, you can't do it separate to your core business. I mean, it's a well known fact, John, right? Like 75% of transformation programs fail to deliver an impact to the business performance, right? And in the same period of time there's been huge cuts in innovation funding, and that's because for the same reason, because they don't deliver the impact to the business performance. And that's why Garage is unique, because it is entirely focused on the outcome, right? We're using user research, through design thinking of course, using agile to deliver it at speed, and all of those other things. But, it's focused on value, on benefits realization and driving to your outcome. And we do that by putting that innovation at the heart of your enterprise in order to drive that transformation, rather than it being something separate. >> Debbie, I saw you gave a talk called 'Innovation is Dead'. Obviously, that's a provocative title, that's an attention-getter. Tell me what you mean by that. Because it seems to be a setup. >> I mean, if the innovation is dead, >> Of course. was it with a question mark? Were you, kind of, trying to highlight that innovation is transformation? >> So, the full title was 'Innovation is dead and transformation is pointless'. And, of course, it's meant to be an eye-catching title so people show up and listen to my pitch rather than somebody else's. But, the reality is I mean it most sincerely, it's back to that stat. 75% of these transformation programs fail to deliver the impact, and I speculate that that is for a few reasons. Because, the idea itself wasn't a good one, or wasn't at the right time. Because, you were unable to understand what the measure of good looked like, and therefore just being able to create that path. And, in order to transform a company, you must transform the individuals within a company. And so that way of working becomes incredibly holistic. And it's those three things, that I think amongst the whole myriad of others, that are the primary reasons why those programs fail. And what Garage does, is it breaks that. By putting innovation at the heart of your enterprise, and by using data-driven value orchestration, that means that we don't guess where the value to be gained is, we know. It's no longer chucking ideas at the wall to see what sticks, it's meaningful research. This is my favorite quote from my dear friend, Courtney Noll, who says, "It's not about searching for the innovation needle in the proverbial haystack, it's using your research in order to de-risk your investment, and drive your innovation to enable your outcomes." And so, if you do innovation without a view to how it's going to yield your business outcomes, I agree, I fundamentally agree that it's pointless. >> Yeah, exactly. And, you know, of course we're on the writing side, we love titles like, 'Innovation is dead, long live innovation'. So, it's classic, you know, to get your attention. >> Exactly, exactly. And of course, what I really mean is that innovation is a separate entity. >> Totally. >> There's no longer relevance for a company to make sure they achieve their business outcomes. >> Well, this is what I wanted to just double-click on that with you on is that you look at transformation. You guys are essentially saying transformation meets innovation with the Garage philosophy, if I get that right. >> Yep >> And it's interesting, and we've experienced this here with theCUBE, we're theCUBE virtual, we're not at IBM Think, there is no physical game day like some of us normally do. >> Well, as you can see, I'm at my house. (Debbie laughs) And so, I was talking to a CEO and I said, "Hey, you guys are doing really, really good. We had to pivot with the cube", and he goes, "You guys did a good pivot yourself". He goes, "No, John, we did not pivot. We actually put our business on hold because of the pandemic. We actually created a line extension, so, technically, we're going to bring that business back when COVID has gone and come back to real life, so it's technically not a pivot, we're not pivoting our business, we've created new functionality." Through the innovations that they were doing. So, this is kind of like, this is the real deal here. Share your thoughts on that. >> To me, it's about people get so focused on the output that they lose track of the outcome, right? And so, be really clear on what you're doing, and why. And the outcomes can be really broad, so instead of saying, "We're all going to implement a new ERP, or build a new mobile app". That's not an outcome, right? What we should be saying is, "What we're trying to achieve is a 10 percent growth in net promoter score in China, right? In this group." Or whatever it is we were trying to achieve, right? Or, "We want to make a 25% reduction in our operating cost base by simplifying our estate". Whatever those outcomes are, that's the starting point, and then driving that to use as the vehicle for what is the right innovation, what is going to deliver that value, and fast, right? Garage delivers three to five times faster than other models and at a reduced delivery cost, and so it's all about that speed. Speed of decision, speed of insight, speed of culture and training, speed of new skills, and speed to outcomes. >> Well, Debbie, you did a great job, love what you're doing, and Garage has got a great model. Congratulations on the growth, love this intersection, or transformation meets innovation because innovation is transformation, and vice versa, this interplay going on there. >> Exactly. >> I think COVID has proven that. Let me dig into a little bit more about the garage, what's going on. How many practitioners do you guys have there now at IBM? You've got growth, are you adding more people in? Obviously, Virtual First, COVID, is there still centers of design? Take us through what's going on at Garage. >> Certainly, so like, I think I mentioned it right up front. Our goal is to make IBM Garage the primary way our clients experience us. We've proven in that it delivers higher value to our clients and they get a really rich and broad set of outcomes. And so, in order for us to deliver on that promise we have to be enabled across IBM to deliver to it, right? So, over the last 18 months or so we've had a whole range of training programs in Enable, we've had a whole badging and certification program, we have all the skills, and the pathways, and the career pathways to find. But Garage is for everybody, right? And so, it isn't about creating a select group that can do this across IBM. This is about making all of services capable. So, in 2020 we trained over 28,000 people, in all the different skills that are needed, from selling, to execution, to QA, to user research, whatever it is. And this year we're launching our Garage Skills Academy, which will take that across all of services and make it easily available. So, you know, we've got hundreds of thousands. >> And talk about the footprint on the global side, because, again, not to bring up global, but global is what is in your title. >> Yep. >> Companies need to be global, because now with virtual workforces you're seeing much more tapped creativity and ability to execute from global teams. How does that impact you? >> Well, so it's global in two perspectives, right? So, number one, we have Garages all around the world, right? It isn't just the market of, you know, our most developed nations in Americas and Europe, it is everywhere, we see it in all emerging markets. From Latin America, through to all parts of eastern Europe, which are really beginning to come into their own. So, we see all these different Garages at different scales and opportunities. So, definitely global from that image. But, what virtualization has also enabled is truly global teams. Because, it's really easy to go, "Oh, I need one of those. Okay, I need a supply chain expert, and I need an AI expert, and I need somebody who's got industry experience in whatever it is." And you can quickly gather them around the virtual table, you know, faster than you can in a physical table. But, we still leverage the global communities with those physical. >> It's an expert network. You have an expert network there at IBM. >> We have a huge network, yeah. And both within IBM, and of course a growing network of ecosystem partners that we continue to work with. >> Well, Debbie, I'm really excited. Congratulations on the growth. I'm looking forward to partnering with you on your ecosystem as that develops. I can almost imagine you must be getting a lot of outside IBM practitioners and experts coming in to collaborate in a social construct. >> Absolutely. >> It's a great program, thanks for sharing. >> My pleasure, it's been great to be here, thank you. >> Okay, IBM's Global Garage Lead, Debbie Vavangas, who's here on theCUBE with IBM Services. A phenomenon, it's a social construct that's helping companies with digital transformation. Intersecting, with innovation. I'm John Furrier, your host. Thanks for watching. (upbeat music)

>> Narrator: From around the globe, it's theCUBE with digital coverage of IBM Think 2021. Brought to you by IBM. >> Hello, everyone. Welcome back to theCUBE's coverage of IBM Think virtual 2021. I'm John Furrier, your host of theCUBE. We're here with Kirsten Craft, who's the global head of business development and marketing at Prolifics. Kirsten, great to see you. Thanks for coming on theCUBE. >> Thanks so much, John. It's great to be here. >> I love the fact that we're getting the content out there. We're still remote. Soon in real life's coming back, but what a time it's been in the past year and a half or so. A lot of change, a lot of action. You guys are in the middle of it here at IBM Think. Let's get into it. But first, take a minute to explain what you guys do at Prolifics, and your business model. >> Sure. So thanks, John. So Prolifics... We've been in business, actually, for over 40 years, which is pretty amazing when you think about technology and everything that's happened in 40 years. We are a global service provider. We've got over 1,000 people worldwide. And we are 100% focused on software, and almost 100% focused on IBM, right? Of course, nobody's focused on a single technology stack these days, so we work with our customers across many different products, but we've been with IBM for a very long time. When we look at our business model, when we talk with our clients, we find that organizations today, they've got really complex challenges, especially now, right, in what all is happening right now. They've got a lot of really interesting opportunities, as well as problems that they have to solve in front of them. And those types of situations, they can't just be addressed by just buying a product. And Prolifics' approach is we work with our clients to get really above the technology conversation, and to really understand what are they trying to accomplish, right? At the end of the day, why is this an important initiative for you? And we help them develop roadmaps, and then we help them get there. So of course we're selling technology along the way, and in that implementation path. So I would say from a business model perspective, we're very services focused. We're very consultative. And of course our resulting technologies are running on IBM. >> About eight years ago, Dave Vellante and I started a little small little section of SiliconANGLE called ServicesANGLE, and our premise was is that services were going to be a big driver. Now, what we missed was cloud had to set up first, and it did, and now we're seeing a boom in services, but cloud services, you're seeing new kinds of services with the edge and other things. So what's your take on this? Because now IBM has this global view. The pandemic has proven that the scale of virtual and digital is so much more compelling. No one's going back. The economics are too good. The value is being realized as clear visibility and to unit economics of projects. Projects, some are obvious double down on. Some not to, maybe. So a lot of these things are going on. What's your take on all this? >> So it is interesting, cause that is both an opportunity as well as a challenge, right, for clients. At Prolifics, we've been-- We were actually pretty blessed because we're very virtual. We're a virtual company anyway, right? So we didn't have one facility where all of our developers are housed. So it was really kind of business as usual for us in terms of how we work with our customers, with the exception of the fact we couldn't go into their offices, right, anymore, which is a bit of a challenge. But as they look at how do they really harness the cloud, how do they harness those technologies? IBM, as well as business partners like Prolifics, we're in a great position to help them with that, because a lot of where IBM is going with cloud packs and containerization, that's where our customers want to be. Now, some of them are a little bit more aggressive than others in terms of how quickly they want to adopt that technology, which is where road mapping comes into place, and helping them really set up, not just for short-term, how do they solve what's in front of their face, but let's look a year or two years down the line. How do you make sure that you're really building an agile type of environment that's going to work across data, which is really the center of all things nowadays, as well as working across other systems. >> I've been covering IBM for very long time. Actually was once an employee as a co-op student back in college. Remember those glory days. (chuckles) And you mentioned you guys have been with IBM for a very, very long time. You got to.... They've always had a business focus. They've always had great technology. They got great technologists and experts there, but I think now more than ever you're seeing the theme at the show this year as hybrid cloud edge data AI as a kind of a underlying system software for business. So you're starting to see a new era of software driving business at a level that's been completely transformed. As an IBM platform software provider, you've been there for all the IBM over the years. What's it like? What's your... What's your take on this? What opportunities do you see with the hybrid cloud? You got Red Hat now under the covers. You've got, you mentioned, containers. Is it a pinch-me moment where people were like, "Wow. There's so much here to integrate," or cloud is going to provide a new clean sheet of paper to do things. What's your... What's the vibe? What's the sentiment? >> It's interesting. We're actually seeing more customers starting to look at themselves as technology companies. So even companies that don't think that historically they're not in a technology industry, they're now identifying internally. They're talking to their staff about... We don't sell widgets. We're a technology company that happens to sell widgets. So it's really an interesting dynamic, and I would also mention that one of the themes we're seeing across a lot of customers, almost all of our customers, is this insane focus on data. I say insane in like a good way, right? So how do we use our data to help inform our processes? How do we make sure that we're sharing data effectively and efficiently with all of our trading partners? We're seeing a lot of modernization when it comes to integration, but again, integration is all about exchanging data. We're seeing customers start to dabble more with AI in terms of how can we get smarter by using the data that we have available to us? Again, I think that's going to be the next wave, because we're seeing a lot of our customers start to dabble in that but not fully embrace it just yet. But they really want to get that underlying platform around data and integration ready to go so that they can do some amazing things in the future. >> How is the hybrid cloud and data impacting Prolifics business? Where does this take you guys for the next chapter? >> Well, it's actually... (chuckles) It's actually perfect for us, because that's almost 100% of what we do. So we... As I mentioned earlier, we are 100% focused on software, right? Software and software-based solutions. We're not a hardware provider. We don't have a data center, but we help customers design and implement software-based systems. And our expertise is squarely in data, business intelligence, analytics, AI, and also integration and business process automation. Those are really our core, especially as it comes to IBM technology. Now, we also have a testing practice, which is technology agnostic, but it's really critical as you... Especially as you look at rapid development cycles, cause that's another theme we're seeing with customers, right? Nobody's got the patience to go through a long waterfall model, right? You've got to get into production. It's the Apple model, right? Get it into production, get feedback, make modifications, and go. But if it gets out there and it's completely broken. Guess what? You just stepped all over yourself. So we integrate testing into everything that we do as well. But the data and the hybrid cloud message, and all of the innovation that IBM is doing, it fits perfectly in with what we're seeing with our customers and where we've invested for so long as far as skills and expertise. >> That testing example really kind of speaks to what's state-of-the-art right now, because people can get into production with the cloud and then they realize that they're adding services pretty quickly and things break. They call it "day-two operations," is a term that there've been kicking around. I call it essentially DevSecOps, but there's a lot of kind of new things that you just got to kind of watch, which recently, IT-like functions that are now cloud ops, cloud operations, so super new. How are you guys seeing that with the customer base that you guys have? As they start to see benefits, does it impact their staffing, their support levels? What's the impact to the customer when they start to realize some of these benefits, but then understanding that with scale comes a whole nother set of operating challenges. >> Yeah. It is interesting. With that scale, it does... It does present other challenges, as you mentioned, from an operations perspective. And we have seen customers that go out there, go live. Well, you remember the commercial? I think there was a commercial many, many years ago back when the internet was kind of a new thing where it was a startup company, and they put an e-commerce site out there, right? And they were like, "Oh, yay! We got our first order." And they're like, "Yay! We have 10. Oh, crap! We have 10,000." Right? So you see customers like this, they get excited to put something out there, but they haven't fully performance tested it, right? So that's... That's also where we try to help our customers take that step back and say, "Okay. How are you going to actually plan, not just for day one, to get it out there, but longer term?" And that's where we also put our performance testing as a part of all of our solutions, because you know that yes, it's a good problem to have, but you really don't want to have that problem in the first place, so how do you make sure that you plan and prepare for that, and incrementally deploy, and make sure that your underlying technology is prepared to support that kind of volume. >> So Kirsten, I want to ask you kind of the important question this day and age in the modern era with cloud and now this new cloud scale, and it's always kind of been true in the past. But now more than ever you're starting to see the role of the ecosystem of partners as super important, because now integrations are happening. You're bringing point solutions into a platform where tools are integrating with other tools. So as a partner of IBM, how is the ecosystem role that you guys are playing, and how important is that, and what are the new things that are needed to be successful in the ecosystem with the premise that rising tide floats all boats, which is kind of... Well, we're seeing that happen now. Certainly, coming out of the pandemic it's going to be a whole new game, but there are ecosystems that are now evolving around IBM, around these big mega trends like cloud edge and data. What's your take? >> Mm-hm. Mm-hm. So first of all, you mentioned IBM's focus on ecosystem, right? And so Arvind has been very vocal about the importance of the ecosystem and how he really wants to change IBM's model out there to embrace partners. And I have to say, I think that's... That's one of the smartest things I think I've heard IBM say in years. And I know that that sounds self-serving because we are a partner, but the reality is there's several different layers where that's really important. One is the value of the partner. And you mentioned that there's a need to integrate across different systems, right? So IBM is not... Gone are the days when customers only have IBM technology. It's just not a thing. And so partners have the ability to work across different vendors, very hybrid, very unique types of environments, and make sure that the IBM interest, the IBM footprint, is well-deployed, well-represented, and set up for future success so that customer's going to want to buy more in the future, but in the context of what that customer's overall landscape is. So that's a big reason why IBM wants business partners involved with customers, and we're a little bit more... Or at least we can work with customers from a consultative perspective, right, and make sure that they are comfortable with the decisions that they're making. That isn't just the manufacturer telling them to buy our stuff. From a partners perspective, one of the biggest things that we struggle with in the marketplace is being known, right? I mean, we're... We're a decent-sized partner with over 1,000 employees, but at the end of the day, how many people know Prolifics as a brand name versus how many people know IBM? So opening those doors, partnering with the IBM sellers that have kind of an easier way in to introduce a partner and give us the credibility that, "Hey. We know Prolifics. We've seen them be successful and help very large companies that are just like you be successful with our technology. Let them help you end to end," is a... It's just a really good synergy as far as how you can actually, how IBM can scale with their customers, and how customers can realize that benefit of a broader ecosystem as well, and skillsets. >> Yeah. Great point. Arvind is very savvy on cloud. I know he loves hybrid cloud. He loves the cloud model. He's changing it with Red Hat. I think you're so smart and accurate on this whole changeover around network effects, organic ecosystems playing a power dynamic in how people buy and nurture themselves. So I think there's going to be a nice change over there. I think you're onto something pretty big with that, because look it, it's multi-vendor at many levels now. IBM has to integrate here, and you're a partner. You're well-known now. You're on theCUBE. So we're going to get the word out here. But it's- (chuckles) You're on a team. It's a group. It's not just... It's about the customer. This is now a different mindset. This is what customers want, because they're out in the organic field too. They're not just getting the emails sent to them. They're out and engaging. This is a new model. >> And one of the things that's interesting that we're seeing from our customers as well is they're no longer looking to buy a product and then have somebody come in, install, and implement. They're actually looking for guidance, right? They want ideas. "Here's what I'm trying to do with my business. How can you help me?" They're looking for an answer to that, and that requires a very different skillset, right? It's not just somebody who knows how to come in and spin up CDs and do some configurations. It's somebody who's worked in their industry before, has worked with similar types of customers, has a little bit of that road rash, can provide some of that guidance. And in order to really do that, you can't find that just in one organization. So I would tell you, actually, I mean Prolifics is a... We're a pretty good-sized company with a wide skillset, but even we partner. We also partner with other partners to help complement our skills when there's a particular expertise that's needed. So it really is a very interesting ecosystem development, and a different way of thinking, that it's not just about you and being able to do everything. It's about you being able to bring the right solution and the right ideas to a customer, and to help them be successful for the long-term. >> Awesome insight, Kirsten Craft, global head of business development and marketing at Prolifics. Great to have you on, and power of networks, power of partnerships, power of the ecosystem. The new world is here. Thanks for coming on theCUBE. >> Thank you. Great to be here. >> Okay. This is IBM Think 2021 coverage. I'm John Furrier, host of theCUBE. Thanks for watching. (smooth music)

>> Narrator: From around the globe It's theCUBE with digital coverage of IBM Think 2021. Brought to you by IBM. >> Welcome back everyone to theCUBE's coverage of IBM Think 2021 virtual, I'm John Furrier, your host. I've got a great guest here Robin Hernandez, vice president Hybrid Cloud Management and Watson AIOps. Robin, great to see you. Thanks for coming on theCUBE. >> Thanks so much for having me, John. >> You know, Hybrid Cloud, the CEO of IBM Arvind loves Cloud. We know that we've talked to him all the time about it. And Cloud is now part of the entire DNA of the company. Hybrid Cloud is validated multi clouds around the corner. This is the underlying pinnings of the new operating system of business. And with that, that's massive change that we've seen IT move to large scale. You're seeing transformation, driving innovation, driving scale, and AI is the center of it. So AIOps is a huge topic. I want to jump right into it. Can you just tell me about your day to day IT operations teams what you guys are doing? How are you guys organized? How you guys bring in value to the customers? What are your teams responsible for? >> Yeah, so for a few years we've been working with our IT customers, our enterprise customers in this transformation that they're going through. As they move more workloads to cloud, and they still have some of their workloads on premise, or they have a strategy of using multiple public clouds, each of those cloud vendors have different tools. And so they're forced with, how do I keep up with the changing rate and pace of this technology? How do I build skills on a particular public cloud vendor when, you know, maybe six months from now we'll have another cloud vendor that will be introduced or another technology that will be introduced. And it's almost impossible for an it team to keep up with the rate and pace of the change. So we've really been working with IT operations in transforming their processes and their skills within their teams and that looking at what tools do they use to move to this cloud operations model. And then as part of that, how do they leverage the benefits of AI and make that practical and purposeful in this new mode of cloud operations >> And the trend that's been booming is this idea of a site reliability engineer. It's really an IT operations role. It's become kind of a new mix between engineering and IT and development. I mean, classic DevOps, we've seen, you know dev and ops, right? You got to operate the developers and the software modern apps are coming in that's infrastructure as course has been around for a while. But now as the materialization of things like Kubernetes and microservices, people are programming the infrastructure. And so the scale is there, and that's been around for a while. Now it's going to go to a whole enterprise level with containers and other things. How is the site reliability engineering persona if you will, or ITOps changed specifically because that's where the action is. And that's where you hear things like observability and I need more data, break down the silos. What's this all about? What's your view? >> Yeah, so site reliability engineering or SRE practices as we call it has really not changed the processes per se that IT has to do, but it's more accelerated at an enormous rate and pace. Those processes and the tools as you mentioned, the cloud native tools like Kubernetes have accelerated how those processes are executed. Everything from releasing new code and how they work with development to actually code the infrastructure and the policies in that development process to maintaining and observing over the life cycle of an application, the performance, the availability, the response time, and the customer experience. All of those processes that used to happen in silos with separate teams and sort of a waterfall approach, with SRE practices now, they're happening instantaneously. They're being scaled out. They're being... Failback is happening much more quickly so that applications didn't do not have outages. And the rate and pace of this has just accelerated so quickly. This is the transformation of what we call cloud operations. And we believe that as IT teams work more closely with developers and they moved towards this SRE model, that they cannot just do this with their personnel and changing skills and changing tools. They have to do this with modernized tools like AI. And this is where we are recommending applying AI to those processes so that you can then get automation out of the back end that you would not think about in a traditional IT operations, or even in an SRE practice. You have to leverage capabilities and new technologies like AI to even accelerate further. >> Let's unpack the AI operations piece because I think that's where I think I'm in hearing. I'd love you to clarify this because it becomes I think the key important point but also kind of confusing to some folks because IT operations people see that changing. You just pointed out why, honestly, the tools and the culture is changing, but AI becomes a scale point because of the automation piece you mentioned. How does that thread together? How does AIOps specifically change the customer's approach in terms of how they work with their teams and how that automation is being applied? 'Cause I think that's the key thread, right? 'Cause everyone kind of gets the cultural shifts and the tools, if they're not living it and putting it in place, but now they want to scale it. That's where automation comes in. Is that right? Is that the right way to think about it? What's your view on this? This is important. >> It's absolutely right. And I always like to talk about AI in other industries before we apply it to IT to help IT understand. Because a lot of times, IT looks at AI as a buzzword and they say, "Oh, you know, yes, sure. "This is going to help me." But if you think about... We've been doing AI for a long time at many different companies not just at IBM, but if you think about the other industries where we've applied it, healthcare in particular is so tangible for most people, right? It didn't replace a doctor but it helps a doctor see the things that would take them weeks and months of studying and analyzing different patients to say, "Hey, John, I think this may be a symptom "that we overlooked or didn't think about "or a diagnosis that we didn't think about," without manually looking at all this research. AI can accelerate that so rapidly for a doctor, the same notion for IT. If we apply AI properly to IT, we can accelerate things like remediating incidents or finding a performance problem that may take your eye months or weeks or even hours to find, AI applied properly find those issues and diagnose just like they could in healthcare it diagnoses issues correctly much more rapidly. >> Now again, I want to get your thoughts on something while you're here 'cause you've been in the business for many, many decades 20 years experience, you know, cloud cold, you know the new modern area you're managing it now. Clients are having a scenario where they, "Okay, I'm changing over the culture." I'm "Okay, I got some cloud, I got some public "and I got some hybrid and man, "we did some agile things. "We're provisioned, it's all done. "It's out there." And all of a sudden someone adds something new and it crashes (chuckles) And now I've got to get in, "Where's the risks? where's the security holes?" They're seeing this kind of day two operations as some people call, another buzz word but it's becoming more of, "Okay, we got it up and running "but we still now going to still push some code "and things are starting to break. "and that's net new thing." So it's kind of like they're out of their comfort zone. This is where I kind of see the AIOps evolving quickly because there's kind of a DevSecOps piece. There's also data involved, observability. How do you talk to that scenario? Where, okay, you sold me on cloud, I've been doing it. I did some projects. We're not been running. We got a production system and we added something new. Something maybe trivial and it breaks stuff? >> Yes. Yeah, so with the new cloud operations and SRE, the IT teams are much more responsible for business outcomes. And not just as you say, the application being deployed and the application being available, but the life cycle of that application and the results that it's bringing to the end users and the business. And what this means is that it needs to partner much more closely with development. And it is hard for them to keep up with the tools that are being used and the new code and the architectures of microservices that developers are using. So we like to apply AI on what we call the change risk management process. And so everyone's familiar with change management that means a new piece of code is being released. You have to maintain where that code is being released to was part of the application architecture and make sure that it's scaled out and rolled out properly within your enterprise policies. When we apply AI, we then apply what we call a risk factor to that change because we know so often, application outages occur not something new within the environment. So by applying AI, we can then give you a risk rating that says, "There's an 80% probability "that this change that you're about to roll out, "a code change is going to cause a problem "in this application." So it allows you to then go back and work with the development team and say, "Hey, how do we reduce this risk?" Or decide to take that calculated risk and put into the visibility of where those risks may occur. So this is a great example, change risk management of how applying AI can make you more intelligent in your decisions much more tied to the business and tied to the application release team. >> That's awesome. Well, I got you here on this point of change management. The term "Shift Left" has come up a lot in the industry. I'd love to get your quick definition of what that is in your mind. What does Shift Left mean for Ops teams with AIOps? >> Yeah, so in the early days of IT there was a hard line definitely between your development and IT team. It was kind of we always said throwing it over the fence, right? The developers would throw the code over the fence and say, good luck IT, you know, figure out how to deploy it where it needs to be deployed and cross your fingers that nothing bad happens. Well, Shift Left is really about a breaking down that fence. And if you think of your developers on your left-hand side you'd being the IT team, it's really shifting more towards that development team and getting involved in that code release process, getting involved in their CI/CD pipeline to make sure that all of your enterprise policies and what that code needs to run effectively in your enterprise application and architecture, those pieces are coded ahead of time with the developer. So it's really about partnering between it and development, shifting left to have a more collaboration versus throwing things over the fence and playing the blame game, which is what happens a lot in the early days IT. >> Yeah, and you get a smarter team out of it, great point. That's great insight. Thanks for sharing that. I think it's super relevant. That's the hot trend right now making dealers more productive, building security from the beginning. While they're doing it code it right in, make it a security proof if you will. I got to ask you one of the organizational questions as IBM leader. What are some of the roadblocks that you see in organizations that when they embrace AIOps, are trying to embrace AI ops are trying to scale it and how they can overcome those blockers. What are some of the things you're seeing that you could share with other folks that are maybe watching and trying to solve this problem? >> Yeah, so you know, AI in any industry or discipline is only as good as the data you feed it. AI is about learning from past trends and creating a normal baseline for what is normal in your environment. What is most optimal in your environment this being your enterprise application running in steady state. And so if you think back to the healthcare example, if we only have five or six pieces of patient data that we feed the AI, then the AI recommendation to the doctor is going to be pretty limited. We need a broad set of use cases across a wide demographic of people in the healthcare example, it's the same with IT, applying AI to IT. You need a broad set of data. So one of the roadblocks that we hear from many customers is, well I using an analytics tool already and I'm not really getting a lot of good recommendations or automation out of that analytics tool. And we often find it's because they're pulling data from one source, likely they're pulling data from performance metrics, performance of what's happening with the infrastructure, CPU utilization or memory utilization, storage utilization. And those are all good metrics, but without the context of everything else in your environment, without pulling in data from what's happening in your logs, pulling in data from unstructured data, from things like collaboration tools, what are your team saying? What are the customers saying about the experience with your application? You have to pull in many different data sets across IT and the business in order to make that AI recommendation the most useful. And so we recommend a more holistic true AI platform versus a very segregated data approach to applying and eating the analytics or AI engine. >> That's awesome, it's like a masterclass right there. Robin, great stuff. Great insight. We'll quickly wrap. I would love to you to take a quick minute to explain and share what are some of the use cases to get started and really get into AIOps system successes for people that want to explore more, dig in, and get into this fast, what are some use case, what's some low hanging fruit? What would you share? >> Yeah, we know that IT teams like to see results and they hate black boxes. They like to see into everything that's happening and understand deeply. And so this is one of our major focus areas as we do. We say, we're making AI purposeful for IT teams but some of the low hanging fruits, we have visions. And lots of our enterprise customers have visions of applying AI to everything from a customer experience of the application, costs management of the application and infrastructure in many different aspects. But some of the low hanging fruit is really expanding the availability and the service level agreements of your applications. So many people will say, you know I have a 93% uptime availability or an agreement with my business that this application will be up 93% of the time. Applying AI, we can increase those numbers to 99.9% of the time because it learns from past problems and it creates that baseline of what's normal in your environment. And then we'll tell you before an application outage occurs. So avoiding application outages, and then improving performance, recommendations and scalability. What's the number of users coming in versus your normal scale rate and automating that scalability. So, performance improvements and scalability is another low-hanging fruit area where many IT teams are starting. >> Yeah, I mean, why wouldn't you want to have the AIOps? They're totally cool, very relevant. You know, you're seeing hybrid cloud, standardized all across business. You've got to have that data and you got to have that incident management work there. Robin, great insight. Thank you for sharing. Robin Hernandez, vice president of Hybrid Cloud Management in Watson AIOps. Thanks for coming on theCUBE. >> Thank you so much for having me John. >> Okay, this theCUBE's coverage of IBM Think 2021. I'm John Furrier your host. Thanks for watching. (bright upbeat music)

>> Announcer: From around the globe, it's theCUBE with digital coverage of IBM Think 2021 brought to you by IBM. >> Hey, welcome to the Cube's coverage of IBM Think 2021. I'm Lisa Martin. Joining me next is Dave Marmer, the vice president offering management for the cognos analytics, planning analytics and regtech portfolios at IBM. Dave, welcome to the program. >> Thank you, Lisa. Thanks for having us today. >> So lots of change in the last year, that's an Epic understatement, right? But I'm curious some of the things that you've seen from a customer's perspective, how are they utilizing planning and reporting technology and analytics to adapt to such a disruptive market? >> Quick question, the pandemic was truly a test for these organizations in terms of their resiliency and agility. But fortunately our clients were able to leverage our planning and reporting technology to do several things. They were able to re-plan their financials to integrate and reset operational areas and planning. They were able to create multiple scenarios as disruptions continue to occur and they were able to maintain confidence in insights for collaborative decision-making at truly an enterprise scale. They were easily able to increase the frequency of their planning process, moving from quarterly to monthly to even daily for their operational areas such as supply and sales. And this was really far reaching for customers like ranging from people like Perona who focuses on private employment to Vasan who is one of the largest bakeries in Europe and ancestry.com, which are the world's largest online family history resource. They're all were able to successfully navigate the radical changes in demand and in workflow and in cashflow. >> That's impressive considering things were in such a mess and still are in somewhat state of flux which is obviously different globally. You talked about the collaboration. That's one of the things that we saw so much change going on in the last year, but this dependence on technology to facilitate collaboration. Talk to me a little bit about how you've helped. Maybe those same customers that you mentioned be able to collaborate collectively across the organizations. >> So the concept that we follow which is sort of this extending planning and analysis model is this concept of decisions, financial decisions, or finance decisions being moved outside of the operational areas, the office of finance, into the areas of supply chain, into sales, into workforce management. These all had to come together far more agilely and far more connected than they ever were before. Decisions that one organization was going to make was going to impact others. And they need to bring in additional exogenous data to kind of augment the decisions they were already doing. So it came very collaborative and high participation for the people closest to the decisions. >> Excellent. So when you look at some of the things that have in the last year, what are some of your observations, that kind of things that surprised you in terms of how companies have evolved their planning and forecasting strategy in such a dynamic market? >> Well, the biggest surprise, and I guess it shouldn't be a surprise, but historical trends that they had been counting on for their planning activity, taking last year's activities and actuals and using those to plan out what would happen. Those were sort of out the window and data sources and drivers, new drivers to their business had to be considered. They hadn't had to deal with this in the past. Like our clients were kind of pleasantly surprised that they're moved to extended planning and analysis. When planning is adopted outside of the office of finance stood up to the global disruption. You know, for example, ancestry had already adopted a enterprise planning platform as a reaction to phenomenal growth they experienced years back as they were first launching their DNA product. This put them in really good shape for what happened more really recently. This allowed them to run multiple scenarios to the impact of their supply chain all the way through the labs and back to the clients. And so when the pandemic hit, the facilities were impacted but they will have to make those adjustments at quarterly and keep up a high level of customer service. >> So these seems like ancestry was already in a really good position to be able to navigate some of the massive disruption that happened so quickly. How have you helped other customers that maybe weren't as far along to do that as well and to be able to forecast and plan in a dynamic time? >> So a customer like the sun, I mentioned, they were like, one of Europe's largest bakeries, right? They live in a world of just hours, right? You're creating product that has a shelf life, a realistic shelf life. And they have much demand changes for their facilities, but also to the stores and their frozen food products that they provide in addition to how they provide them the daily fresh stuff that they do. They're very known for their rye bread, their sourdough those type of things. But they had to make a lot of changes based on what they were seeing and take into consideration, even margin. So they've been evolving and taking more advantage of AI in augmenting their human intelligence in this way. They've been able to use very sophisticated algorithms with planning analytics to allow them to plan for things like energy consumption where they calculate the expected outside temperatures and the need for the facilities, because where they are based in the Nordics, they face freezing temperatures where, you know, the facility subs health have, because there's a lot of fluctuation in seasonality to that. And so they need to adjust for that. They also really use this to take a look at the product life cycles that they had been using to get a better longterm estimate of what people would be buying instead of using human intuition, because as they said, you can get sort of into this methodical radar listening model of looking at what had occurred in the past. And they were able to start to see things months earlier that they would have normally not been able to see if they'd not augmented their human intelligence with artificial intelligence. And I think the third thing they started to use was customer purchasing behavior where they actually were just starting to see actual patterns of things that were changing. And the expected propensity was changing for repeat purchases and cross sell purchases. And they're able to make adjustments on their offerings as a result. >> If we talk about AI to augment human intelligence to empower decision making, that's a great example of that that you talked about. What's the adoption been like that around different industries and different countries in the last year? >> So we see this universally happening that there's an adoption occurring. Certain industries are definitely moving faster. It's happening in the sales and operations planning area more so than the traditional places like the financial and planning and analysis areas. So once you get into the areas like supply chain and demand planning, you know, we generally see retail and distribution, you know, companies, a high adoption of this because of the sensitivity of making sure the right product is there at the right time. We see this near a customer service. And we definitely see this as I mentioned in workforce analytics. This pandemic brought large disruption to people who had to exit the normal facilities and work in different alternative locations. And then this idea of how do we bring them back in a very managed way is a universal problem that everyone is facing and they're all starting to adopt that. So we're seeing adoptions on many of these things across all the different industries, but I'd say the ones I mentioned were certainly highly sensitive to the immediate problems that we all personally experienced. >> Right. In your opinion based on just what you've observed, what do you think the true value of integrated planning field Bay by AI? What's the true business value there? >> It's a great question. I think in business terms, the predictive capabilities like the algorithmic forecasting is really helping companies more accurately forecast their demand. And while prescriptive capabilities like decision optimization, help them determine the best way to meet that demand, typically decision optimization excels at developing scenarios and considering constraints such as time prices, cost and capacities. And those are pulled in to help augment the decisions. Whereas predictive capability really helps the forecast demand as an example, you know, man changes by season by day by hour, the prescriptive capabilities, like this is an optimization, help determine the best plan for meeting the demand. But if you think about the energy example I gave before, you have to consider things like, is it hydro? Is it coal? Is it nuclear? One of those types of things that are involved because each method has a different cost and a different capacity. So they kind of work together in that way. >> When you're having customer conversations. I'm curious what the perspective is of customers understanding the obvious business value of integrating AI with integrated planning. Is that something that they get right away? What kinds of questions do they have for you? >> Again, I think they understand the concept or scenario planning and the fact of building different scenario modeling. I think what they're getting accustomed to is the superpower that we get to augment these humans with an intent to work against their intuition. We've seen this time and time again where project planning for, you know, one of our customers who manages on behalf of the government certain projects that they would look at it and say, if it wasn't for AI, we wouldn't have detected these issues and some of the project scope, because we look at managing them in a certain way based on historical patterns. So you almost have to unlearn their historical patterns that's had to accept what the data is telling you and you're really matching properlistic and deterministic information together to get a more accurate and an informed decision to help you move and progress further. >> So for businesses, I'm curious to get your advice here. For companies that are in this state of flux as we all are and varying degrees of that across the globe, what advice do you have for those companies that are looking into utilizing planning and reporting technology to really fine tune their business performance but they don't really know where to start? >> Yeah, so from a very high level, the advice I would say is first you've got to examine your current planning process and really identify what's working well and what business questions need to be answered. Then you have to understand that planning is primarily driver-based. And because it's driver-based, you really have to understand and take a look at your current financial reports to see what's really making up the bulk of your business, what's really driving revenue, what's really driving expenses and really focusing on the drivers that have material impact. Probably you've that 80, 20 rule. What is 80% of our costs and revenues coming from? And then you need to understand the level of granularity that you need in your data to really develop the appropriate values that you want to plan again and set those targets. And you should refer to the existing spreadsheets. They have lots of value just to understand the sources of data, the calculations that get used, what's effective and not effective across the different functions and how they link together. And then you really need to determine your planning horizon. You need to understand who's going to be contributing to the plan who hasn't been doing this before, because you want people closest to the processes and the decisions to do that. And what's the frequency? As I mentioned, people moved from quarterly to monthly as a matter of fact, in a rolling forecast and they started moving to daily and you got to understand when do you recommend this kind of a model for what businesses and what's that, how much attention do you want to give to those plans on a regular basis? >> One more question for you, Dave. When you're in those customer conversations, I'm curious, is this a C-level conversation now in terms of, "Hey, we need to be able to utilize AI and predictive for planning technology and reporting technology", Has that elevated in conversation within the organization? >> So yes, the pandemic has opened up, and just disruptions in general have opened up the conversation around about the importance of better planning and business continuity and building resilience into an organization. That is a boardroom conversation that's very important. So it is definitely raised up into that level. As planning starts to sprawl outside of just the office of finance into these operational areas, those line of business executives are getting very involved and saying, you know, we need to plan to perform and setting that conversation up and using these types of new technologies and capabilities that we're kind of replacing what can't be automated by human beings, right? Or just can't be done with the amount of manual work involved. And we see this today, just the amount of sheer number of data, the amount of volume and the amount of data intersections that have to occur. You need the capabilities of something like planet windows with Watson to go to deliver something like that. >> Awesome. Well, Dave, thanks so much for joining me today sharing what you've seen in the last year and how some of the customers have been very successful at adapting to a pretty dynamic time. We appreciate you coming on the show. >> Thank you very much. I appreciate this. >> Bye Dave Marmer. I'm Lisa Martin, you're watching the cubes coverage of IBM Think. (upbeat music)

>> Announcer: From around the globe. It's theCUBE with digital coverage of IBM Think 2021, brought to you by IBM. >> Welcome to theCUBEs coverage of IBM Think 2021. I'm Lisa Martin, joined next by Peter Morrow the VP of sales and marketing at IBM partner, TRM. Peter, welcome to the program. >> Hi, thank you. Happy to be here. >> Tell me a little bit about yourself and TRM before we dig in. >> Well, TRM is a long time business partner for IBM. We for about 30 years, specialize in helping IBM customers implement Maximo and have a lot of deep technology expertise and in Maximo and related software in the enterprise asset management industry. I'm the VP of sales and marketing, I've been at TRM for about 10 years and I'm proud to lead our talented sales teams and our sole mission is to help our customers get value out of their EAM solutions. And we're really excited about recent developments in AI and bringing value to a lot of our customers and their organization, and finally get ROI out of their long time investments in the EAM. >> Let's dig in a bit more to the IBM relationship. I know TRM is a gold partner, but talk to me about that and how TRM has leveraged that partnership with IBM to help your customers be successful. >> Sure. Now, we're a little bit of a unique partner with IBM for a long time. We've been pure resell and implementation services. And recently we've transitioned into an OEM relationship with IBM where we actually embed IBM products into broader TRM offerings. And this relationship that we have with IBM is really important as IBM is the dominant player in EAM and AI and hybrid cloud it's really a natural fit for us to leverage those really mature solutions and build on top of them TRMs deep expertise and the technology and the reliability side to offer more of an end to end solution to our customers. >> Got it. So the last year or so we've seen a lot of market dynamics. Talk to me about the EAM market what's going on there. What are some of the changes? >> Well, there's a couple of key changes that we see, one of the biggest changes I think that impacts our business and IBM is that customers really don't have an appetite for long expensive implementations of custom solutions. They're really looking for more turnkey solutions that have proven value already and very mature. They've already spent tens of millions of dollars implementing Maximo or related EAM solution. They really don't want to embark on this really expensive long journey to get to that next level. And so to meet this requirement we've been focused for the past couple of years on developing much more turnkey solutions. One of which is one that we call TRMs Maximo AAM, solution and that's built on Maximo, but it's also layered with IBM's new AI solution for Maximo customers. And we marry that with our deep reliability expertise and we're really excited about being able to roll it out in literally weeks instead of months or years for a lot of new customers. And that's a really short time to value and ROI is something that's pretty much unheard of until now in this industry. >> Talk to me about some of the advantages that your customers are getting like on a general level from AI, from hybrid cloud, from data. >> I mean, it's this really groundbreaking. What we're finding is that there's, until very recently AI was really not embraced as a practical solution to a lot of maintenance problems. You're looking at a community of pretty old school mindsets and maintenance and reliability where, it's a very, RCM is a very structured methodology for breaking down equipment and failure types and solutions, ways to predict those failures. And for a long time RCM specialists didn't really feel like AI was a solution that was the answer. And what we're finding is that, with the maturity level of IBM's products, it is now at a point where AI is a great fit and you take a experienced reliability specialist and you've armed them with AI tools like IBM's asset monitor and Maximo health and predict and you give them those tools and they can roll out predictive solutions that scale like really they've never had the chance to before. >> And talk to me about some of the adaptations that TRM has made in the last year or so as the market has been so much influx and so many dynamics going on, how have you adapted to that to really help those customers take advantage of the latest technologies? And for example, use AI. >> The big thing for us is recognizing that customers really aren't interested in a long expensive, drawn out solution. They recognize they have problems, but until you can come to table with something that they can digest in small bites. And that is at a price point that isn't over the top they're really happy staying with the status quo, at least until the solutions can be delivered and like that very bite-sized implementation programs. So we've spent a lot of time trying to make our solutions more turnkey, packaging up offerings in a way that you can start small, but all that effort you put in on a small scale, you can ramp up and scale enterprise wide without making a huge investment. And it doesn't take years to roll it out. You can really do something and make an impact within a couple of weeks or months, rather than you know, many months and years down the road. >> That time to value is key. Especially I think we've learned in the last year that real time is so essential for so many things. I'm just curious if any industries in particular that TRM and IBM are really helping transform like energy, for example, give me some examples of industries that are really moving forward with your technologies. >> It's really the classic asset intensive industries. Utilities are really big maximum users in there. They're the ones that, they've embraced Maximo for many, many years. They're hungry for innovative technology, but still cautious about moving forward on a large scale but we're able to get them excited with the programs that we're offering. And the same goes with oil and gas. That's another big user of Maximo, asset intensive organization and manufacturing definitely big Maximo users, all three have been very interested in moving forward with the AI for maintenance solutions that TRM and IBM are together bringing to the market. >> We summed up across the oil and gas, energy utilities, as you mentioned what are some of the biggest things that you hear in terms of demands from customers when you're in sales meetings? What are they looking for problems they need you to help solve? >> You know, it's honestly, it's the classic problems that we've been working with them for 20 years and really have they haven't been able to solve effectively where they're talking about critical assets that break down on expectedly, maintenance teams, running around doing a lot of maintenance on assets. That's in perfect health, making big promises on transforming maintenance, massively reducing maintenance budgets. And it really hasn't happened. And there's really been until now no real solution that solves those problems directly. And we believe the combination of AI and reliability engineering and in the key EAM fundamental principles is what's going to help our customer base really get value and really solve the problems that they really suffered from all these years. >> It's interesting that you say that it really they haven't been able to solve those problems but from a technological perspective the technology is there now to help them do that. What's the time window when you're talking with customers especially given the market dynamics that we're still living in, are they coming to you saying help us within a week, two weeks, we got to turn this around? >> I mean, the ones that are approaching this with an open mind, we can communicate to them that a huge undertaking is not required. They can get started on a small project, select one critical asset and then begin to plug in some data, around that asset that they know is related to equipment failures. We can get that data connected with the maximum asset monitor and within weeks they begin monitoring that asset health. They do some anomaly detection and it does not require of big long-term investment. And so for somebody who is willing to keep an open mind about AI and really wants to give it a try, that sales cycle is very short. They're willing to get going relatively quickly. We do find that many organizations want to step back take it slow, assess other options. And for them that's that aligns more with the classic, big bang type of implementation project, where that takes months of planning, budget planning approvals. And that goes into that 12, 18 month sales cycle or project planning phase, that's fine. And at the end of that, it's a big project but we really do recommend starting small. It is definitely possible to see some early quick wins and then roll out on a larger scale. And frankly, you could have something deployed at scale within that entire period of planning that they would otherwise naturally do on their own. >> Take us out of here Peter, with some predictions, some thoughts, maybe a crystal ball on where you see the EAM market going, the rest of this year and what TRM is planning to do to help customers really leverage opportunities and growth. >> You know I really do believe we're at a tipping point where there's been a lot of anticipation leading up to the release of Maximo and the Maximo eight and the Maximo application suite. There's the AI apps that are in the suite like asset monitor and health and predict that they really are mature products. There's not, I think until now there's the customer base has viewed AI as more of a like a fantasy or science fiction as it relates to maintenance, but these products are real. And I think with a lot of spending having been on hold over the past year, there's a lot of interest in learning more trying to test the waters. I really think that we're going to see a lot of interest in predictive solutions, a lot of interest in IOT projects. And, we're in a position where we're ready to begin rolling these out and it's really exciting. >> Yeah, the maturation is there, the technology is the customer interest is there certainly the opportunities are there. Peter takes out with where can customers go to learn more information about your solutions? >> I mean the best places to check us out on our website, www.trmnet.com. We're also on LinkedIn. We do a lot of blogs. We do a lot of webinars, we're out in front and trying to make the market aware of our thought leadership and deep expertise in Maximo and EAM and in predictive solutions we've got a YouTube channel where we post demos and all of our webinars. So we're trying to push information out there happy to, we look forward to interacting with prospects and customers about how our solutions can impact them. >> Excellent, Peter, thanks for stopping by and sharing with us more about the TRM IBM relationship, the opportunities in the EAM market and the appetite for AI that your customers and very big industries are having. We appreciate your time. >> Thank you very much. I enjoyed it. >> Me too, for Peter Morrow, I'm Lisa Martin. You're watching theCUBEs coverage of IBM Think 2021. (upbeat music)

>> Announcer: From around the globe. >> (upbeat music) It's the cube with digital coverage of IBM Think 2021 brought to you by IBM. >> Hi, welcome back everyone to the Cubes coverage of IBM Think 2021 virtual. I'm John Furrier, host of the cube. Got a great guest, Rick Smith, CTO of IBM Anthem client team. Rick. Great to see you. Thanks for coming on the cube. >> Yeah. Thank you, John. Nice to see you as well, virtually. >> First introduce yourself, what you do there, what's going on on your plate these days, honestly, COVID, we're coming out of it soon. Take a minute to introduce yourself. >> Yeah, so I've got about 15 years in the seat with Anthem. Previous to that I worked at Pretty university as the CTO in Indiana. So haven't really left, but started working with Anthem as a technical architect, eventually moved into the CTO role and have been part of, you know, a long journey with them that started at a managed services agreement in 2005. And here we are in 2021. So I've been through a lot of changes they've made to improve themselves and move into digitalization. And certainly the changes we've made too to accommodate that as we went through the years. >> Awesome. Well, thanks for that setup. I really want to dig into this expansion of project Cirrus. You guys have had a multi decade partnership with IBM and then last year you launched this expansion, project Cirrus. Can you describe this project? And what does it mean? And this new term I've heard, enterprise hybrid cloud as a service. Sounds very interesting. >> Yeah. So that's my term. I'm hoping you made it patent or something like that. But the reality is you hear our CEO talk and say that 75% of corporate workloads are not in the cloud yet. Right? And Anthem is no different, right? So they starting to go into cloud and those kinds of things. But they said to us, you know, "Hey, we've got a long series of excellence with you from a delivery perspective, reliability perspective is kind of the bedrock of what we do, but we don't want to be in the data center business, right? And we want to transform and move to cloud. We want to become a more of an AI company and these kinds of things. And we said, well, we think we can actually put together a program... Excuse me, program for you to allow you to do that, right? And so we formed something called project Cirrus which is really an expansion of our partnership. So if I look back, John, we did about 80% of the end-to-end delivery for Anthem from a managed services perspective. In other words, they did a few pieces and we said, we think we could improve that if we had the entire 100%. And so project Cirrus was about, you know, extending from 80% to 100%. It was also about taking a series of applications that were important to them and actually say, we'll actually take them on and transform them 100% all the way to cloud and take advantage of new things. It was about a commitment to closing those data centers, right? So they have five strategic data centers. And about 24,000 hosts that we said we will actually commit to getting those, you know, getting you out of the data centers and moving those to either IBM cloud or close to IBM cloud if you will, I'll come back to that in a minute. And we'll also build something called ATEC, Anthem Technology Excellent Center, if you will. And that's near and dear to my heart because that's sort of my baby, right? So it's a transformation engine and we can talk a little bit more about that in a second. But he said the key to this for us is that, if we look at our trend line, John, over the number of years with Anthem, when we started about 2007 looking at this data, we've grown the number of hosts. We've had to manage, over 600% during that time period. But we've driven down high priority incidents by over 90%. So think about that. You know, this is really important for them to have resiliency and stability in their organization. You know, huge acceleration number of hosts, but drive down the a P zero incidents, if you will. And they said, we need to maintain that and continue to improve upon that. Right? >> Yeah. >> So Cirrus was a commitment to take that further, right? Start driving AAN, AI into the operations, if you will in everything that we do. So Anthem is transforming to do AI and machine learning for their members. We're committed to transforming and doing the same kind of thing on our operational side if you will. >> Yeah, that's awesome. And I think one of the things that's interesting that jumps out at me just as you're talking, first of all super exciting that project you got out there, a lot going on to unpack, but let's do that. I mean, what I hear you saying which is getting me kind of all triggered in a good way is you got transformation going on and innovation same time. You're innovating with this new enterprise hybrid clouds of service concept. You take in more efficiency, you're doing the classic transformational things, making things more efficient, all that good stuff for agility, but it's actually innovative. So this idea of an enterprise hybrid cloud as a service is pretty innovative because now you're talking about things with AI and scale that come into play, right? So you got the setup, you got it moving into being innovative but scales right there. What is this enterprise hybrid cloud as a service? Because is it just agility, is it the AI piece? Where do you see that going? >> Yeah, that's a great question. Right? And you're a great stuff, man, Johnson. (Smith laughs) So again, Anthem's not ready to move all of their workload to cloud, right? And we recognize (indistinct)is going to be out of the data center business. So how can we take non traditional workloads, right? Get them close to cloud, right? Get them very close to cloud, get us out of the managing the data center and actually allow us to move seamlessly from non traditional workloads into cloud. And so what we did was something we think is very innovative. This is the enterprise hybrid cloud piece for me, right? 'Cause normally hybrid cloud says, you have a client data center location and you have cloud. We marry the two together. We said, you're not going to have a data center location anymore. We're going to have our data centers, you know, IBM cloud. And we're actually going to put some dedicated space right next to cloud. And when I say next to cloud, I literally mean within a few feet. And we're going to bring these non traditional workloads there, we're going to take the network operation brain and bring it there. And we're going to allow you then to basically be able to move seamlessly from that to directly into cloud and improve operations at the same time. There's other a side benefit to this too. The other unintended sort of benefit is that what any organization, right? That you find stuff in the data center that hasn't been looked at for a long period of time, right? Application teams haven't looked at it, et cetera, et cetera. We're literally touching every single host. Right? So this gives us an opportunity to also work with our teams and find things that really can just be thrown away. Right? And this is great because we're actually making them more efficient, optimizing the cost structures as we go about it. >> Yeah. I mean the operational model changes me. You mentioned that just that whole point about you're kind of doing some discovery on apps, this becomes kind of sets the table for AI ops which is just code word for day two operations or full cloud native environments, which now you're seeing cloud native include legacy. Yes. Because you can put containers into the mix and you can then create these integration points that you don't have to kind of get rid of the old to bring in the new. So the dimension of what's going on here is pretty interesting, right? When you start thinking about that, "Okay. I can modernize the same time as connect two existing systems." >> That's exactly right. And we put the things very close to one another. And if there's any concerns over data security compliance or healthcare regulated industry, of course, we can have the workloads located in the best location to ensure that security is in place. Right? So that's what's beautiful about it, right? We can kind of hit every layer that's possible from having it just as secure as completely privatized to going directly over to public cloud or connecting the two together as we go along. >> Well, you're definitely a pioneer. I love that enterprise hybrid cloud as a service. I think that's something that's relevant. We're living in a hybrid world. I mean, the cube, we used to go to events now it's virtual events, but when now the events come back, they're hybrid events. Every company is experiencing this phenomenon on hybrid something, not just technology. The ops got to adapt, so super cool. You mentioned something that was your baby. I want to get back to you. And you said you want to talk about, I want to just bring that up. This Anthem technology excellence center is your baby. ATech I think you said for short. >> Yeah. We call it Atech for short. And really, John, we said that it's got to be more than just taking that other 20% that we don't run today. And we're doing some very innovative things moving non-traditional workloads. Like I said, all that kind of stuff was very cool, right? But we need a transformation engine, right? And we need the ability to transform skills. Like upscale the people at Anthem as well as IBM, right there on the account team, it's a big account. We want to think of new ways to work together. Right? Traditional managed services is like, what? Someone cuts a ticket and says, "Give me X by her seat." Right? That's the traditional model. And we said, that's not good enough. We need to collaborate better together. And we are willing to redefining how we form our teams to work with Anthem. Right? So if we want to form, for example, a product ownership team that builds it, runs it, maintains it. And that team has Anthem plus IBM together. we're going to use ATEC as a vehicle to design that and drive it and make sure they have all the skills they need within that group to do that. Right? That's new ways of working together. And it's also to drive things like site reliability engineering, right? Cloud service management operations, make sure that Anthem has the right training, make sure we work together on these kinds of things. So it's really kind of an exciting thing. And it's intended to be a co-created model, right? So we actually work with the Anthem, we co-create using IBM garage methodologies and then the idea is to coast staff it, but it's tended to be a thin layer of world-class engineering. That's really the whole point of it. And yeah, I'm super excited about that. As you move forward, yeah. >> While you're speaking our language, the cube we'd love the co-creation we do with media. It's always fun to create content together. And sometimes in real time put it together like we're doing now. And it creates a bond. I mean, I got to bring this up because this is becoming more and more obvious. And now mainstream, the notion of co-creation, the notion of ecosystems and ecosystems really meaning network effect and integrating with other parties, right? Companies and our systems. If you look at the underlying business model as a systems management software bottle. Okay. So with that, these ecosystems, the network effect. If you build together, you stay together. I mean, this is a different mindset. It's different dynamic. It's a different relationship that companies are now looking for in what used to be called suppliers. Are you supplying something? Are you building together? Right. So this seems to be the theme. Can you expand on this new trend? >> Right. And get away from the strict racing, this person does, this person does that. Instead, we build a team together that has all the skills necessary and that team owns a product life cycle. They build it, run it and maintain it. And that's changing the way we deliver services from IBM perspective significantly, right? Because that's not our traditional model but that's what we're doing. So we're really out in the front end, on the front edge if you will. Changing that model completely. And it's one of the most exciting things for me, you know, as far as going forward. >> You know, this whole idea of partnerships has always kind of been there but now it gets modernized and uplifted if you will, to a new level. And it really is about watching each other's backs too when you have that kind of... 'Cause we're talking about like pushing the envelope on probably the biggest confluence of tech trends I've ever seen in my career. And I've seen many big waves, you know, from the different revolutions and inflection points. Now it's sort of all coming together, right? At scale too, it's happening very fast. I mean, the change over is happening in years that once you took decades before. So it's really is a team approach. >> Yeah. There's no doubt about it. And I see it every day in the work we're doing. And it's like, for example, at Atech where we're working with the data scientists at the Anthem, we're thinking of new ways to build things they've never done before. We're hoping to enable their science, enable the things they want to do for digitization standpoint, the same token I'm taking, you know, a data scientist and putting them on the operation side too. Right? So we're doing both these kinds of things together. And really I didn't say this before, but this whole thing is about driving automation, right? Driving down, no human touch, soft service, automation. That is kind of been the linchpin of this. And I also want to say John, that doing this all during a pandemic, you know, we signed our new agreement together with them at a quarter, at the end of March in 2020. And we went live in August 1st with all the changes, the extra 20% capacity to over 300 plus applications completely, started Atech from co-creation in a pandemic. And we both agreed as a company, I give great credit to our client and to the numbers involved that everyone set up front and during March. The pandemic's not an excuse to get anything done. So, we're going to go forward and make it happen. That's probably the thing I'm most proud about. That was just... It's crazy when you think of how big the project was and do pull it off during a pandemic. >> Yeah. There's going to be two sides of the street and this one, this pandemics over the ones who made it through and refactored and or innovated. Cause it's not just about being and having a tale, it's about taking advantage of the situation and the ones who didn't do anything. Whether they were in the cloud or not, that's not to me. That's not the issue of you're in the cloud you had an advantage. >> It's not. Right. >> But there's going to be two sides of the streets. And I think the one thing that the pandemic has shown us and I'd love to get your reaction as a final comment here is that when you pull back when the pandemic, it showed all the scabs, it shows everything. And you can see what's obvious and it becomes a forcing function. Necessity's the mother of all invention as expression goes so you can see what's worth doubling down on and you can see the productivity gains and that becomes clear. >> Yeah. Yeah. And I think there's good and bad with everything, right? Pros and cons, like you said, and you know, one of the cons I think is the having to schedule all interactions is definitely a con, right? Because when you spend time not only with the client virtually but in person, you do get the advantage of having, you know, chalk talks and things like that. They're not scheduled. Right? So that's definitely one of the cons side, but one of the pro side is it did provide some focus, right? Kind of extreme focus and on what's important and allowed us to, you know, I think dove some bonds with the Anthem leadership team and the application teams doing it virtually over cameras like this that maybe happen at a larger scale than they might have normally been because the pandemic kind of allowed us to do that and made that happen. >> Great stuff, Rick, great insight. Great to have you on the cube as always. Great to talk tech, talk business, talk about the transformation and innovation and the cloud scale. Thanks for coming on Rick Smith, CTO of the IBM Anthem client team. Thanks for coming on the cube. >> You're welcome. Thanks John. >> Okay. Cube coverage of IBM Think 2021. I'm John. For your host of the cube. Thanks for watching. (soft music) (upbeat music)

>> Announcer: From around the globe, it's theCUBE! With digital coverage of IBM Think 2021. Brought to you by IBM. >> Welcome back everyone to theCUBE's coverage of IBM Think 2021. I'm John Furrier, host of theCUBE. We're here with Mark Foster, Senior Vice President of IBM Services and IBM's Global Business Services. It's a global landscape, the world's changing, it's going hybrid. Mark, thanks for coming on theCUBE. >> Great to see you, John, good to be with you. >> You know, the theme this year is all about hybrid cloud. Global transformation is the innovation at scale. That's the discussion, that's the way I see it. The question I have for you to start right away is how has the last year in particular changed businesses as they're leveraging the tech? You know, they want to solve their critical problems and transform themselves, the pandemic has forced them to look at this. How has this last year changed the way businesses are leveraging tech? >> Well, there's definitely been an acceleration in the digital transformations across all of our clients around the world. They have been compelled to leverage technology to connect with their customers in these unique times. They've been forced to use technology tools to allow their teams to connect and operate around the world. And all of this has reinforced also the opportunity to leverage things like extreme automation, AI, and the leverage of things like the cloud to deal with the virtual and more remote nature of working around the world. >> How much of the change last year do you think's going to to be temporary or long lasting. What's not going to be given up? (laughs) What are people realizing? Is it temporary or is it long lasting? What's your take? >> Well, I think we have to recognize that we are moving into a genuinely hybrid world, well, hybrid insofar as I think that some of the lessons we've learned over this past period are going to durably change the way we work, but we're also going to have a certain amount of back to the future, as well, as we try and put back some of the aspects of physical interaction, the ways of actually bringing empathy, creativity together through being together in groups. But I do think also we're going to take a number of these areas of acceleration and they're going to be extrapolated out to genuinely lead to an acceleration of what might've taken place over over five years taking place over a lot shorter period. >> You know, I think that group dynamic is really a big deal. I think that's going to be something that, to me, jumps out at this transformation. People want to work together. They want to be part of something, totally right on. With that, I got to ask you, now that we have this kind of new virtual experience, we're remote, we're not in person, wish we were, but even when we are in personal, it'll still be hybrid virtual experience events means we're still going to act as a group. This kind of brings up the idea of a virtual enterprise. You kind of mentioned that. What you mean and how do you define a virtual enterprise? >> Well, I think a virtual enterprise for us is an extension of the thought process we've had before around how technology is transforming the way all businesses operate. If you do apply, you know, the power of technology to build new business platforms and think about new ways of applying technology to transform your business processes, you think about the way that all of us are reinventing the relationship between people and technology in our organizations, the virtual enterprise just takes that to the next level. It recognizes that if you are able to take a location out of the equation, if you're able to leverage ecosystems more completely through connecting through networks of organizations, all of this extends the vision that we have of how the cognitive enterprise of the past comes to life. And we create this even more connected, even more expansive vision of business which is of course able to leverage technology within its own four walls. It's able to leverage it powerfully with its business partners. But then finally, it's about how you create the platforms upon which you create new ecosystems for competition and new markets that can be created in that way. >> That's really compelling insight right there. I think that's right on the money. I have to ask you, what do you think the differentiating characteristics are for this enterprise? What's going to be the differentiator, what's going to make it work? What do you need- >> I think what's going to make it work first of all, I think we think there's going to be a sort of a golden thread of what you might call an extended intelligent workflow that runs through the enterprise and its partners. And the power of that sort of thread of core processes and core differentiation to be brought to life by the mutual leverage of technology through partnerships is going to be a hugely powerful. So therefore all the partners' ability to embrace those technologies to embrace the vision for how those workflows come together is going to be very important. I think it's going to be very important that actually the ecosystem and its success becomes the strategy of the of the participants as opposed to being something that they happened to be going along with. So it becomes the strategy of the organization. And I think finally, there's a huge amount around here around how you leverage and think about the power of your people, the culture that you create to be inclusive and expansive in terms of applying new talent, building new talent, to allow this virtual enterprise to thrive. >> That's actually brilliant. You know, ecosystem is part of it, not an afterthought or a marketing gimmick. It's got to be part of it, that's awesome. Let's bring that to the next level. The role of the ecosystems are taking a bigger role for you, as you said, what specifically can you point to that has a change that's made in the ecosystem that you can point to, says that's an impactful change, this is a table stake, this is a guaranteed continuing practice. Can you give an example? >> Well, I think what we can see around the world in terms of how the world has solved for something like you're getting vaccines created and distributed on the back of the COVID crisis, that's taken an ecosystem coming together to work in completely different ways in an accelerated way to deliver on very big outcomes. Well, we can also see, you know, clients who are developing their strategies to try and connect the dots across different players to position their business as a platform upon which others bring their parts, their organizations to bear. And I think that we can see therefore that this idea of ecosystems is being used to solve really big problems, but it's also potentially a model that can be used to actually define really big market opportunities as well. And when you can connect the dots and you can expand your market footprint by combining with other key players at scale and also create a way that smaller organizations can come and sit upon the platforms that you create and leverage those capabilities, then the opportunity to actually use that to really expand your horizons of where your business can go are very real. >> You know, that's a really interesting, mind blowing concept. You think about the idea of a network effect or ecosystems, and integration, and collective intelligence. These are paradigms that have been around for awhile, at least past 10 years. It was the Holy Grail, let's hope we get to that. It seems like that's happening right now. And I think more than ever, it can be harnessed. And so I think you starting to see that with the hybrid cloud and it's not just tech, it's societal impact, it's impacting people, their jobs, and their ability to contribute and work. So this is a huge concept. So really excited this conversation. I guess the next question I have for you, Mark, is how do you bring clients this value? How do they create value? And how do they take this and transform their business with it? What's the playbook? >> Well, I think for clients, the first thing for them to recognize is to understand that this is the world that they are operating in. And I think that from a playbook point of view, the first thing I would say is you do need to think about which ecosystems do I want to play in? How do I think I could win by being a part of, or shaping an ecosystem? I think, secondly, there's the opportunity to think about how you use all the data that's out there in the world to be a stronger source of innovation across an ecosystem, to think about how your products and services could be modernized to succeed in that world. How you build those innovations into this new vision of an extended workflow or process view that binds the players of your ecosystem together. And you're really thinking about how to reinvent the way work gets done. Apply automation, apply AI, apply blockchain, apply IoT to transform those workflows is a massive, massive opportunity. To recognize that actually by the power of that, you're able to have significantly more impact than before. So make sure you're setting your ambitions high enough around the impact the change you're trying to drive can bring, and then I think also just making sure you're thinking all the time about what this means for the culture of your organizations, the workforce you want to connect with, how you want to access talent and bring it to bear across this new extended value chain? You know, who do you need to employ, versus who do you need to contract with, versus who do you need to make sure are participating in the processes that you're driving? And then finally, how do you make sure that you have the infrastructure, and the systems, and the applications that are open enough to allow you to really bring this vision to life? So the underlying hybrid cloud, hybrid architectures that you have and the networks you have that bind you together become fundamental. >> That's awesome. Great insight there. I guess my final question is how has your personal outlook changed in the past year when everyone is working from home? And now we're starting to see the pandemic, you know, light at the end of the tunnel from this pandemic, once we emerge out of it, people want to have a growth strategy, want to get back to real life. Any words of advice for our viewers on your personal outlook and as we come out of the pandemic and they can participate- >> Well, I think the first thing to recognize is we all have a collective wish around the world, probably for the first time for a long time, I think pretty much most people in humanity are sharing a shared view about a desire to have a more expansive horizon than the one that's outside the window of their kitchen, which I'm looking out of right now, and being able to get out and about, and engage in some more aspects that of normal life. And I do think that we're all looking forward to that opportunity. I think we're going to have to recognize that we're probably all going to also adapt our behaviors, going forward, but there's almost an enormous amount of exciting things that we've all got pent up we want to go and do, and I think, you know, the critical thing for us all is to hopefully approach that world safely. But at the same time, recognize that there is hope, we are working our way through this as a world. And as long as we try and make sure we do that in a way that is actually equitable, and that we do make sure that all boats are lifted as we return here, then I think that's a really positive view of how the future will be for all of us. So we should all look forward to that. >> Mark, it's great to have you on theCUBE. I love the insight, I love your message. It's right on, it's relevant, and super cool because that's what people want. They want to collaborate and be with people. I guess with the final minute we have left, share an observation from the past year and a half. Something that surprised you that happened in the industry, something that you didn't expect or something that you did expect that's positive that we can look to and say, "That's a good thing, we want to double down on that." >> Well, I think the positive thing that I think we can double down on is that we have all actually learned to be perhaps more open to interacting with people who we wouldn't otherwise have interacted with through this medium, that actually I have found that I've broadened my network of people that I've been engaging with through the fact that it has been actually relatively easy to connect even at high levels with people, but all the people have been able to connect in a strange way with a bigger group of connections than you would have done through the normal physical constraints of flying somewhere, seeing someone, meeting someone, and how you use your time to do that. So I would say one of the positive things is actually how open people have been to start new relationships over this virtual medium. Of course, the trick is going to be, can we build on those virtual relationships we've created and make them more sustainable once we're back to a more normal life and they become, you know, the new friendships, the new business relationships and networks that we can thrive on for the future? >> That's genius, love it. I agree. CUBE Virtual's here doing it. We're trying content, community, collaboration, connection, friendships, new things, touch someone with a click and engage. Mark Foster here, clicking into our CUBE Virtual for IBM Think. I'm John Furrier, thanks for watching. (upbeat music) ♪ Dah, deeah ♪ ♪ Dah, dee ♪ (chimes ringing)

>> Announcer: From around the globe it's theCUBE with digital coverage of IBM Think 2021. Brought to you by IBM. >> And welcome back here on theCUBE. John Walls, your host with you as we continue our IBM Think 2021 initiative. Been talking a lot about IBM's assistance in terms of what it's doing for its client-base. We're going to talk about partnerships today, a little bit with Bill Patterson who is the EVP and General Manager of CRM Applications at Salesforce who has a really good partnership in great practice right now, with IBM. And Bill, thanks for the time today. Lookin' forward to spending some time with you, here. >> Yeah, thank you John, thanks for having me today. >> You bet. Well, let's just jump right in. First off, let's share with the viewers about your core responsibilities at Salesforce. We talked about CRM, what your engagement is there, but if you would just kind of of give us an idea of the kind of things that you're handling on a day-to-day basis. >> Well, I am responsible for our CRM applications here, at Salesforce, which are our sales cloud technologies to help organizations get back to growth, our service cloud technologies which are really helping organizations to take care of their customers, you know, through all moments of the digital lifecycle, our small business solutions, so to help growing organizations thrive, and our Work.com and vaccine management solutions which are helping the economy safely reopen through the crisis modes that we've all been living in. So broad range responsibilities and my day-to-day is nothing like it was a year ago. >> Yeah and I could only imagine, especially when you throw that last component in, COVID, which hopefully, we'll have time to talk about just because, I think, people are so are taken to the subject now and obviously it's impacting business on so many different levels. But let's talk, first off, about IBM and your partnership with them, kind of the genesis of that, how that came about, and maybe how you're working together. How are you integrated these days with IBM? >> Well, you know, one of the things at Salesforce that are key value as an organization is is to establish trust around the transformation of organizations across the world. And when you think about brands that you can trust to drive transformations with, IBM and Salesforce really stand apart. So IBM is an incredible partner for us on the technology side, on a service delivery side, and in an innovation side for us to create new solutions to help our clients really go in this from-to state of how their businesses used to operate to how they need to operate in the future. I loved working with the IBM team. We have a lot of great values that are shared across our two organizations. But most fundamentally, those values are deeply rooted in customer success. And I think that that is one of the things that really draws me too, working with such a great partner here. >> Go into the process a little bit, if you will. So if I'm a prospective client of yours and I come to you with some cloud needs, you know, again, whether it's storage or whether it's applications or whether it's Edge, whatever it is I'm coming to you for, how do you then translate that to IBM and how does IBM come into play, where do the boundaries kind of start and stop or do they? Or is it a complete mesh? >> Yeah, well I think one of the things that's sort of unique about today's climate is people aren't just looking to solve technology problems, they're looking to solve business problems. And what we really do at Salesforce is lead with the business transformation opportunity and deeply partner with IBM on a number of fronts to really go help those opportunities become realized. The first is in the services line. IBM has great partnerships with Salesforce around the transformation about core business processes, configuration, integration services. That's one of the dimensions that we work together on. We also work together on areas of artificial intelligence and how we help businesses become smart in their operations every day to empower their workforce to really achieve more. And finally, you know that you mentioned about core technology, you know, oftentimes, the business requirements translate into great technology transformation. And that's what we do deeply with the IBM team is really outlining a blueprint and a roadmap for modernizing the technical infrastructure to help organizations move fast, increase their operational agility, and run at such scale and safely in today in the modern world that we all operate in on. So through all those facets of the lifecycle, IBM continues to be one of our leading partners, globally, to help clients, you know, not just here, in the United States, but around the world to think about how they need to maximize their transformational abilities. >> Yeah, and you touched on this at the outset of the interview. We were talking about IBM and the impact and obviously, the great association relationship that you have with them and the value in that. I'd like you to amplify on that a little bit more in terms of, specifically, what are you getting out of it you think, from a Salesforce perspective to have kind of the power and the weight and the bench, basically, that IBM provides. >> Well you think about transformation and you know, you read a lot about digital transformation online, that means so many different things to so many different businesses. Businesses, not just, like I said, here in one country, but globally, the transformational needs really need to come with incredible bench and domain expertise by industry, by geography, even by some micro-regions in those geographies given what we've been experiencing here, in the public sector in the United States with this COVID response activity we've been doing with the IBM team. And so when you talk about the deep bench, what I love about working with IBM on is, again, commanding just great industry insights and knowledge of where industries are heading and also cross-industry insights so that you can really bring great best practices from say, one industry to another. Second is that real understanding of the global nature of business today. And I don't think the one thing that's fascinating about digital, it is not a sovereign identity, today. Digital really means that you need to understand how to operate in every country, every region, every location, you know, safely. And so IBM has incredible depth in bench of experiences to help our clients truly transform those areas. Maybe another area that I really have appreciated working with IBM on is that deep technical understanding and deep technical domain of excellence maybe in the area of artificial intelligence. And our partnership is quite unique between Salesforce and IBM. Not only do we work together for external clients but inside of IBM, IBM is using Salesforce today to run a lot of your core operations. And so the partnership we work with, not only IBM as a kind of delivery excellence, but internally as a customer, is really helping IBM transform its operations from service to sales to marketing all around the world. So I think this partnership is one that is deeply rooted in working together and really, like I mentioned before, finding the right path to drive the outcomes of tomorrow. >> You know, you mentioned COVID and so we'd like to touch on that. But I assume that's a big part of your current relationship, if you will, in terms of the partnership goes. What, specifically, are you doing with IBM in that space and what have you done, and then what are you continuing to do as we go through now, the vaccination process and the variant identification processes and all these things? So maybe you can share with our viewers a little bit about the kinds of things that you have been working on together and the kind of progress that you've been making. >> Well, back a year ago, you know, when the world was really at a standstill, Salesforce created a solution called Work.com which was to engineer new technologies to help businesses kind of deal with the reality of a hard shutdown to business in the, say, private sector and then in the public sector, to really create new innovation around key solutions like contact tracing that you might have needed to track, you know, kind of outbreak and the rate of progression of the virus. And what we did with the IBM team, working with clients around the world first was work together to deploy those technologies rapidly into the hands of our customers. Through those moments of opportunity and realization, you know, working with our clients, we also started to hear of, you know, kind of about where we find ourselves today, this mass vaccination wave of where our citizens and societies are kind of on the recovery journey. And the work that we did with IBM was to start to plan out the next wave of recovery options around vaccine managements, Salesforce creating a core vaccine scheduling, distribution, and administration management services and IBM focusing on more of that credentialing and vaccination state of how someone has gone from receiving a shot in arm to now having a trusted profile of which vaccines, when did you receive them, are they still accurate and valid around those solutions. So where we're working with the IBM team most acutely on COVID now is in the vaccine credential management side through Watson Health. >> Well, can you give us an idea now, let's see if we can dig in a little deeper on some of those other things you talked about to about core technologies, you talked about, I mentioned Edge, you know, and that's people tryin' to figure out how they integrate these Edge technologies into their primary systems, now. So can you give us some examples, some specific examples of some things that you're actually collaborating on today in those areas or maybe another that comes to mind? >> Yeah, Edge computing is probably one of the other more exciting things that we're doing with the IBM team and I think you find that really working with our field service business and IBM cloud services, you know, globally speaking. On the Edge, as devices become smarter and more digital, they have a lot of signals that organizations can now tap into, not only for real-time intelligence but also fault intelligence when a device is starting to need repair or preventative maintenance around the solutions that kind of need to be administered. And the work that we're doing to really broker this connected, not just enterprise, but connected sort of experiences with IBM, super powerful here, because the IBM Edge services are now helping us get into anomaly detection. Those anomaly detections are automatically routing to workers who use the Salesforce field service capabilities, and now we can help organizations stay running safely and with continuity which is really all our customers are asking us for. So the ability for us to be creative and understand, you know, our parts of the picture together are really the things that I think are most exciting for what we're doing for clients around the world. >> Yeah, you mentioned continuity, kind of a cousin to that, I think, is security in a way because you're-- >> Absolutely. >> So what are you hearing from your customer-base these days with regard to security? You know, a lot of high profile instances certainly from bad state actors, as we well know. But what are you hearing in terms of security that you're looking at and maybe cooperating or collaborating with IBM on to make sure that those concerns are being addressed? >> Yeah, you know, I think, well, first off, security is on the top of minds for all decision-makers, executives, today. It's the number one threat that a lot of companies are really needed to respond to given what we've seen in the geo-political world that we're in. And security isn't just about securing your servers, it's also about securing every operational touchpoint that you might have with, you know, your every end-user or even every customer that's inter-operating with your services that you project as an organization. And what I love about working with the IBM team is, as we mentioned, you know, such great insights across all parts of technology infrastructure to really help understand both the threat level, how to contain that threat level, and more importantly, how to engineer with, you know, great solutions all the way into the hands of customers so they become safe and easy for all actors in your environment to really operate with. And that's where, again, you know, you think about a solution like mobile sales professionals, they're out traveling around the world on mobile devices, sometimes, their AG even brought their own personal devices into the enterprise. And so IBM is a great partner for ours just to help us understand the overall threat level of every device every moment that an employee might have within their organizational data, and really help create great solutions to help keep organizations running safely. >> Yeah, I think it's interesting you tell about people bringing their own devices on, back when, I remember that acronym, BYOB was like a huge thing, right? (chuckling) And this major problem or conundrum and now it's almost like an afterthought, you've got it solved, you've got it well taken care of. >> Well you think about, again, devices in the enterprise and how much we've been able to achieve with the BYOB becoming commonplace and norm, even today, the workman place from home kind of environment that we're in. I mean, who would have thought a year ago that most of our operations can be conducted safely from our home offices, not just our regional or corporate offices? And again, that's the kind of thing that working with IBM has been such a great value for our clients because no one could have forecasted that the contact center would've had to moved to your kitchen last year. And yet, we had to really go achieve that in this time and working with great partners like IBM, it became not just a conversation but real practice. >> By the way, I think I said BYOB. I meant BYOD, so you know where my mind's at, right? (chuckling) >> I wasn't going to correct you. >> Hey thanks, Bill, I appreciate that. It just kind of hit me. I think that that just, that was a Freudian slip, certainly. Hey Bill, thanks for the time. I certainly do appreciate and thanks for shining a light on this really good partnership between Salesforce and IBM. And we wish you continued success down the road with that, as well. >> Yeah, thanks again. And again, love being your partner and love the impact we're having together. >> Great, thank you very much. Bill Patterson joining us, the EVP work in CRM at Salesforce talking about IBM and that relationship that they're putting into practice for their client-base. John Walls reporting here, on theCUBE. Thanks for joining us with more on IBM Think. (soft music) ♪ Dah de dah ♪ ♪ Dah ♪

>>from around the globe. >>It's the cube >>With digital coverage of IBM think 2021 brought to you by IBM. Welcome back to the cube coverage of IBM Think 2021. I'm john for your host of the cube ricardo for lenses here with me is the global managing director for IBM at Citigroup recorded. Great to see you. Thank you for coming on the cube. >>Thanks for having me. >>You're the team leader for Citigroup Managing Director um, a lot going on in the world of finance, Fintech technology, scale transformation. All this is happening. Always a leading edge indicator give us your perspective on the market right now on the, on that vertical and in general because there's so much scale is so much machine learning, so much going on, so much competitive advantages. Give us an overview of the industry, how you see them. >>So john I had the good fortune of working essentially around the world of work in europe in Asia in Australia, back here in north America. And I'll tell you what, there are some, some uh, dynamics are specific to a market. There are also a lot of common threads, right? You know, a lot of common threads right? As you know, my industry, financial services in the middle of uh great disruption right from payments to a global wealth to understand exactly. Not to reposition yourself is a, is a startup. Oftentimes looking time to be dis intimidated by many of the context. I have found that many financial institutions are very adept, a change in the way they operate a lot more nimble than they had been in the past. And they found ways to incorporate a lot of the techniques that some of the Frontex operate with. So they all have shark tanks, they all find a way to uh progress investments that they get to a point of uh, failing fast, right, more are some more adept than others. But for the most part, I'd say that everyone in the market is looking to beef up their, their core competences. >>And, you know, the financial, um, industry has never been shy of using technology ever. They've always poured it on. They always want to get more edge. Um, what's your, what is the edge now in the industry for, um, financial and, and in general, businesses who were learning how to be agile? What's the edge? >>I think the edges really finding a way to be ambidextrous, right? Because in many respects that you don't want to hold on to a franchise to what got you to a level of success. It's oftentimes it's in the case of my client is to be in good stead for more than 100 years, Right? So you don't want to let that go. But you also want to grow a new set of skills and grow competences that they need to take into the future. I have found that in many respects that many of my clients are remind me of what lookers and one said maybe 2025 years ago, our former Ceo and chairman, who said the last thing that IBM needs is a strategy. In fact, I think that many of our financial institutions that don't need a strategy, they just need the competences to innovate and executed scale and it's a lot easier said than that >>card. I want to get your perspective before we move on to some of the initiatives and work at city, which is probably compelling. But I want to get your expert opinion on a question that comes up all the time with customers and that are going post pandemic and looking at growth strategies. The idea of the unit economics of their business models tend to change with more data, more digital acceleration. Is there any observations that you could share for leaders who are looking to get that financial mindset or how the business is changing with whether it's copies or business models. Because at the end of the day, the financial upside of what we're seeing with digital is pretty significant. The economics are seem to be a real game changer on these, these conversations about acceleration, but also the results are business results are money. >>Absolutely, john, as a matter of fact, that I'd argue that while it's true that the common theme, so many and that several of our financial institutions are growing a skill in, in a, in a uh, approaching problems in a different fashion is also true that there's been a lot of redistribution of wealth across financial enterprises, Right? So it's not lost on all of us. Right. The security look at market globalization of the financial institutions, on the work. They really come all over the place with the clear winners in several sectors, site in Asia and europe as quality of North America. So what I argue is that while I think we're all tired of hearing the data is the new oil, right? It's also true that we need to find a way to finally harness the power of it. Right? And that's what I think IBM is more more adept at, right, argue that many of the common threads that we've seen across the financial institutions and back to the, to the measures of success you would indicate in a minute ago, not really around cloud, right around data and around digital transformation. Right? So our approach to cloud, for instance is unique, right? While there are a number of uh very competent hyper scholars, we've taken a different approach to it, right? We've taken our approach is more than after other highly specialized regulated workloads, right. Organ after the layer that allows you to port application seamlessly based on regulation costs and competition across multiple platforms. Right? So this hybrid concept has only been at the center of our strategy and that's the one that mama is is delivering our clients greatest value. Tell you what. I think one client told me once after hearing our hybrid story that while there were many cloud providers, there wasn't anyone that could help them out as much as I B. M. Dealing with your legacy and in all candor. I think it's fair to say that legacy is here to say well past our investment horizon. Right? So that level of self awareness, I think ended up believe forming our collaborations for years to come. >>You know, I'm a big believer and I've reported this and certainly talked to Arvin when um he was on the cube about this microservices, containers, kubernetes, these kinds of new technologies really allow for legacy to integrate well into the new modern era of computing in hybrid cloud. So totally agree. And that is really key tailwind for for innovation and these transformations. I have to ask you ricardo what's going on at city and IBM tell us take us through some things that you're working on, some of the exciting projects that you're driving. >>So the disclaimer is that I started this well three months ago, so I'll try to do my my team proud here. But what I'll tell you is that the teams you talk about are alive and well, it's sitting right? So on the cloudfront we are doing exactly that. We're focusing on on on being uh cities partner on the heavy cloud deployment, acknowledging that higher Ecologist is an ecosystem of participants, right? Technology that IBM s dominance in on prime computing. We'll go through a very different face going forward. We not only a comfortable with it, but we are trying to accelerate its deployment. Right? So you mentioned communities, you mentioned containers, Hence a redhead acquisition, right? Which has been central to the collaboration that we've uh we've established the city and we look at the broad, I'm also gonna go back to data and I will tell you that, uh, you know, uh, cities in the midst of a transformation journey of their own right. It's also the middle of a regulatory challenge. That's second to none. Right. With with the zero cc. Findings that then led to a financial remediation plan that the bank has put in place over the past two months. With that in mind we are looking to help the bank make a make a good crisis make the most of the crisis, right? And so helping, for instance, Mark Sabino, the head of Innovation City, find ways to infuse Ai into their internal Codec practices doing that. It's just smart business. The results in much better outcome at a lower cost and it's something that can scale because it's all seen before. Oftentimes our solutions have lacked the ability to scale to really keep up with them in >>ricardo. The relationship between IBM and city has been long standing. I believe. I read somewhere you're celebrating 100 year partnership. Is that true? If so. I mean, it's a huge milestone. What's the take us through the history and where this is going as a partnership? >>I've heard as a matter of fact is that as I first came on board that in fact our companies have been added for more than 100 years and someone showed me an actual document 100 years old, there was proof positive of that. So I'll tell you, I know that our firms would be added again 100 years from now. I will probably not be here to toast to it but I'm certain they will continue to collaborate and for the strong is this is my responsibility. I'll do whatever I can to help you continue to grow. We're only going to focus on three things I spoke about every cloud. Would you also want to be the partner? Is the bank transforms its operations right and infuse in it. Our Ai and process, information skills and capabilities. I think if we do that, we'll continue to collaborate and will continue to have our partnership fully rests on two pillars that is always independent, which are really innovation can trust >>great commentary, great uh an account that you're leading probably a great team behind how many people are on this team must be pretty massive and I'd love to see that document by the way, was it a memo? Was that type written was a handwritten? You know, it was a P. O. >>It was an Akron document and I get your copy. >>Uh so historic. I love those history. I love the IBM culture longstanding relationships. Final question for you. You've been in the industry for a while, you've seen many waves of innovation if you're talking to a customer, your friend or colleague and they had asked you ricardo, why is this wave so big and so important? What would you tell them, >>john I think at the heart of this transformation, the evolution, the way they should call it is not the intellectual products, the international new processes but entire no value chains that are being established by players that in many cases need need each other to coexist. This is hardly been the case in the past. I think IBM will form a great example of it, right? And so I do think that this is far more disruptive than what we have witnessed in years past and I can't wait to get get in it and my part to lead us through it >>ricardo, great insight, totally agree. This is a time of open collaboration, an ecosystem you're seeing in the ecosystem and network effect where people are integrating together in this new connected distributed economy. Global economy, thank you for coming on the cube, appreciate your >>time. Thank you so much for having me. >>Okay, Ricardo for Relenza, Global managing director for IBM at Citigroup. This is the Cube coverage of IBM think 2021. I'm John for your host. Thanks for watching. Yeah.

>>from around the globe, it's >>the cube >>With digital coverage of IBM think 2021 brought to you by IBM Hello welcome back to the cubes coverage of IBM Think 2021. I'm john for your host of the cube had a great conversation here about cloud data, AI and all things. C X O from KPMG is Vinod Swaminathan who's the strategy head of strategy of Ai data and cloud as well as the C. I. O advisory at KPMG you know thanks for coming on the cube. >>My pleasure jOHn thanks for having me. >>So you guys have an interesting perspective, you sit between the business value being created from technology and the clients trying to put it to work um and KPMG impeccable reputation over the years obviously bringing great business value to clients. You guys do that. Um you're in the middle of the hot stuff cloud data and Ai um Ai is great if you have the data and the architecture do that in cloud scale brings so many new good things to the table. Um how is this playing out right now in your mind because we're here at IBM think where the story is transformed, transformation is the innovation. Innovation does set the table for net new capabilities at scale. This seems to be a common thread here. What's your take on the current situation? >>Well, let me start with the fundamental premise that we're seeing playing out with many of our clients and that is, clients are beginning to connect the different silos within their business to better respond to what their customers are asking for. Um you know, we we tend to work with large enterprises, very well established businesses and we're also fortunate to serve the needs of high growth companies as well. So we're in a very unique position as a trusted advisor to both legacy companies transforming and high growth companies looking to drive the transformation in the industry as well. So there are a few things that we're seeing right the first and foremost is responding quickly and effectively to very rapidly changing customer needs. And I think the pandemic really you know put a spotlight on how fast organizations had to pivot and I have to commend a lot of these organizations and doing a phenomenal job, I would argue, spit band aiding and gluing together a response to what their customers expected. Right? So as I look at post pandemic, we're seeing a lot of clients now looking to take stock of things that they did during the pandemic, how they address customer demand to really smooth them out and streamline as a strategy, how they're going to become more customer driven at KPMG. We call this the connected enterprise where you really work effectively across the front, middle and back office in an enterprise to seamlessly address the client. Right? Anything you do in finance really is driven by what your customers want. It's no longer, hey finance sit in the back office, right. Anything you do in marketing is no longer hey I'm doing it just to address the demand side of the equation, right? It's very integral to connect marketing with fulfillment. Right? So we call this the connected enterprise. So that transformation is only possible if customers and our clients are able to effectively leverage cloud from an architectural perspective. And when I say cloud, what we're seeing, smarter clients of ours start to think about is cloud in its entirety. So it's not just the public cloud, it's the cloud architecture, right? The ability to scale up scale out right scale down, right, irrespective of where all of this sits from an infrastructure perspective. So cloud is very critical for becoming that connected enterprise. Uh The data pieces integral, I think the data business today represents trillions of dollars. I think everybody has bought into the fact that data is the new oil and all of that good stuff that we've heard. Uh but it really is a trillion dollar business and it has some unique challenges. So being connected requires, right? That are that an enterprise become very data driven? I think it's hard to escape ai it's everywhere. To the point where we don't even uh we're not even conscious of ai at work, Right? So I think uh five years ago a I was a novel concept today. It's the expectation of customers who interact with big brands that ai is an integral part of how they are being served. Right, So cloud data ai architecture sort of the ingredients if you will. And then cool technology really starts to bring this connected concept together and post pandemic. We're going to start to see a lot of rationalization uh and big investments and moving forward in this trajectory. >>It's interesting cloud data now you, the way you talk about it makes me think about like just the constant of the old Os I stack right? You have infrastructure and cloud, you have data in the middle layer and then A. I. Is that that wonder area where the upside takes advantage of that data? Um Very cool insight. You know. Thanks for sharing that. The question I have for you put the pandemic I want to get your reaction to some conversations I've had in the industry and they tend to go like this. Um When we come out of the pandemic this is like a C X. O. Talking to Ceo. Or C. I. O. Or C. So when we come out of the pandemic we need a growth strategy, we need to be hidden, we need to be on the upswing, okay, not on the downswing or still trying to figure it out. Um And and that's a cool conversation because there's been to use cases that we've identified companies that had no has had a headwind because of the pandemic, either because of business disruption or the second categories, they've had a tail when they had a business opportunity. So the ones that had a headwind, they would retool, they used the pandemic to retool and the ones that had the tailwind would use the pandemic to either bring net new capabilities or or transform and innovate. So either way that's a successful use case. The ones who didn't do anything aren't going to survive much. We know that, but in those two cases they're not mutually exclusive. That's what the smart money's been doing. The smart teams. What's your advice now that we're in that mode where we're coming around the corner? How do companies get on that uptick? What have you guys advise into clients? What are you hearing and what, what's your reaction to that concept? >>Well, I think every company that is going to be on the survivors list post pandemic actually has digitally transformed, um, you know, even if they don't want to acknowledge it right in a lot of different ways. Um, so I think that's here to stay. Um, what I, and I'll give you a simple example, um, you know, I, I belong to a local club, you know, kitchen shut down, you know, no activities. I was amazed that it took them only four days John four days to actually bring a digital reservation system online through their mobile app. So in the past, the mobile app was simply for me to go look at the directory. But now I can do so many more things. Right? And I was talking to my club CI. All right. I mean, really not a C I. O. But you know, it was uh, it was, it was a staff member who was charged with driving the digital transformation. So there you go >>right to consult you, you know. >>Um, but what he talked to me about was fascinating. And this is what we're going to see, right? So first he said, another was so easy to bring some of those, you know, interactive experience type capabilities online to serve our customer base. It made us think, why the hell didn't we do it before? Alright, so, back to your question, I think post pandemic, we're going to see a lot of companies recognizing that low code, no code, right? Cloud AI capabilities are very much within the reach of the average business user, right? In companies like IBM have done a phenomenal job of demystifying the technology and trying to make it much more accessible for the business user. We're going to see continued momentum, right? And adopting these kinds of simple technologies to transform right business processes, customer interaction, so on and so forth. Right? So we we see that coming out of the pandemic, there's no stopping that. I think the second thing we see is a very firm commitment at the leadership level um that you know, stopping or slowing down these kinds of activities is a non starter at the board level. That's a nonstarter at the management committee level, right? Don't come to me saying we need to slow down things. Come to me saying we need to speed up things, right? But that said, we're seeing rationalization, conversations begin to happen and that starts with the strategy, right, tailwind or headwind, irrespective of which side of the equation you fell right in that, in that dynamic, what we're seeing is clients coming back and saying, all right, we know our strategy needs to be different. Let's make sure that we have a strategy that aligns better with um where our customers want to go, where the industry is headed. And let's acknowledge that there are technological capabilities now, but actually turbocharge the execution of the strategy. Technology is not the strategy, it's still connected enterprise thought, How do I serve my customers whose expectations have dramatically changed coming out of the pandemic? And that's why I gave you the club example. I never want to call anybody to make a reservation anymore. I mean even the local hair salon has a queuing system and a reservation system because you know, that's just the way it is. Right? So there are some simple things that have happened on the customer side of uh, you know, the equation, which is forcing a lot of our clients to start, you know, accelerating their digital investments. Um, you know, rather than decelerating, >>it's interesting. That's great insight. I think just to summarize that, I think you're pointing out is the obvious, hey, it works the indifference of the digital to go the next level and see X. O. S and C I. O. S have had, you know, either politics or blockers or just will it work? And I think with the pandemic necessity is the mother of all inventions. You say, hey, we got to get back on business that the economics and the user experience is more than acceptable. It's actually preferred. I think that club example really highlights that expectation change and I >>think that's an interesting architecture discussion right? And I don't mean that technically I think businesses are starting to think about how are they architected, right. And this is where the connected enterprise concept from KPMG is resonating because now you know, we see our clients no longer thinking about finance, sales, marketing, right? And fulfillment right? That's how the architect of their business. Before now they're realizing that they need to sort of put it on its side. Right, I love the cube analogy, I'm going to borrow it, they're flipping the cube on the side and pulling out a whole new business architecture which by the way is enabled and supported by an underlying technology architecture that's very different. Right? So I think businesses are going to get re architected in technology companies like IBM and Red Hot are going to be right there helping clients go through that re architected along with partners like us, >>the script has been flipped, the cube has been turned and I think this was the revelation. The economics are clear. So I gotta ask you, I mean I've always been I've been joking with IBM the president like it, but I've been saying that, you know, business now is software enabled and the operating systems, distributed computing. As you mentioned, these subsystems are part of this fabric and red hat there and operating systems company. Um, so kind of in a good position with what Marvin's doing. If you think about if you look at squint through and connect the dots, I mean you're looking at an underlying operating system that's open and connected to business, it's not just software apps that run something like an ear piece system, it's an business software model for the entire company completely instrumented. This is what hybrid cloud is. Could you, could you take a few minutes to talk about the relationship that you guys have with IBM on how you guys are working together to bring this hybrid cloud vision to their customers into the market. >>So KPMG and IBM go back about 20 plus years long standing relationship. Um in fact, I kid around with many of my fellow partners here at KPMG that IBM is the only relationship that we did not divest off when we went through our let's flip management consulting off from our accounting business, so on and so forth that everybody went through. Right? So very long standing relationship, you know, we're a trusted partner of IBM but we're very different from a lot of the partners that IBM has were business consultants, right? We don't have, you know, we help clients think through their business first before we get into the technology implementation. So I don't have armies of IBM certified engineers sitting on the bench looking for work to do. It's actually the other way around. Right? So it's been a great marriage when IBM has phenomenal technology in this case, you know, they have been leaders in AI, we've got an AI based relationship now going back five years, um you know, where we consumed Watson proved to ourselves and the world that it can be done very innovatively supporting business transformation. And now we're able to together with IBM effectively have that conversation with clients, right? Because we're client number zero, uh we're big into a hybrid, multi cloud, um you know, we're big red hat customers. Uh you know, we use red hat in our own modernization of several different workloads. So our relationship with IBM is very strong, were a good supplier to them as well, so we help them with their strategy and go to market as well. So an interesting sort of relationship. Um look when we work with clients, we typically tend to, you know, take a trusted advisor role with clients. Our brand speaks to the trust that we're able to bring when we talk to clients. Uh I kid around um you know, when you're going through a transformation, you probably want the town skeptic holding your hand. That's us, right? We're very risk averse. We like working with clients who you know, kind of want that, you know, critical look when they're investing in technology driven transformation. Um you know, some of the things that IBM has done is pretty phenomenal. Right? So for example, I don't see um you know, I don't see a lot of providers out there who give clients the kind of options that IBM gives with their multi cloud capabilities. Right? So show me conversational ai capability that can run on private cloud, that can run on google amazon IBM and a whole bunch of other cloud providers. Right, So I think as IBM invests in that open right philosophy and obviously the Red hat acquisition only further enhances that. Right, um it's a great opportunity for us to be able to take very powerful KPMG value propositions um you know, enabled by this kind of IBM technology. Right, so that's how we tend to go to market. Um one of the solutions were offering with IBM is called the KPMG data mesh. It's built on IBM cloud pack for data, which is enabled by red hats open shift and it's a very innovative solution in the marketplace that fundamentally asked the question to clients, why are you spending inordinate amount of time and resources moving data around in order to become data driven? Uh it just amazes me john how much money is being thrown at, you know, moving data around, particularly as you get into this complex hybrid, multi cloud world. Right. How many times am I going to move data from, you know, a mainframe database into my, you know, cloud repository before I can start doing uh, you know, real higher value work. Right, So KPMG data mesh enabled by the IBM cloud back, the data says, hey, legal data, wherever it is. You know, we can take up to 30 of costs out and really get you on this journey to become data driven without spending the first nine months of every project building a data warehouse or building an expensive data where data lake. Right? Because all of those, frankly our 20th century mindset, right? So if I can leave the data where it is your favorite terminology virtually is the data and really focus on what do I do with the data as opposed to you know, how do I move the data? Right. It really starts to change the mindset around becoming data driven. Right, so that's a great example of a solution where we've married our value proposition to clients around connected and trusted and leveraged IBM technology right? In a hybrid multi cloud >>but no great insight. Love the focus. Hybrid cloud, congratulations on your KPMG mesh solution. Their cloud mesh awesome. Taking advantage of the IBM work and love your perspective on the industry. I think you you called it right. I think that's a great perspective. That's the way we're on big transformation innovation wave. Thanks for coming on the key. Appreciate it. >>Absolutely my pleasure. Thanks for having me have a good day. >>Okay, Cube coverage of IBM think 2021. I'm John for your host of the Cube. Thanks for watching.