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Unpacking IBM's Summer 2021 Announcement | CUBEconversation


 

(upbeat music) >> There are many constants in the storage business, relentlessly declining costs per bit. Innovations that perpetually battle the laws of physics, a seemingly endless flow of venture capital, very intense competition. And there's one other constant in the storage industry, Eric Herzog. And he joins us today in this CUBE video exclusive to talk about IBM's recent storage announcements. Eric, welcome back to theCUBE. Great to see you, my friend. >> Great Dave, thank you very much. Of course, IBM always loves to participate with theCUBE and everything you guys do. Thank you very much for inviting us to come today. >> Really our pleasure. So we're going to cover a lot of ground. IBM Storage made a number of announcements this month around data resilience. You've got a new as a service model. You've got performance enhancements. Eric, can you give us, give us the top line summary of the hard news? >> Yeah. Top line. IBM is enhancing data and cyber resiliency across all non mainframe platforms. We already have it on the mainframe of course, and we're changing CapEx to OpEx with our storage as a service. Those are the key takeaways and the hot ticket items from an end user perspective. >> So maybe we could start with sort of the cyber piece. I mean, wow. I mean the last 18 months have been incredible and you're just seeing, you know, new levels of threats. The work from home pivot has created greater exposure. Organizations are kind of rethinking hybrid. You're seeing the ascendancy of some of the sort of hot cyber startups, but, but you're also seeing the, not only of the attack vectors winded, but the, the techniques are different. You know, threat hunting has become much more important. Your responses to threats. You have to be really careful the whole ransomware thing. So what are some of the big trends that you guys are seeing that are kind of informing how you approach the market? >> Well, first of all, it's gotten a lot worse. In fact, Fortune magazine just released the Fortune 500 a couple of weeks ago, and they had a survey that's public of CEOs, and they said, "What's the number one threat to your business? With no list just what's the number one threat?" Cyber security was number one 66% of the Fortune 500 Chief Executive Officers. Not CIOs not CTOs, but literally the CEOs of the biggest companies in the world. However, it's not just big companies. It hits the mid size, the small companies, everyone is open now to cyber threats and cyber attacks. >> Yeah. So for sure. And it's (chuckles) across the board. Let's talk about your solution, the announcement that you made here. Safeguard Copy, I think is what the branding is. >> Yeah. So what we've done is we've got a number of different technologies within our storage portfolio. For example, with our Spectrum Protect product, we can see anomalous pattern detection and backup data sets. Why would that matter? If I am going to hold theCUBE for ransom, if I don't get control of your secondary storage, snaps, replicas, and backups, you can just essentially say, I'm not paying you. You could just do a recovery, right? So we have anomalous protection there. We see encryption, we encrypt at rest with no performance penalty with our FlashSystem's family. We do air gapping. And in case of safeguarded copy, it's a form of air gapping. So we see physical air gapping with tape. logical air gapping, but to a remote location with snaps or replicas to your Cloud provider, and then local logical on-prem, which is what safeguarded copy does. We've had this technology for many years now on the mainframe platform. And we brought it down to the non mainframe environments, Linux, UNIX, and the Windows Server world by putting safeguarded copy on our FlashSystem's portfolio. >> So, okay. So part of the strategy is air gapping. So you're taking a copy, your air gapping it. You probably, you probably take those snaps, you know, at different intervals, you mix that up, et cetera. How do you manage the copies? How do you ensure if I have to do a recovery that you've got kind of a consistent data set? >> Yeah. So a couple things, first of all, we can create on a single FlashSystem array the full array up to 15,000 immutable copies, essentially they're weren't, you can't delete them, you can't change them. On a per volume basis, you can have 255. This is all managed with our storage copy manager, which can automate the entire process. Creation, deletion, frequency, and even recovery mode. So for example, I could have volume one and volume one perhaps I need to make immutable copies every four hours, while at 255 divided by four a day, I can go for many months and still be making those immutable copies. But with our Copy Services Manager, you can set up to be only 30 days, 60 days, you can set the frequency and once you set it up, it's all automated. And you can even integrate with IBM's QRadar, which is a threat detection and breach software from the security division of IBM. And when certain threats hit, it can actually automatically kick off a safeguarded copy. So what we do is make sure you've got that incredibly rapid recovery. And in fact, you can get air gapping, remotely. We have this on the main frame and a number of large global Fortune 500's actually do double air gapping, local logical, right? So they can do recovery in just a couple hours if they have an attack. And then they take that local logical and either go remote logical. Okay. Which gives them a second level of protection, or they'll go out to tape. So you can use this in a myriad of ways. You can have multiple protection. We even, by the way Dave, have three separate different admin levels. So you can have three different types of admins. One admin can't delete, one admin can. So that way you're also safe from what I'll call industrial espionage. So you can never know if someone's going to be stealing stuff from inside with multiple administrative capabilities, it makes it more difficult for someone to steal your data and then sell it to somebody. >> So, okay. Yeah, right. Because immutable is sort of, well, you're saying that you can set it up so that only one admin has control over that, is that right? If you want it... >> There's three, there's three admins with different levels of control. >> Right. >> And the whole point of having a three admins with different levels of control, is you have that extra security from an internal IT perspective versus one person, again, think of the old war movies, you know, nuclear war movies. Thank God it's never happened. Where two guys turn the key. So you've got some protection, we've got multiple admin level to do that as well. So it's a great solution with the air gapping. It's rapid recovery because it's local, but it is fully logically air gapped separated from the host. It's immutable, it's WORM, Write Once, Read Many can't delete can't change. Can't do anything. And you can automate all the management with our Copy Services Manager software that will work with safeguard copy. >> You, you talked about earlier, you could detect anomalous behavior. So, so presumably this can help with, with detecting threats, is that? >> Well, that's what our spectrum protect product does. My key point was we have all levels of data resiliency across the whole portfolio, whether it be encrypting data at rest, with our VTLs, we can encrypt in-flight. We have safeguarded copy on the mainframe, safeguarded copy on FlashSystems, any type of storage, including our competitor storage. You could air gap it to tape, right? With our spectrum virtualized software in our SAN Volume Controller, you could actually air gap out to a Cloud for 500 arrays that aren't even ours. So what we've done is put in a huge set of data and cyber resiliency across the portfolio. One thing that I've noticed, Dave, that's really strange. Storage is intrinsic to every data center, whether you're big, medium, or small. And when most people think about a cybersecurity strategy from a corporate perspective, they usually don't even think about storage. I've been shocked, but I've been in meetings with CEOs and VPs and they said, "oh, you're right, storage is, is a risk." I don't know why they don't think of it. And clearly many of the security channel partners, right? You have channel that are very focused on security and security consultants, they often don't think about the storage gaps. So we're trying to make sure, A, we've got broad coverage, primary storage, secondary storage, backup, you know, all kinds of things that we can do. And we make sure that we're talking to the end users, as well as the channel to realize that if you don't have data resilience storage, you do not have a corporate cybersecurity strategy because you just left out the storage part. >> Right on. Eric, are you seeing any use case patterns emerge in the customer base? >> Well, the main use case is prioritizing workloads. Obviously, as you do the immutable copies, you chew up capacity. Right now there's a good reason to do that. So you've got these immutable copies, but what they're doing is prioritizing workloads. What are the workloads? I absolutely have to have up and going rapidly. What are other workloads that are super important, but I could do maybe remote logical air gapping? What ones can I put out to tape? Where I have a logical, where I have a true physical air gap. But of course tape can take a long recovery time. So they're prioritizing their applications, workloads and use case to figure out what they need to have a safeguarded copy with what they could do. And by the way, they're trying to do that as well. You know, with our FlashSystem products, we could encrypt data at rest with no performance penalty. So if you were getting, you know, 30,000 database records and they were taken, you know, 10 seconds for sake of argument, when you encrypt, normally you slow that down. Well, guess what, when you encrypt with our FlashSystem product. So in fact, you know, it's interesting Dave, we have a comprehensive and free cyber resiliency assessment, no charge to the end-user, no charge to a business partner if they want to engage with us. And we will look at based on the NIST framework, any gaps. So for example, if theCUBE said, these five databases are most critical databases, then part of our cyber resilience assess and say, "ah, well, we noticed that you're not encrypting those. Why are you not encrypting those?" And by the way, that cyber resilience assessment works not only for IBM storage, but any storage estate they've got. So if they're homogenous, we can evaluate that if they're heterogeneous in their storage estate would evaluate that, and it is vendor agnostic and conforms to the NIST framework, which of course is adopted all over the world. And it's a great thing for people to get free, no obligation. You don't have to buy a single thing from IBM. It's just a free assessment of their storage and what cyber security exposure they have in their storage estate. And that's a free thing that we offer that includes safeguarded copy, encryption, air gapping, all the various functionality. And we'll say, "why are you not encrypting? Why are you not air gapping?" That if it's that important, "what, why are you leaving these things exposed?" So that's what our free cyber resilience assessment does. >> Got to love those freebies take advantage of those for sure. A lot of, a lot of organizations will charge big bucks for those. You know, maybe not ridiculously huge bucks, but you're talking tens of thousands. Sometimes you'll get up to hundreds of thousands of dollars for that type of type of assessment. So that's, you've got to take advantage of that if you're a customer out there. You know, I, I wanted to ask you about just kind of shift topics here and get into the, as a service piece of it. So you guys announced your, your as a service for storage, a lot of people have also done that. What do we need to know about the IBM Solution? And what's different from the others, maybe two part question, but what's the first part. What do we need to know? >> A couple of thing is, from an overall strategy perspective, you don't buy storage. It's a full OpEx model. IBM retains legal title. We own it. We'll do the software upgrades as needed. We may even go ahead and swap the physical system out. You buy an SLA, a tier if you will. You buy capacity, performance, we own it. So let's take an easy one. Our tier two, we give you our worst case performance at 2,250 IOPS per terabyte. Our competitors by the way, when you look at their contracts and look what they're putting out there, they will give you their best case number. So if they're two is 2,250, that's the best case. With us it's our worst case, which means if your applications or workloads get 4,000 IOPS per terabyte, it's free. We don't charge you for that. We give you the worst case scenario and our numbers are higher than our competition. So we make sure that we're differentiated true OpEx model. It's not a modified Lease model. So it's truly converts CapEx into operational expense. We have a base as everybody does, but we have a variable. And guess what? There's the base price and the variable price are the same. So if you don't use the variable, we don't charge you. We bill you for 1/4 in arrears, every feature function that's on our FlashSystem technology such as safeguarded copy, which we just talked about. AI based tiering, data at rest encryption with no performance penalty, data in compression with no performance, all those features you get, all of them, all we're doing is giving you an option. We still let you buy CapEx. We will let you lease with IBM Global Financial Services. And guess what? You could do a full OpEx model. The technology though, our flash core modules, our spectrum virtualized software is all the same. So it's all the same feature function. It's not some sort of stripped down model. We even offer Dave, 100% availability option. We give Six Nines of availability as a default, several of the competitor, which is only five minutes and 26 seconds of downtime, several of our competitors, guess what they give? Fournines. If you want five or six, you got to pay for it. We just give you six as a default differentiator, but then we're the only vendor to offer 100% availability guarantee. Now that is an option. It's the one option. But since we're already at Six Nines, when our competitors are at Four or Five Nines, we already have better availability with our storage as a service than the competition does. >> So let me just make this, make sure I'm clear on this. So you got Six Nines as part of the service. That's >> Absolutely >> Fundamental. And I get, I can pay up for 100% availability option. And, >> Yes you can. >> So what does that, what does that mean? Practically? You're putting in redundancies and, >> Right, right. So we have a technology known as HyperSwap. We have several public references by the way, at ibm.com. We've been shipping HyperSwap on both the mainframe, probably eight or nine years now. We brought it to our FlashSystem product probably five years ago. As I mentioned, we've got public references. You don't pay for the software by the way, you do have to have a dual node cluster. And HyperSwap allows you to do that. But you can do that as a service. You can buy it. You can do as CapEx, right? When you need the additional FlashSystem to go with it again, the software is free. So you're not to pay for the software. You just have to pay for the additional system level componentry, but you can do that as a service and have it completely be an OpEx model as well. We even assign a technical account manager to every account. Every account gets a technical account manager. If you will, concierge service comes with every OpEx version of our storage as a service. >> So what does that mean? What does that concierge do? Just paying attention to (indistinct) >> Concierge service will do a quarterly, a quarterly review with you. So let's say theCUBE bought 10,000 other analyst firms in the industry. You're now the behemoth. And you at theCUBE are using IBM storage as a service. You call up your technical account manager to say, "Guess what? We just bought these companies. We're going to convert them all to storage as a service, A, we need a higher tier, you could upgrade the tier B, we have a one-year contract, but you know what we'd like to extend it to two, C, we think we need more capacity." You tell your technical account manager, they'll take care of all of that for you, as well as giving you best practices. For example, if you decide you want to do safeguarded copy, which you can do, because it's built into our spectrum virtualized software, which is part of our storage as a service, we can give you best practices on that he would tell you, or she would tell you about our integration with our security visions, QRadar. So those are various best practices. So the technical account manager makes sure the software is always up to date, right? All the little things that you would have to do yourself if you own it, we take care of, because we legally own it, which is allow you to buy it as a service. So it is a true OpEx model from a financial perspective. >> In the term of the contracts are what? One, two and three years. >> One to five. >> Yeah. Okay. >> If you don't renew and you don't cancel, we'll automatically re up you at the exact tier you're at, at the exact same price. Several of our competitors, by the way, if you do that, they actually charge you a premium until you sign a contract. We do not. So if you have a contract based on tier two, right? We go buy SLA tier one, tier two, tier three. So if I have a tier two contract at theCUBE, and you forgot to get the contract done at the end of two years, but you still want it, you can go for the next 2/4. I mean, well our business partner as I should say, "Dave, don't you want to sign a contract, you said you like it." Obviously you would, but we will let you stay. You just say, now I want to keep it without a contract. And we don't charge your premium. Our competitors if you don't have a contract, they charge your premium. If you keep it installed without putting a contract in place. So little things like that clearly differentiate what we do. We don't charge a premium. If you go above the base. One of the competitors, in fact, when you go into the variable space, okay? And by the way, we provide 50% extra capacity. We over-provision. The other competitors usually do 25%. We do 50%. No charge, is just part of the service. So the other vendors, if you go into the variable space, they raised the price. So if it's $5, you know, for X capacity and you go into the, which is your base, and then you go above that, they charge you $7 and 50 cents. We don't. It's $5 at the base and $5 at the variable. Now obviously your variable can be very big or very small, but whatever the variable is, we charge you. But we do not charge you an a bigger price. Couple of competitors when you go into the variable world, they charge you more. Guess what it gets you to do, raise your base capacity. (Eric laughs) >> Yeah. I mean, that's, that should, the math should be the opposite of that, in my view. If you make a commitment to a vendor, say, okay, I'm going to commit to X. You have a nice chart on this, actually in your, in your deck. If I'm going to commit to X, and then I'm going to add on, I would think the add on price per bit should be at the same or lower. It shouldn't be higher. Right? And I get, I get what you're saying there. They're forcing you to jack up the base, but then you're taking all the risk. That's not a shared risk model. I get... >> And that's why we made sure that we don't do that. In fact, Dave, you can, you know, the fact that we don't charge you a premium if you go beyond your contract period and say, "I still wanted to do it, but I haven't done the contract yet." The other guys charge you a premium, if you go beyond your contract period. We don't do that either. So we try to be end-user friendly, customer friendly, and we've also factored in our business partners can participate in this program. At least one of our competitors came out with a program and guess what? Partners could not participate. It was all direct. And that company by happens to have about 80% of their business through the channel and their partners were basically cut out of the model, which by the way, is what a lot of Cloud providers had done in the past as well. So it was not a channel friendly model, we're channel friendly, we're end user-friendly, it's all about ease of use. In fact, when you need more capacity, it takes about 10 minutes to get the new capacity up and going, that's it? >> How long does it take to set up? How long does it take to set up initially? And how long does it take to get new capacity? >> So, first of all, we deploy either in a Colo facility that you've contracted with, including Equinix, Equinix, is part of our press release, or we install on your site. So the technical account managers is assigned, he would call up theCUBE and say, "When is it okay for us to come install the storage?" We install it. You don't install anything. You just say, here's your space. Go ahead and install. We do the installation. You then of course do the normal rationing of the capacity to this goes to this Oracle, this goes to SAP. This goes to Mongo or Cassandra, right? You do that part, but we install it. We get it up and going. We get it turned on. We hook it up to your switching infrastructure. If you've got switching infrastructure, we do all of that. And then when you need more capacity, we use our storage insights pro which automatically monitors capacity, performance, and potential tech support problems. So we give you 50% extra, right? If you drop that to 25%, so you now don't have 50% extra anymore, you only have 25% extra, we'll, the technical account manager would call you and say, "Dave, do you know that we'd like to come install extra capacity at no charge to get you back up to that 50% margin?" So we always call because it's on your site or in your Colo facility, right? We own the asset, but we set it up and you know, it takes a week or two, whatever it takes to ship to whatever location. Now by the way, our storage as a service for 2021 will be in North America and Europe only, we are really expanding our storage as a service outside into Asia and into Latin America, et cetera, but not until 2022. So we'll start out with North America and Europe first. >> So I presume part of that is figuring out just the compensation models right? And so how, how did you solve that? I mean, you can't, you know, you don't seem to be struggling with that. Like some do. I think there's some people dipping their toes in the water. Was that because, you know, IBM's got experience with like SAS pricing or how were you thinking about that and how did you deal with kind of the internal (indistinct) >> Sure. So, first of all, we've had for several years, our storage utility model. >> Right? >> Our storage utility model has been sort of a hybrid part CapEx and part OpEx. So first of all, we were already halfway there to an OpEx model with our storage utility model that's item, number one. It also gave us the experience of the billing. So for example, we bill you for a full quarter. We don't send you a monthly bill. We send you a quarterly bill. And guess what, we always bill you in arrears. So for example, since theCUBE is going to be a customer this quarter, we will send you a bill for this quarter in October for the October quarter, we'll send you a bill for that quarter in January. Okay. And if it goes up, it goes up. If it goes down, it goes down. And if you don't use any variable, there's no bill. Because what we do is the base you pay for once a year, the variable you pay for by on a quarterly basis. So if you, if you are within the base, we don't send you a bill at all because there's no bill. You didn't go into the variable capacity area at all. >> I love that. >> When you have a variable It can go up and down. >> Is that unique to some, do some competitors try to charge you up front? Like if it's a one-year term. (Dave laughs) >> Everbody charges, everybody builds yearly on the base capacity. Pretty much everyone does that. >> Okay, so upfront you pay for the base? Okay. >> Right. And the variable can be zero. If you really only use the base, then there is no variable. We only bill for it's a pay for what you use model. So if you don't use any of the variable, we never charge you for variable. Now, you know, because you guys have written about it, storage grows exponentially. So the odds of them ending up needing some of the variable is moderately high. The other thing we've done is we didn't just look at what we've done with our storage utility model, but we actually looked at Cloud providers. And in fact, not only IBM storage, but almost every of our competitors does a comparison to Cloud pricing. And when you do apples to apples, Cloud vendors are more expensive than storage as a services, not just from us, but pretty much for a moment. So let's take an example. We're Six Nines by default. Okay. So as you know, most Cloud providers provide three or Fournines as the default. They'll let you get five or Six Nines, but guess what? They charge you extra. So item number one. Second thing, performance, as you know, the performance of Cloud storage is usually very weak, but you can make it faster if you want to. They charge extra for that. We're sitting at 2,250 terabytes per IOPS, excuse me, per terabytes. That's incredible performance If you've got 100 terabytes, okay. And if your applications and workloads and that's the worst case, by the way, which differentiates from our competitors who usually quote the best case, we quote you the worst case and our worst case by the way, is almost always higher than their best cases in each of the tiers. So at their middle tier, our worst case is usually better than their best case. But the point is, if you get 4,000 IOPS per terabyte and you're on a tier two contract, it's a two-tier contract. And in fact, let's say that theCUBE has a five-year deal. And we base this on our FlashSystem technology. And so let's say for tier two, for sake of argument, FlashSystem, 7,200. We come out two years after theCUBE has it installed with the FlashSystem, 7,400. And let's say the FlashSystem, 7,400, won't deliver a 2,250 IOPS per terabyte, but 5,000, if we choose to replace it, 'cause remember it's our physical property. We own it. If we choose to replace that 7,200 with a 7,400, and now you get 5,000 IOPS per terabyte, it's free. You signed a tier two contract for five years. So two years later, if we decide to put a different physical system there and it's faster, or has four more software features, we don't charge you for any of that. You signed an SLA for tier two. >> You haven't Paid for capacity, right? All right. >> You are paying for the capacity (indistinct) performance, you don't pay for that. If we swap it out and the, the array is physically faster, and has got five new software features. You pay nothing, you pay what your original contract was based on the capacity. >> What I'm saying is you're learning from the Cloud providers 'cause you are a Cloud provider. But you know, a lot of the Cloud providers always sort of talk about how they lower prices. They lower prices, but you know, well, you worked at storage companies your whole life and they, they lower prices on a regular basis because they 'cause the cost of the curve. And so. >> Right. The cost of storage to Cloud, I mean, the average price decline in the storage industry is between 15 and 25%, depending on the year, every single year. >> Right. >> As, you know, you used to be with one of those analysts firms that used to track it by the numbers. So you've seen the numbers. >> For sure. Absolutely. >> On average it drops 15 to 25% every year. >> So, what's driving this then? If it's, it's not necessarily, is it the shift from, from CapEx to OPEX? Is it just a more convenient model than on a Cloud like model? How do you see that? >> So what's happened in IT overall is of course it started with people like salesforce.com. Well, over 10 years ago, and of course it's swept the software industry software as a service. So once that happened, then you now see infrastructure as a service, servers, switches, storage, and an IBM with our storage as a service, we're providing that storage capability. So that as a service model, getting off of the traditional licensing in the software world, which still is out there, but it's mostly now is mostly software as a service has now moved into the infrastructure space. From our perspective, we are giving our business partners and our customers, the choice. You still want to buy it. No problem. You want to lease it? No problem. You want a full OpEx model. No problem. So for us, we're able to offer any of the three options. The, as a service model that started in software has moved now into the systems world. So people want to change often that CapEx into OpEx, we can even see Global Fortune 500s where one division is doing something and a different division might do something else, or they might do it different by geography. In a certain geography, they buy our FlashSystem products and other geographies they lease them. And in other geographies it's, as a service. We are delivering the same feature, function, benefit from a performance availability software function. We just give them a different way to procure. Do you want CapEx you want leasing or OpEx you pick what you want, we'll deliver the right solution for you. >> So, you got the optionality. And that's great. You've thought that out, but, but the reason I'm asking Eric, is I'm trying to figure out this is not just for you for everybody. Is this a check-off item or is this going to be the prevailing way in which storage is consumed? So if you had, if you had a guess, let's go far out. So we're not making any near-term forecast, but end of the decade, is this going to be the dominant model or is it going to be, you know, one of the few. >> It will be one of a few, but it'll be a big few. It'll be the big, one of the biggest. So for sake of argument, there we'll still be CapEx, they'll still be OpEx they'll still be, or there will be OpEx and they're still be leasing, but I will bet you, you know, at the end of this decade, it'll be 40 to 50% will be on the OpEx model. And the other two will have the other 50%. I don't think it's going to move to everything 'cause remember, it's a little easier during the software world. In the system world, you've got to put the storage, the servers, or the networking on the prem, right? Otherwise you're not truly, you know, you got to make it a true OpEx model. There's legal restrictions. You have to make it OpEx, if not, then, you know, based on the a country's practice, depending on the country, you're in, they could say, "Well, no, you really bought that. It's not really a service model." So there's legal constraints that the software worldwise easier to get through and easier to get to bypass. Right? So, and remember, now everything is software as a service, but go back when salesforce.com was started, everyone in the enterprise was doing ELAs and all the small companies were buying some sort of contract, right, or buying by the (indistinct) basis. It took a while for that to change. Now, obviously the predominant model is software as a service, but I would argue given when salesforce.com started, which was, you know, 2007 or so, it took a good 10 years for software as a service to become the dominant level. So I think A, it won't take 10 full years because the software world has blazed a trail now for the systems world. But I do think you'll see, right. We're sitting here know halfway through 2021, that you're going to have a huge percentage. Like I said, the dominant percentage will be OpEx, but the other two will still be there as well. >> Right. >> By the way, you know in software, almost, no one's doing ELAs these days, right? A few people still do, but it's very rare, right? It's all software as a service. So we see that over time doing the same thing in the, in the infrastructure side, but we do think it will be slower. And we'll, we'll offer all three as, as long as customers want it. >> I think you're right. I think it's going to be mixed. Like, do I care more about my income statement or my balance sheet and the different companies or individual different divisions are going to have different requirements. Eric, you got to leave it there. Thanks much for your time and taking us through this announcement. Always great to see you. >> Great. Thank you very much. We really appreciate our time with theCUBE. >> All right. Thank you for watching this CUBE conversation. This is Dave Vellante and we'll see you next time. (upbeat music)

Published Date : Jul 29 2021

SUMMARY :

in the storage business, and everything you guys do. Eric, can you give us, and the hot ticket items how you approach the market? of the Fortune 500 Chief the announcement that you made here. you can just essentially say, So part of the strategy is air gapping. So you can use this in a myriad of ways. If you want it... different levels of control. And you can automate all the management you could detect anomalous behavior. And clearly many of the security are you seeing any use So in fact, you know, So you guys announced your, So if you don't use the So you got Six Nines And I get, And HyperSwap allows you to do that. we can give you best practices on that In the term of the contracts are what? Yeah. So the other vendors, if you If you make a commitment if you go beyond your So we give you 50% extra, right? and how did you deal with kind of the So, first of all, we've the variable you pay for When you have a variable to charge you up front? on the base capacity. Okay, so upfront you pay for the base? So if you don't use any of the variable, You haven't Paid for capacity, right? you pay what your original contract was But you know, decline in the storage industry As, you know, For sure. 15 to 25% every year. Do you want CapEx you want leasing or OpEx So if you had, if not, then, you know, By the way, you know in software, Eric, you got to leave it there. Thank you very much. Thank you for watching

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Dominique Dubois & Paul Pappas, IBM | IBM Think 2021


 

>> (lively music) >> Narrator: From around the globe it's theCUBE, with digital coverage of IBM Think 2021. Brought to you by IBM. >> Welcome to theCUBE's coverage of IBM Think 2021, the digital event experience. I'm your host, Lisa Martin. I've got an alumni joining me and a brand new guest to the CUBE please welcome Paul Papas, the Global Managing Partner, for IBM Global Business Services, this is transformation services. Paul, welcome back to the virtual CUBE. >> Thanks Lisa great to be here with you today. And Dominique Dubois is here as well. She is the Global Strategy and Offerings Leader in business transformation services or BTS at IBM. Dominique, welcome to the program. >> Thanks Lisa, great to be here. So, we're going to be talking about accelerating business transformation with intelligent workflows. We're going to break through all that, but Paul we're going to start with you. Since we last got together with IBM, a lot has changed so much transformation, so much acceleration of transformation. Talk to me from your perspective, how have you seen the way that businesses running change and what some of the changes in the future are going to be? >> Well, you hit on two key words there Lisa and thanks so much for that question. Two key words that you hit on were change and acceleration. And that's exactly what we see. We were seeing this before the pandemic and if anything, with the pandemic did when things started started kind of spreading around the world late or early last year, around January, February timeframe we saw that word acceleration really take hold. Every one of our clients were looking for new ways to accelerate the change that they had already planned to adapt to this new, this new normal or this new abnormal, depending on how you view it. In fact, we did a study recently, an IBV study that's our Institute of Business Value and found that six out of 10 organizations were accelerating all of their transformation initiatives they had already planned. And that's exactly what we're seeing happening right now in all parts of the world and across all industries. This acceleration to transform. >> So, one of the things that we've talked about for years, Paul, before the pandemic was even a thing, is that there was a lot of perceived technical barriers in terms of like the tech maturity for organizations and employees being opposed to change. People obviously it can be a challenge. They're used to doing things the way they are. But as you just said, in that IBV survey, nearly 60% of businesses say we have to accelerate our transformation due to COVID, probably initially to survive and then thrive. Talk to me about some of those, those barriers that were there a little over a year ago and how businesses 60 plus percent of them have moved those out of the way. >> You know at IBM we've got a 109 year history of being a technology innovation company. And the rate of pace of technical change is always increasing. It's something that we love and that we're comfortable with. But the rate and pace of change is always unsettling. And there's always a human element for change. And the human element is always the rate, the rate setter in terms of the amount of change that you can have in an organization. Our former chairman Ginni Rometty, used to say that growth and comfort cannot co-exist. And it's so true because changing is uncomfortable. It's unsettling. It can be, it can be nerve-racking. It can instill fear and fear can be paralyzing in terms of driving change. And what we also see is there's a disconnect, a lot of times and that IBV study that I was referring to before, we saw results coming back where 78% of executives feel that they have provided the training and enablement to help their employees transform to new required skills and new ways of working but only half of the people surveyed felt the same way. Similarly, we saw a disconnect in terms of companies feeling that they're providing the right level of health and wellness support during the pandemic. And only half of the employees responded back they feel that they're getting that level of support. So, the people change aspect of doing a transformation or adapting to new circumstances is always the most critical component and always the hardest component. And when we talk about helping our clients do that in IBM that's our service as organization. That's the organization that Dominique Dubois is representing here today. I'm responsible for business transformation services within our organization. We help our clients adapt using new technologies, transforming the way they work, but also addressing the people change elements that could be so difficult and hitting them head on so that they can make sure that they can survive and thrive in a meaningful and lasting way in this new world. >> One of the hardest things is that cultural transformation regardless of a pandemic. So, I can't imagine I'd love to get one more thing, Paul from you before we head over to Dominique. IBM is on 109 year old organization. Talk to me about the IBM pledge. This is something that came up last year, huge organization massive changes last year, not just the work from home that the mental concerns and issues that people had. What did IBM do like as a grassroots effort that went viral? >> Yeah, so, it's really great. So, when the pandemic started, we all have to shift it, We all have to shift to working from home. And as you mentioned, IBM's 109 year old company, we have over 300,000 employees working in 170 countries. So, we had to move this entire workforce. It's 370,000 humans to working in a new way that many of which have never done before. And when we started experiencing, the minute we did that, within a few weeks, my team and I were talking Dominique is on my team and we were having conversations where we were feeling really exhausted. Just a few weeks into this and it was because we were constantly on Webex, we were constantly connected and we're all used to working really hard. We travel a lot, we're always with our clients. So, it wasn't that, you have a team that is adapting to like working more hours or longer hours, but this was fundamentally different. And we saw that with schools shutting down and lock downs happening in different of the world the home life balance was getting immediately difficult to impossible to deal with. We have people that are taking care of elderly parents, people that are homeschooling children, other personal life situations that everyone had to navigate in the middle of a pandemic locked at home with different restrictions on when you can go out and get things done. So, we got together as a group and we just started talking about how can we help? How can we help make life just a little bit easier for all of our people? And we started writing down some things that we would, we would commit to doing with each other. How we would address each other. And when that gave birth to was what we call the IBM Work From Home Pledge. And it's a set of principles, all grounded in the belief that, if we act this way, we might just be able to make life just a little bit easier for each other and it's grounded in empathy. And there are parts of the Plex that are pledging to be kind. Recognizing that in this new digital world that we're showing up on camera inside of everyone's home. We're guests in each other's homes. So, let's make sure that we act appropriately as guests at each other's home. So, if children run into the frame during the middle of a meeting or dog started barking during the middle of a meeting, just roll with it. Don't call out attention to it. Don't make people feel self-conscious about it. Pledged the support so your fellow IBM by making time for personal needs. So, if someone has to, do homeschooling in the middle of the day, like Dominique's got triplets she's got to do homeschooling in the middle of the day. Block that time off and we will respect that time on your calendar. And just work around it and just deal with it. There are other things like respecting that camera ready time. As someone who's now been on camera every day it feels like for the last 14 months we want to respect the time that people when they have their cameras off. And not pressure them to put their cameras on saying things like, Hey, I can't see you. There's no reason to add more pressure to everyone's life, if someone's camera's off, it's all for a reason. And then other things like pledging to checking on each other, pledging to set boundaries and tend to our own self-care. So, we published that as a group, we just again and we put it on a Slack channel. So it's kind of our communication method inside the company. It was just intended to be for my organization but it started going viral and tens of thousands of IBM members started taking, started taking the pledge and ultimately caught the attention of our CEO and he loved it, shared it with his leadership team, which I'm a part of. And then also then went on LinkedIn and publicly took the pledge as well. Which then also got more excitement and interaction with other companies as well. So, grassroots effort all grounded in showing empathy and helping to make life just a little bit easier for everyone. >> So important, I'm going to look that up and I'm going to tell you as a person who speaks with many tech companies a week. A lot of businesses could take a lead from that and it gets really important and we are inviting each other into our homes and I see you're a big Broadway fan I'll have to ask you that after we wrap (giggles) Dominique I don't know how you're doing any of this with triplets. I only have two dogs (Dominique laughs) but I'd love to know this sense of urgency, that is everywhere you're living it. Paul talked about it with respect to the acceleration of transformation. How from your lens is IBM and IBM helping customers address the urgency, the need to pivot, the need to accelerate, the need to survive and thrive with respect to digital transformation actually getting it done? >> Right, thanks Lisa, so true our clients are really needing to and ready to move with haste. That that sense of urgency can be felt I think across every country, every market, every industry. And so we're really helping our clients accelerate their digital transformations and we do that through something that we call intelligent workflows. And so workflows in and of themselves are basically how organizations get work done. But intelligent workflows are how we infuse; predictive properties, automation, transparency, agility, end to end across a workflow. So, pulling those processes together so they're not solid anymore and infusing. So, simply put we bring intelligent workflows to our clients and it fundamentally reinvents how they're getting work done from a digital perspective, from a predictive perspective, from a transparency perspective. And I think what really stands apart when we deliver this with our clients in partnership with our clients is how it not only delivers value to the bottom line, to the top line it also actually delivers greater value to their employees, to the customers, to the partner to their broader ecosystem. And intelligent workflows are really made up of three core elements. The first is around better utilizing data. So, aggregating, analyzing, getting deeper insight out of data, and then using that insight not just for employees to make better decisions, but actually to support for emerging technologies to leverage. So we talked about AI, automation, IOT, blockchain, all of these technologies require vast amounts of data. And what we're able to bring both on the internal and external source from a data perspective really underpins what these emerging technologies can do. And then the third area is skills. Our skills that we bring to the table, but also our clients deep, deep expertise, partner expertise, expertise from the ecosystem at large and pulling all of that together, is how we're really able to help our clients accelerate their digital transformations because we're helping them shift, from a set of siloed static processes to an end-to-end workflow. We're helping them make fewer predictions based on the past historical data and actually taking more real-time action with real time insights. So, it really is a fundamental shift and how your work is getting done to really being able to provide that emerging technologies, data, deep skills-based end to end workflow. >> That word fundamental has such gravity. and I know we say data has gravity being fundamental in such an incredibly dynamic time is really challenging but I was looking through some of the notes that you guys provided me with. And in terms of what you just talked about, Dominique versus making a change to a silo, the benefits and making changes to a spectrum of integrated processes the values can be huge. In fact, I was reading that changing a single process like billing, for example might deliver up to 20% improved results. But integrating across multiple processes, like billing, collections, organizations can achieve double that up to 40%. And then there's more taking the intelligent workflow across all lead to cash. This was huge. Clients can get 50 to 70% more value from that. So that just shows that fundamental impact that intelligent workflows can make. >> Right, I mean, it really is when we see it really is about unlocking exponential value. So, when you think about crossing end to end workflow but also, really enhancing what clients are doing and what companies are doing today with those exponential technologies from kind of single use the automation POC here and AI application POC here, actually integrating those technologies together and applying them at scale. When I think intelligent workflows I think acceleration. I think exponential value. But I also really think about at scale. Because it's really the ability to apply these technologies the expertise at scale that allows us to start to unlock a lot of that value. >> So let's go over Paul, in the last few minutes that we have here I want to talk about IBM garage and how this is helping clients to really transform those workflows. Talk to me a little bit about what IBM garage is. I know it's not IBM garage band and I know it's been around since before the pandemic but help us understand what that is and how it's delivering value to customers. >> Well, first I'm going to be the first to invite you to join the IBM garage band, Lisa so we'd love to have you >> I'm in. no musical experience required... >> I like to sing, all right I mean (laughs) We're ready, we're ready for. So, let me talk to you about IBM garage and I do want to key on two words that Dominique was mentioning speed and scale. Because that's what our clients are really looking for when they're doing transformations around intelligent workflows. How can you transform at scale, but do that with speed. And that really becomes the critical issue. As Dominique mentioned, there's a lot of companies that can help you do a proof of concept do something in a few weeks that you can test an idea out and have something that's kind of like a throw away piece of work that maybe proves a point or just proves a point. But even if it does prove the point at that point you'd have to restart a new, to try to get something that you could actually scale either in the production technology environment or scale as a change across an organization. And that's where IBM garage comes in. It's all a way of helping our clients co-create, co-execute and then cooperate, innovating at scale. So, we use methods like design thinking inside of IBM we've trained several hundred thousand people on design thinking methods. We use technologies like neural and other things that help our clients co-create in a dynamic environment. And what's amazing for me is that, the cause of the way we were, we were doing work with clients in a garage with using IBM garage in a garage environment before the pandemic. And one of our clients Frito-Lay of North America, is an example where we've helped them innovate at scale and speed using IBM garage over a long period of time. And when the pandemic hit, we in fact were running 11 garages across 11 different workflow areas for them the pandemic hit and everyone was sent home. So, we all instantly overnight had to work from home together with relay. And what was great is that we were able to quickly adapt the garage method to working in a virtual world. To being able to run that same type of innovation and then use that innovation at scale in a virtual world, we did that overnight. And since that time which happened, that happened back in March of last year throughout the pandemic, we've run over 1500 different garage engagements with all of our clients all around the world in a virtual, in a virtual environment. It's just an incredible way, like I said to help our clients innovate at scale. >> That's fantastic, go ahead Dominique. >> Oh, sorry, was just said it's a great example, we partnered with FlightSafety International, they train pilots. And I think a great example of that speed and scale right is in less than 12 weeks due to the garage methodology and the partnership with FlightSafety, we created with them and launched an adaptive learning solution. So, a platform as well as a complete change to their training workflow such that they had personalized kind of real-time next best training for how they train their pilots for simulators. So, reducing their cycle time but also improving the training that their pilots get, which as people who normally travel, it's really important to us and everyone else. So, just a really good example, less than 12 weeks start to start to finish. >> Right, talk about acceleration. Paul, last question for you, we've got about 30 seconds left I know this is an ecosystem effort of IBM, it's ecosystem partners, it's Alliance partners. How are you helping align right partner with the right customer, the right use case? >> Yeah, it's great. And our CEO Arvind Krishna has really ushered in this era where we are all about the open ecosystem here at IBM and working with our ecosystem partners. In our services business we have partnerships with all the major, all the major technology players. We have a 45 year relationship with SAP. We've done more SAP S 400 implementations than anyone in the world. We've got the longest standing consulting relationship with Salesforce, we've got a unique relationship with Adobe, they're only services and technology partner in the ecosystem. And we just recently won three, procedures Partner Awards, with them and most recently we announced a partnership with Celonis which is an incredible process execution software company, process mining software company that's going to help us transform intelligent workflows in an accelerated way, embedded in our garage environment. So, ecosystem is critical to our success but more importantly, it's critical to our client success. We know that no one alone has the answers and no one alone can help anyone change. So, with this open ecosystem approach that we take and global business services and our business transformation services organization, we're able to make sure that we bring our clients the best of everyone's capabilities. Whether it's our technology, partners, our services IBM's own technology capabilities, all in the mix, all orchestrated in service to our client's needs all with the goal of driving superior business outcomes for them. >> And helping those customers in any industry to accelerate their business transformation with those intelligent workloads and a very dynamic time. This is a topic we could keep talking about unfortunately, we are out of time but thank you both for stopping by and sharing with me what's going on with respect to intelligent workflows. How the incremental exponential value it's helping organizations to deliver and all the work that IBM is doing to enable its customers to be thrivers of tomorrow. We appreciate talking to you >> Paul: Thanks Lisa. >> Dominique: Thank you >> For Paul Papas and Dominique Dubois I'm Lisa Martin. You're watching the CUBE's coverage of IBM Think the digital event experience. (gentle music)

Published Date : May 12 2021

SUMMARY :

Brought to you by IBM. to the CUBE please welcome Paul Papas, She is the Global Strategy in the future are going to be? and thanks so much for that question. and employees being opposed to change. and always the hardest component. that the mental concerns that are pledging to be kind. and I'm going to tell you to and ready to move with haste. and making changes to a Because it's really the ability in the last few minutes that we have here I'm in. the garage method to and the partnership with FlightSafety, the right use case? So, ecosystem is critical to our success We appreciate talking to you the digital event experience.

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Paul Pappas + Dominique Dubois


 

(lively music) >> From around the globe it's theCUBE, with digital coverage of IBM Think 2021. Brought to you by IBM. >> Welcome to theCUBE's coverage of IBM Think 2021, the digital event experience. I'm your host, Lisa Martin. I've got an alumni joining me and a brand new guest to the CUBE please welcome Paul Papas, the Global Managing Partner, for IBM Global Business Services, this is transformation services. Paul, welcome back to the virtual CUBE. >> Thanks Lisa great to be here with you today. And Dominique Dubois is here as well. She is the Global Strategy and Offerings Leader in business transformation services or BTS at IBM. Dominique, welcome to the program. >> Thanks Lisa, great to be here. So, we're going to be talking about accelerating business transformation with intelligent workflows. We're going to break through all that, but Paul we're going to start with you. Since we last got together with IBM, a lot has changed so much transformation, so much acceleration of transformation. Talk to me from your perspective, how have you seen the way that businesses running change and what some of the changes in the future are going to be? >> Well, you hit on two key words there Lisa and thanks so much for that question. Two key words that you hit on were change and acceleration. And that's exactly what we see. We were seeing this before the pandemic and if anything, with the pandemic did when things started started kind of spreading around the world late or early last year, around January, February timeframe we saw that word acceleration really take hold. Every one of our clients were looking for new ways to accelerate the change that they had already planned to adapt to this new, this new normal or this new abnormal, depending on how you view it. In fact, we did a study recently, an IBV study that's our Institute of Business Value and found that six out of 10 organizations were accelerating all of their transformation initiatives they had already planned. And that's exactly what we're seeing happening right now in all parts of the world and across all industries. This acceleration to transform. >> So, one of the things that we've talked about for years, Paul, before the pandemic was even a thing, is that there was a lot of perceived technical barriers in terms of like the tech maturity for organizations and employees being opposed to change. People obviously it can be a challenge. They're used to doing things the way they are. But as you just said, in that IBV survey, nearly 60% of businesses say we have to accelerate our transformation due to COVID, probably initially to survive and then thrive. Talk to me about some of those, those barriers that were there a little over a year ago and how businesses 60 plus percent of them have moved those out of the way. >> You know at IBM we've got 109 year history of being a technology innovation company. And the rate of pace of technical change is always increasing. It's something that we love and that we're comfortable with. But the rate and pace of change is always unsettling. And there's always a human element for change. And the human element is always the rate, the rate setter in terms of the amount of change that you can have in an organization. Our former chairman Ginni Rometty, used to say that growth and comfort cannot co-exist. And it's so true because changing is uncomfortable. It's unsettling. It can be, it can be nerve-racking. It can instill fear and fear can be paralyzing in terms of driving change. And what we also see is there's a disconnect, a lot of times and that IBV study that I was referring to before, we saw results coming back where 78% of executives feel that they have provided the training and enablement to help their employees transform to new required skills and new ways of working but only half of the people surveyed felt the same way. Similarly, we saw a disconnect in terms of companies feeling that they're providing the right level of health and wellness support during the pandemic. And only half of the employees responded back they feel that they're getting that level of support. So, the people change aspect of may doing a transformation or adapting to new circumstances is always the most critical component and always the hardest component. And when we talk about helping our clients do that in IBM that's our service as organization. That's the organization that Dominique Dubois are representing here today. I'm responsible for business transformation services within our organization. We help our clients adapt using new technologies, transforming the way they work, but also addressing the people change elements that could be so difficult and hitting them head on so that they can make sure that they can survive and thrive in a meaningful and lasting way in this new world. >> One of the hardest things is that cultural transformation regardless of a pandemic. So, I can't imagine I'd love to get one more thing, Paul from you before we head over to Dominique. IBM is on 109 year old organization. Talk to me about the IBM pledge. This is something that came up last year, huge organization massive changes last year, not just the work from home that the mental concerns and issues that people had. What did IBM do like as a grassroots effort that went viral? >> Yeah, so, it's really great. So, when the pandemic started, we all have to shift it, We all have to shift to working from home. And as you mentioned, IBM's 109 year old company, we have over 300,000 employees working in 170 countries. So, we had to move this entire workforce. It's 370,000 humans to working in a new way that many of which have never done before. And when we started experiencing, the minute we did that, within a few weeks, my team and I were talking Dominique is on my team and we were having conversations where we were feeling really exhausted. Just a few weeks into this and it was because we were constantly on Webex, we were constantly connected and we're all used to working really hard. We travel a lot, we're always with our clients. So, it wasn't that, you have a team that is adapting to like working more hours or longer hours, but this was fundamentally different. And we saw that with schools shutting down and lock downs happening in different of the world the home life balance was getting immediately difficult to impossible to deal with. We have people that are taking care of elderly parents, people that are homeschooling children, other personal life situations that everyone had to navigate in the middle of a pandemic locked at home with different restrictions on when you can go out and get things done. So, we got together as a group and we just started talking about how can we help? How can we help make life just a little bit easier for all of our people? And we started writing down some things that we would, we would commit to doing with each other. How we would address each other. And when that gave birth to was what we call the IBM Work From Home Pledge. And it's a set of principles, all grounded in the belief that, if we act this way, we might just be able to make life just a little bit easier for each other and it's grounded in empathy. And there are parts of the Plex that are pledging to be kind. Recognizing that in this new digital world that we're showing up on camera inside of everyone's home. We're guests in each other's homes. So, let's make sure that we act appropriately as guests at each other's home. So, if children run into the frame during the middle of a meeting or dog started barking during the middle of a meeting, just roll with it. Don't call out attention to it. Don't make people feel self-conscious about it. Pledged the support so your fellow IBM by making time for personal needs. So, if someone has to, do homeschooling in the middle of the day, like Dominique's got triplets she's got to do homeschooling in the middle of the day. Block that time off and we will respect that time on your calendar. And just work around it and just deal with it. There are other things like respecting that camera ready time. As someone who's now been on camera every day it feels like for the last 14 months we want to respect the time that people when they have their cameras off. And not pressure them to put their cameras on saying things like, Hey, I can't see you. There's no reason to add more pressure to everyone's life, if someone's camera's off, it's all for a reason. And then other things like pledging to checking on each other, pledging to set boundaries and tend to our own self-care. So, we published that as a group, we just again and we put it on a Slack channel. So it's kind of our communication method inside the company. It was just intended to be for my organization but it started going viral and tens of thousands of IBM members started taking, started taking the pledge and ultimately caught the attention of our CEO and he loved it, shared it with his leadership team, which I'm a part of. And then also then went on LinkedIn and publicly took the pledge as well. Which then also got more excitement and interaction with other companies as well. So, grassroots effort all grounded in showing empathy and helping to make life just a little bit easier for everyone. >> So important, I'm going to look that up and I'm going to tell you as a person who speaks with many tech companies a week. A lot of businesses could take a lead from that and it gets really important and we are inviting each other into our homes and I see you're a big Broadway fan I'll have to ask you that after we wrap (giggles) Dominique I don't know how you're doing any of this with triplets. I only have two dogs (Dominique laughs) but I'd love to know this sense of urgency, that is everywhere you're living it. Paul talked about it with respect to the acceleration of transformation. How from your lens is IBM and IBM helping customers address the urgency, the need to pivot, the need to accelerate, the need to survive and thrive with respect to digital transformation actually getting it done? >> Right, thanks Lisa, so true our clients are really needing to and ready to move with haste. That that sense of urgency can be felt I think across every country, every market, every industry. And so we're really helping our clients accelerate their digital transformations and we do that through something that we call intelligent workflows. And so workflows in and of themselves are basically how organizations get work done. But intelligent workflows are how we infuse; predictive properties, automation, transparency, agility, end to end across a workflow. So, pulling those processes together so they're not solid anymore and infusing. So, simply put we bring intelligent workflows to our clients and it fundamentally reinvents how they're getting work done from a digital perspective, from a predictive perspective, from a transparency perspective. And I think what really stands apart when we deliver this with our clients in partnership with our clients is how it not only delivers value to the bottom line, to the top line it also actually delivers greater value to their employees, to the customers, to the partner to their broader ecosystem. And intelligent workflows are really made up of three core elements. The first is around better utilizing data. So, aggregating, analyzing, getting deeper insight out of data, and then using that insight not just for employees to make better decisions, but actually to support for emerging technologies to leverage. So we talked about AI, automation, IOT, blockchain, all of these technologies require vast amounts of data. And what we're able to bring both on the internal and external source from a data perspective really underpins what these emerging technologies can do. And then the third area is skills. Our skills that we bring to the table, but also our clients deep, deep expertise, partner expertise, expertise from the ecosystem at large and pulling all of that together, is how we're really able to help our clients accelerate their digital transformations because we're helping them shift, from a set of siloed static processes to an end-to-end workflow. We're helping them make fewer predictions based on the past historical data and actually taking more real-time action with real time insights. So, it really is a fundamental shift and how your work is getting done to really being able to provide that emerging technologies, data, deep skills-based end to end workflow. >> That word fundamental has such gravity. and I know we say data has gravity being fundamental in such an incredibly dynamic time is really challenging but I was looking through some of the notes that you guys provided me with. And in terms of what you just talked about, Dominique versus making a change to a silo, the benefits and making changes to a spectrum of integrated processes the values can be huge. In fact, I was reading that changing a single process like billing, for example might deliver up to 20% improved results. But integrating across multiple processes, like billing, collections, organizations can achieve double that up to 40%. And then there's more taking the intelligent workflow across all lead to cash. This was huge. Clients can get 50 to 70% more value from that. So that just shows that fundamental impact that intelligent workflows can make. >> Right, I mean, it really is when we see it really is about unlocking exponential value. So, when you think about crossing end to end workflow but also, really enhancing what clients are doing and what companies are doing today with those exponential technologies from kind of single use the automation POC here and AI application POC here, actually integrating those technologies together and applying them at scale. When I think intelligent workflows I think acceleration. I think exponential value. But I also really think about at scale. Because it's really the ability to apply these technologies the expertise at scale that allows us to start to unlock a lot of that value. >> So let's go over Paul, in the last few minutes that we have here I want to talk about IBM garage and how this is helping clients to really transform those workflows. Talk to me a little bit about what IBM garage is. I know it's not IBM garage band and I know it's been around since before the pandemic but help us understand what that is and how it's delivering value to customers. >> Well, first I'm going to be the first to invite you to join the IBM garage band, Lisa so we'd love to have you >> I'm in. no musical experience required... >> I like to sing, all right I mean (laughs) We're ready, we're ready for. So, let me talk to you about IBM garage and I do want to key on two words that Dominique was mentioning speed and scale. Because that's what our clients are really looking for when they're doing transformations around intelligent workflows. How can you transform at scale, but do that with speed. And that really becomes the critical issue. As Dominique mentioned, there's a lot of companies that can help you do a proof of concept do something in a few weeks that you can test an idea out and have something that's kind of like a throw away piece of work that maybe proves a point or just proves a point. But even if it does prove the point at that point you'd have to restart a new, to try to get something that you could actually scale either in the production technology environment or scale as a change across an organization. And that's where IBM garage comes in. It's all a way of helping our clients co-create, co-execute and then cooperate, innovating at scale. So, we use methods like design thinking inside of IBM we've trained several hundred thousand people on design thinking methods. We use technologies like neural and other things that help our clients co-create in a dynamic environment. And what's amazing for me is that, the cause of the way we were, we were doing work with clients in a garage with using IBM garage in a garage environment before the pandemic. And one of our clients Frito-Lay of North America, is an example where we've helped them innovate at scale and speed using IBM garage over a long period of time. And when the pandemic hit, we in fact were running 11 garages across 11 different workflow areas for them the pandemic hit and everyone was sent home. So, we all instantly overnight had to work from home together with relay. And what was great is that we were able to quickly adapt the garage method to working in a virtual world. To being able to run that same type of innovation and then use that innovation at scale in a virtual world, we did that overnight. And since that time which happened, that happened back in March of last year throughout the pandemic, we've run over 1500 different garage engagements with all of our clients all around the world in a virtual, in a virtual environment. It's just an incredible way, like I said to help our clients innovate at scale. >> That's fantastic, go ahead Dominique. >> Oh, sorry, was just said it's a great example, we partnered with FlightSafety International, they train pilots. And I think a great example of that speed and scale right is in less than 12 weeks due to the garage methodology and the partnership with FlightSafety, we created with them and launched an adaptive learning solution. So, a platform as well as a complete change to their training workflow such that they had personalized kind of real-time next best training for how they train their pilots for simulators. So, reducing their cycle time but also improving the training that their pilots get, which as people who normally travel, it's really important to us and everyone else. So, just a really good example, less than 12 weeks start to start to finish. >> Right, talk about acceleration. Paul, last question for you, we've got about 30 seconds left I know this is an ecosystem effort of IBM, it's ecosystem partners, it's Alliance partners. How are you helping align right partner with the right customer, the right use case? >> Yeah, it's great. And our CEO Arvind Krishna has really ushered in this era where we are all about the open ecosystem here at IBM and working with our ecosystem partners. In our services business we have partnerships with all the major, all the major technology players. We have a 45 year relationship with SAP. We've done more SAP S 400 implementations than anyone in the world. We've got the longest standing consulting relationship with Salesforce, we've got a unique relationship with Adobe, they're only services and technology partner in the ecosystem. And we just recently won three, procedures Partner Awards, with them and most recently we announced a partnership with Celonis which is an incredible process execution software company, process mining software company that's going to help us transform intelligent workflows in an accelerated way, embedded in our garage environment. So, ecosystem is critical to our success but more importantly, it's critical to our client success. We know that no one alone has the answers and no one alone can help anyone change. So, with this open ecosystem approach that we take and global business services and our business transformation services organization, we're able to make sure that we bring our clients the best of everyone's capabilities. Whether it's our technology, partners, our services IBM's own technology capabilities, all in the mix, all orchestrated in service to our client's needs all with the goal of driving superior business outcomes for them. >> And helping those customers in any industry to accelerate their business transformation with those intelligent workloads and a very dynamic time. This is a topic we could keep talking about unfortunately, we are out of time but thank you both for stopping by and sharing with me what's going on with respect to intelligent workflows. How the incremental exponential value it's helping organizations to deliver and all the work that IBM is doing to enable its customers to be thrivers of tomorrow. We appreciate talking to you >> Thanks Lisa. >> Thank you >> For Paul Papas and Dominique Dubois I'm Lisa Martin. You're watching the CUBE's coverage of IBM Think the digital event experience. (gentle music)

Published Date : Apr 21 2021

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>>From around the globe. It's the Cube with digital coverage of IBM think 2021 brought to you by >>IBM. Welcome back to IBM Think 2021. This is the cubes ongoing coverage where we go out to the events, we extract the signal from the noise of course, virtually in this case now we're going to talk about ecosystems, partnerships in the flywheel, they deliver in the technology business and with me or Jason kelly, general manager, global strategic partnerships, IBM global business services and Mani Das Gupta, who is the vice president of marketing for IBM Global Business services folks. It's great to see you again in which we're face to face. But this will have to do >>good to see you Dave and uh same, I wish we were face to face but uh we'll we'll go with this >>soon. We're being patient, Jason. Let's start with you. You have a partner strategy. I wonder if you could sort of summarize that and tell us more about it. >>So it's interesting that we start with the strategy because you said we have a partner strategy dave and I'd say that the market has dictated back to us a partner strategy something that we it's not new and we didn't start it yesterday. It's something that we continue to evolve and build even stronger. This thought of a partner strategy is it nothing is better than the thought of a partner ship. And people say oh well you know you got to work together as one team and as a partner And it sounds almost as a 1-1 type relationship. Our strategies is much different than that. David our execution is even better and that that execution is focused on now. The requirement that the market our clients are showing to us and our strategic partners that one player can't deliver all their needs, they can't Design solution and deliver that from one place. It does take an ecosystem to the word that you called out. This thought of an ecosystem and our strategy and execution is focused on that. And the reason why I say it evolves is because the market will continue to evolve and this thought of being able to look at a client's let's call it a a workflow, let's call it a value chain from one end to the other, wherever they start their process to wherever it ultimately hits that end user. It's going to take many players to cover that. And then we, as IBM want to make sure that we are the general contractor of that capability with the ability to convene the right strategic partners, bring out the best value for that outcome, not just technology for technology's sake, but the outcome that the incline is looking for so that we bring value to our strategic partners and that in client. >>I think about when you talk about the value chain, you know, I'm imagining, you know, the business books years ago you see the conceptual value chain, you can certainly understand that you can put processes together to connect them and now you've got technology, I think of a P. I. S. It's it's really supports that everything gets accelerated and and uh money. I wonder if you could address some of the the go to market how this notion of of ecosystem which is so important, is impacting the way in which you go to market. >>Absolutely. So modern business, you know, demands a new approach to working the ecosystem. Thought that Jason was just alluding to, it's a mutual benefit of all these companies working together in the market, it's a mutual halo of the brands, so as responsible for the championship of the IBM and the global business services brand. I am very, very interested in this mutual working together. It should be a win win win, as we say in the market, it should be a win for our clients, first and foremost, it should be a win for our partners and it should be a win for IBM and we are working together right now on an approach to bring this, go to market strategy to life. >>So I wonder if we could maybe talk about how this actually works and and pull in some examples, uh you must have some favorites that that we can touch on. Uh is that, is that fair? Can we, can we name some names, >>sure names, always working debut, right. And it's always in context of reality that we can talk about, as I said, this execution and not just a strategy. And I'll start with probably what's right in the front of many people's minds as we're doing this virtually because of what because of an unfortunate pandemic, um, this disastrous loss of life and things that have taken us down a path. We go well, how do we, how do we address that? Well, any time there's a tough task, IBM raises its hand first. You know, whether it was putting a person on the moon and bringing them home safely or standing up a system behind the current Social Security Administration, you know, during the Depression, you pick it well here we are now. And why not start with that as an example? Because I think it calls out just what we mentioned here first day, this thought of a, of an ecosystem because the first challenge, how do we create uh and address the biggest data puzzle of our lives, which is how do we get this vaccine created in record time, which it was the fastest before that was four years. This was a matter of months. Visor created the first one out and then had to get it out to distribution. Behind. That is a wonderful partner of R. S. A. P. Trying to work with that. So us working with S. A. P. Along with Pfizer in order to figure out how to get that value chain. And some would say supply chain, but I'll address that in a second. But there's many players there. And so we were in the middle of that with fires are committed to saying, how do we do that with S. A. P. So now you see players working together as one ecosystem. But then think about the ecosystem that that's happening where you have a federal government agency, a state, a local, you have healthcare, life science industry, you have consumer industry. Oh wait a second day. This is getting very complicated, Right? Well, this is the thought of convening an ecosystem and this is what I'm telling you is our execution and it has worked well. And so it's it's it's happening now. We still it's we see it's still developing and being, being, you know, very productive in real time. But then I said there was another example and that's with me, you mani whomever you pick the consumer. Ultimately we are that outcome of of the value chain. That's why I said, I don't want to just call it a supply chain because at the end is a someone consuming and in this case we need a shot. And so we partnered with Salesforce, IBM and Salesforce saying, wait a minute, that's not a small task. It's not just get the content there and put it in someone's arm instead they're scheduling that must be done. There's follow up an entire case management like system sells force is a master at this, so work dot com team with IBM, we sit now let's get that part done for the right type of UI UX capability that the user experience, user interaction interface and then also in bringing another player in the ecosystem, one of ours Watson health along with our block changing, we brought together something called a Digital Health pass. So I've just talked about two ecosystems work multiple ecosystems working together. So you think of an ecosystem of ecosystems. I called out Blockchain technology and obviously supply chain but there's also a I I O T. So you start to see where look this is truly an orchestration effort. It has to happen with very well designed capability and so of course we master and design and tying that that entire ecosystem together and convening it so that we get to the right outcome you me money all getting into shot being healthy. That's a real time example of us working with an ecosystem and teeming with key strategic partners, >>you know, money, I mean Jason you're right. I mean pandemics been horrible, I have to say. I'm really thankful it didn't happen 20 years ago because it would have been like okay here's some big pcs and a modem and go ahead and figure it out. So I mean the tech industry has saved business. I mean with not only we mentioned ai automation data, uh even things basic things like security at the end point. I mean so many things and you're right, I mean IBM in particular, other large companies you mentioned ASAP you have taken the lead and it's really I don't money, I don't think the tech industry gets enough credit, but I wonder if there's some of your favorite, you know, partnerships that you can talk about. >>Yeah, so I'm gonna I'm gonna build on what you just said. Dave IBM is in this unique position amongst this ecosystem. Not only the fact that we have the world leading most innovative technologies to bring to bear, but we also have the consulting capabilities that go with it now to make any of these technologies work towards the solution that Jason was referring to in this digital health pass, it could be any other solution you would need to connect these disparate systems, sometimes make them work towards a common outcome to provide value to the client. So I think our role as IBM within this ecosystem is pretty unique in that we are able to bring both of these capabilities to bear. In terms of you know, you asked about favorite there are this is really a coop petition market where everybody has products, everybody has service is the most important thing is how how are we bringing them all together to serve the need or the need of the hour in this case, I would say one important thing in this. As you observe how these stories are panning out in an ecosystem in in part in a partnership, it is about the value that we provide to our clients together. So it's almost like a cell with model from from a go to market perspective, there is also a question of our products and services being delivered through our partners. Right? So think about the span and scope of what we do here. And so that's the sell through. And then of course we have our products running within our partner companies and our partner products, for example. Salesforce running within IBM. So this is a very interesting and a new way of doing business. I would say it's almost like the modern way of doing business with modernity. >>Well. And you mentioned cooperation. I mean you're you're part of IBM that will work with anybody because your customer first, whether it's a W. S. Microsoft oracle is a is a is a really tough competitor. But your customers are using oracle and they're using IBM. So I mean as a those are some good examples. I think of your point about cooper Titian. >>Absolutely. If you pick on any other client, I'll mention in this case. Delta, Delta was working with us on moving, being more agile. Now this pandemic has impacted the airline sector particularly hard, right With travel stopping and anything. So they are trying to get to a model which will help them scale up, scale down, be more agile will be more secure, be closer to their customers, try and understand how they can provide value to their customers and customers better. So we are working with Delta on moving them to cloud on the journey to cloud. Now that public cloud could be anything. The beauty of this model and a hybrid cloud approach is that you are able to put them on red hat open shift, you're able to do and package the services into a microservices kind of a model. You want to make sure all the applications are running on a portable, almost platform. Agnostic kind of a model. This is the beauty of this ecosystem that we are discussing is the ability to do what's right for the end customer at the end of the day, >>how about some of the like sass players, like some of the more prominent ones and we watched the ascendancy of service now and and, and work day, you mentioned Salesforce. How do you work with those guys? Obviously there's an Ai opportunity, but maybe you could add some, you know, color there. >>So I like the fact that you call out the different hyper scholars for example, uh whether it's a W. S, whether it's Microsoft, knowing that they have their own cloud instances, for example. And when you, when you mentioned, he had this happened a long time ago, you know, you start talking about the heft of the technology, I started thinking of all the truckloads of servers or whatever they have to pull up. We don't need that now because it can happen in the cloud and you don't have to pick one cloud or the other. And so when people say hybrid cloud, that's what comes out, you start to think of what I I call, you know, a hybrid of hybrids because I told you before, you know, these roles are changing. People aren't just buyers or suppliers, they're both. And then you start to say what we're different people supplying well in that ecosystem, we know there's not gonna be one player, there's gonna be multiple. So we partner by doing just what monty called out is this thought of integrating in hybrid environments on hybrid platforms with hybrid clouds, Multi clouds, maybe I want something on my premises, something somewhere else. So in giving that capability that flexibility we empower and this is what's doing that cooperation, we empower our partners are strategic partners, we want them to be better with us. And this is this thought of being able to actually bring more together and move faster which is almost counterintuitive. You're like wait a minute you're adding more players but you're moving faster. Exactly because we have the capability to integrate those those technologies and get that outcome that monty mentioned, >>I would add to this one. Jason you mentioned something very very interesting. I think if you want to go just fast you go alone but if you want to go further, you go together. And that is the core of our point of view in this case is that we want to go further and we want to create value that is long lasting. >>What about like so I get the technology players and there may be things that you do that others don't or vice versa. So the gap fillers etcetera. But what about how to maybe customers that they get involved? Perhaps government agencies, may they be they be customer or an N. G. O. As another example, Are they part of this value chain? Part of this ecosystem? >>Absolutely. I'll give you I'll stick with the same example when I mentioned a digital health past that Digital Health Pass is something that we have as IBM and it's a credential Think of it as a health credential not a vaccine passport because it could be used for a test for a negative test on Covid, it could be used for antibiotics. So if you have this credential, it's something that we, as IBM created years back and we were using it for learning. When you think of getting people uh certifications versus a four year diploma, how do we get people into the workforce? That was what was original. That was a jenny Rometty thought, let's focus on new collar workers. So we had this asset that we'd already created and then it's wait, there's a place for it to work with, with health, with validation verification on someone's option, it's optional. They choose it. Hey, I want to do it this way. Well, the state of new york said that they wanted to do it that way and they said, listen, we are going to have a digital health pass for all of our, all of our new york citizens and we want to make sure that it's equitable, it could be printed or on a screen and we want it to be designed in this way and we wanted to work on this platform and we want to be able to, to work with the strategic Partners, a Salesforce and ASAP and work. I mean, I can just keep and we said okay let's do this. And this is the start of collaboration and doing it by design. So we haven't lost that day but this only brings it to the forefront just as you said, yes, that is what we want. We want to make sure that in this ecosystem we have a way to ensure that we are bringing together convening not just point products or different service providers but taking them together and getting the best outcome so that that end user can have it configured in the way that they want it >>guys, we got to leave it there but it's clear you're helping your customers and your partners on this this digital transformation journey that we already we all talk about. You get this massive portfolio of capabilities, deep, deep expertise, I love the hybrid cloud and AI Focus, Jason and money really appreciate you coming back in the cubes. Great to see you both. >>Thank you so much. Dave Fantastic. All >>Right. And thank you for watching everybody's day Vigilante for the Cuban. Our continuous coverage of IBM, think 2021, the virtual edition. Keep it right there. Yeah. Mhm. Mhm. >>Mhm.

Published Date : Apr 16 2021

SUMMARY :

think 2021 brought to you by It's great to see you again in which we're I wonder if you could sort of summarize that and tell us more about it. So it's interesting that we start with the strategy because you said we have I think about when you talk about the value chain, you know, I'm imagining, So modern business, you know, demands a new approach to working the ecosystem. in some examples, uh you must have some favorites that that we can touch and convening it so that we get to the right outcome you me money all getting favorite, you know, partnerships that you can talk about. it is about the value that we provide to our clients together. part of IBM that will work with anybody because your customer first, whether it's a W. that you are able to put them on red hat open shift, you're able to do and package how about some of the like sass players, like some of the more prominent ones and we watched the ascendancy So I like the fact that you call out the different hyper scholars And that is the core of our point of view in this case is that we want to go What about like so I get the technology players and there may be things that you do that others So if you have this credential, it's something that we, as IBM created years back Great to see you both. Thank you so much. And thank you for watching everybody's day Vigilante for the Cuban.

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>>from >>Around the globe, it's the cube with digital coverage of IBM think 2021 brought to you by IBM. >>Welcome back to IBM Think 2021 we're gonna dig into the intersection of finance and business strategy. My name is Dave Volonte and you're watching the cubes continuous coverage of IBM thinking with me is brian Hoffman is the chief operating officer of IBM Global financing, brian, thanks for coming on the cube today. >>Good morning, Great to be here. >>Hey, good morning. So I think we've heard a lot about the impact of hybrid cloud ai digital transformation and I wonder as a finance person in a former CFO, what do you see? And how do you think about some of the key considerations and financials and strategies that are supporting these major projects? Right? We got to come to the CFO and say, hey, we want to spend some money and here's the benefit, here is the cost. How can see IOS and their teams work with CFOs to try to really accelerate that digital transformation. >>Great question. And actually that question, I think I might have answered it a little bit differently, like two years ago, a year ago before the pandemic, I think it's actually changed a little bit with pandemic in my experience is the CFO people would come into me for projects and there's three ways you can justify it, but you can justify short term immediate, quick payback kind of hitters, you can justify it with, you know, improving our efficiency or effectiveness, um you know, reducing costs in the long run, making the client experience better or more from a strategic point of view, um you know, growing revenue getting to new clients, improving margins right? And so the the hybrid cloud transformation journey really still addresses those three things and when we come in, a lot of people focus like I said, on that third strategic point, but but all three of those come into play, and what's really interesting now is is as I'm dealing with it, I'm talking to other Cfos. The pandemic is really, if you will throw in a wrinkle in here, right? So the clients that I'm talking to, the IBM clients, they have to operate their business very differently and and their business models, some of them are changing clearly. Their clients, their business models are changing their operating differently as well. Um So, so our clients have to react to that and Hybrid Cloud and that that that type of of a structure really can support that. So there's really an emphasis here now to act with much more speed on this journey to get moving on it to get there because you have to make these changes and doing those two things in concert really has a ton of business value. >>Yeah I mean the cfos that I've talked to in the C. I. O. S. It's really kind of industry dependent, right? If you're in airlines or hospitality was like uh we got to cut costs. A lot of organizations said okay we're gonna support remote workers put in V. D. I. Or deal with endpoint security or whatever it was. But we're actually gonna double down on our digital transformation. This is we're gonna lean into an opportunity for us to come out stronger. How did you guys approach it in terms of your own internal digital >>transformation? Yeah. We we we were working on our digital transformation uh a little bit before the pandemic and it kind of followed those those three uh those three items when they when they first started implementing it, they came in and said hey if we can if we can move to a cloud platform, our infrastructure savings will be pretty significant. You know the I. T. Infrastructure savings will be 30 to 40%. So you know, quick payback CFO types love that. So you know, we went forward with that. Um but then quickly we saw the real benefits of moving to a hybrid cloud strategy. So just as an example as we were making some of these changes, we found a workflow tool in one of our markets in europe, that was a great tool and uh if we wanted to implement that across the business um in the old days, You know, we're in 40 countries, we've got 2500 employees, three lines of business. It would have been very complex because our operating structure is is very robust, very complex. Um Probably have taken a year, two years to do that. But since we are now on a cloud platform we got that rolled out that workflow tool rolled out across our business in months, Saving 20-30 of of workload. Being much more um efficiently getting to our clients and reacting quickly to them. And in fact that tool got adopted across IBM because that cloud platform enabled that to happen. And then the great thing which I didn't even realize at the time but now thinking more strategically um are my I. T. Resource earlier was running at about 50 50 50 people working on maintenance. The kind of things with 50 on development as we've now transition to this cloud. My I. T. Resources now 70 plus percent dedicated to new development. So now we can go attack new things that really provide customer value in the pandemic. You know the first thing to look at is can we get into more um you know electronic contracts, E signatures, things that would provide value to customers anyway. But in the pandemic is like really a significant, you know differentiator for us. So all those things were enabled by that journey that we've been taking, >>interesting. I mean most of the CF I uh in fact every CFO I know of a public company took advantage of cheap debt and improving their balance sheets. And liquidity is not the problem today, especially in the tech industry at the same time. You know I'm interested in how companies are using financing. They don't want to necessarily build out data centers but they do want to fund their digital transformation. So what are you seeing in terms of how your customers are using financing? You know, what's the conversation like? What advice are you giving? >>Yeah. So um you know, it depends a little bit on the type of customer, like you said, you know, we we deal with a lot of the biggest, strongest customers in the world. And, and as we deal with them, financing really helps the return on their investment, right, aligning the payments of those cash flows for when they're getting the benefits. Uh And and we see a real good value in improving the return on those investments in helping, you know, if it's something that's going to go to the board that really makes a difference to them. Uh So, you know, that that's always been a value proposition. It continues to be. Um The other thing that's helping now, like you said, is even in this environment, people want to accelerate this transition. Um but it's a, it's a, it's a big time of uncertainty. So, you know, some of the smaller clients, some of the more uh you know, the industries that are a little more cash constrained airlines, et cetera, you know, they're looking for the the immediate cash flow benefits. Um But many of the cfos are saying, hey, listen, you know, I can I want to go as fast as I can help me put together a structure that lets me, you know, get this in place as quick as possible, but not below my budget is not make me take too much risk in this time of uncertainty, but keeps me moving and I think that's where financing really comes in as well. Um And we're kind of talking much more about that value proposition than just if you will be improved ri proposition that we've had all along. >>I want to talk a little bit more about IBM global financing. I mean, people, a lot of times people misunderstand it. You know when you look at I. B. M. S. Debt, you gotta you gotta take out the piece that IBM global financing because that's a significant portion and that's sort of self self fulfilling. But what do people need to know about IBM global financing, >>We actually run three different businesses and we've been transforming our strategy over time. So you know right now with with IBM being all in on hybrid, we are very focused on helping IBM and IBM clients on this digital journey on IBM growing their revenue. Um you know, we we in the past have been more of if you're really full service. It finance are doing a lot more than just IBM but we are really focused now on on helping IBM. So I think the best thing for for IBM clients to know is as you're talking to IBM about the total solution, the total value profit IBM brings that financing, that cash flow solution should be embedded in what they're looking at and can provide a lot of value. Um You know, the second thing I think most people know is we provide financing for IBM s channel, so you know, distributors, resellers etcetera, if you're an IBM distributor or reseller, you know about us, because just about 100% of IBM partners use us to provide that working capital financing, uh you know, we have a state of the art platforms were just so integrated with them. Again, I don't have to I don't have to do a sales pitch on that because they don't know us. Um and the third one just because people might not realize this is, we do haven't we call it an asset recovery business, um it's a pretty small business, you know, it's bringing back equipment that comes off lease, so that uh is used by IBM internally. Um and while, you know, it's not, it's not as well known, I'm pretty proud of it because it really does help with the focus that the world that IBM has on sustainability and reuse and um and making sure that, you know, we're treating the planet fairly here, so that that's a small but powerful piece of our business well, >>You're quite broader than leasing mainframes in the 80s, >>that's for sure. >>Talking more about give, you can double click on that sort of hybrid cloud and obviously machine intelligence is a big piece of those digital transformation. So, so how specifically are you, are you helping clients really take advantage of things like hybrid cloud? >>So yeah, so um what we have typically had been doing and I can give you a couple different examples if you will, you know, for larger clients. What we tend to be doing is helping them like I said, accelerate their business. So um, you know, they're looking to modernize their applications but they still have a big infrastructure in place and so they'll run into uh you know, budget constraints and and you know, cash is still be careful to managed. So for them we are much more typically focused on, you know, if you will project based financing that allows those cash flows to line up with the savings. Again, those are tend to be bigger projects that often go to boards that return benefit is very important. Ah a little bit different value proposition for more mid market customers. So, you know, as I was kind of just looking recently, we have a couple of different customers like form engineering um or or Novi still there to smaller uh compared to some of the other customers we use uh they are again much more focused on how do I, how do I conserve and best use my cash immediately? But they want to get this, they want to get this transformation going. So you know we provide flexible payment plans to them so they can go at the rate and pace that they need to, they can align up those cash deals with their budgets for their business cycles etcetera. So again, where smaller customers where timing of the cash flow in their business cycle is very important. We provide that benefit as well. >>You know, I wonder if I could ask you. So you remember of course the early days of public cloud, one of the first tail winds for public cloud was the pen was not the pandemic, the for the financial crisis of 2007. And a lot of CFO said, Okay let's shift to uh to an apex model. And now you can always provide financial solutions to customers. But it seems like today when I talk to clients, it's it's much more integrated, it's not just the public cloud, you can do that for on premises and again you always could do that. But it seems like there's much more simpatico uh in the way in which you provide that that that solution is that >>fair? Absolutely. And this might be a little to finance geeky, I don't know. But if you go back, well if you go back to the financial crisis and all that and at that time um a lot of people were looking to financing for you call that ah please. But you know if if I was talking about off balance sheet transactions right? Um and and you know between regulation etcetera etcetera, that that off balance sheet thing. First of all, people are seeing through it that much more clearly. But second, you know the the uh financial disclosure say you kind of have to show that stuff so that that if you will, window dressing benefit has gone away. So now which is great for me, we really get to talk about what's the real benefit, what is the, you know, what is the real benefit of? You know, you want to make sure that you have known timed expenditures. You know that if your business grows that your your expenses can grow evenly with those with that business growth, you don't have to take big chunky things and so you know uh financing under the covers of an integrated solution and IBM has a lot of those integrated solutions allows businesses to have that, you know, known timing known quantities. Most of the benefits that people were looking for from that affects cloud model. Um without, you know, some of the problems that you have, when you try to have to go straight to a public cloud for very, you know, big sensitive businesses, confidential confidential data etcetera. >>Thanks for that. So, okay, we're basically out of time. But I wonder if you could give us the bumper sticker and key takeaways, maybe you could summarize for our audience. >>Yeah. For those that noah global financing or dealing with IBM, my view would be in the past we might have been a little more, you know, out there with our own with our own banner etcetera. In the future. I think that you should expect to see us very well integrated into anything you're doing. I think our value proper is clear and compelling and and and will be included uh in these hybrid con transformations to the benefit of our clients. So that's that's our objective and we're well on our way there. >>Great. Anywhere, anywhere I'm gonna go for more, more familiar, obviously IBM dot com. You got some resources there. But there is >>there any Absolutely dot com? There's there's a thank you. Just probably a slash financing. But yeah, there's >>were >>loaded with information of people. >>Excellent brian thanks so much for coming to the cube. Really great to have you today. >>I appreciate the time. >>My pleasure. Thank you for watching everybody's day. Volonte for the Cuban. Our coverage of IBM think 2021, the virtual edition right back.

Published Date : Apr 16 2021

SUMMARY :

think 2021 brought to you by IBM. Welcome back to IBM Think 2021 we're gonna dig into the intersection of finance and And how do you think about some of the key my experience is the CFO people would come into me for projects and there's three ways you can justify How did you guys approach it in terms of your own internal digital You know the first thing to look at is can we get into more um you know electronic contracts, So what are you seeing in terms of how Um But many of the cfos are saying, hey, listen, you know, I can I You know when you look at I. B. M. S. Debt, you gotta you gotta take out the piece that IBM Um and while, you know, it's not, it's not as well known, Talking more about give, you can double click on that sort of hybrid cloud and obviously machine place and so they'll run into uh you know, budget constraints and and you integrated, it's not just the public cloud, you can do that for on premises and again you always could do that. of those integrated solutions allows businesses to have that, you know, known timing known quantities. But I wonder if you could give us the bumper sticker and key I think that you should expect to see us very well integrated into anything you're doing. But there is But yeah, Really great to have you today. Thank you for watching everybody's day.

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David La Rose, IBM Partner Ecosystem | IBM Think 2020


 

>>Yeah, >>from The Cube Studios in Palo Alto and Boston. It's the Cube covering IBM. Think brought to you by IBM. >>Hi, everybody. We're back. And you're watching the Cube's coverage of the IBM think digital event for 2020. This is that he's socially distant and socially responsible. You? My name is Dave a lot. David Larose. Who's the general manager of the IBM partner ecosystem? David, Good to see you. >>Likewise. Great to be here. >>Yes, it is. Your first year in running the the ecosystem. You probably don't expect to be managing through the this world crisis this novel Corona virus. But what was your first move? Your outreach to partners? How are you communicating to them? Maybe you could share with us how that's all going. >>It certainly wasn't in the break. So when I took this job, you're right. But, you know, we have a very strong relationship with with our partners, and what we have is we have a global advisory board. So about 25 or 30 of our largest customers across the world, we engaged with them very, very quickly. That's all of the CIOs presidents, vice presidents of styles, um, and we engage with them on a survey and said, How are you thinking about it's what are the what are your big concerns and, you know, not unusually. They came back with a couple of key things. Number one was, and their primary concern is how do they support their clients? That was probably number one on their list of things followed very closely. By enabling their firms that have a financial stability that was number two and then probably number three. I would say it was, you know, managing their work. But they're moving to a digital only type of environment, similar to what IBM has done ever kind of the three, the three big concerns. And then we spent some time talking to them about how we could help, then really deal with that and address some of those problems. And earlier this week, we we announced so therefore very key things around. How do we help them? One. How do we adapt our programs and our incentives and, uh, really looking at providing them with, you know, extension of things like loyalty program. So don't worry about you know, your ability to re validate and recertify. We gotta protect your loyalty for 2020. We added a lot of incentives in the hardware systems program in the second quarter, so we've increased by half a percent off their based incentive from the first dollar that a lot of areas around programs in terms. Then we sort of really tried to address that point of view around digital. Um, some companies were digitally ready, but there are many companies that weren't actually know a digital platform, but also we very quickly rolled out what we call it my digital marketing platform, where partners can come in and download content and curate content from IBM and then wrap their own campaigns around that and get that out and continue to engage with their clients and their partners. Um, and we funding all of that 100% from an IBM perspective on using our car marketing goals. We used to have a 50 50 funding model without with their partners. But in this particular scenario, that's a digital program that they're running with funding at 100%. And then we're also opening up to provide consultancy on how to optimize digital. So I think you know the thing that we've done here is just their programs in terms quickly, um, or money back into the into the program during the second quarter and protect the ability for our partners and then really trying to help them and enable them to get Teoh Digital our workforce and the digital program. >>Yeah, a couple things there. I mean, we were talking earlier to the the folks from IBM Global Finance, and that's a key part that you mentioned liquidity. You know, certainly these partners air obviously very much concerned about the uncertainty ahead. So having a partner like IBM that can, whether it's, you know, pass on, you know, lease terms, etcetera and provide that sort of blacking is this key? I think the other thing, too we've heard from a lot of executives, is you've got to stay close to your clients during we always do, but especially during times like this, And that's where partners are so crucial in IBM huge company, you know, massive direct sales force, but you can't cover everything. And so having the partner who's got intimate relationships, I mean, I was on a call earlier this week with a partner in Minneapolis I mean, he knows everybody in that region. And so you just that level of intimacy, I think becomes very, very important in times like this, doesn't it? >>Absolutely. And stay connected with with that. So we have about, you know, just a lot of, Ah, 21,000 active planners across across the world and staying close to the senior members of our largest partners is is really important to us. We had a We hosted a call earlier this week actually, with with their advisory council to test the programs that we've gotten in the market, Are they getting where they need, where they need the help the most? We take a lot of feedback with adjusted our programs. We're looking at this on a literally a daily basis right now on don't envisage that we would we would update pretty agile in terms of how we move that. But you know, to your point, having a partner network that we do have around by the hardware and software only on and is right, so learn what were wrong. You know what they're hearing from their pot from their clients and, you know, it allows us to more easily and quickly address needs across all of the IBM client set. >>So we interview a lot of partners, and, you know, when you talk to the familiar, they've got to make money. They have. The margin is very important to them, but it's almost it's table stakes. I mean, again, they can make money a lot of different ways. So what differentiates the suppliers is all these other things that you're talking about? Um, So I want to ask you when you came in to this this role, what you're doing priorities in terms of, you know, partner outreach, retaining that, that loyalty And what do you see changing a za result of this pandemic? >>Yeah, it's a great question. So look, four key priorities that we declared very early on and, by the way, you know, took over from John Touched at the time. And John has spent the last two years really transforming, um, your channel and the way we engage with channel. And so there was a lot of hard lifting that was already done, but it was sort of four. Things that we focused in on one was obviously, how do we continue? Accelerate IBM drive into the hybrid multi cloud market, particularly now with the integration of Red Hat into the organization. That's a very different, you know, sales motion that Wei had so accelerating that was one of the key parties, the 2nd 1 waas. And how do we continue to differentiate on the value and so ensuring that that our programs are staying up to speed and that they're being modernized? You know, the IBM possible program is being a program predominantly built on Recile over the last 10 years. Now the microchip that we're now talking about platforms not talking about consumption. And this week during Partner World, we're gonna talk about how we are going to evolve the part of the program to move into the rest partners who are building on platforms. And how about they're moving to consumption again, all around hybrid, multi, multi cloud. That's kind of the second thing skills, skills and expertise for out for a channel. We kind of have declared that we want our channel to be the most skilled channel in the industry, and it's really interesting, Dave, during this period of the pandemic, it's one of these times where we seem to have more recent and more time, and the partners have been giving us a lot of feedback to say during this time around. Workforce is home and is connected digitally. Why don't we? Wasn't IBM help with in enhancing the enablement programme certification? And so we're doing a lot around that. We see a Z great opportunity to CIO to really develop certifications and skills and expertise during this period. Um, and then the full thing is around winning in what we call out selective segments. And so we want our partners to operate across the IBM portfolio and across our client set. But where we really need the help and where we're putting the money in the programs is around the mid size organizations where they can bring the portfolio into places that it doesn't have this today, new clients or existing clients with with IBM. But the Jason like server was that kind of the four priorities and what we're seeing is and this situation that we're going through this pandemic going through, it's actually accelerating the areas around moving. My partner multi cloud cloud is becoming a differentiator for us and accelerating. I need to get a program that is relevant beyond just resell. But you know this, this concept of platforms and building. But as they build with their own light beyond platform and consumption, So I think it's it's actually accelerating what we've seen and have it moving forward. >>It's interesting what you're saying about resale. We've talked many, many years now on the Cube about the partner ecosystem. It really used to be about resale. You know, we have a majority of his box selling, and you could make a lot of money doing that, you know, a decade or two ago. But when Cloud came, partners really started to underst and that that there was a sea change happening in I T. For a while there, they thought, Wow, you know, this is really going to be challenging. Cloud's going to kill us. But what they realized after a while is with five exactly complex hybrid Cloud is it's not simple to cure and create a seamless experience across clouds on prime etcetera. So the huge opportunities open up, add value. So there's been a massive change in the mindset. Uh, and it sounds like particularly with digital, that the pandemic is going to accelerate that on. People are going to come out of this, um, almost having done some exercises, maybe in a little bit better shape than they came into it. You buy that premise? >>My question is no question about it. I mean, if you think about, you know, IBM portfolio for a minute. Um, and over the last really 6 to 9 months, we have containerized out our software portfolio. It's based on the, you know, the kubernetes container ization and an open ship. So we're ready from a portfolio perspective. And, you know, now we're catching up from a program perspective we're introducing this week and out in the world this concept of a build program and a service program, and so that is their will preserve and continue to evolve the cell program that resell. But you know this concept of the build program and the service programs and only extend the reach that we have to the data and the ecosystem that we're operating in new sets of partners. But is that one of transition, that business from recent consumption? We're going to support that. But then you have to your point around this whole digital everything from digital capabilities around, generating amount of opportunity and a little bit about that earlier with my program and the funding that we've got behind that the experience that we're we're offering as consultants, but also this concept of digital selling. You know, there's not all about partners are savvy around digital selling. So we've been doing that for many, many years. And, uh and so we're opening up digital selling Enablement sessions, Webinars consultancy and a bunch of assets that that IBM has and has invested in for many, many years and opening that up to you want to add channel? >>Yes, There was some great opportunities there for our partners. I mean, we The Cube has been covering the Red Hat Summit we had Jim Whitehurst on. We're in the process of scheduling Arvin so great to see, you know, kind of connect the dots between those franchises and identify the opportunities, and they're significant. I mean, Red Hat has a lot of momentum in the market. IBM has a huge presence, great opportunity to modernize applications, And then your point about the hardware side we just saw on IBM s latest earnings, released at the Fisher running in hardware right now on, uh, you know, obviously tailwind of the Z cycle, but other parts of the portfolio storage from 19%. So so some exciting times for partners, even though there's so much uncertainty in the market again, staying close to customers, you know, doing doing right by your employees, leveraging the IBM relationship where you're obviously providing a lot of backdrop in support. David, I wonder if you could just sort of wrap a bow around. You know, think 2020 is the virtual trucks are pulling away away from the virtual digital Mosconi. What's the take? Aways will give us the bumper sticker. >>Look, the bumper sticker is that it's never been a better time to be an idea. We've got a leading portfolio that is now ready for the new world. Will the consumption and the world building on um, we are, you know, we're modernizing our programs to ensure that you can make money here. There's a lot of money to be made as we as we get into this thing, this new world and we are behind you right now to support you financially and to get you develop digitally enabled guy. So never been a time to be an IBM partner right now. >>David. Great message. Thank you very much for coming on the Cube. And best of luck to you. Stay safe and ah, again, really appreciate your time. >>You too, Dave. Thanks very much. Bye. Site. >>You know, uh, and you're watching the Cube here at IBM? Think 2020. Our digital coverage. We'll be right back right after this short break. I'm Dave Volante, and you're watching the Cube? >>Yeah, yeah, yeah.

Published Date : May 5 2020

SUMMARY :

Think brought to you by IBM. Who's the general manager of the IBM Great to be here. How are you communicating to them? So don't worry about you know, whether it's, you know, pass on, you know, lease terms, etcetera and provide But you know, to your point, having a partner network that we do have around So we interview a lot of partners, and, you know, when you talk to the familiar, they've got to make money. on and, by the way, you know, took over from John Touched at the time. You know, we have a majority of his box selling, and you could make a lot of money doing that, Um, and over the last really 6 to 9 months, in the market again, staying close to customers, you know, doing doing right by your employees, There's a lot of money to be made as we as we get into this thing, this new world and we are And best of luck to you. You know, uh, and you're watching the Cube here at IBM?

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Bill Smith, IBM Global Financing | IBM Think 2020


 

[Music] from the cube studios in Palo Alto in Boston it's the cube covering the IBM think brought to you by IBM welcome back to the cubes coverage of IBM think 2020 the digital version of IBM think Bill Smith is here he's the general manager of IBM Global Financing bill thanks for coming on thank you very much for having me up I'm looking forward to it yeah me too so you know I remember the days of the the glory days of IBM you know leasing I used to run the leasing program for a couple of years at IDC and it was just it was an awesome time but things have changed a lot I mean iBM has really transformed its financing army what do we need to know about today's IBM Global Financing well some things are still saying but as you said a lot is different we constantly are celebrating our 40th anniversary this year a big part of our business is now software and services financing a lot of project man Singh we still do a lot of hardware business but it's a much much smaller portion of our thirty billion dollar asset base so it's a great business it was a great business back then when you were involved in it the very profitable and and interesting business today as it was then as I said big difference though a lot of software and services yeah well I've of course I would have mentioned that most if not all mainframes are still leased but now you've expanded it to many many more areas what can you tell us about you know some of the financial metrics you know what's the profile of the business look like yeah sure it's a it's a big business it looks a lot like a bank and we're around 30 billion in asset we do business and you know 40 plus countries around the world 26% return on equity most of the portfolio's very high percentage of that portfolio is investment rate so a couple other key metrics is we we actually issue our own debt we became an SCC registrant a couple years ago we have a you know many debt holders we only have one owner and one equity owner and that's IBM it's a very good business but 2% of IBM's revenue but about 10% of IBM's from yeah well so now this is an important aspect that I want to join to it when people you know look at the IBM balance sheet they'll you know go out or whatever Yahoo Finance and say oh my gosh look at all this debt must be you know I know of course the redhead acquisition is part of that but you're carrying a lot of the debt as part of the financing operation but people need to understand it's a very profitable and very high quality debt and if we could just address that one of the big benefits to becoming an SCC registrant is the amount of transparency that we were able to provide the investors so unlike other captive financing companies they just get rolled in to different units or parts of the books you know we actually report in the segment reporting every quarter we certify just like they you know public company would we're still a wholly owned subsidiary but the level of transparency is really great for the investors which is why you know debt holders were able to Willington by our paper it's still a very client based business we do very specialized structures we only do business and NIT as I told the board many times I'd be on board many times we don't do planes trains and automobiles we only do we only do I see and and really you know 99 percent of our businesses is IBM only so you talked about branching into software and services I'm interested in how the the client base has has transformed as a result of that sure you know there's a lot of digital transformations going on there's still a lot of ERP implementations around the world very large project so we we described it as project financing so if client will come to us and say bill we'd like to match the benefit of this very large GBS or services engagement that the IBM team is leading we like to match the benefit when we have the cash outlay so we'll put a structure together that will delay the payment for when those benefits begin to come online for the enterprise and then match payment with when benefits are actually received it's proven to be a very very effective financing instrument for us but highly effective economic instruments for the clients also gives if I'm you know contracting with IBM services you've got a major incentive for the services organization to deliver value as soon as possible and that aligns everybody doesn't it it absolutely does you know we have a lot of business partners where they'll do similar structures as well so other integrators you know if the redhead acquisition and and clients moving to a hybrid cloud model sometimes there's a migration that will take place between the traditional legacy systems and when they move that cloud well that bubble of been we take Dera so will will finance that migration effort for the client and again to match their cash outlays with when they receive the benefit that I've left from that cloud migration in the day there were tons of leasing companies who would take the risk and predict the residual values and then they'd take the paper and and and then it was just an awesome business and of course the government provided some incentives to do that with the investment tax credit what about things like refurbished equipment is that's still something that you do today or is that a thing of the mainframe pass that's great yeah that's a great question you know it's a it's still a really important and a sustainable business for us we we take equipment back that comes off of a lease or sometimes alone but typically a lease and we will refurbish that or reman factor that equipment and then put it back into market oftentimes it goes into our services organization for them to use with their clients the global technology services typically you know we will we will matram a fact or a remarket about 29,000 IT devices a week 16,000 tons of idea quipment around the in a year around the world so these remanufacturing refurbishing centers so it's a even though the hardware business has come down in its percentage of IBM's business compared to software and services it's still a very very big business as you can see by the the size of the number of equipment and the tonnage what about some of the initiatives that are so you mentioned you know the digital transformation a lot going on with cloud machine intelligence I mean those big projects you know some of them are still multi-year you know seven weeks people say oh there's no more multi-year projects but digital transformations are multi-year projects even though you might take them in chunks but I'm going to capitalize those can I finance them as well what role does does IBM finance play in that you absolutely can and and that is a big big part of our business today though the the client will they look I've got a very large digital transformation project going to take place in four countries we are looking for an opportunity to match those cash outlays with when those countries come online or when we begin to receive the benefits we also want you've been and some of the software that goes with this digital transformation and we also want to spin and the IT infrastructure that's required so we may put those services software and hardware on a different financial instruments but it looks like you know one total bill for the client and it and its global it's a global footprint so we're able to handle the different currencies around the world and and again most importantly match those cash outlays with when the benefits are received so bill you know as long as I've been in this business the IT investments from a CFOs perspective have always been viewed as a higher risk granted higher reward but but you know the the CFOs would say okay you're gonna have to have a little higher IRR for this one because you know the business moves so fast technology changes so quickly how are you seeing the CIO - CFO conversation evolve what's your advice to see iPods in terms of how they talk to two CFO's that's another really good question so I was just on with actually new client this morning one was the F of the other one was a treasurer and they were asking my opinion about this financial instrument and and and getting some advice actually the conversation went look it's not really cost the debt issue the cost of money is always part of the economic decision but oftentimes those clients use financing instrument as a way to manage the asset manage the asset throughout the life the project they also want to focus on the delivery the quality of the delivery I think that takes place during these very very large project financing engagements so the CFO specifically said look I really like business case it's quite clear when we're gonna receive these benefit what I'd like to know Bill is how do you view the risk of the implementation and you know we were able to share with them the risk work that we do with with GBS team our level of confidence that it will be done on time and on budget and the skill level of the of the partner team that's been assigned so it actually has allowed us to have a different conversation with different group or senior level at the account CFO Treasury sometimes the controller you play an important role in de-risking the the business case and as well I mean I would imagine right now in there you know these on certain times that you know IBM Global Financing can provide liquidity to businesses who need it that you you know are confident you know are stable business but might need some help you know getting through this pandemic we can and as you said the what makes us a little different is you know we make credit decisions on what we call arm's length credit visions you know for a standalone albeit at the financing company so we're very very focused on maintaining the right investment grade of the portfolio we're going to make really really good prudent risk decisions you know that being said we have some fabulous IBM clients that have been clients for a long time we work very closely with them understanding their financial structures what's what's important to them and they're very transparent with us about you know with financial challenges they have so we'll continue to provide that liquidity we are going to be very prudent but we'll certainly help those really good clients well last question it's kind of where do you see this going what's your kind of vision for IBM global global finance and give us a little glimpse of the future sure you know I think you'll see us continue to migrate in the direction of the IBM company moves the IBM company is aggressively moving towards a hybrid cloud model we'll continue to provide those migration services will continue to do you know some short-term financing a part of the business we didn't talk about was the commercial financing we provide short-term working capital through IBM 6000 isness partners so to help them with their free cash flow running their businesses you know that's a pretty big business for us we'll do about you know 14 billion or so in financing to that commercial financing business so I'll see that continue as well and then finally I'm sure you'll see us continue to grow the software and services financing as well and we'll stay with the very very high anything rate for whatever is left of IBM's Hardware portfolio point you made about the partner financing is huge like you said it helps them bridge their free cash flow it makes IBM a more attractive partner for through those resellers and partners it does and we've been in that business for a very very long time oftentimes we are one of the you know largest predators for those partners so the liquidity that we provide Danville allow them to run their businesses day to day with that short term working capital is something that we're very committed to you over the long term for IBM product and services so IBM Global Financing a very important and strategic part of IBM's business a differentiator a very few companies actually can provide that type of service to their clients and so bill really appreciate you coming to the Kuban and sharing that with with our audience great to have you back yeah very much Brad you've been a real pleasure - our pleasure as well thank you for watching everybody this is Dave Volante for the cube our continuous coverage of IBM think 2020 we'll be right back right after this short break you're watching the cube [Music] you

Published Date : May 5 2020

**Summary and Sentiment Analysis are not been shown because of improper transcript**

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IBM promo Aliye SOLO v1


 

>>Hi, everyone. My name is Julia Moskin. Indeed. Data operations data offs, global marketing leader >>at IBM. >>Big data is all about delivering trusted data fast through applications, operations, >>the business user. Why important? >>Why now? To meet market demands past and to give it to changing market conditions past. It is essential for organizations to put the right data into the right hands at the right time passed. And that is what they do provide a data ops gets you well, I believe we put in our virtual program for you. Bringing industry experts from Standard sprang from Associated Bank from Hardy Davidson and also from IBM Global Data >>Office Chief Data Office >>sharing their experiences discussing the why the what and the how, as well as discussing the questions like, Is there the best time to implement today the ops program? More importantly, you will have a chance to chat with the crowd and with these experts and subject matter experts and beyond During 30 minutes asking your questions, sharing your insights, it will be a very fulfilling learning experience for you. We're looking forward to seeing you there. Stay well. Stay safe. >>Thank you.

Published Date : May 4 2020

SUMMARY :

the business user. for organizations to put the right data into the right hands forward to seeing you there.

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Survey Data Shows Momentum for IBM Red Hat But Questions Remain


 

>> From the SiliconANGLE Media office in Boston, Massachusetts, it's theCUBE! (upbeat electronic music) Now, here's your host, Dave Vellante. >> Hi, everybody, this is Dave Vellante, and I want to share with you some recent survey data that talks to the IBM acquisition of Red Hat, which closed today. It's always really valuable to go out, talk to practitioners, see what they're doing, and it's a hard thing to do. It's very expensive to get this type of survey data. A lot of times, it's very much out of date. You might remember. Some of you might remember a company called the InfoPro. Its founder and CEO was Ken Male, and he raised some money from Gideon Gartner, and he had this awesome survey panel. Well, somehow it failed. Well, friends of mine at ETR, Enterprise Technology Research, have basically created a modern version of the InfoPro. It's the InfoPro on steroids with a modern interface and data science behind it. They've now been at this for 10 years. They built a panel of 4,500 users, practitioners that they can go to, a lot of C level folks, a lot of VP level and then some doers down at the engineering level, and they go out and periodically survey these folks, and one of the surveys they did back in October was what do you think of the IBM-Red Hat acquisition? And then they've periodically gone out and talked to customers of both Red Hat and IBM or both to get a sense of the sentiment. So given that the acquisition closed today, we wanted to share some of that data with you, and our friends at ETR shared with us some of their drill down data with us, and we're going to share it with you. So first of all, I want to summarize something that they said. Back in October, they said, "We view this acquisition as less of an attempt "by IBM to climb into the cloud game, cloud relevance, "but rather a strategic opportunity "to reboot IBM's early 1990s IT services business strategy." I couldn't agree with that more. I've said all along this is a services play connecting OpenShift from Red Hat into the what Ginni Rometty talks about as the 80% of the install base that is still on prem with the workloads at the backend of mission critical systems that need to be modernized. That's IBM's opportunity. That's why this is a front end loaded cashflow deal 'cause IBM can immediately start doing business through it services organization and generate cash. They went on to say, ETR said, "Here, IBM could position itself "as the de facto IT services partner "for Fortune 100 to Global 2000 organizations "and their digital transformations. "Therefore, in theory, this could reinvigorate "the global services business for IBM "and their overlapping customer bases "could alow IBM to recapture and accelerate a great deal "of service revenues that they have lost "over the past few years." Again, I couldn't agree more. It's less about a cloud play. It is definitely about a multi-cloud play, which is how IBM's positioning this, but services de-risks this entire acquisition in my opinion even though it's very large, 34 billion. Okay, I'm show you some data. So pull up this slide. So what ETR does is they'll go out. So this is a survey of right after the acquisition of about 132 Global 2000 practitioners across a bunch of different industries, energy, utilities, financial services, government, healthcare, IT, telco, retail consumers, so a nice cross section of industries and largely in North America but a healthy cross section of AMIA and APAC. And again, these are large enterprises. So what this slide shows is conditioned responses, which I love conditioned responses. It sort of forces people to answer which of the following best describes. But this says, "Given IBM's intent to acquire Red Hat, "do you believe your organization will be more likely "to use this new combination "or less likely in your digital transformation?" You can see here on the left hand side, the green, 23% positive, on the right hand side, 13% negative. So, the data doesn't necessarily support ETR's original conclusions and my belief that this all about services momentum because most IT people are going to wait and see. So you can see the fat middle there is 64%. Basically you're saying, "Yeah, we're going to wait and see. "This really doesn't change anything." But nonetheless, you see a meaningfully more positive sentiment than negative sentiment. The bottom half of this slide shows, the question is, "Do you believe that this acquisition "makes or will make IBM a legitimate competitor "in the cloud wars between AWS and Microsoft Azure?" You can see on the left hand side, it says 45% positive. Very few say, all the way on the left hand side, a very legitimate player in the cloud on par with AWS and Azure. I don't believe that's the case. But a majority said, "IBM is surely better off "with Red Hat than without Red Hat in the context of cloud." Again, I would agree with that. While I think this is largely a services play, it's also, as Stu Miniman pointed out in an earlier video with me, a cloud play. And you can see it's still 38% is negative on the right hand side. 15% absolutely not, IBM is far behind AWS and Azure in cloud. I would tend to agree with that, but IBM is different. They're trying to bring together its entire software portfolio so it has a competitive approach. It's not trying to take Azure and AWS head on. So you see 38% negative, 45% positive. Now, what the survey didn't do is really didn't talk to multi-cloud. This, to me, puts IBM at the forefront of multi-cloud, right in there with VMware. You got IBM-Red Hat, Google with Anthos, Cisco coming at it from a network perspective and, of course, Microsoft leveraging its large estate of software. So, maybe next time we can poke at the multi-cloud. Now, that survey was done of about over 150, about 157 in the Global 2000. Sorry, I apologize. That was was 137. The next chart that I'm going to show you is a sentiment chart that took a pulse periodically, which was 157 IT practitioners, C level executives, VPs and IT practitioners. And what this chart shows essentially is the spending intentions for Red Hat over time. Now, the green bars are really about the adoption rates, and you can see they fluctuate, and it's kind of the percentage on left hand side and time is on the horizontal axis. The red is the replacement. We're going to replace. We're not going to buy. We're going to replace. In the middle is that fat middle, we're going to stay flat. So the yellow line is essentially what ETR calls market share. It's really an indication of mind share in my opinion. And then the blue line is spending intentions net score. So what does that mean? What that means is they basically take the gray, which is staying the same, they subtract out the red, which is we're doing less, and they add in the we're going to do more. So what does this data show? Let's focus on the blue line. So you can see, you know, slightly declining, and then pretty significantly declining last summer, maybe that's 'cause people spend less in the summer, and then really dropping coming into the announcement of the acquisition in October of 2018, IBM announced the $34 billion acquisition of Red Hat. Look at the spike post announcement. The sentiment went way up. You have a meaningful jump. Now, you see a little dip in the April survey, and again, that might've been just an attenuation of the enthusiasm. Now, July is going on right now, so that's why it's phased out, but we'll come back and check that data later. So, and then you can see this sort of similar trend with what they call market share, which, to me, is, again, really mind share and kind of sentiment. You can see the significant uptick in momentum coming out of the announcement. So people are generally pretty enthusiastic. Again, remember, these are customers of IBM, customers of Red Hat and customer of both. Now, let's see what the practitioners said. Let's go to some of the open endeds. What I love about ETR is they actually don't just do the hardcore data, they actually ask people open ended questions. So let's put this slide up and share with you some of the drill down statements that I thought were quite relevant. The first one is right on. "Assuming IBM does not try to increase subscription costs "for RHEL," Red Hat Enterprise Linux, "then its organizational issues over sales "and support should go away. "This should fix an issue where enterprises "were moving away from RHEL to lower cost alternatives "with significant movement to other vendors. "This plus IBM's purchase of SoftLayer and deployment "of CloudFoundry will make it harder "for Fortune 1000 companies to move away from IBM." So a lot implied things in there. The first thing I want to mention is IBM has a nasty habit when it buys companies, particularly software companies, to raise prices. You certainly saw this with SPSS. You saw this with other smaller acquisitions like Ustream. Cognos customers complained about that. IBM buys software companies with large install bases. It's got a lock in spec. It'll raise prices. It works because financially it's clearly worked for IBM, but it sometimes ticks off customers. So IBM has said it's going to keep Red Hat separate. Let's see what it does from a pricing standpoint. The next comment here is kind of interesting. "IBM has been trying hard to "transition to cloud-service model. "However, its transition has not been successful "even in the private-cloud domain." So basically these guys are saying something that I've just said is that IBM's cloud strategy essentially failed to meet its expectations. That's why it has to go out and spend $34 billion with Red Hat. While it's certainly transformed IBM in some respects, IBM's still largely a services company, not as competitive as cloud as it would've liked. So this guys says, "let alone in this fiercely competitive "public cloud domain." They're not number one. "One of the reasons, probably the most important one, "is IBM itself does not have a cloudOS product. "So, acquiring Red Hat will give IBM "some competitive advantage going forward." Interesting comments. Let's take a look at some of the other ones here. I think this is right on, too. "I don't think IBM's goal is to challenge AWS "or Azure directly." 100% agree. That's why they got rid of the low end intel business because it's not trying to be in the commodity businesses. They cannot compete with AWS and Azure in terms of the cost structure of cloud infrastructure. No way. "It's more to go after hybrid multi-cloud." Ginni Rometty said today at the announcement, "We're the only hybrid multi-cloud, opensource vendor out there. Now, the third piece of that opensource I think is less important than competing in hybrid and multi-cloud. Clearly Red hat gives IMB a better position to do this with CoreOS, CentOS. And so is it worth 34 billion? This individual thinks it is. So it's a vice president of a financial insurance organization, again, IBM's strong house. So you can here some of the other comments here. "For customers doing significant business "with IBM Global Services teams." Again, outsourcing, it's a 10-plus billion dollar opportunity for IBM to monetize over the next five years, in my opinion. "This acquisition could help IBM "drive some of those customers "toward a multi-cloud strategy "that also includes IBM's cloud." Yes, it's a very much of a play that will integrate services, Red Hat, Linux, OpenShift, and of course, IBM's cloud, sprinkle in a little Watson, throw in some hardware that IBM has a captive channel so the storage guys and the server guys can sell their hardware in there if the customer doesn't care. So it's a big integrated services play. "Positioning Red Hat, and empowering them "across legacy IBM silos, will determine if this works." Again, couldn't agree more. These are very insightful comments. This is a largely a services and an integration play. Hybrid cloud, multi-cloud is complex. IBM loves complexity. IBM's services organization is number one in the industry. Red Hat gives it an ingredient that it didn't have before other than as a partner. IBM now owns that intellectual property and can really go hard and lean in to that services opportunity. Okay, so thanks to our friends at Enterprise Technology Research for sharing that data, and thank you for watching theCUBE. This is Dave Vellante signing off for now. Talk to you soon. (upbeat electronic music)

Published Date : Jul 9 2019

SUMMARY :

From the SiliconANGLE Media office and it's kind of the percentage on left hand side

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Inderpal Bhandari & Martin Schroeter, IBM | IBM CDO Summit 2019


 

(electronica) >> Live, from San Francisco, California it's theCube. Covering the IBM Chief Data Officer Summit. Brought to you by IBM. >> We're back at Fisherman's Wharf covering the IBM Chief Data Officer event, the 10th anniversary. You're watching theCube, the leader in live tech coverage. Just off the keynotes, Martin Schroeter is here as the Senior Vice President of IBM Global Markets responsible for revenue, profit, IBM's brand, just a few important things. Martin, welcome to theCube. >> They're important, they're important. >> Inderpal Bhandari, Cube alum, Global Chief Data Officer at IBM. Good to see you again. >> Good to see you Dave, >> So you guys, just off the keynotes, Martin, you talked a lot about disruption, things like digital trade that we're going to get into, digital transformation. What are you hearing when you talk to clients? You spent a lot of time as the CFO. >> I did. >> Now you're spending a lot of time with clients. What are they telling you about disruption and digital transformation? >> Yeah, you know the interesting thing Dave, is the first thing every CEO starts with now is that "I run a technology company." And it doesn't matter if they're writing code or manufacturing corrugated cardboard boxes, every CEO believes they are running a technology company. Now interestingly, maybe we could've predicted this already five or six years ago because we run a CEO survey, we run a CFO, we run surveys of the C-suite. And already about five years ago, technology was number one on the CEO's list of what's going to change their company in the next 3-5 years. It led. The CFO lagged, the CMO lagged, everyone else. Like, CEO saw it first. So CEOs now believe they are running technology businesses, and when you run a technology business, that means you have to fundamentally change the way you work, how you work, who does the work, and how you're finding and reaching and engaging with your clients. So when we talk, we shorthand of digitizing the enterprise. Or, what does it mean to become a digitally enable enterprise? It really is about how to use today's technology embedded into your workflows to make sure you don't get disintermediated from your clients? And you're bringing them value at every step, every touchpoint of their journey. >> So that brings up a point. Every CEO I talk to is trying to get "digital right." And that comes back to the data. Now you're of course, biased on that. But what are your thoughts on a digital business? Is digital businesses all about how they use data and leverage data? What does it mean to get "digital right" in your view? >> So data has to be the starting point. You actually do see examples of companies that'll start out on a digital transformation, or a technology transformation, and then eventually back into the data transformation. So in a sense, you've got to have the digital piece of it, which is really the experience that users have of the products of the company, as well as the technology, which is kind of the backend engines that are running. But also the workflow, and being able to infuse AI into workflows. And then data, because everything really rides on the data being in good enough shape to be able to pull all this off. So eventually people realize that really it's not just a digital transformation or technology transformation, but it is a data transformation to begin with. >> And you guys have talked a lot at this event, at least this pre-event, I've talked to people about operationalizing AI, that's a big part of your responsibilities. How do you feel about where you're at? I mean, it's a journey I know. You're never done. But feel like you're making some good progress there? Internally at IBM specifically. >> Yes, internally at IBM. Very good progress. Because our whole goal is to infuse AI into every major business process, and touch every IBM. So that's the whole goal of what we've been doing for the last few years. And we're already at the stage where our central AI and data platform for this year, over 100,000 active users will be making use of it on a regular basis. So we think we're pretty far along in terms of our transformation. And the whole goal behind this summit and the previous summits as you know, Dave, has been to use that as a showcase for our clients and customers so that they can replicate that journey as well. >> So we heard Ginni Rometty two IBM thinks ago talk about incumbent disruptors, which resonates, 'cause IBM's an incumbent disruptor. You talked about Chapter One being random acts of digital. and then Chapter Two is sort of how to take that mainstream. So what do you see as the next wave, Martin? >> Well as Inderpal said, and if I use us as an example. Now, we are using AI heavily. We have an advantage, right? We have this thing called IBM Research, one of the most prolific Inventors of Things still leads the world. You know we still lead the world in patents so have the benefit. For our our clients, however, we have to help them down that journey. And the clients today are on a journey of finding the right hybrid cloud solution that gives them bridges sort of "I have this data. "The incumbency advantage of having data," along with "Where are the tools and "where is the compute power that I need to take advantage of the data." So they're on that journey at the same time they're on the journey as Inderpal said, of embedding it into their workflows. So for IBM, the company that's always lived sort of at the intersection of technology and business, that's what we're helping our clients to do today. Helping them take their incumbent advantage of data, having data, helping them co-create. We're working with them to co-create solutions that they can deploy and then helping them to put that into work, into production, if you will, in their environments and in their workflows. >> So one of the things you stressed today, two of the things. You've talked about transparency, and open digital trade. I want to get into the latter, but talk about what's important in Chapter Two. Just, what are those ingredients of success? You've talked about things like free flow of data, prevent data localization, mandates, and protect algorithms and source codes. You also made another statement which is very powerful "IBM is never giving up its source code to our government, and we'd leave the country first." >> We wouldn't give up our source code. >> So what are some of those success factors that we need to be thinking about in that context? >> If we look at IBM. IBM today runs, you know 87% of the world's credit card transactions, right? IBM today runs the world's banking systems, we run the airline reservation systems, we run the supply chains of the world. Hearts and lungs, right? If I just shorthand all of that, hearts and lungs. The reason our clients allow us to do that is because they trust us at the very core. If they didn't trust us with our data they wouldn't give it to us. If they didn't trust us to run the process correctly, they wouldn't give it to us. So when we say trust, it happens at a very base level of "who do you really trust to run you're data?" And importantly, who is someone else going to trust with your data, with your systems? Any bank can maybe figure out, you know, how to run a little bit of a process. But you need scale, that's where we come in. So big banks need us. And secondly, you need someone you can trust that can get into the global banking system, because the system has to trust you as well. So they trust us at a very base level. That's why we still run the hearts and lungs of the enterprise world. >> Yeah, and you also made the point, you're not talking about necessarily personal data, that's not your business. But when you talked about the free flow of data, there are governments of many, western governments who are sort of putting in this mandate of not being able to persist data out of the country. But then you gave an example of "If you're trying to track a bag at baggage claim, you actually want that free flow of data." So what are those conversations like? >> So first I do think we have to distinguish between the kinds of data that should frow freely and the kinds of data that should absolutely, personal information is not what we're talking about, right? But the supply chains of the world work on data, the banking system works on data, right? So when we talk about the data that has to flow freely, it's all the data that doesn't have a good reason for it to stay local. Citizen's data, healthcare data, might have to stay, because they're protecting their citizen's privacy. That's the issue I think, that most governments are on. So we have disaggregate the data discussion, the free flow of data from the privacy issues, which are very important. >> Is there a gray area there between the personal information and the type of data that Martin's talking about? Or is it pretty clear cut in your view? >> No, I think this is obviously got to play itself out. But I'll give you one example. So, the whole use of a blockchain potentially helps you address and find the right balance between privacy of sensitive data, versus actually the free flow of data. >> Right. >> Right? So for instance, you could have an encryption or a hashtag. Or hash, sorry. Not a hashtag. A hash, say, off the person's name whose luggage is lost. And you could pass that information through, and then on the other side, it's decrypted, and then you're able to make sure that, you know, essentially you're able to satisfy the client, the customer. And so there's flow of data, there's no issue with regard to exposure. Because only the rightful parties are able to use it. So these things are, in a sense, the technologies that we're talking about, that Martin talked about with the blockchain, and so forth. They are in place to be able to really revolutionize and transform digital trade. But there are other factors as well. Martin touched on a bunch of those in the keynote with regard to, you know, the imbalances, some of the protectionism that comes in, and so on and so forth. Which all that stuff has to be played through. >> So much to talk about, so little time. So digital trade, let's get into that a little bit. What is that and why is it so important? >> So if you look at the economic throughput in the digital economy, the size of the GDP if you will, of what travels around the world in the way data flows, it's greater than the traded goods flow. So this is a very important discussion. Over the last 10 years, you know, out of the 100% of jobs that were created, 80% or so had a digital component to it. Which means that the next set of jobs that we're creating, they require digital skills. So we need a set of skills that will enable a workforce. And we need a regulatory environment that's cooperative, that's supportive. So in the regulatory environment, as we said before, we think data should flow freely unless there's a reason for it not to flow. And I think there will be some really good reasons why certain data should not flow.. But data should flow freely, except for certain reasons that are important. We need to make sure we don't create a series of mandates that force someone to store data here. If you want to be in business in a country, the country shouldn't say "Well if you want to business here "you have to store all your data here." It tends to be done on the auspice of a security concern, but we know enough about security that doesn't help. It's a false sense of security. So data has to flow freely. Don't make someone store it there just because it may be moving through or it's being processed in your country. And then thirdly, we have to protect the source code that companies are using. We cannot force, no country should force, a company to give up their source code. People will leave, they just won't do business there. >> That's just not about intellectual property issue there, right? >> It's huge intellectual property issue, that's exactly right. >> So the public policy framework then, is really free flow of data where it makes sense. No mandates unless it makes sense, and- >> And protection of IP. >> Protection of IP. >> That's right. >> Okay, good. >> It's a pretty simple structure. And based on my discussions I think most sort of aligned with that. And we're encouraged. I'm encouraged by what I see in TPP, it has that. What I see in Europe, it has that. What I see in USMCA it has that. So all three of those very good, but they're three separate things. We need to bring it all together to have one. >> So it was a good example. GDDPR maybe as a framework that seems to be seeping its way into other areas. >> So GDPR is an important discussion, but that's the privacy discussion wrapped around a broader trade issue. But privacy is important. GDPR does a good job on it, but we have a broader trade issue of data. >> Inderpal give me the final word, it's kind of your show. >> Well, you know. So I was just going to say Dave, I think one way to think about it is you have to have the free flow of data. And maybe the way to think about it is certain data you do need controls on. And it's more of the form in which the data flows that you restrict. As opposed to letting the data flow at all. >> What do you mean? >> So the hash example that I gave you. It's okay for the hash to go across, that way you're not exposing the data itself. So those technologies are all there. It's much more the regulatory frameworks that Martin's talking about, that they've got to be there in place so that we are not impeding the progress. That's going to be inevitable when you do have the free flow of data. >> So in that instance, the hash example that you gave. It's the parties that are adjudicating, the machines are adjudicating. Unless the parties want to expose that data it won't be exposed. >> It won't happen, they won't be exposed. >> All right. Inderpal, Martin, I know you got to run. Thanks so much for coming out. >> Thank you. Thanks for the talk. >> Thank you >> You're welcome. All right. Keep it right there everybody, we'll be back with our next guest from IBMCDO Summit in San Francisco. You're watching theCube. (electronica)

Published Date : Jun 24 2019

SUMMARY :

Brought to you by IBM. as the Senior Vice President of IBM Global Markets Good to see you again. So you guys, just off the keynotes, What are they telling you about disruption the way you work, how you work, who does the work, And that comes back to the data. So data has to be the starting point. And you guys have talked a lot at this event, and the previous summits as you know, Dave, So what do you see as the next wave, Martin? So for IBM, the company that's always lived So one of the things you stressed today, because the system has to trust you as well. But when you talked about the free flow of data, and the kinds of data that should absolutely, So, the whole use of a blockchain Because only the rightful parties are able to use it. So much to talk about, so little time. So in the regulatory environment, as we said before, It's huge intellectual property issue, So the public policy framework then, We need to bring it all together to have one. GDDPR maybe as a framework that seems to be seeping its way but that's the privacy discussion And it's more of the form in which the data flows So the hash example that I gave you. So in that instance, the hash example that you gave. Inderpal, Martin, I know you got to run. Thanks for the talk. Keep it right there everybody,

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Day 2 Keynote Analysis | Dell Technologies World 2019


 

>> Live from Las Vegas, it's theCUBE! Covering Dell Technologies World 2019. Brought to you by Dell Technologies and its ecosystem partners. >> Hello everyone, welcome to theCUBE's live coverage here in Las Vegas for Dell Technologies World 2019. I'm John Furrier, Stu Miniman, Dave Vellante. Day two of three days of wall-to-wall coverage. We got two sets called theCube Cannon. We've got the Cannon of Content, interviews all day long, out at night at the analyst briefings, meet-ups, receptions, talking to all the executives at Dell Technologies VMware and across the industry. Stu, Dave, today is product announcements on the keynotes. Yesterday was the grand vision with Michael Dell and the big reveal on the Microsoft partnership with Satya Nadella's surprise visit onstage, unveiling new Azure-VMware integrations with Dell Technologies. Dell announced the Dell Cloud, which is a little bit of Virtustream, but they're trying to position this cloud, I guess it's a cloud if you want to call it a single cloud of glass. Dave, single pane in the glass with a variety of other things, unified workspace and some other things. This is Dell trying to be a supplier end-to-end. This is the pitch from Dell Technologies. We'll be talking to Michael Dell, also Pat Gelsinger, the CO of VMware. Dave, were you impressed, were you shocked, were you surprised with yesterday's big news and as the products start coming online here, what's your analysis? >> Well yesterday, John, was all about the big strategic vision, Michael Dell laying out check for good and then the linchpin of Dell strategy which of course is VMware for cloud, multicloud, hybrid cloud, kind of VMware everywhere. I was surprised that Satya Nadella flew down from Seattle and was here on stage in person. Didn't come in from the big screen. So I thought that was pretty impressive. You had the three power players up on stage. Today of course was all about the products. Both Dell and EMC have always been very practical in terms of their engineering. Stu, you used to work there. Their R&D is a lot of D. It's sort of incremental product improvements to keep the customers happy, to keep ahead of the competition, to keep the lifecycle going. They had like 10 announcements today. I can go through 'em real quick if you want, but they range from new laptops to talking about new branding on servers, new storage devices. You had PowerProtect which is their new rebranded backup and data protection and data manage portfolio, an area where Dell EMC has been behind. So lots of announcements. Another kind of mega launch tradition and again, a lot of incremental but important tactical improvements to the product line. >> Last year, what we heard from Jeff Clarke is they're looking to simplify that portfolio. Back in the EMC days, it was oh my gosh, look at the breadth of this. Every category, they had two or three offerings and you know, the stated goal is to simplify that and that means most categories are going to get one product. It's interesting. You talk about networking just got rebranded with that Power branding. I kind of said there there's marketing behind it. If you know what that product is because it's the Power brand and they put it out there. So you know, PowerMax, has been their tiered storage. They had a good update for Unity. It's Unity XT. Doesn't have a power name yet so maybe there's still some dry powder left in the product portfolio there, but they're making progress going through this 'cause these things don't happen overnight. It's great to spin up the clouds, but in the storage world, customers, they trust, they have the code, they test it out. So going to new generations, making that change, does take time but you've seen that progress. The tail end of that integration between Dell and EMC on the product side. >> Stu, what's your analysis of the products so far 'cause again like Dave said, it's a slew of announcements. What's resonating, what's popping out, what's boiling up to the surface? >> Yeah so look, the area that I spent so much time on, John, that hyper-converged infrastructure. If you look at a lot of the pieces underneath it all, it's VxRail. One of the things we've had a little bit of a challenge squinting through is oh wait, there's this managed service stack, it's VxRail underneath. Oh wait I've taken the appliance and I put VCF. Oh that's VxRail and then I've got this other, it's like I see three or four solutions and I'm like is it all just VxRail with like a VMware stack on top of it? But it's how do I package it, what applications live on it, how is it consumed, manage service, op ex, cap ex. So they've got that a little bit of complexity when VxRail itself is you know, dirt simple and really there so they're making progress on the cloud piece. Dell is the leader in hyper-converged. I'll point out, you don't hear anybody talking about Nutanix here, but Dell still has a partnership on the XC Core. They're going to sell a lot of Dell servers into Nutanix environment so I expect you'll still have the Nutanix show. John you're going to be at that next week. They're still going to talk about Dell. I'm sure you'll talk to Dheeraj. Yes they made a partnership with HP, but that does not kill the relationship with Nutanix just like Microsoft, heck. I'm going to see Satya Nadella on stage at Red Hat Summit next week and you're like oh well VMware and Red Hat. Red Hat's here. Red Hat's a Dell-ready partner. If you want to put open shift on top of their stack, they can do that so hardware and software, everybody's got their pieces, everybody's got their pieces, everybody competes a lot, but they partner across the board. IBM Global Services is here. There's so many companies here. Dell's a broad company, deep partnerships. The question I have is Pat Gelsinger was just on stage saying that this SDDC will be the building block for the future. I said kudos to them. They've got it on AWS, they've got it announced with Azure, we announced it with Google, but that is not necessarily the end state. VMware is a piece of the puzzle. I don't know if VMware will be the leader in multicloud management. vCenter was the leader in virtualization management so how much of that will there or do I get an Amazon and then start moving some stuff over? Do I get to Azure and start modernizing my environment so that I don't need to pay VMware and I don't need virtualization. VMware and Dell are going to containerize everything so in the future, are they containerware, you know? That's the competition kind of post-it note. They are VMware at their core. VMware is centra of the strategy and there's still some work to go, but they're making some good progress. >> I want to get your thoughts, guys, on the role VMware is playing here at the show. Normally they're here, usually they're here, but this year it seems to be much more smoother integration of talking points, messaging, product integrations. The show's got a good beat to it. Pretty packed, but the role of VMware, Dave, Stu, what's your reaction and thoughts? We've seen them dance all the time. Obviously VMware, Dave as you pointed out yesterday, a big part of the valuation of Dell Technologies, but what's your observation on the presence of VMware here at Dell Technologies World? >> I mean I've said many times that this company and I said this about EMC, it's kind of a boring company without VMware. You put VMware in the mix and all of a sudden, it becomes very strategic and very interesting from a lot of standpoints. Certainly from a financial standpoint. Remember, the Class V transaction that took Dell public was the result of an $11 billion dividend because of VMware. They took VMware's cash and they said okay, we're going to give nine billion to the shareholders. Without VMware, that wouldn't have happened. As well, the multicloud strategy, the underpinning of that multicloud strategy is VMWare. What strikes me, John and Stu, is that the cultural change. You had Dell, you had EMC. They said ah yeah the companies are compatible, but they're different companies. They maybe had shared kind of goals and values, but they had different cultures and really in a short timeframe, Michael Dell and his team have put these two companies together and they have aligned in a big way. I mean they are basically saying VMware and Dell, boom. That's how we're going to market and you know, Pat's coming on later today and I'm sure he'll say hey we love NetApp, we love HBE, we love IBM, but it's clear what the preferred partnership is. >> Dave, when the acquisition happened, there was talks of synergies and we were like oh where are they going to cut everything? If I look around here, they've got the seven logos of the primary companies. It's Dell, Dell EMC, Pivotal, RSA, Secureworks, Virtustream and VMware. They're one company. Michael Dell will go on calls for any of them. Friends of mine at Pivotal says you talk to Michael quite a bit. You know, he's out there. We talked about it yesterday. Dell and VMware are closer and tighter aligned than EMC and VMware ever were. Now on the one hand, EMC kept them separate because the growth of virtualization required that. Today in this cloud environment, it's a different world and it's matured so VMware, sure, there's still work on HP and IBM and all this other stuff, but Dell leads that move as you said, Dave. >> John, you're big on culture. This is a founder culture. What's your take on what Michael Dell has accomplished and how does it stand to compare with sort of other great cultural transformations that you've seen? >> Well I think HBE is a great example of a culture that split, was uncharged there. We know what happened there and I think they're hurting, they're losing talent and they're not winning in categories across the board like Dell is. I think Michael Dell, the founder-led approach that he's having 'cause he told us years ago, if you guys remember, here on the record, also privately that I'm going to take this off the table with EMC and I'm going to do all these things. We're going to execute. So he brought his execution mojo and ecos of Dell and become Dell Technologies, as Stu pointed out, a portfolio of multiple companies under one umbrella and he brought the execution discipline and this is a theme, Dave. Last night at the analysts reception, as I was talking to other analysts and talking to some of the execs, both from VMware and Dell Technologies, that the execution performance across the board both on product integration, which was a weak spot as you know, is getting better, the business performance discipline. We're going to have the CFO on here to talk more about it, they're executing. Howard Elias is going to be on this afternoon. He called this three years ago when he was talking about the integration that they saw synergies, they saw opportunities and they were going to unpack those. They stayed relentless on that. So I think this is a great example of keeping the founders around for all the VC-backed companies. You're thinking about getting rid of founders. Never let a founder leave a company. They bring the vision, they bring also some guts and grit and they bring a perspective and you can put great talent and team around that, that attract and retain great executives like Michael's done and he's poaching HPE, other companies and pulling talent in 'cause they're executing. They pay well, it's a great place to work according to the statistics. So again, this is all because of the founder and if the founder's not around, you have all the fiefdoms and the policists who kick in and then it becomes kind of sideways. So that's kind of what I see other companies that don't have founders around and HP lost their founders obviously and then the culture kind of went a little bit sideways. So they're trying to get back in the game, seeing them go back to their roots. We'll see how they do. We don't do that show anymore and again we don't have a lot of visibility into what HP's doing but we do know, Dave, that they do not have a lot of the pieces on the board that Dell does. So if you want to have an end-to-end operating model, and you're missing key value activities of an end-to-end value chain, that's going to be hard to automate, it's hard to be a performant, it's going to be hard to be successful. So I think Dell is showing the playbook of how to be horizontally scalable operationally and offer perspectives and data-driven specialism in any industry in any vertical. >> Yeah Dave, if I can just on the cultural piece 'cause it's really interesting. You talked about EMC, East Coast hard driving versus VMware, software, Silicon Valley company. While they're working together, a lot of it, you know, I talk to VMware people and they're like well it's great the Dell force is just selling our stuff. It's not like I'm having storage shoved down my throat or we have to have our arms twisted. It's the product portfolio that they're selling, the vSAN, NSX, the management software suite and those pieces, things like SD-WAN, there's some good synergies there. So the product portfolio is a nice fit that just jointly go out to market that they just really line up well together and Dell's a very different cultural beast than EMC was. >> Well again, staying on culture for a moment, when I discussed with some of the folks that I know out of Hopkinton the narrative early on was oh Dell's ruining EMC, tearing it apart and so forth. When you talk to people today, they say, you know what, it was painful. Dell came in and said okay, you're going to be accountable, really had an accountability culture, but now they've come out the other side, the narrative is it was the right thing to do. Jeff Clarke came in and sort of forced this alignment. There's like no question about it. People, this is a guy who you know, his calendar's set for the year. People know where he's going to be, what meeting he's going to have, what's expected and they're prepared and it seems to be taking hold. I mean if a $90 billion company that's growing at 14% in revenues, in profitable revenues, that's quite astounding when you think about it and I think it's a big result of the speed at which Dell has brought in its operating model to the broader EMC and transformed itself. It's quite amazing. >> Awesome show, guys. We've got clips out there on the #DellTechWorld on Twitter. We've got a lot of videos. We've got two sets here, three days of wall-to-wall coverage. Final word on this intro for day two, guys. Thoughts on the show? It's not a boring show. It's a lot of activities, a lot of things. They've got an Alienware eSports gaming studio which I think is totally badass. A lot of kind of cool things here. It's not the glitz and glam that we've seen in other EMC Worlds before or Dell Worlds, but it's meat and potatoes and it's got a spring to its step here. I feel it's not, it feels good. That's my takeaway. >> Well the big theme is hybrid cloud and multicloud. Jon Rowe as we were leaving the room today that we were early with that multicloud. Thanks for everybody else in the industry for hopping on board. The reality is the first time I heard the sort of hybrid cloud was called private cloud. Chuck Hollis wrote a blog back in the mid to late 2000s. Now I will make an observation in the customers that I talk to. Multicloud is not thus far, has not thus far has been a deliberate strategy. In my opinion, it's been the outcropping of multivendor, shadow IT, lines of business and I think the corner office is saying hold on, we need to reign this in, we need to have a better understanding of what our cloud strategy is, build a platform that is hybrid and sure, multicloud, to build our digital transformation. We need IT to basically help us build this out to make sure we comply with the corporate edicts and that's what's happening. It is early days. There's a long way to go. >> Yeah, as Dave, as you know, I sat right down the hallway from Chuck Hollis when he wrote that piece and I went and I called up Chuck and I was like hey Chuck, this sure sounds like my next generation virtual data center stuff that I joined the CTO office to work on and he's like yeah, yeah, new marketing branding and I wrote a piece, exactly what you said, Dave, on Wikibon.com, hybrid and multicloud were a bunch of pieces, you know. It's not a cohesive strategy. The management's not there. We're starting to see maturation. Some of the point products, you know, developed really fast. When we talk about VMware on AWS, that happened really fast. I heard if you stop by the VMware booth here at the show, they're showing outposts and I said is a diagram? No, no, I've got customers in production running this. I'm like hold on, I need to hear about this. Outpost in production? But that strategy as you said, hybrid and multicloud, we're starting to get there, starting to pull it together. David Foyer wrote a phenomenal piece about hybridcloud taxonomy. We've spent a lot of time on the research side. Really what does the industry need to do, how should customers think about all of the layers? You know, data and networking and all of these components to help make not just a bunch of pieces but actually drive innovation and help be better than the sum of its parts. >> Well ironic followup on that post, the Chuck Hollis post was around they called it the private cloud and it was all about homogeneity and now multicloud is everything but homogeneous. Outpost, however, is. Same hardware, same software, same control plane, same data plane so interesting juxtaposition. >> We'll see Amazon Outpost. Guys, go to SiliconAngle.com, Wikibon.com. Great hybridcloud, multicloud analysis coverage and news. And some of the headlines hitting the net here. Dell Technologies makes VMware linchpin of hybrid cloud, data center as a service, end user strategies from Zdnet. eWEEK, Dell makes major hybrid cloud push. Obviously great analysis, guys, right on the number. Day two, CUBE coverage here in Las Vegas. I'm John Furrier, Dave Vellante, Stu Miniman. We've got two sets. Rebecca Knight, Lisa Martin and more. Stay tuned for more coverage of day two after the short break. (upbeat music)

Published Date : Apr 30 2019

SUMMARY :

Brought to you by Dell Technologies and the big reveal on the Microsoft partnership Didn't come in from the big screen. and that means most categories are going to get one product. Stu, what's your analysis of the products so far but that does not kill the relationship with Nutanix is playing here at the show. What strikes me, John and Stu, is that the cultural change. of the primary companies. and how does it stand to compare with sort of other and if the founder's not around, you have all the It's the product portfolio that they're selling, and they're prepared and it seems to be taking hold. and it's got a spring to its step here. in the customers that I talk to. Some of the point products, you know, the private cloud and it was all about homogeneity And some of the headlines hitting the net here.

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Sanjay Poonen, VMware | Dell Technologies World 2019


 

>> live from Las Vegas. It's the queue covering Dell Technologies. World twenty nineteen. Brought to you by Dell Technologies and its ecosystem partners. >> The one Welcome to the Special Cube Live coverage here in Las Vegas with Dell Technologies World 2019. I'm John Furrier with Dave Vellante breaking down day one of three days of wall the wall Coverage - 2 Cube sets. Uh, big news today and dropping here. Dell Technology World's series of announcements Cloud ability, unified work spaces and then multi cloud with, uh, watershed announced with Microsoft support for VMware with Azure are guests here theCUBE alumni that Seo, senior leader of'Em Where Sanjay *** and such a great to see you, >> John and Dave always a pleasure to be on your show. >> So before we get into the hard core news around Microsoft because you and Satya have a relationship, you also know Andy Jassy very well. You've been following the Clouds game in a big way, but also as a senior leader in the industry and leading BM where, um, the evolution of the end user computing kind of genre,  that whole area is just completely transformed with mobility and cloud kind of coming together with data and all this new kinds of applications. The modern applications are different. It's changing the game on how end users, employees, normal people use computing because some announcement here on their What's your take on the ever changing role of cloud and user software? >> Yeah, John, I think that our vision , as  you know, it was the first job I came to do at VMware almost six years ago, to run and use a computing. And the vision we had at that time was that you should be able to work at the speed of life, right? You and I happen to be on a plane at the same time  yesterday coming here, we should be able to pick our amps up on our devices. You often have Internet now even up at thirty thousand feet. In the consumer world, you don't lug around your CDs, your music, your movies come to you. So the vision of any app on any device was what we articulated with the digital workspace We. had Apple and Google very well figured out. IOS later on Mac,  Android,  later on chrome . The Microsoft relationship in end use the computing was contentious because we overlapped. They had a product, PMS and in tune. But we always dreamed of a day. I tweeted out this morning that for five and a half years I competed with these guys. It was always my dream to partner with the With Microsoft. Um, you know, a wonderful person, whom I respect there, Brad Anderson. He's a friend, but we were like LeBron and Steph Curry. We were competing against each other. Today everything changed. We are now partners. Uh, Brad and I we're friends, we'll still be friends were actually partners  now why? Because we want to bring the best of the digital workspace solution VMware brings workspace one to the best of what Microsoft brings in Microsoft 365 , active directory, E3 capabilities around E. M. S and into it and combined those together to help customers get the best for any device. Apple, Google and Microsoft that's a game changer. >> Tell about the impact of the real issue of Microsoft on this one point, because is there overlap is their gaps, as Joe Tucci used to say, You can't have any. There's no there's no overlap if you have overlapped. That's not a >> better to have overlapped and seems right. A gaps. >> So where's the gaps? Where this words the overlapping cloud. Next, in the end user world, >> there is a little bit of overlap. But the much bigger picture is the complementarity. We are, for example, not trying to be a directory in the Cloud That's azure active directory, which is the sequel to Active Directory. So if we have an identity access solution that connect to active directory, we're gonna compliment that we've done that already. With Octo. Why not do that? Also inactive Directory Boom that's clear. Ignored. You overlap. Look at the much bigger picture. There's a little bit of overlap between in tune and air Watch capabilities, but that's not the big picture. The big picture is combining workspace one with E. M s. to allow Office 365 customers to get conditional access. That's a game, so I think in any partnership you have to look past, I call it sort of these Berlin Wall moments. If the U. S and Soviet Union will fighting over like East Germany, vs West Germany, you wouldn't have had that Berlin wall moment. You have to look past the overlaps. Look at the much bigger picture and I find the way by which the customer wins. When the customer wins, both sides are happy. >> Tearing down the access wall, letting you get seamless. Access the data. All right, Cloud computing housely Multi cloud announcement was azure something to tell on stage, which was a surprise no one knew was coming. No one was briefed on this. It was kind of the hush hush, the big news Michael Delll, Pat Girl singer and it's nothing to tell up there. Um, Safia did a great job and really shows the commitment of Microsoft with the M wear and Dell Technologies. What is this announcement? First, give us your take an analysis of what they announced. And what does it mean? Impact the customers? >> Yeah, listen, you know, for us, it's a further That's what, like the chess pieces lining up of'Em wars vision that we laid up many years for a hybrid cloud world where it's not all public cloud, it isn't all on premise. It's a mixture. We coined that Tom hybrid loud, and we're beginning to see that realize So we had four thousand cloud providers starting to build a stack on VM, where we announced IBM Cloud and eight of us. And they're very special relationships. But customers, some customers of azure, some of the retailers, for example, like Wal Mart was quoted in the press, released Kroger's and some others so they would ask us, Listen, we're gonna have a way by which we can host BMO Workloads in there. So, through a partnership now with Virtue Stream that's owned by Dell on DH er, we will be able to allow we, um, where were close to run in Virtue Stream. Microsoft will sell that solution as what's called Azure V M, where solutions and customers now get the benefit of GMO workloads being able to migrate there if they want to. Or my great back on the on premise. We want to be the best cloud infrastructure for that multi cloud world. >> So you've got IBM eight of us Google last month, you know, knock down now Azure Ali Baba and trying you. Last November, you announced Ali Baba, but not a solution. Right >> now, it's a very similar solutions of easy solution. There's similar what's announced with IBM and Nash >> So is it like your kids where you loved them all equally or what? You just mentioned it that Microsoft will sell the VM wear on Azure. You actually sell the eight of us, >> so there is a distinction. So let me make that clear because everything on the surface might look similar. We have built a solution that is first and preferred for us. Called were MacLeod on a W s. It's a V m er manage solution where the Cloud Foundation stack compute storage networking runs on a ws bare metal, and V. Ember manages that our reps sell that often lead with that. And that's a solution that's, you know, we announced you were three years ago. It's a very special relationship. We have now customer attraction. We announce some big deals in queue, for that's going great, and we want it even grow faster and listen. Eight of us is number one in the market, but there are the customers who have azure and for customers, one azure very similar. You should think of this A similar to the IBM ah cloud relationship where the V C P. V Partners host VM where, and they sell a solution and we get a subscription revenue result out of that, that's exactly what Microsoft is doing. Our reps will get compensated when they sell at a particular customer, but it's not a solution that's managed by BM. Where >> am I correct? You've announced that I think a twenty million dollars deal last quarter via MacLeod and A W. And that's that's an entire deal. Or is that the video >> was Oh, that was an entirely with a customer who was making a big shift to the cloud. When I talked to that customer about the types of workloads, they said that they're going to move hundreds off their APs okay on premise onto via MacLeod. And it appears, so that's, you know, that's the type of cloud transformation were doing. And now with this announcement, there will be other customers. We gave an example of few that Well, then you're seeing certain verticals that are picking as yours. We want those two also be happy. Our goal is to be the undisputed cloud infrastructure for any cloud, any cloud, any AP any device. >> I want to get your thoughts. I was just in the analysts presentation with Dell technology CFO and looking at the numbers, the performance numbers on the revenue side Don Gabin gap our earnings as well as market share. Dell. That scales because Michael Delll, when we interviewed many years ago when it was all going down, hinted that look at this benefits that scale and not everyone's seeing the obvious that we now know what the Amazon scale winds so scale is a huge advantage. Um, bm Where has scale Amazon's got scale as your Microsoft have scales scales Now the new table stakes just as an industry executive and leader as you look at the mark landscape, it's a having have not world you'd have scale. You don't If you don't have scale, you're either ecosystem partner. You're in a white space. How do companies compete in this market? Sanjay, what's your thoughts on I thinkit's >> Jonah's? You said there is a benefit to scale Dell, now at about ninety billion in revenue, has gone public on their stock prices. Done where Dellvin, since the ideal thing, the leader >> and sir, is that point >> leader in storage leader inclined computing peces with Vienna and many other assets like pivotal leaders and others. So that scale VM, Where about a ten billion dollar company, fifth largest software company doing verywell leader in the softer to find infrastructure leader, then use a computing leader and softer, defined networking. I think you need the combination of scale and speed, uh, just scale on its own. You could become a dinosaur, right? And what's the fear that every big company should have that you become ossified? And I think what we've been able to show the world is that V M wear and L can move with scale and speed. It's like having the combination of an elephant and a cheetah and won and that to me special. And for companies like us that do have scaled, we've to constantly ask ourselves, How do we disrupt ourselves? How do we move faster? How do we partner together? How do we look past these blind spots? How do we pardon with big companies, small companies and the winner is the customer. That's the way we think. And we could keep doing that, you'll say so. For example, five, six years ago, nobody thought of VMware--this is going before Dell or EMC--in the world of networking, quietly with ten thousand customers, a two million dollar run rate, NSX has become the undisputed leader and software-defined networking. So now we've got a combination of server, storage and a networking story and Dell VMware, where that's very strong And that's because we moved with speed and with scale. >> So of course, that came to an acquisition with Nice Sarah. Give us updates on the recent acquisitions. Hep C e o of Vela Cloud. What's happening there? >> Yeah, we've done three. That, I think very exciting to kind of walk through them in chronological order about eighteen months ago was Velo Cloud. We're really excited about that. It's sort of like the name, velocity and cloud fast. Simple Cloud based. It is the best solution. Ston. How do we come to deciding that we went to talk to our partners like t other service providers? They were telling us this is the best solution in town. It connects to the data center story to the cloud story and allows our virtual cloud network to be the best softer. To find out what you can, you have your existing Mpls you might have your land infrastructure but there's nobody who does softer to find when, like Philip, they're excited about that cloud health. We're very excited about that because that brings a multi cloud management like, sort of think of it like an e r P system on top of a w eso azure to allow you to manage your costs and resource What ASAP do it allows you to manage? Resource is for materials world manufacturing world. In this world, you've got resources that are sitting on a ws or azure. Uh, cloud held does it better than anybody else. Hefty. Oh, now takes a Cuban eighty story that we'd already begun with pivotal and with Google is you remember at at PM world two years ago. And that's that because the founders of Cuban eighties left Google and started FTO. So we're bringing that DNA we've become now one of the top two three contributors to communities, and we want to continue to become the de facto platform for containers. If you go to some of the airports in San Francisco, New York, I think Keilani and Heathrow to you'LL see these ads that are called container where okay, where do you think the Ware comes from Vienna, where, OK, and our goal is to make containers as container where you know, come to you from the company that made vmc possible of'Em where So if we popularized PM's, why not also popularised the best enterprise contain a platform? That's what helped you will help us do >> talk about Coburn at ease for a minute because you have an interesting bridge between end user computing and their cloud. The service is micro. Services that are coming on are going to be powering all these APS with either data and or these dynamic services. Cooper, Nettie sees me the heart of that. We've been covering it like a blanket. Um, I'm gonna get your take on how important that is. Because back Nelson, you're setting the keynote at the Emerald last year. Who burn it eases the dial tone. Is Cooper Netease at odds with having a virtual machine or they complimentary? How does that evolving? Is it a hedge? What's the thoughts there? >> Yeah, First off, Listen, I think the world has begun to realize it is a world of containers and V ems. If you looked at the company that's done the most with containers. Google. They run their containers in V EMS in their cloud platform, so it's not one or the other. It's vote. There may be a world where some parts of containers run a bare metal, but the bulk of containers today run and Beyonce And then I would say, Secondly, you know, five. Six years ago, people all thought that Doctor was going to obliterate VM where, But what happened was doctors become a very good container format, but the orchestration layer from that has not become daugher. In fact, Cuban Eddie's is kind of taking a little of the head and steam off Dr Swarm and Dr Enterprise, and it is Cooper Navy took the steam completely away. So Senses Way waited for the right time to embrace containers because the obvious choice initially would have been some part of the doctor stack. We waited as Borg became communities. You know, the story of how that came on Google. We've embraced that big time, and we've stated a very important ball hefty on All these moves are all part of our goal to become the undisputed enterprise container platform, and we think in a multi cloud world that's ours to lose. Who else can do multi cloud better than VM? Where may be the only company that could have done that was Red Hat. Not so much now, inside IBM, I think we have the best chance of doing that relative. Anybody else >> Sanjay was talking about on our intro this morning? Keynote analysis. Talking about the stock price of Dell Technologies, comparing the stock price of'Em where clearly the analysis shows that the end was a big part of the Dell technologies value. How would you summarize what v m where is today? Because on the Kino there was a Bank of America customers. She said she was the CTO ran, she says, Never mind. How we got here is how we go floors the end wars in a similar situation where you've got so much success, you always fighting for that edge. But as you go forward as a company, there's all these new opportunities you outlined some of them. What should people know about the VM? We're going forward. What is the vision in your words? What if what is VM where >> I think packed myself and all of the key people among the twenty five thousand employees of'Em are trying to create the best infrastructure company of all time for twenty one years. Young. OK, and I think we have an opportunity to create an incredible brand. We just have to his use point on the begins show create platforms. The V's fear was a platform. Innocent is a platform workspace. One is a platform V san, and the hyper convert stack of weeks right becomes a platform that we keep doing. That Carbonetti stuff will become a platform. Then you get platforms upon platforms. One platforms you create that foundation. Stone now is released. ADelle. I think it's a better together message. You take VX rail. We should be together. The best option relative to smaller companies like Nutanix If you take, you know Veum Where together with workspace one and laptops now put Microsoft in the next. There's nobody else. They're small companies like Citrix Mobile. I'm trying to do it. We should be better than them in a multi cloud world. They maybe got the companies like Red Hat. We should have bet on them. That said, the end. Where needs toe also have a focus when customers don't have Dale infrastructure. Some people may have HP servers and emcee storage or Dell Silvers and netapp storage or neither. Dellery emcee in that case, usually via where, And that's the way we roll. We want to be relevant to a multi cloud, multi server, multi storage, any hardware, any cloud. Any AP any device >> I got. I gotta go back to the red hat. Calm in a couple of go. I could see you like this side of IBM, right? So So it looks like a two horse race here. I mean, you guys going hard after multi cloud coming at it from infrastructure, IBM coming at it with red hat from a pass layer. I mean, if I were IBM, I had learned from VM where leave it alone, Let it blossom. I mean, we have >> a very good partisan baby. Let me first say that IBM Global Services GTS is one about top sai partners. We do a ton of really good work with them. Uh, I'm software re partner number different areas. Yeah, we do compete with red hat with the part of their portfolios. Relate to contain us. Not with Lennox. Eighty percent plus of their businesses. Lennox, They've got parts of J Boss and Open Stack that I kind of, you know, not doing so well. But we do compete with open ship. That's okay, but we don't know when we can walk and chew gum so we can compete with Red Hat. And yet partner with IBM. That's okay. Way just need to be the best at doing containing platform is better than open shifter. Anybody, anything that red hat has were still partner with IBM. We have to be able to look at a world that's not black and white. And this partnership with Microsoft is a good example. >> It's not a zero sum game, and it's a huge market in its early days. Talk >> about what's up for you now. What's next? What's your main focus? What's your priorities? >> Listen, we're getting ready for VM World now. You know in August we want to continue to build momentum on make many of these solutions platforms. So I tell our sales reps, take the number of customers you have and add a zero behind that. OK, so if you've got ten thousand customers of NSX, how do we get one hundred thousand customers of insects. You have nineteen thousand customers of Visa, which, by the way, significantly head of Nutanix. How do we have make one hundred ninety thousand customers? And we have that base? Because we have V sphere and we have the Delll base. We have other partners. We have, I think, eighty thousand customers off and use of computing tens of millions of devices. How do we make sure that we are workspace? One is on billion. Device is very much possible. That's the vision. >> I think that I think what's resonating for me when I hear you guys, when you hear you talk when we have conversations also in Pat on stage talks about it, the simplification message is a good one and the consistency of operating across multiple environments because it sounds great that if you can achieve that, that's a good thing. How you guys get into how you making it simple to run I T. And consistent operating environment. It's all about keeping the customer in the middle of this. And when we listen to customs, all of these announcements the partnership's when there was eight of us, Microsoft, anything that we've done, it's about keeping the customer first, and the customer is basically guiding up out there. And often when I sit down with customers, I had the privilege of talking hundreds of thousands of them. Many of these CEOs the S and P five hundred I've known for years from S athe of'Em were they'LL Call me or text me. They want us to be a trusted advisor to help them understand where and how they should move in their digital transformation and compared their journey to somebody else's. So when we can bring the best off, for example, of developer and operations infrastructure together, what's called DEV Ops customers are wrestling threw that in there cloud journey when we can bring a multi device world with additional workspace. Customers are wrestling that without journey there, trying to figure out how much they keep on premise how much they move in the cloud. They're thinking about vertical specific applications. All of these places where if there's one lesson I've learned in my last ten twenty years of it has become a trusted advisor to your customers. Lean on them and they will lean on you on when you do that. I mean the beautiful world of technology is there's always stuff to innovate. >> Well, they have to lean on you because they can't mess around with all this infrastructure. They'LL never get their digital transformation game and act together, right? Actually, >>= it's great to see you. We'Ll see you at PM, >> Rollo. Well, well, come on, we gotta talk hoops. All right, All right, All right, big. You're a big warriors fan, right? We're Celtics fan. Would be our dream, for both of you are also Manny's themselves have a privileged to go up against the great Warriors. But what's your prediction this year? I mean, I don't know, and I >> really listen. I love the warriors. It's ah, so in some senses, a little bit of a tougher one. Now the DeMarcus cousins is out for, I don't know, maybe all the playoffs, but I love stuff. I love Katie. I love Clay, you know, and many of those guys is gonna be a couple of guys going free agents, so I want to do >> it again. Joy. Well, last because I don't see anybody stopping a Celtics may be a good final. That would be fun if they don't make it through the rafters, though. That's right. Well, I Leonard, it's tough to make it all right. That sounds great. >> Come on. Sanjay Putin, CEO of BM Wear Inside the Cube, Breaking down his commentary of you on the landscape of the industry and the big news with Microsoft there. Other partner's bringing you all the action here Day one of three days of coverage here in the Cubicle two sets a canon of cube coverage out there. We're back with more after this short break.

Published Date : Apr 29 2019

SUMMARY :

Brought to you by Dell Technologies The one Welcome to the Special Cube Live coverage here in Las Vegas with Dell Technologies World 2019. It's changing the game And the vision we had at that time was that you should be Tell about the impact of the real issue of Microsoft on this one point, because is there overlap is their gaps, better to have overlapped and seems right. Next, in the end user world, That's a game, so I think in any partnership you have to look Tearing down the access wall, letting you get seamless. But customers, some customers of azure, some of the retailers, for example, like Wal Mart was quoted in the press, Last November, you announced Ali Baba, but not a solution. There's similar what's announced with IBM and Nash You actually sell the eight of us, You should think of this A similar to the IBM ah cloud relationship where the V C P. Or is that the video We gave an example of few that Well, then you're seeing certain verticals that are picking not everyone's seeing the obvious that we now know what the Amazon scale winds so scale is a You said there is a benefit to scale Dell, now at about ninety billion in revenue, That's the way we think. So of course, that came to an acquisition with Nice Sarah. OK, and our goal is to make containers as container where you know, Services that are coming on are going to be powering all these APS with either data to become the undisputed enterprise container platform, and we think in a multi cloud world that's ours What is the vision in your words? OK, and I think we have an opportunity to create an incredible brand. I could see you like this side of IBM, Open Stack that I kind of, you know, not doing so well. It's not a zero sum game, and it's a huge market in its early days. about what's up for you now. take the number of customers you have and add a zero behind that. I think that I think what's resonating for me when I hear you guys, when you hear you talk when we have conversations Well, they have to lean on you because they can't mess around with all this infrastructure. We'Ll see you at PM, for both of you are also Manny's themselves have a privileged to go up against the great I love Clay, you know, and many of those guys is gonna be a couple of guys I Leonard, it's tough to make it all right. of you on the landscape of the industry and the big news with Microsoft there.

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Joe Damassa, IBM & Murali Nemani, ScienceLogic | IBM Think 2019


 

>> Live from San Francisco. It's theCUBE covering IBM Think 2019 brought to you by IBM. >> Welcome back everyone, this is the CUBE's live coverage in San Francisco at Moscone Center for IBM Think 2019. I'm John Furrier with Dave. Volante Dave it's been in AI, it's been cloud, it's been in data changing the game. We've got two great guests here Murali Nemani, CMO of ScienceLogic, your CEO has been on the CUBE before and Joe Damassa who is the VP of strategy and offerings for hybrid cloud service at IBM. Thanks for joining us. >> Welcome. >> Appreciate it. >> Thank you guys. >> Welcome to CUBE. So day four of four days coverage, yes, you can see the messaging settling the feedback settling, AI clearly front and center, role of data in that and then cloud scale across multiple capabilities. Obviously on premise multi cloud is existing already. Software's changing all this. >> Right. >> And so AI impacting operations is key. So how do you guys work together? What's the relationships in ScienceLogic and IBM? Could you just take a minute to explain that? >> I think I mean, clearly, as you talked about the hybrid nature of what we're dealing with, with the complexity of it, it's all going to be about the data. You know, software is great, but it's about software that collects the data, analyzes the data, and gives you the insights so you can actually automate and create value for our clients. So it's really this marriage, it's a technology but it's a technology that allows us to get access to the data so we can make change, it's all about the data. >> And so a lot of what IBM has been doing is building the analytics engines and Watson it's for them. Our partnership has been really building the data and the data lake and the real time aspects of collecting and preparing that data so that you can really get interesting outcomes out of it. So when you think about predictive models, when you think about the the way that data can be applied to doing things like anomaly detection that ultimately accelerate and automate operations. That's where the relationship really starts taking hold. >> So you guys are specialized in AIops and IT apparatus as that transforms with scale and data which you need machine running, you need a kind of gave it automation. >> Yes. >> And which is the devops use of operations is don't go down, right, up and running, high availability. >> Yeah. >> So on the cloud services side, talk about where the rubber is meeting the road from a customer standpoint, because the cultural shift from IT Service Management, IT operations has been this manual, some software here and there, but it's been a process. Older processes change a little bit, but this is a new game. Talk about how you guys are engaging the customers. >> Well, a part of it I mean, it's interesting when you step back and you stop breathing, you're on exhaust in terms of pushing what you're trying to sell and you listen to your customers what we're hearing is that they all understand the destination. They understand they're moving to the cloud, they understand the value that's going to bring, they're having a hard time getting started. It's how do I start the journey ? I've got all of this estate and traditional IT operations capabilities it's kind of move. How do I modernize it? How do I make it so it's portable across different environments. And so when you step back, you know, we basically said, hey, you need the portability of the platform. So what we're doing with Red Hat, what we're doing with IBM, cloud private, it creates that portable containerizing ability to take our existing workloads and start moving them, right. And then the other thing that the clients need are the services. Who's going to help me advise me on what workloads should move, which one shouldn't, most of the staff fails because you move the wrong things. How do you manage that? How do you build it? And then when you're done, and you've got this hybrid complex environment, how do we actually get insights to it and the data I need to operationalize it? How do I do IT apps, when I don't own everything within the four walls of my data set. >> Now, are you guys going to market together? You guys sell each other products, the relationship with ScienceLogic and IBM is it a partnership, is it a joint development? Can you explain a little bit more on how you guys work together? >> Well, we're one of the largest sort of services provider in the industry. So as we bring, our products, our technologies and our capabilities to market, we bring ScienceLogic into those deals, we use ScienceLogic in our services so that we can actually deliver the value to our clients. So it is sort of a co development, co joint partnership plus also our goal to market. >> So you use that as a tool to do discovery and identify the data that's in and the data that we're talking about is everything I need to know about my IT operations, my applications, the dependencies. Maybe you could describe a little bit more. >> Sure if you think about one of the things that Joe was mentioning is, today, the workloads are shifting, you're going from, let's say management performance monitoring and management platforms that you need to evolve from, to incorporate new technologies like containers and microservices and server-less architectures. That's one area of how did the tool sets fundamentally evolve to support the latest technologies that are being deployed? So think about that. Second is, how do you consolidate those set of tools now you're managing? Because you're adopting cloud based technologies or new capabilities, and so get consolidation there. And the third is, these workloads that are now migrating out of your private cloud or private data center into public clouds, right? And then that workload migration, I think it is Forrester level saying, about 20% of the total workloads are currently in some sort of a public cloud environments. So there's a lot of work to do in terms of getting to that tipping point of where workloads are now truly in a multi cloud hybrid cloud. So as IBM accelerates that transition and their core competencies in helping these large enterprises make that transition, you need a common manageable environment, that the common visibility across those workloads. So that's at the heart of what we're pulling, and then the data sets happened to be data sets that are coming either from the application layer, data coming from the log management systems, it could be data coming from a service desk in terms of the kind of CMDB based data sets, and we're building a data lake that ultimately allows you to see across these heterogeneous system. >> It could be service request to get that really touches the business process so you can now start to sort of map the value and how change is going to affect that value, right? >> Yeah, exactly. >> Yeah. >> I mean, what's interesting about ScienceLogic as a partner, it's the breadth of their platform in terms of the different things they can monitor, the depth, the ability to go into containers, and kind of understand what the applications are doing in them and the scale in terms of the types of devices. So when you think about, the types of devices, we're going to have to manage everything from, sensors in an Internet of Things, environment to routers, to sophisticated servers and applications that can be running anywhere, you need the flexibility of the platform that they have in order to be able to deliver that. >> And I think that's a key point when you talking about containers and Kubernetes, we heard your CEO Jeannie remitting mentioned Kubernetes, onstage like, that's great, good time(mumbles) I know no one like Kubernetes now it's mainstream. >> Yeah. >> So this is showing them what's going on the industry which is the on premise decomposition of on premise with cloud private, you guys have. >> Yes. >> Is giving them the ability to use containers to manage their existing stuff and do that work and then have the extension to cloud, public cloud or whatever public cloud. This gives them more mount modern capabilities. So the question is, this change the game we know that but how has it changed AIOps and what does it mean? So I guess the first question is, what is AIOps? And what is this new on premise with cloud private and full public cloud architecture look like in AIOps 2.0? >> So for me, it's a very simple definition. It's really using algorithmic mechanisms, right? Towards automating operations, right? It's a very simple way, simplistic way of looking at it. But ultimately, the end game is to automate operations because you need to move at the pace of business and machine speed. And if you want to go, move in machine speed, you can have, I mean, you can't throw enough humans at this problems, right? Because of the pace of change, the familiarity of the workloads spinning up and sitting down. We have a bank as a customer who turns up containers for every 90 seconds and then turn them down. Just can't keep that in that real time state of change and being able to understand the topological relationships between the application layer and the underlying infrastructure so that you can truly understand the service health because when an application degrades in performance, the biggest issue is a war room's scenario where everyone's saying, it's not me, it's not me and because everyone's green on their front, but it's now how do you get that connective tissue all the way running-- >> Well it's also not only the change, it's also the velocity of data coming off that exhaust or the changes and services is thrown off tons of data that you need machines now I mean, that's kind of the thing. >> Exactly, yeah. And I would add to that, I think part of the definition of AIOps is evolving. We know where we're coming from is more fit for purpose analytics, right? I have this problem, I'm the collect this data, I'm going to put these automations in place too address it. We need to kind of take it data Model approach that says, how do I ingest all of this data? You know, even at the start, when you're looking at which workloads and you're doing discovery and assessment of workloads, that data should go into a data lake that can be used later when you're actually doing the operations and management of those workloads. So what data do we collect at every stage of the migration and the transformation of it, and including the operational data? And then how do we put a form analytics on it, and then get the true insights? I think we're just scratching the surface of applying to AI, because it's all been very narrow cast, narrow focus, I have this problem, I collect this data, I can automate this server, it needs to move much beyond that to it... >> And services are turning up and on and off so fast as a non deterministic angle here, and you got state, non deterministic, I mean, those are hard technical computer science problems to solve >> Yeah. >> That's you don't just put a processor around say, oh, yeah. >> Well, let's back to the the scalability of the platform, the ability in real time to be monitoring and looking at that data and then doing something right. >> All right now, humans aren't completely removed from the equation, right? And so I'm interested in how the humans are digesting and visualizing all this data, especially at this speed there a visualization component? How does that all evolving? >> Yeah, I think that to me I mean, that's part of the biggest challenges. You humans are a, they have to be the ones that kind of analyze what's coming and say, what does this mean when you haven't already algorithmically built it into your automation technology, right? And then they also don't have to be the one to train, the system is doing to actually do it. So one of the things that were are that struggling with not struggling with, we're experimenting with is, how best to visualize this, right? We do some things now, we've got a hybrid cloud management platform, we're teaming with the product guys, and it's the ability to have four consoles. One from a consumption, how do I consume services from Amazon, IBM Cloud on premise, how do I deploy it? So in a Dev apps model, how do I fulfill that very quickly and operational councils, right, and then cost on asset management so you can actually have at glance say, oh, you know, I've got a big Hadoop cluster which been spun up, I'm paying $100,000 for it and it has zero utilization. So how do you visualize that so you can say oh, I'm need to put a rule in that if somebody's spinning something up on, you know, IBM Cloud and they're not using it, I either shut it down, or I sent messages out, right, for governance in top of it. So it's putting business rules and logic in terms, in addition to visualization to help automate. >> And Jeannie talked about this at our keynote efficiency versus innovation around how to manage and this is where the scale comes in. Because if you know that something's working, you want to to double down on it, you can then, kind of automate that away and then you just move someone, the humans to something else. This is where the AIOps I think it's going to be, I think, going to change the category. I mean, it's a Gartner Magic Quadrant for the IT operations. >> Right. >> AI potentially decimates that, I mean... >> Yeah, there's this argument that you know, you have these nice quadrants or let's say nicely defined market segments. You have the NPMD, the ITSM, the ITOM, you know, you have APM and so what's happening is in this world of AIOps, none of those D marks really fit anymore because you're seeing the convergence of that. And then the other transition that's happening is this movement from, you know, classic ops or Dev and a dev to Ops, Dev Ops and now dev sec Ops, you know, you're trying to get worlds to converge. And so when we talk about the data and being able to build data models, those data models need to converge across those domains. So a lot of the work we do is collect data sets from log management, from service desk and service management, from APM etc, and then build that data model in real time. So you can.... >> It kind of building an Uber or CMDB or I mean, right? (loud laughter) I mean, do most of your clients have a single CMDB? Probably not, right? >> Yeah. So this is sort of a new guidepost, isn't it? >> Yeah, a part of it is. There are these data puddles if you will, all right data exist in a lot of different places How do you bring them together so you can federate different data sources, different catalogs into a common platform because if a user is trying to decide, okay, should I spin this up on, you know, this environment or that one, you want the full catalog of capabilities that are on premise in your CMDB system with the legacy environment out of the catalogs that may exist on Amazon or Azure, etc and you want data across all that. >> It seems that everything's a data problem now. And datas are being embedded into the applications which are then the workflows are defining infrastructure, architecture, or are sole cloud, multi cloud, whatever the resource is, so we had JPMorgan Chase on top data geek on and she was talking about, we have models for the models and IBM has been talking about this concept of reasoning around the data. This is why I always like the cognition kind of angle of cognitive, because that's not just math, math is math, you do math on, you know, supervised machine learning and knowing processes to be efficient, but the cognition and the reasoning really helps get at that data set, right. So can you guys react to that? I mean, is everything a data problem? Is that how you should look at it and how does reasoning fit into all this? >> Well, I mean, that's back to your point about what is the humans role in this, right. So we're moving in a services business from primarily labor base with tools to make them more efficient to the technology doing the work. But the humans have to then say, when the technology get stumped, what does that mean? So should I build a new, how do I train it better? How do I, you know, take my domain expertise? How do I do the deep analytics to tell me all right, how do I solve those problems in the future? So the role changes I think Jenny talks about in terms of new collar workers. I mean, these are data scientists, these are people that understand the dynamics of the inner relationship of the different data, the data models that need to get built and they are guiding in effect the automation. >> I thought your CTO was on theCUBE talking about, Paul was talking about, you know, take the heavy and Rob Thomas was also on, the GM of the data plus AI team. I think he really nailed it. If you guys to take away the heavy lifting of the setup work then the data science who're actually there to do the reasoning or help assist in managing what's going on and putting guard rails around whatever business policy is. >> Today, I mean, we talked to in this about 79 percent I think it's a gardener stat of 79 percent of the data scientists. And these are these PhDs, they're highly valuable, spend their time collecting, preparing, cleansing those data models, right? So, you're now really applying that PhD level knowledge base towards solving a problem, you're just trying to make sense of the data. So one, do you have a holistic and a few? Two, is there a way to automate those things so you can then apply the human aspects towards the things that Joe was talking about. So that's a big part of what we're trying to come together in terms of the market for. >> Well guys thanks for the insight, thanks for coming on, great job. I think we talked for you know, an hour and on cultural shift because you mentioned the sets in here Ops and devs. It's a melting pot and it's a cultural shifts. I think that topic is worth following up on. But I'll let you guys just get a quick plug for you. I know you going to an event coming up and you got some work. You can talk about what you guys are doing. You got an event coming up, what your pitch, give a quick flag. >> Yeah, so we've got our symposium, which is our big user conference. It's in April. It's right in, it's on April 22 to 23rd to the 25th. It's in downtown Washington DC, Cherry Blossom festival season at the Ritz Carlton. And so a lot of that, we'll have theCUBE there as well. >> Yeah of course. >> So, we're looking forward to it. A lot of great energy to be carried over. >> We love going to the District. (laughs loudly) >> What don't we say, you guys are great, great to visit. So give the plugs with a service you're doing. Just give an update on what you guys are up to. >> Yeah, I think I mean, we're also we're investing the technology when we're full on board with the containerization, as we talked about, we're putting together a services portfolio. I think Jenny mentioned that we're taking a whole bunch of capability across IBM Global Technology Services, Global Business Services, and really coalescing into about, you know, 23 offerings to help customers advise on cloud, move to cloud build for cloud and manage on cloud and then you've seen the announcements here about what we're doing around the multi cloud management system. Those four console I talked about how do we help, you know, put a gearbox in place to manage the complexity of the hybrid nature that our customers are dealing with. >> It seems IBM got clear visibility on what's happening with cloud, cloud private, I think a really big announcement. I think it's not talked about in the show and I'll always kind of mentioned the key linchpin but you see cloud, multi cloud, hybrid cloud, you got AI and you got partnerships, ecosystem now its execution time, right? >> Yeah, exactly and, and frankly, that's the challenge, right? So we used to be able to manage it all on the four runs, right? Your SAP instances was in the data center, your servers were in the data center, your middleware is in the data center. Now I got my applications running in Salesforce.com often software as a service. I've got three or four different infrastructures of service providers. But I still have the legacy that I got to deal with. I mean the integration problems are just tremendous. >> Chairman VP of strategy at IBM hybrid cloud and Murali Nemani, CMO ScienceLogic, AI operations, bringing in hybrid clouds to theCUBE bringing all the coverage day four. I'm with Dave Volante, it's all about cloud AI developers all happening here in San Francisco this week. Stay with us from this short break. (upbeat music)

Published Date : Feb 15 2019

SUMMARY :

brought to you by IBM. it's been in data changing the game. the feedback settling, So how do you guys work together? that collects the data, analyzes the data, and the data lake and So you guys are specialized in AIops and running, high availability. So on the cloud services and the data I need to operationalize it? and our capabilities to market, and the data that we're talking about and management platforms that you need flexibility of the platform point when you talking about private, you guys have. So the question is, this and the underlying infrastructure that you need machines now I mean, the surface of applying to AI, That's you don't just put the ability in real time to be monitoring the system is doing to actually do it. the humans to something else. AI potentially the ITOM, you know, you have APM So this is sort of a and you want data across all that. of reasoning around the data. How do I do the deep analytics to tell me GM of the data plus AI team. of the data scientists. I think we talked for you know, an hour season at the Ritz Carlton. A lot of great energy to be carried over. We love going to the District. So give the plugs with of the hybrid nature and you got partnerships, But I still have the legacy bringing all the coverage day four.

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Jesus Mantas, IBM & Mani Dasgupta, IBM | IBM Think 2019


 

>> Live from San Francisco, it's theCUBE. Covering IBM Think 2019. Brought to you by IBM. >> Welcome back to Moscone North, this is IBM Think 2019. You're watching theCUBE, I'm Stu Miniman, and we're going to dig into a segment talking about the cognitive enterprise. And helping me through that, I have one returning guest and one new guest to theCUBE, so furthest away from me, the returning guest is Jesus Mantas, who is the managing partner strategy for the digital platforms and innovation in the IBM Global business services. Jesus, welcome back. >> Thank you >> A little bit of a mouthful on the title. And Mani Dasgupta, CMO of the same group, the IBM Global business services. Thanks so much both for joining us. Alright, so cognitive enterprise. We're going to play a little game here first. Buzzword Bingo here, you know, can we talk about, what cognitive is, where you can't say AI, ML, platform, or enterprise in there. So do we start with the CMO first? >> Sure, I can go. Cognitive enterprise, those are two bing bing right there. What's your core competitive advantage, is what I would say. As a company, do you know why you exist? And once you get to that, how do you then take it to your clients, in a way that would help you grow, and sustain growth in the future. That truly is the future of a smart business, what we call the cognitive enterprise. >> So, Jesus, data is something we talk about a lot, at all the shows, we hear all the tropes about it's the new oil, the rocket fuel that are going to drive companies. You've got strategy and innovation in your title, I'd love you to build off as to where this cognitive enterprise fits in to those big trends of AI that we were talking about. Jinny was just on the keynote stage, talking about Watson, talking about all those pieces, so where does that fit with some of these megawaves that we're talking about. >> I think it's the way that we define this new, smarter organizations that use data to the fullest extent. And I think the way that we define it is, one is this reuse of data, your own data, the external data, and the way you aggregate it, the way that you apply AI or other things to use that. But the technology itself is a means to an end, it's not the end, so these organizations change the way the work flows, and they also train people to make sure that they understand how to operate in a world where they have more information and they can make better decisions with that data that they could before. All of that is what we are labeling. It's more than digital, it's more than AI. It is this concept of a cognitive enterprise. It's a smarter way to do what a company does. >> Okay, I'd love if you could give us a little bit of a compare, contrast. You know, the wave of big data was, there's massive amounts of data, we're going to allow the business practitioner, to be able to leverage that data. Was a great goal, unfortunately when we did research, at least half the time it wasn't really panning out there. Doesn't mean we didn't learn good things, and there weren't lots of great tools and business value generated out there. So, give us, you know, what's the same and what's different, as to this new wave. >> This is how do you make that data work for you, really. It is about, when you talk of data, you think of data that's out there, but 80% of the data today, is owned by you. And by you, I mean a business, right, you own your customers' data, you know your customer better than anybody else. So what do you really do with it? And we are at an inflection point right now, where these technologies that you just talked about, be it blockchain, be it internet of things, be it AI. You can truly bring the power of these technologies, to start making sense of that data that you own, and use it to create, what we call, your competitive advantage, your business platform. So, think about it, I can break it down. Would you just be a retailer of clothes? Or, would you be a fashion expert? And which one would have long-term success for you? Or if you think of a completely different industry, would you be an insurance provider, you sell insurance products, or would you be a risk management expert? That decision to be who you want to be, is really at the heart of the cognitive enterprise, and what we are proposing to the clients here. >> Alright, help frame for us your group, where that fits in. IBM sells hardware, software, has a huge services organization. What are the deliverables and the services and products involved in your group? >> Sure, we are the services organization of IBM, and one of the core reasons why we exist is to help our clients solve their toughest business problems. And so, if you think about it, you think about it as different puzzle pieces, but they don't quite always fit together. We exist to sharpen the edges, to sometimes round the edges, make it customized, make it right for you, so that at the end of the day, you're able to deliver results for your customers and be closer to them than ever before. >> The balance we look at in this multi-cloud world, it'd be nice if you have a little bit more standardization, but of course we know when we talk with businesses, every company is different and is challenging. So, where are the architectural engagements? What are the design criteria? Where is some of the hard work your group gets involved in? >> Yeah, I think we've been spending a lot of work and a lot of time on understanding how to get clients, most clients have done a lot of experimentation. But they rarely figured out how to get that experimentation into real production, at scale, with impact. So that's where we've spent a lot of the time. Fundamentally it has to do with, not only understanding Agile as a method, but being able to combine that with taking that journey all the way through to production, actually integrating with compliance requirements that, if you're in a regulated industry, you have to do, and do that in a way that doesn't become a digital island. I think what we have learned is, when companies see this big divide between, that's the legacy world and that's the new world you can never put those two together. So we came up with this concept of IBM Garage, which is the way in which our team, the services side, can actually bring it all together, and it gets massively enhanced and improved, with technology like containers, like Kubernetes, because now you can actually open up architectures, without reinventing them, and connect them with new technology, and do that synchronously. So you can basically be modernizing your legacy, you can be creating new innovation, in the form of new platforms, but you can do it at the same time, and as you do that through cycles, you also change the skillsets that you have in your company, because if you don't change that skillset, you're always going to have a problem scaling. That's what we do, that's what we help the clients do. >> Yeah, skillsets are so critical. Something we've been hearing over and over is, that whole digital transformation, this isn't some 18 to 24 month going to deploy some software, bring in a lot of consultants, they go and do it, hopefully it works and then they walk away. We're talking about much faster time frames, usually agile methodology, talk about skillset-changing. How do we help customers move fast and accelerate, because that's really the faster, faster, faster, it's just one of those driving things we hear. >> I was talking to one of the clients this morning, and what she said is, it's so helpful to have a framework, just to know where to start, and also to know, sometimes it's there in their mind, but they want to see it in front of them, how to break a problem down into smaller components, so that you can get to value faster, so we have actually a seven-step process, of the cognitive enterprise. So we start with, what is your core platform? In fact, Jesus coined this term, he calls it the digital Darwinism. Do you want to talk about the digital Darwinism, Jesus? >> Yeah, I think it reflects very well this urgency. In the analog world when most businesses are based on how clients choose you based on proximity, based on convenience, based on brand, based on trust, based on price. Even if you're not great at it, you have enough friction in an analog world, that the clients will keep coming. All of us and more of our things that we do every day, are in our phone, and they are digitally accessible, all of that friction disappears, and what happens then is, the people that are very good at something becomes, everybody goes to them, and the people that are not the best. I call it, they either thrive or they die very quickly. So in the digital world, being really good at something is a lot more important than in the analog world. You can survive being average in the analog world. Once you get to the digital world, it's transparent. Everyone will know, you're the best, you're not the best, and nobody would pick you if you're not the best, so it's really important to reconfigure yourself, and understand the trust and your brand, understand how digitally you translate what you are, and then make sure that your clients will keep choosing you in a digital world as much as they were choosing you in an analog world. >> I tell you, that resonates really well with me. The old line you used to hear is, if you want to get something done, give it to someone who's really busy, because they will usually figure out a way to do it. I spent a handful of years in my career doing operations, and what I did when I was in operations, when I talked to people in IT, is tell me next quarter and next year, do you think you're going to have more or less work more data to deal with, more thing thing, and of course the answer is, we all know that pace of change is the only thing that's constant in this industry. So, if I don't figure out how I automate, change, or get rid of the stuff that I'm not good at, we're just going to continue to be buried. Are there commonalities that you see, as success factors or how do you help measure, what are some key KPIs that customers walk out of, when they go through an engagement like this? >> Yeah, just carrying on from where Jesus left off, the second step is very close to what you were just saying. It's about the data and how you're using that data. So some of the key success factors would be, what is the output of it, and it's not in the proof of concept phase anymore. It is real-time, it is big, people are doing it at a grand scale. I think, Jesus, maybe we take it through the seven steps, and then the key success criteria comes right at you, right after that. So after you do the workflow, after you do the data for internal competitive advantage, we go to the next step, which is all about workflows. You want to talk a bit about that? >> Yeah, I think one of the advantages that artificial intelligence brings to companies is, the fact that you can now, I mean as a human, there is only so much data that you can ingest. There is a limit, and most businesses try to optimize what that is and how you make decisions. But, artificial intelligence becomes this aid that will read and summarize things for you. So now you can take into account, into workflows, massive amounts of information, to optimize, or even not having to do things you had to do before, at a scale that, as a human you cannot do. This idea of inserting AI into workflows is the real idea. I think we talk a lot about AI as a technology, but that's just a means to an end. The end is a workflow that is embedded with blockchain, with AI, with IOT, and then people that are trained to engage with those workflows, so you actually change the output. And I think that's the big idea, that step of, it is workflow that is embedded with AI, it's not just about the technology, it's the combination of the main industry, and the technology that actually creates that >> And where does it sit, right? Where does it sit? Your tech choices, the architecture choices are also important. And we joked about this, like if you really like Netflix, and you're watching something and something is coming up after three seconds, how does it know what you really like? But it does, but think about this. This wouldn't be possible on a 1950s television set. So you've got to think about what's your tech platform of choice, how do you upgrade that, and what's the architecture look like? >> I want to give you both the final word. Lots of users here at the show. What are you most excited about? Give us an insight on some of the conversations you've been having already. >> Amazing conversations so far. The really aha-moment was, people really like to share within their peer set, so this morning I was at the business exchange, and people were having conversations, but just to bounce it off someone, who is facing the same issues that you do, across different industries, was a really aha-moment, and we have the IBM Garage actually right behind us on the other side of Moscone. We set it up so that clients can come in, and unpack their problems, and we helped them think it through, used design thinking, help them think it through. We are hoping in the next couple of days, we get lots of brilliant ideas, come from the sessions like that, and really putting the customer at the core of what you want to do. >> It's a recurring theme of all the client conversations, this idea of, they all want the speed and agility of a startup at the strength and scale of an enterprise. That's what they're asking us, as the services organization of IBM, to do is, help us not just experiment, that was good before, not good enough now. Help us do that with agility, with new technologies, but we want it to mean something at scale, globally implement it, create an impact. And I think again, the way in which hybrid multi-cloud can play into that, the way in which IBM Garage can combine the legacy world with the new world and moving people into new platforms is a really exciting method and approach that is resonating a lot with clients. >> Really appreciate you both sharing updates and absolutely as you painted a picture, just as in 1950 we didn't have the tools to run Netflix, now in 2019, we have the tools for customers to be able to help build the cognitive enterprise and not only test but get into real-world deployment at a speed that was really unheralded before today. Thanks so much for joining. We'll be back with more coverage here from IBM Think 2019. I'm Stu Miniman, and thanks for watching theCUBE. (upbeat techno music)

Published Date : Feb 13 2019

SUMMARY :

Brought to you by IBM. and one new guest to theCUBE, what cognitive is, where you can't say AI, ML, platform, and sustain growth in the future. the rocket fuel that are going to drive companies. the way that you apply AI or other things to use that. So, give us, you know, what's the same That decision to be who you want to be, What are the deliverables and the services so that at the end of the day, you're able to Where is some of the hard work your group gets involved in? and as you do that through cycles, because that's really the faster, faster, faster, so that you can get to value faster, and nobody would pick you if you're not the best, and of course the answer is, the second step is very close to what you were just saying. the fact that you can now, I mean as a human, And we joked about this, like if you really like Netflix, I want to give you both the final word. of what you want to do. of a startup at the strength and scale of an enterprise. and absolutely as you painted a picture,

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Sanjay Poonen, VMware | AWS re:Invent 2018


 

>> Live, from Las Vegas, it's theCube! Covering AWS re:Invent 2018. Brought to you by Amazon Web Services, Intel, And their ecosystem partners. >> Hey, welcome back everyone, live here, in Las Vegas, Amazon Web Services AWS re:Invent 2018. 52,000 people here. Two days. Second day of three days of wall to wall coverage here at theCUBE. I'm John, with Dave Vellante. Dave, six years, we've been doing theCUBE. We've been to all re:Invents except for the first year. We've been a customer, we've been following these guys. >> Plus the summits! >> Plus the summits. Great ecosystem. And VMware and VMworld, similar dynamic. I want to talk about that now, obviously the new announcement, on-premise, is huge. Want to dig in to it with our guest, Sanjay Poonen, who's the Chief Operating Officer of VMware. Sanjay, great to see you. Cube alumni, many times, thanks for coming back again. >> John and Dave, pleasure to be on your show. >> Thanks for coming on, great to see you. >> Congratulations on all this success, you've got a wonderful booth and presence here, and I think this is becoming like the Mecca of all IT events. >> You know, we have our new video cloud service on AWS, we're ingesting over 110 videos, we'll have 500 short video clips behind it. Tons of blog posts, tons of coverage. There's an insatiable appetite for Amazon Web Services content as Andy pointed out in my interview with him. And it's just the beginning. You guys at VMware really, I mean, talk about a seminal moment in the history of the computer industry, and VMware was, when you guys recognized the sea change of operators on IT and cloud developers coming together, you guys were very proactive two years ago. Raghu, yourself, and the team, Pat. We're going to, hey you know what? Let's just align. Culture's a fit with Amazon. Let's co-develop. Let's ride the wave together, and let's see where the chips fall. Which is basically, I'm oversimplifying, but that's kind of what's happened. So much has happened. I saw Raghu last night at the Greylock partner event. This is a historic moment. Good outcome so far, deep partnership, meaningful partnership. A lot of resonance in the marketplace, you guys are iterating and raising the bar. That's Amazon talk for success. How do you feel? >> Yeah, no, I think it's, absolutely, John. We, if you think about how this has evolved, you know five years ago when I joined VMware, I felt like cloud and containers, the two C's, were our big headwinds. We've turned those headwinds now into tailwinds, but it took some catharsis from us. We had vCloud Air, our own public cloud. We had to divest that. And I think the Amazon VMware coming together, when we announced it two and a half years ago, was like a Berlin Wall moment, where you had the US and the Soviet Union getting together. That was good for world peace. People were surprised, because these are two purported enemies now, and it really built trust. And step by step, launching VMware on AWS, announcing RDS on VMware, the beginning of on-premise, and then today, announcing Outposts, it's just an example of not just the validity of VMware as a hybrid cloud leader, but the strength of this partnership. We have a very special relationship with Andy, Pat, myself, Raghu, spent a lot of time together. Often, you can't tell, when our engineering teams meet, when an Amazon engineer and a VMware apart from each other. They're like finishing each other's sentences. That, we don't do, like, Mickey Mouse, Barney, you know press releases. It's real stuff. >> And the culture of, the engineering culture of VMware, which has been a core, cultural thing, the DNA of VMware is technical. Very community oriented. Amazon, technical, very operationally efficient, good community. This is good fit there. I got to get your perspective, though, on how that is going to evolve, specifically around on-premise. Because certainly Andy Jassy validates on-premises with the announcement that VMworld, which you guys covered, Pat Gelsinger uses words like dial tone, Kubernetes, you mentioned containers. Andy, when I asked him, "Andy, you know you told me "in theCUBE, five years ago, "that everything's going to the public cloud. "Change of tune? "You mind if I pin you down?" "No, John, you can pin me down all you want." He says good leaders are self-aware. He said "Our customers wanted this." And he's cool to it. And the partnership with VMware highlights that this is not going to happen overnight, he recognizes the duration, the role of on-premise. And then he also says that the data center's like a big Edge. So, if everything's cloud, what you guys basically announced with Outpost is, cloud, public cloud everywhere. So, just, there's no public, private, it's just cloud. This is a game changer, because-- >> Absolutely. >> Just, why wouldn't I want to buy this product? >> I mean, first off, congratulations on scoring that interview. Not many people have access to Andy that way, and you guys have built a very good relationship. I thought that interview you did with him was phenomenal. There was a special point in that, John, where you tried to get him to talk about Outposts, this was before he announced it, which is will Amazon go on-premise. So a couple of months ago, when Andy called us, and Matt Garman, to talk about this project under NDA, it was a continuation of those RDS type discussions where we basically said, if you want to do anything on-premise, you should do it with VMware, because you're going to have to go through this door called VMware. We are the de facto king of the on-premise private cloud world. Many of these customers are used to our tooling, vSphere, vMotion. They want anything to run on VMware. So from that became a sequence of discussions that really really evolved very quickly, and well, so we can announce this together. I mean, you know, Andy had three guests on stage, and only one partner, and that was VMware. And that's an indication of the strength of this partnership. Vice versa, of the 50,000 people here, probably all of them have VMware on-premise. So if Amazon's going to do more on premise, why not do it with the leader in that area, VMware. And we want to be in the software industry. The de facto standard for software-defined infrastructure. Right? And that's a special space that we can fill. >> Well, the amazing thing to me, is, here's VMware, no public cloud, Amazon wouldn't even say the word hybrid, or private cloud, doesn't use private cloud, but it wouldn't say hybrid before. You've now emerged as the tandem, de facto leader in hybrid cloud. Overnight. With an ecosystem that all wants to connect and partner with VMware and all wants to partner with AWS. Overnight. I mean, it feels that way anyway, 24 months. >> I think that's absolutely right. I mean, we were the first to start using the term hybrid, three or four years ago. As we did, then it took a while, because I think a lot of customers, and some of the public cloud vendors, felt it was going to be binary, all public cloud and no private cloud, but they began to realize you need both. But your point on the ecosystem, also surrounding, I just came back from meeting one of the top SIs in the world. They're betting big with us because they see this as the place for both of them, and they're also betting big with AWS. The System Integrators are all over this. The security vendors, all over this. Palo Alto Networks, Splunk, want to see. Often, many of these companies come to us and say, "You have cracked something special "in your relationship with Amazon. "How did you do that and how can we follow that model?" We're happy to share our playbook of how we think about ecosystems. So, we want to create a platform, just like Amazon's a platform, where everybody, SIs, tech vendors, software vendors, can all plug in to. >> And the other observation I make is, you know, previously the distance between infrastructure players and the guys who really are driving application value, the application developers, was quite a distance. And now it's closing, with infrastructure as code. And it's just so transformative for organizations. >> I think, and one of the things that's making that is microservices and containers. And as you know, since we last talked, we acquired Heptio. If you think about Heptio, they are the founders of Kubernetes, okay? They left Google, started their own company, Craig and Joe, and we're excited about that. That platform will augment PKS, which was our big bet in containers, and become something that could run on-premise, or in a public cloud environment like this. We acquired CloudHealth. CloudHealth is a multi-cloud management tool for costing resource management. That becomes something that could send, a lot of Amazon reps actually refer CloudHealth as the preferred way to get your insights. So we're beginning to see this now a lot more clearly than we did two years ago, thanks to this partnership. >> So, Sanjay, I know that Outposts, super exciting, it's been covered on Silicon Angle, there's a zillion stories on our site on this whole event. But, it's not going to be shipping for about a year. But you guys already have some working products now. What's the current track to that shipping because when that comes out, that'll be a game changer. Why would anyone want to buy hardware again? Michael Dell wins either way because he's got VMware. But others who sell hardware, this is a real, it could be a killer blow. But, I don't want to (laughs), you can comment on that if you want, but what's in-between that one year, you've got a product now, how do customers move along? >> Yeah, I think there's some very tangible things that, first off, VMware Cloud on AWS is, as you've described Dave, the best hybrid cloud option. You get the best of the on-premise world and the public cloud. You know, we announced hundreds of customers, we have a goal to get to thousands of customers, and then tens of thousands of customers. We're going to continue down that march. I want to have a significant number, over 500,000 customers. If Amazon has 40, 50 percent market share, based on some of the numbers that Andy shared today, a significant number of our customers have Amazon, we should get them onto VMC. VMware Cloud and AWS. Secondly, we do have, we announced Project Dimension, some Edge computing capabilities running on existing hardware players, so we are beginning this journey ourselves, in terms of cloud managed on-premise environment. Right? Project Dimension was announced before this, and that will run on Dell and Lenovo hardware, and that's well and good to go. They will have Edge IOT use cases. And then when Amazon comes and gets us ready, we would have learned a lot about this market. Which is really kind of this Edge computing market, cloud-managed. So we're not going to be, we're going to plan and do the other pieces. Much of the software components that VMware is building is not completely from scratch code. We're taking NSX. One of the most important components that VMware is adding to Outposts is NSX. We're not rewriting NSX, we're taking the NSX and applying this now, to a use case that's very much like that because we've adapted NSX now to be container-friendly, cloud-friendly. We've added NSX into the branch, VeloCloud. So those are the things that we're, you know, there's no rest for the weary anymore. >> And that gives you a consistent networking model, which is not trivial, as we've talked about. >> One of the things that I'm excited by, intrigued by, is, I know it's nuanced, but I see it as a key point, containers sometimes don't meet the security boundary issue. So, you guys can run a VM around a container, and run it under the covers. With Lambda. At super lightning speeds. It's not like a ten second instance to stand up. So that means there's more opportunities to create more abstractions around Kubernetes. And maintain security. There's so many benefits from this integrated kind of concept of consistency of operations for the software developer. >> John, you're absolutely right. Part of what we're trying to do is that word you talked about. Consistent infrastructure and operations. Consistent infrastructure and operations. And the container, if you've been seeing some of the ads in the San Francisco airport, we have some in London, and a few of the airports in New York, you'll see an ad that says "Containerware." It's playing on the word "ware", VMware. We want to be everyWARE, W-A-R-E. And if you think about the container being as pervasive as the vm in the future, I'm not going to say we're going to change the name of the company to be Containerware, but we want to be as pervasive as vm has been in VMware. So we have tens of millions of vms, in the twenty years we've had, maybe there'll be ten times as many containers. We want to become that de facto platform and containerware starts to take over. Right? What is that? Kubernetes-based. And we'll partner with the best. We've partnered with Google, we've partnered with Pivotal. Some of it would land on AWS, some of it will land on Azure. And you get a lot of the flexibility you have with that microservices platform. >> So, since you guys are on more of the software side, obviously Amazon's got software, but you guys actually are going to be much more broader, multiple clouds, as Amazon moves up the stack, I would imagine that as customers, I'm not going to buy in to only one cloud, there's other clouds out there, you guys should become a real strategic, traversal between clouds. So, we were debating, will customers have certain instances in, say, different clouds for specific, unique things, but yet run still horizontally, scalable on-premises, with VMware across multiple clouds. >> I think, you know John, it's going to be a lot like the hardware market was 20 years ago. It started to evolve into two or three major players. What's today Dell, HPE, Lenovo, at the time it was IBM, they divested to Lenovo, Cisco. In the storage place, two or three. I think the public cloud is not going to be three, five, ten. It's going to be two or three. Maybe four. And then maybe, in like China, Alibaba. So already, we have certain tools. Like CloudHealth's proposition is to manage costs and resources across multiple clouds. So we began to be already thinking about what is a multi-cloud world do? That said, in areas like this, which is a data center offer, we felt it was good for us to focus and get VMware Cloud and AWS to be the best hybrid cloud option. Give that a couple years, rather than trying to do everything and do it poorly, when you peanut butter your approach and try to do a lot of things with various different, so this is why we put a lot of special attention on VMware Cloud and AWS. We have an offering with IBM. We announced something with Alibaba. In due course VMware will need to have multiple cloud offerings. But I feel like this partnership and the specialness of this has really benefited both sides. >> Well, it's going to be very interesting, because IBM just made a 34 billion dollar validation of multi-cloud, so, and we talk about competition all the time. And it's evolving. >> We have a very good relationship with IBM. And listen, you have to be reasonably nuanced in your partnerships. So we're going to partner very heavily with IBM Global Services. We're going to partner very well with IBM Cloud. We're going to compete really hard with Red Hat! That's okay! Well, we'll compliment Linux. The bulk of their revenue's Linux. >> Of course, yeah. >> But make no mistake, we're going to compete hard with OpenShift. That's okay! That doesn't mean our IBM relationship is competitive. There's one piece of that, a very small part of the Red Hat revenue, OpenShift, that we overlap. The rest of it is complementary. We can be nuanced. It's sort of like walking and chewing gum. We can do both. And that's how we play. >> Before you wrap, now you know what we think of you, we think very highly of you, you're a superstar in our minds. However, you got to interview Sushmita, in India-- >> You know who Sushmita is? >> a true Bollywood superstar. Yes, an amazing actress, beautiful, talented. That must have been quite an experience. >> Well I got to tell ya, I was very intimidated. I opened-- >> I'll bet. >> Cause somehow I get assigned all these interviews to do. Malala, I'm usually on the opposite end. Your end. Malala, and Condoleezza Rice, and I told her I was really intimidated by her, and she said "Why?" I said, it's the first time that, I'm usually not tongue tied, but I did not know how to explain to my wife that I was going to be interviewing Ms. Universe. Okay, and she's like "What do you guys do at VMware? What the heck does Sushmita Sen have to do" But it was a good interview, I mean listen, for the India audience, we were celebrating our 20 year anniversary. She is an amazing woman who has achieved something that very few Indians have. And we wanted our Indian audience there to see that women can be successful. She's a big supporter of more women in business, fairness, equality, no prejudice, equal pay, all those things that we stand for. Which is part of our values. And if it weren't for the India audience she probably, I don't know if she would have worked at a Vmworld. We had Malala there, we had Condoleezza Rice at our last sales kickoff. We do these because we want to both teach our employees something, but also inspire them. And sometimes these speakers help with that cause. >> Sanjay, great to see you, thanks for coming on. I know you got to catch a flight. Big day today for you guys at VMware, congratulations. >> Thank you very much for having me. >> Thanks for all your support, great to see you. Great commentary, great insight. Sanjay Poonen, COO at VMware breaking down the announcement of Outposts, its relevance and impact on the market, and more importantly, the VMware AWS relationship. This is theCUBE bringing you all the action, day two of three days of wall-to-wall coverage. Two sets, hundreds of video assets coming, tons of posts on siliconangle.com, where all the coverage is. We'll be right back with more after this short break. (techno music)

Published Date : Nov 29 2018

SUMMARY :

Brought to you by Amazon Web Services, We've been to all re:Invents except for the first year. Want to dig in to it with our guest, and I think this is becoming like the Mecca and VMware was, when you guys recognized the sea change it's just an example of not just the validity of VMware And the partnership with VMware highlights and you guys have built a very good relationship. Well, the amazing thing to me, is, and some of the public cloud vendors, And the other observation I make is, you know, And as you know, since we last talked, we acquired Heptio. But, it's not going to be shipping for about a year. and applying this now, to a use case And that gives you a consistent networking model, One of the things that I'm excited by, intrigued by, and a few of the airports in New York, So, since you guys are on more of the software side, and the specialness of this Well, it's going to be very interesting, We're going to partner very well with IBM Cloud. And that's how we play. Before you wrap, now you know what we think of you, a true Bollywood superstar. Well I got to tell ya, I was very intimidated. What the heck does Sushmita Sen have to do" I know you got to catch a flight. and impact on the market, and more importantly,

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Rebecca Shockley & Alfred Essa, IBM | IBM CDO Fall Summit 2018


 

>> Live from Boston, it's theCUBE. Covering IBM Chief Data Officer Summit. Brought to you by IBM. >> Welcome back, everyone, to theCUBE's live coverage of the IBM CDO Summit here in Boston, Massachusetts. I'm your host, Rebecca Knight, along with my co-host Paul Gillin. We have two guests for this session, we have Rebecca Shockley, she is executive consultant and IBM Global Business Services, and Alfred Essa, vice president analytics and R&D at McGraw-Hill Education. Rebecca and Alfred, thanks so much for coming on theCUBE. >> Thanks for having us. >> So I'm going to start with you, Rebecca. You're giving a speech tomorrow about the AI ladder, I know you haven't finished writing it-- >> Shh, don't tell. >> You're giving a speech about the AI ladder, what is the AI ladder? >> So, when we think about artificial intelligence, or augmented intelligence, it's very pervasive, we're starting to see it a lot more in organizations. But the AI ladder basically says that you need to build on a foundation of data, so that data and information architecture's your first rung, and with that data, then you can do analytics, next rung, move into machine learning once you're getting more comfortable, and that opens up the whole world of AI. And part of what we're seeing is organizations trying to jump to the top of the ladder or scramble up the ladder really quickly and then realize they need to come back down and do some foundational work with their data. I've been doing data and analytics with IBM for 21 years, and data governance is never fun. It's hard. And people would just as soon go do something else than do data governance, data security, data stewardship. Especially as we're seeing more business-side use of data. When I started my career, data was very much an IT thing, right. And part of my early career was basically just getting IT and business to communicate in a way that they were saying the same things. Well now you have a lot more self-service analytics, and business leaders, business executives, making software decisions and various decisions that impact the data, without necessarily understanding the ripples that their decisions can have throughout the data infrastructure, because that's not their forte. >> So what's the outcome, what's the result of this? >> Well, you start to see organizations, it's similar to what we saw when organizations first started making data lakes, right? The whole concept of a data lake, very exciting, interesting, getting all the data in together, whether it's virtual or physical. What ended up happening is without proper governance, without proper measures in place, you ended up with a data swamp instead of a data lake. Things got very messy very quickly, and instead of creating opportunities you were essentially creating problems. And so what we're advising clients, is you really have to make sure that you're focused on taking care of that first rung, right? Your data architecture, your information architecture, and treating the data with the respect as a strategic asset that it is, and making sure that you're dealing with that data in a proper manner, right? So, basically telling them, yes we understand that's fun up there, but come back down and deal with your foundation. And for a lot of organizations, they've never really stepped into data governance, because again, data isn't what they think makes the company run, right? So banks are bankers, not data people, but at the same time, how do you run a bank without data? >> Well exactly. And I want to bring you into this conversation, Alfred, as McGraw-Hill, a company that is climbing the ladder, in a more steady fashion. What's your approach? How do you think about bringing your teams of data scientists together to work to improve the company's bottom line, to enhance the customer experience? >> First I'd sort of like to start with laying some of the context of what we do. McGraw-Hill Education has been traditionally a textbook publisher, we've been around for over a hundred years, I started with the company over a hundred years ago. (all laughing) >> You've aged well. >> But we no longer think of ourselves as a textbook publisher. We're in the midst of a massive digital transformation. We started that journey over five years ago. So we think of ourselves as a software company. We're trying to create intelligent software based on smart data. But it's not just about software and AI and data, when it comes to education it's a tale of two cities. This is not just the U.S., but internationally. Used to be, we were born, went to school, got a job, raised a family, retired, and then we die. Well now, education is not episodic. People need to be educated, it's life-long learning. It's survival, but also flourishing. So that's created a massive problem and a challenge. It's a tale of two cities, by that I mean there's an incredible opportunity to apply technology, AI, we see a lot of potential in the new technologies. In that sense, it's the best of times. The worst of times is, we're faced with massive problems. There's a lot of inequity, we need to educate a people who have largely been neglected. That's the context. So I think in now answering your question about data science teams, first and foremost, we like to get people on the teams excited about the mission. It's like, what are we trying to achieve? What's the problem that we're trying to achieve? And I think the best employees, including data scientists, they like solving hard problems. And so, first thing that we try to do is, it's not what skills you have, but do you like solving really, really hard problems. And then taking it next step, I think the exciting thing about data science is it's an interdisciplinary field. It's not one skill, but you need to bring together a combination of skills. And then you also have to excel and have the ability to work in teams. >> You said that the AI has potential to improve the education process. Now, people have only so much capacity to learn, how can AI accelerate that process? >> Yeah, so if we stand back a little bit and look at the traditional model of education, there's nothing wrong with it but it was successful for a certain period of years, and it works for some people. But now the need for education is universal, and life long. So what our basic model, current model of education is lecture mode and testing. Now from a learning perspective, learning science perspective, all the research indicates that that doesn't work. It might work for a small group of people, but it's not universally applicable. What we're trying to do, and this is the promise of AI, it's not AI alone, but I think this is a big part of AI. What we can do is begin to customize and tailor the education to each individual's specific needs. And just to give you one quick example of that, different students come in with different levels of prior knowledge. Not everyone comes into a class, or a learning experience, knowing the same things. So what we can do with AI is determine, very, very precisely, just think of it as a brain scan, of what is it each student need to know at every given point in time, and then based on that we can determine also, this is where the models and algorithms are, what are you ready to learn next. And what you might be ready to learn next and what I might be ready to learn next is going to be very different. So our algorithms also help route delivery of information and knowledge at the right time to the right person, and so on. >> I mean, you're talking about these massive social challenges. Education as solving global inequity, and not every company has maybe such a high-minded purpose. But does it take that kind of mission, that kind of purpose, to unite employees? Both of you, I'm interested in your perspectives here. >> I don't think it takes, you know, a mission of solving global education. I do firmly agree with what Al said about people need a mission, they need to understand the outcome, and helping organizations see that outcome as being possible, gives them that rally point. So I don't disagree, I think everybody needs a mission to work towards but it doesn't have to be solving-- >> You want to extract that mission to a higher level, then. >> Exactly. >> Making the world a better place. >> Exactly, or at least your little corner of the world. Again what we're seeing, the difficulty is helping business leaders or consumers or whomever understand how data plays into that. You may have a goal of, we want better relationship with our customer, right? And at least folks of my age think that's a personal one-on-one kind of thing. Understanding who you are, I can find that much more quickly by looking at all your past transactions, and all of your past behaviors, and whether you clicked this or that. And you should expect that I remember things from one conversation to the next. And helping people understand that, you know, helping the folks who are doing the work, understand that the outcome will be that we can actually treat our customers the way that you want to be treated as a person, gives them that sense of purpose, and helps them connect the dots better. >> One of the big challenges that we hear CDOs face is getting buy-in, and what you're proposing about this new model really appending the old sage on the stage model, I mean, is there a lot of pushback? Is it difficult to get the buy-in and all stakeholders to be on the same page? >> Yeah, it is, I think it's doubly difficult. The way I think about it is, it's like a shift change in hockey, where you have one shift that's on the ice and another one that's about to come on the ice, that's a period of maximum vulnerability. That's where a lot of goals are scored, people get upset, start fighting. (all laughing) That's hockey. >> That's what you do. >> Organizations and companies are faced with the same challenge. It's not that they're resisting change. Many companies have been successful with one business model, while they're trying to bring in a new business model. Now you can't jettison the old business model because often that's paying the bills. That's the source of the revenue. So the real challenge is how are you going to balance out these two things at the same time? So that's doubly difficult, right. >> I want to ask you quickly, 'cause we have to end here, but there's a terrible shortage of cybersecurity professionals, data science professionals, the universities are simply not able to keep up with demand. Do you see the potential for AI to step in and fill that role? >> I don't think technology by itself will fill that role. I think there is a deficit of talented people. I think what's going to help fill that is getting people excited about really large problems that can be solved with this technology. I think, actually I think the talent is there, what I see is, I think we need to do a better job of bringing more women, other diverse groups, into the mix. There are a lot of barriers in diversity in bringing talented people. I think they're out there, I think we could do a much better job with that. >> Recruiting them, right. Alfred, Rebecca, thanks so much for coming on theCUBE, it was a pleasure. >> Thank you so much for having us. >> I'm Rebecca Knight, for Paul Gillin, we will have more from theCUBE's live coverage of the IBM CDO Summit here in Boston coming up in just a little bit.

Published Date : Nov 15 2018

SUMMARY :

Brought to you by IBM. of the IBM CDO Summit here in Boston, Massachusetts. about the AI ladder, I know you haven't But the AI ladder basically says that you need to but at the same time, how do you run a bank without data? And I want to bring you into this conversation, Alfred, laying some of the context of what we do. it's not what skills you have, You said that the AI has potential And just to give you one quick example of that, that kind of purpose, to unite employees? I don't think it takes, you know, the way that you want to be treated as a person, and another one that's about to come on the ice, So the real challenge is how are you going to balance out the universities are simply not able to keep up with demand. I think we need to do a better job of coming on theCUBE, it was a pleasure. of the IBM CDO Summit here in Boston

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Jed Ayres, Igel | CUBEConversation, August 2018


 

(intense orchestral music) >> Welcome back everybody, Jeff Frick here with theCUBE, we're in our Palo Alto studio havin' a CUBEConversation, we're getting ready for the madness of the fall conference season to hit us full force, so we're excited to have things a little bit quiet this week and have a special guest, he's Jed Ayres, he is the North American CEO, and the Global CMO for IGEL, great to see you. >> Well, great to be here, thanks for inviting me, I know a lot of luminaries in the tech industry have sat in this chair so, >> That's right. >> It's an honor to have a chance to chat with you today. >> Well thank you, I appreciate that. So give a, for the people that aren't familiar with IGEL, give us kind of the IGEL 101. >> Yeah, so I wasn't actually that familiar with IGEL two years ago, and I've spent, you know over a decade in the end user compute space, so they were a little bit of a mystery I think to most people in the US; however, the companies been around for over 20 years, they're actually the number one Thin Client player in Germany since 2006. So what they really specialize in is a Linux, read-only operating system, that's fused to a management console that just really works for these cloud delivered desktops and applications, right? And so, a little bit shrouded in sort of this world of Thin Client hardware, but the company is really a software company. And so, the opportunity for me was to really help them build their US operation, but probably more importantly, put the right sort of US marketing prowess and kind of English first, we got out and kind of re-wrote their marketing playbook, and we really have exposed the IP of this beautiful, light, Linux OS, and the management tool which you know couldn't have been at a better time in terms of what's happening in the industry. >> So just to call those three things out specifically, so it's a light OS, that's Linux based, for x86 devices, >> Exactly. >> And so you're workin' with Citrix and VMware, and a lot of those platforms. >> I mean there's 17 different protocols that it works with out of the box, so, really when you think about you know Microsoft RDP, Parallels, Ericom, some of the, some things that you know, back in the history of end user compute, we still, out of the box, are synced up with those technologies. But the primary ones today are Citrix, and VMware, and Microsoft, and yeah we'll soon be doing some things with Amazon as well workin' with them to be their first Linux client for workspaces, so. >> So, we talked a little bit before we turned the cameras on, you know the bring your own device thing, we saw it first in mobile phones in a big, big way, you know people are bringing their laptops and all kinds of interesting stuff. At the same time you've got kind of this cloud move with the centralized control, and you don't have all this kind of rogue stuff, and you know some of the clouds like I don't have the right excel spreadsheet on this laptop, it's on my home desktop. So you guys are kind of riding that wave, but enabling a really interesting play on it, you enable a BYOD, but you actually have an opportunity to basically supplant that, overlay, I don't know what's the right verb, to enable a secure, lightweight, centralized control. >> Yeah, so there's really three ways to get this operating system, right? You can get it on the traditional hardware form factors that you find for most Thin Clients, right, we've got kind of a entry level, mid, high-level all in one. And then we have the ability to convert a device, so we would actually wipe the entire operating system off the device, and just, you'll have a last boot to the IGEL OS. But then, really what, two years ago we came out with this, and this is what we call the UD Pocket, it's about the size of your thumbnail, it's a hardened USB read-only stick, it has the same OS that the hardware has and the converter software has, it's just a bootable, right? So I could plug this into that laptop you have there, and you would boot to a secure Linux operating system, and we'd point it to whatever cloud delivery service that you're, you know, theCUBE was using, so if it was Citrix or VMware, so. Yeah, this has opened up a lot of new use cases, it's sort of changed how people think about Thin Clients too right, you sort of think Thin Client, kiosk task worker, not necessarily the CEO of a company or a knowledge worker, or a physician running an emergency room might want to have their own device, same device they use at home. So yeah, this has opened up a lot of interesting use cases: contractors, interns, we even see it being used for people in environments, in hospitals, where they keep a stash of these, for high availability, I guess ransomware. Right, you've seen these hospitals basically being attacked, what they would do is go and put these in, boot to a secondary epic or server environment, and you know this is kind of their way of not knowing which device is infected, they can just easily bypass that device, boot to this read-only operating system. >> It's a real game changer in terms of opening up >> It really is. >> Not only, not only, removing all the vulnerabilities that come with with kind of a classic laptop situation, but even giving the things new life, right, enabling them to kind of be reborn, really as a Thin, or excuse me as a light client. >> Yeah, we see three reasons why people are are buying IGEL today. And it's fun for me 'cause I get go out you know talk to a lot of customers and partners, you know we're 100% partner oriented organization, which is fun for me since I spent 20 years as a partner. But what's been really fun is that it's a C-level conversation, you wouldn't think Thin Client, I can go talk to a CEO or a CFO or a CIO, but this is a game changer. And it's really three things, right, we can save people money, which people like that, right, when you can save a company from having to go purchase 5000 new endpoints; we just had a hospital in Texas, they were about to buy 5000 new endpoints, that's about five million dollars, right? We walked in and sold them 5000 convertor licenses, for about a half a million dollars, so they saved four and a half million dollars in not having to buy new hardware. And then, you know the second piece is the operational headcount savings. When you think about managing Windows today, it's you know maybe great organizations one person can do 500 devices maybe; if you're lucky and you really have all the right tools. With IGEL we have numbers like one person managing 30000 devices, in retail, you know places where you don't have a lot of smart hands. And then the third reason why, you know we can talk to a lot of CSOs now too, right, as people are gravitating towards Linux, because of the challenges with Windows, and managing Windows, and securing windows. And Linux, when I first started people said kind of don't talk about Linux, you know, it's maybe kind of a bad word and people get you know scared. Today we walk in and we lead with this is a very mature Linux operating system, and we have a fantastic security roadmap... >> And 20 years of history, right? So you've got institutional, a foundation that you can build off of. It's funny on the Linux thing right, 'cause I'm sure they said the same thing when they wanted to roll Linux into the data centers back in the day. >> Exactly. (Jeff laughs) Yeah, this is the year where we believe, and IDC is tracking this pretty closely, that this is the year where on the endpoints of this Thin Client, you're going to see Windows is going to be surpassed by Linux; and that tracker that IDC does doesn't even track the ones that are being repurposed, right, where Linux is going in because it's going in on old hardware. So just on the new hardware it's going to be about 40% Linux and 40% Windows, and then there's you know some other you know operating systems out there, but. Yeah, this is, this is an exciting time to be in this space, right? We look at the challenges of managing Windows 10, we look at the security issues of GDPR, you know and people are just really gravitating towards towards this idea of a Linux OS. >> Right. It's funny, it's not, not directly related, but corollary, you know as Google really pushes Chromebooks as part of their enterprise play as a much more secure platform with central control, and in fact I think Diane mentioned at the Google Cloud show that we use like 37 different basically online applications to get work done these days, whether you're in your Salesforce application, or Marketo, or Gmail Suite, or you know. So we're all basically browser based application delivery, so it really does open up this opportunity for the incline 'cause you don't really need that much function, >> Exactly. >> But you know it's serving up that central HTTP. >> I talk to people all the time who have fancy, thousands of dollar laptops, and their like, all they do is hit a browser, right? And the reality is, is that's where we're going right, it's a pane of glass accessing data somewhere else, an application somewhere else right? But the underlying operating system still needs to be secured. If you look at sort of the priorities of CIOs today, endpoint--securities number one right, and inside of that it's typically endpoint security, as you know the most important piece of it right? And so that's really where IGEL is having a wonderful time taking tremendous market share, you know we've moved, in just the time that I've been in the US, from seven to three, just in the sort of hardware part of it. And we're just having a lot of fun growing an organization that's, you know and you're growin' in triple digits, it's kind of a Cinderella moment for your career, right, so. >> Plus different kind of challenges. (laughs) >> Exactly. Exactly. >> So is there a particular vertical, is there a particular kind of business group within the companies that you guys use as a point of entry? Or, I mean how do you, what's kind of your go-to-market, >> Yeah, so there's some very specific-- >> 'cause it's a huge opportunity right. >> Yeah, very specific verticals where we're having great success in: hospitals are number one, we've sold to 143 hospitals in the US, if you can believe that, and we're in pretty, and that was just last year. >> 140? Just in a typical, typical, average, whatever metric you want to use, is how many OS's going into a hospital? >> I mean, last quarter we sold about 10000 into one hospital, you know it's usually anywhere from 2500 to 5000, 10000. And then you know these hospitals are all merging with each other, that's another value of IGEL is that they're all kind of combing, and as they combine, IGEL can take all this heterogeneous hardware, heterogeneous operating systems, homogenize it, make it easy to manage and secure. >> Putting it all back in the same spot. >> So yeah, it's definitely healthcare, healthcare's number one, but we're also doing very well in retail, very well in finance, kind of banks, really well in higher education; and like I said, we're getting to talk to at the C-level, right, they really love the savings, right? Not only are the saving on the hardware, but they can get rid of antivirus, disk encryption, they can redeploy people to do things other than patching devices. We have some brilliant things in terms of the technology; you mentioned we have the IP of 20 years, the three guys who wrote the code at the very beginning of the 20 years ago actually they were with an IGEL version before the current iteration. So literally in the end of the '90s they were, idea was let's build an operating system for the internet, which you know they may have been a bit ahead of their time in 1999, but those three guys are actually still in the building. There's a hundred engineers in Germany that are sort of iterating on this and solving for this problem, and I think they've, you know now with the US operation and the new marketing, we're kind of, it's just a perfect storm I would say. >> And then with 5G and again the increasing importance of cloud-based applications, whether it be Salesforce, or whether it be, whatever that's delivered through Amazon, I mean you guys are in a very good spot. >> Yeah, and it's, I would tell you it's not just about, you know it's this operating system fused to a management console, but then it's sort of the curation of that, right? Like okay, every 12 weeks I'm going to push you a new OS, and I have an elegant way to get that to 10's of thousands of devices. So we're also starting to see managed service providers, right, the guys that are under contract to manage millions of devices. You know the DxEs and Wipros and IBM Global Services, those guys are starting to really look at IGEL also, right, 'cause, for the same reasons the enterprises who are managing large environments; so that's been an exciting part of our growth as well. >> Yeah, and that's another huge validation point, 'cause those guys don't make small bets, they only make big bets. >> Exactly and market's sort of hardened into their architecture, which is great. >> Alright, Jed, well it sounds like a great story, and we look forward to watching it unfold over the next couple years. >> Yeah! Well hopefully, for those of the people who are out watchin' we'd love to have them come by; we're doing an event in Las Vegas inside the Mandalay Bay, at VMworld, we actually have our own event, rightfully called disrupt. And we're going to be there from the 26th to the 29th, and-- >> What venue? >> In the Border Grill, so we actually taken over this restaurant, that's kind of like right you know in the footpath of-- >> In the hallway, right? >> In the hallway yeah. >> That's the inside, I know exactly where that is. >> So yeah, we're actually takin' a page out of your book, we're going to have a little EUC TV, so we'll be interviewing people about you know what they're doing to solve for their end user compute challenges, and talkin' to the ecosystem; we have an innovation theater in the Border Grill, we're going to throw a pool party at the end, out at one of those beautiful pools that no one ever gets to go to in Vegas. (both laugh) >> We look at it though as we walk just past the Border Grill, you can find a long beautiful look at that pool. >> So we're going to try to take advantage of it, although it'll be a bit hot out there, yeah it's a hundred plus degrees in Vegas this time of year, but we're going to have some fun. You know, you got to do that a little bit, work hard, play hard. >> Alright, we'll see ya in Vegas in a couple weeks! >> Yep! Look forward to it. >> Thanks for stopping by. >> Thanks very much. >> Alright he's Jed, I'm Jeff, you're watchin' the CUBEConversation from our Palo Alto studios, thanks for watchin', I'll see ya next time. (intense orchestral music)

Published Date : Aug 16 2018

SUMMARY :

and the Global CMO for IGEL, great to see you. to have a chance to chat with you today. So give a, for the people that aren't familiar with IGEL, you know over a decade in the end user compute space, Citrix and VMware, and a lot of those platforms. really when you think about you know Microsoft RDP, and you know some of the clouds like and you know this is kind of their way of but even giving the things new life, right, And then, you know the second piece a foundation that you can build off of. and then there's you know some other you know as Google really pushes Chromebooks But you know it's as you know the most important piece of it right? Plus different kind of challenges. Exactly. if you can believe that, And then you know these hospitals are which you know they may have been I mean you guys are in a very good spot. you know it's this operating system Yeah, and that's another huge validation point, Exactly and market's sort of and we look forward to watching it unfold And we're going to be there from the 26th to the 29th, you know what they're doing to solve for their you can find a long beautiful look at that pool. You know, you got to do that a little bit, Look forward to it. you're watchin' the CUBEConversation

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Veeru Ramaswamy, IBM | CUBEConversation


 

(upbeat music) >> Hi we're at the Palo Alto studio of SiliconANGLE Media and theCUBE. My name is George Gilbert, we have a special guest with us this week, Veeru Ramaswamy who is VP IBM Watson IoT platform and he's here to fill us in on the incredible amount of innovation and growth that's going on in that sector of the world and we're going to talk more broadly about IoT and digital twins as a broad new construct that we're seeing in how to build enterprise systems. So Veeru, good to have you. Why don't you introduce yourself and tell us a little bit about your background. >> Thanks George, thanks for having me. I've been in the technology space for a long time and if you look at what's happening in the IoT, in the digital space, it's pretty interesting the amount of growth, the amount of productivity and efficiency the companies are trying to achieve. It is just phenomenal and I think we're now turning off the hype cycle and getting into real actions in a lot of businesses. Prior to joining IBM, I was junior offiicer and senior VP of data science with Cable Vision where I led the data strategy for the entire company and prior to that I was the GE of one of the first two guys who actually built the Cyamon digital center. GE digital center, it's a center of excellence. Looking at different kinds of IoT related projects and products along with leading some of the UX and the analytics and the club ration or the social integration. So that's the background. >> So just to set context 'cause this is as we were talking before, there was another era when Steve Jobs was talking about the next work station and he talked about objectory imitation and then everything was sprinkled with fairy dust about objects. So help us distinguish between IoT and digital twins which GE was brilliant in marketing 'cause that concept everyone could grasp. Help us understand where they fit. >> The idea of digital twin is, how do you abstract the actual physical entity out there in the world, and create an object model out of it. So it's very similar in that sense, what happened in the 90s for Steve Jobs and if you look at that object abstraction, is what is now happening in the digital twin space from the IoT angle. The way we look at IoT is we look at every center which is out there which can actually produce a metric on every device which produces a metric we consider as a sense so it could be as simple as the pressure, temperature, humidity sensors or it could be as complicated as cardio sensors and your healthcare and so on and so forth. The concept of bringing these sensors into the to the digital world, the data from that physical world to the digital world is what is making it even more abstract from a programming perspective. >> Help us understand, so it sounds like we're going to have these fire hoses of data. How do we organize that into something that someone who's going to work on that data, someone is going to program to it. How do they make sense out of it the way a normal person looks at a physical object? >> That's a great question. We're looking at sensors as a device that we can measure out of and that we call it a device twin. Taking the data that's coming from the device, we call that as a device twin and then your physical asset, the physical thing itself, which could be elevators, jet engines anything, physical asset that we have what we call the asset twin and there's hierarchical model that we believe that will have to be existing for the digital twin to be actually constructed from an IoT perspective. The asset twins will basically encompass some of the device twins and then we actually take that and represent the digital twin on a physical world of that particular asset. >> So that would be sort of like as we were talking about earlier like an elevator might be the asset but the devices within it might be the bricks and the pulleys and the panels for operating it. >> Veeru: Exactly. >> And it's then the hierarchy of these or in manufacturing terms, the building materials that becomes a critical part of the twin. What are some other components of this digital twin? >> When we talk about digital twin, we don't just take the blueprint as schematics. We also think about the system, the process, the operation that goes along with that physical asset and when we capture that and be able to model that, in the digital world, then that gives you the ability to do a lot of things where you don't have to do it in the physical world. For instance, you don't have to train your people but on the physical world, if it is periodical systems and so on and so forth, you could actually train them in the digital world and then be able to allow them to operate on the physical world whenever it's needed. Or if you want to increase your productivity or efficiency doing predictive models and so forth, you can test all the models in your digital world and then you actually deploy it in your physical world. >> That's great for context setting. How would you think of, this digital twins is more than just a representation of the structure, but it's also got the behavior in there. So in a sense it's a sensor and an actuator in that you could program the real world. What would that look like? What things can you do with that sort of approach? >> So when you actually have the data coming this humongous amount of terabyte data that comes from the sensors, once you model it and you get the insights out of that, based on the insight, you can take an actionable outcome that could be turning off an actuator or turning on an actuator and simple thngs like in the elevator case, open the door, shut the door, move the elevator up, move the elevator down etc. etc All of these things can be done from a digital world. That's where it makes a humongous difference. >> Okay, so it's a structured way of interacting with the highly structured world around us. >> Veeru: That's right. >> Okay, so it's not the narrow definition that many of us have been used to like an airplane engine or the autonomous driving capability of a car. It's more general than that. >> Yeah, it is more general than that. >> Now let's talk about having sort of set context with the definition so everyone knows we're talking about a broader sense that's going on. What are some of the business impacts in terms of operational efficiency, maybe just the first-order impact. But what about the ability to change products into more customizable services that have SLAs or entirely new business models including engineered order instead of make to stock. Tell us something about that hierarchy of value. >> That's a great question. You're talking about things like operations optimization and predicament and all of that which you can actually do from the digital world it's all on digital twin. You also can look into various kinds of business models now instead of a product, you can actually have a service out of the product and then be able to have different business models like powered by the hour, pay per use and kinds of things. So these kinds of models, business models can be tried out. Think about what's happening in the world of Air BnB and Uber, nobody owns any asset but still be able to make revenue by pay per use or power by the hour. I think that's an interesting model. I don't think it's being tested out so much in the physical asset world but I think that could be interesting model that you could actually try. >> One thing that I picked up at the Genius of Things event in Munich in February was that we really have to rethink about software markets in the sense that IBM's customers become in the way your channel, sometimes because they sell to their customers. Almost like a supply chain master or something similar and also pricing changes from potentially we've already migrated or are migrating from perpetual licenses to service softwares or service but now we could do unit pricing or SLA-based pricing, in which case you as a vendor have to start getting very smart about, you owe your customers the risk in meeting an SLA so it's almost more like insurance, actuarial modeling. >> Correct so the way we want think about is, how can we make our customers more, what do you call, monetizable. Their products to be monetizable with their customers and then in that case, when we enter into a service level agreement with our customers, there's always that risk of what we deliver to make their products and services more successful? There's always a risk component which we will have to work with the customers to make sure that combined model of what our customers are going to deliver is going to be more beneficial, more contributing to both bottom line and top line. >> That implies that your modeling, someone's modeling and risk from you the supplier to your customer as vendor to their customer. >> Right. >> That sounds tricky. >> I'm pretty sure we have a lot of financial risk modeling entered into our SLAs when we actually go to our customers. >> So that's a new business model for IBM, for IBM's sort of supply chain master type customers if that's the right word. As this capability, this technology pervades more industries, customers become software vendors or if not software vendors, services vendors for software enhanced products or service enhanced products. >> Exactly, exactly. >> Another thing, I'd listened to a briefing by IBM Global Services where they thought, ultimately, this might end up where there's far more industries are engineered to order instead of make to stock. How would this enable that? >> I think the way we want think about it is that most of the IoT based services will actually start by co-designing and co-developing with your customers. And that's where you're going to start. That's how you're going to start. You're not going to say, here's my 100 data centers and you bring your billion devices and connect and it's going to happen. We are going to start that way and then our customers are going to say, hey by the way, I have these used cases that we want to start doing, so that's why platform becomes so imortant. Once you have the platform, now you can scale, into a scale, individual silos as a vertical use case for them. We provide the platform and the use cases start driving on top of the platform. So the scale becomes much easier for the customers. >> So this sounds like the traditional application. The traditional way an application vendor might turn into a platform vendor which is a difficult transition in itself but you take a few use cases and then generalize into a platform. >> We call that a zone application services. The zone application service is basically, is drawing on perfectly cold platform service which actually provides you the abilities. So for instance like an asset management. An asset management can be done in an oil and gas rig, you can look at asset management in power tub vine, you can can look at asset management in a jet engine. You can do asset management across any different vertical but that is a common horizontal application so most of the time you get 80% of your asset management API's if you will. Then you can be able to scale across multiple different vertical applications and solutions. >> Hold that thought 'cause we're going to come back to joint development and leveraging expertise from vendor and customer and sharing that. Let's talk just at a high level one of the things that I keep hearing is that in Europe industry 4.0 is sort of the hot topic and in the states, it's more digital twins. Help parse that out for us. >> So the way we believe how digital twin should be viewed is a component view. What we mean the component view is that we have your knowledge graph representation of the real assets in the digital world and then you bring in your IoT sensors and connections to the models then you have your functional, logical, physical models that you want to bring into your knowledge graph and then you also want to be able to give the ability of search visualize allies. Kind of an intelligent experience for the end consumer and then you want to bring your similation models when you do the actual similation models in digital to bring it in there and then your enterprise asset management, your ERP systems, all of that and then when you connect, when you're able to build a knowledge graph, that's when the digital twin really connects with your enterprise systems. Sort of bring the OT and the IT together. >> So this is sort of to try and summarize 'cause there are a lot of moving parts in there. You've got you've got the product hierarchy which, in product Kaiser call it building materials, sort of the explosion of parts in an assembly, sub-assembly and then that provides like a structure, a data model then the machine learning models in the different types of models that they could be represent behavior and then when you put a knowledge graph across that structure and behavior, is that what makes it simulation ready? >> Yes, so you're talking about entities and connecting these entities with the actual relationship between these entities. That's the graph that holds the relation between nodes and your links. >> And then integrating the enterprise systems that maybe the lower level operation systems. That's how you effect business processes. >> Correct. >> For efficiency or optimization, automation. >> Yes, take a look at what you can do with like a shop floor optimization. You have all the building materials, you need to know from your existing ERP systems and then you will actually have the actual real parts that's coming to your shop floors to manage them and now base supposing, depending on whether you want to repair, you want to replace, you want an overall, you want to modify whatever that is, you want to look at your existing building materials and see, okay do I first have it do we need more? Do we need to order more? So your auditing system naturally gets integrated into that and then you have to integrate the data that's coming from these models and the availability of the existing assets with you. You can integrate it and say how fast can you actually start moving these out of your shop, into the. >> Okay that's where you translate essentially what's more like intelligent about an object or a rich object into sort of operational implications. >> Veeru: Yes. >> Okay operational process. Let's talk about customer engagement so far. There's intense interest in this. I remember in the Munich event, they were like they had to shut off attendance because they couldn't find a big enough venue. >> Veeru: That's true. >> So what are the characteristics of some of the most successful engagements or the ones that are promising. Maybe it's a little early to say successful. >> So, I think the way you can definitely see success from customer engagement are two fold. One is show what's possible. Show what's possible with after all desire to connect, collection of data, all of that so that one part of it. The second part is understand the customer. The customer has certain requirements in their existing processes and operations. Understand that and then deliver based on what solutions they are expecting, what applications they want to build. How you bring them together is what is, so we're thinking about. That Munich center you talked about. We are actually bringing in chip manufacturers, sensor manufacturers, device manufacturers. We are binging in network providers. We are bringing in SIs, system integrators all of them into the fold and show what is possible and then your partners enable you to get to market faster. That's how we see the engagement with customer should happen in a much more foster manner and show them what's possible. >> It sounds like in the chip industry Moore's law for many years it wasn't deterministic that you we would do double things every 18 months or two years, it was actually an incredibly complex ecosystem web where everyone's sort of product release cycles were synchronized so as to enable that. And it sounds like you're synchronizing the ecosystem to keep up. >> Exactly The saxel of a particular organization IoT efforts is going to depend on how do you build this ecosystem and how do you establish that ecosystem to get to market faster. That's going to be extremely key for all your integration efforts with your customer. >> Let's start narrowly with you. IBM what are the key skills that you feel you need to own starting from sort of the base rocket scientists you know who not only work on machine learning models but they come up with new algorithms on top of say tons of flow work or something like that. And all the way up to the guys who are going to work in conjunction with the customer to apply that science to a particular industry. How does that hold together? >> So it all starts on the platform. On the platform side we have all the developers, the engineers who build these platform all the video connection and all of that to make the connections. So you need the highest software development engineers to build these on the platform and then you also need the solution builders so who is in front of the customer understanding what kind of solutions you want to build. Solutions could be anything. It could be predictive maintenance, it could be as simple as management, it could be remote monitoring and diagnostics. It could be any of these solutions that you want to build and then the solution builders and the platform builders work together to make sure that it's the holistic approach for the customer at the final deployment. >> And how much is the solution builder typically in the early stages IBM or is there some expertise that the customer has to contribute almost like agile development, but not two programmers but like 500 and 500 from different companies. >> 500 is a bit too much. (laughs) I would say this is the concept of co-designing and co-development. We definitely want the ultimate, the developer, the engineers form, the subject exports from our customers and we also need our analytics experts and software developers to come and sit together and understand what's the use case. How do we actually bring in those optimized solution for the customer. >> What level of expertise or what type of expertise are the developers who are contributing to this effort in terms of do they have to, if you're working with manufacturing let's say auto manufacturing. Do they have to have automotive software development expertise or are they more generically analytics and the automotive customer brings in the specific industry expertise. >> It depends. In some cases we have RGB for instance. We have dedicated servers, that particular vertical service provider. We understand some of this industry knowledge. In some cases we don't, in some cases it actually comes from the customer. But it has to be an aggregation of the subject matter experts with our platform developers and solution developers sitting together, finding what's the solution. Literally going through, think about how we actually bring in the UX. What does a typical day of a persona look like? We always by the way believe it's an augmented allegiance which means the human and the machine work together rather than a complete. It gives you the answer for everything you ask for. >> It's a debate that keeps coming up Doug Anglebad sort of had his own answer like 50 years ago which was he sort of set the path for modern computing by saying we're not going to replace people, we're going to augment them and this is just a continuation of that. >> It's a continuation of that. >> Like UX design sounds like someone on the IBM side might be talking to the domain expert and the customer to say how does this workflow work. >> Exactly. So have this design thinking, design sessions with our customers and then based on that we take that knowledge, take it back, we build our mark ups, we build our wire frames, visual designs and the analytics and software that goes behind it and then we provide on top of platform. So most of the platform work, the standard what do you call table state connections, collection of data. All of that as they are already existing then it's one level above as to what the particular solution a customer wants. That's when we actually. >> In terms of getting the customer organization aligned to make this project successful, what are some of the different configurations? Who needs to be a sponsor? Where does budget typically come from? How long are the pilots? That sort of stuff so to set expectations. >> We believe in all the agile thinking, agile development and we believe in all of that. It's almost given now. So depending on where the customer comes from so the customer could actually directly come and sign up to our platform on the existing cloud infrastructure and then they will say, okay we want to build applications then there are some customers really big customers, large enterprises who want to say, give me the platform, we have our solution folks. We will want to work on board with you but we also want somebody who understands building solutions. We integrate with our solution developers and then we build on top of that. They build on top of that actually. So you have that model as well and then you have a GBS which actually does this, has been doing this for years, decades. >> George: Almost like from the silicon. >> All the way up to the application level. >> When the customer is not outsourcing completely, The custom app that they need to build in other words when when they need to go to GBS Global Business Services, whereas if they want a semi-packaged app, can they go to the industry solutions group? >> Yes. >> I assume it's the IoT, Industry Solutions Group. >> Solutions group, yes. >> They then take a it's almost maybe a framework or an existing application that needs customization. >> Exactly so we have IoT-4. IoT for manufacturing, IoT for retail, IoT for insurance IoT for you name it. We have all these industry solutions so there would be some amount of template which is already existing in some fashion so when GBS gets a request to say here is customer X coming and asking for a particular solution. They would come back to IoT solutions group to say, they already have some template solutions from where we can start from rather than building it from scratch. You speed to market again is much faster and then based on that, if it's something that is to be customizable, both of them work together with the customer and then make that happen, and they leverage our platform underneath to do all the connection collection data analytics and so on and so forth that goes along with that. >> Tell me this from everything we hear. There's a huge talent shortage. Tell me in which roles is there the greatest shortage and then how do different members of the ecosystem platform vendors, solution vendors sort of a supply-chain master customers and their customers. How do they attract and retain and train? >> It's a fantastic question. One of the difficulties both in the valley and everywhere across is that three is a skill gap. You want advanced data scientists you want advances machinery experts, you want advanced AI specialists to actually come in. Luckily for us, we have about 1000 data scientists and AI specialists distributed across the globe. >> When you say 1000 data scientists and AI specialists, help us understand which layer are they-- >> It could be all the way from like a BI person all the way to people who can build advanced AI models. >> On top of an engine or a framework. >> We have our Watson APIs from which we build then we have our data signs experience which actually has some of the models then built on top of what's in the data platform so we take that as well. There are many different ways by which we can actually bring the AM model missionary models to build. >> Where do you find those people? Not just the sort of band strengths that's been with IBM for years but to grow that skill space and then where are they also attracted to? >> It's a great question. The valley definitely has a lot of talent, then we also go outside. We have multiple centers of excellence in Israel, in India, in China. So we have multiple centers of excellence we gather from them. It's difficult to get all the talent just from US or just from one country so it's naturally that talent has to be much more improvement and enhanced all the wat fom fresh graduates from colleges to more experienced folks in the in the actual profession. >> What about when you say enhancing the pool talent you have. Could it also include productivity improvements, qualitative productivity improvements in the tools that makes machine learning more accessible at any level? The old story of rising obstruction layers where deep learning might help design statistical models by doing future engineering and optimizing the search for the best model, that sort of stuff. >> Tools are very, very hopeful. There are so many. We have from our tools to python tools to psychic and all of that which can help the data scientist. The key part is the knowledge of the data scientist so data science, you need the algorithm, the statistical background, then you need your applications software development background and then you also need the domestics for engineering background. You have to bring all of them together. >> We don't have too many Michaelangelos who are these all around geniuses. There's the issue of, how do you to get them to work more effectively together and then assuming even each of those are in short supply, how do you make them more productive? >> So making them more productive is by giving them the right tools and resources to work with. I think that's the best way to do it, and in some cases in my organization, we just say, okay we know that a particular person is skilled is up skilled in certain technologies and certain skill sets and then give them all the tools and resources for them to go on build. There's a constant education training process that goes through that we in fact, we have our entire Watson ED platform that can be learned on Kosera today. >> George: Interesting. >> So people can go and learn how to build a platform from a Kosera. >> When we start talking with clients and with vendors, things we hear is that and we were kind of I think early that calling foul but in the open source infrastructure big data infrastructure this notion of mix-and-match and roll your own pipeline sounded so alluring, but in the end it was only the big Internet companies and maybe some big banks and telcos that had the people to operate that stuff and probably even fewer who could build stuff on it. Do we do we need to up level or simplify some of those roles because mainstream companies can't have enough or won't will have enough data scientists or other roles needed to make that whole team work >> I think it will be a combination of both one is we need to up school our existing students with the stem background, that's one thing and the other aspect is, how do you up scale your existing folks in your companies with the latest tools and how can you automate more things so that people who may not be schooled will still be able to use the tool to deliver other things but they don't have to go to a rigorous curriculum to actually be able to deal with it. >> So what does that look like? Give us an example. >> Think of tools like today. There are a lot of BI folks who can actually build. BI is usually your trends and graphs and charts that comes out of the data which are simple things. So they understand the distribution and so on and so forth but they may not know what is the random model. If you look at tools today, that actually gives you to build them, once you give the data to that model, it actually gives you the outputs so they don't really have to go dig deep I have to understand the decision tree model and so on and so forth. They have the data, they can give the data, tools like that. There are so many different tools which would actually give you the outputs and then they can actually start building app, the analytics application on top of that rather than being worried about how do I write 1000 line code or 2000 line code to actually build that model itself. >> The inbuilt machine learning models in and intend, integrated to like pentaho or what's another example. I'm trying to think, I lost my, I having a senior moment. These happen too often now. >> We do have it in our own data science tools. We already have those models supported. You can actually go and call those in your web portal and be able to call the data and then call the model and then you'll get all that. >> George: Splank has something like that. >> Splank does, yes. >> I don't know how functional it is but it seems to be oriented towards like someone who built a dashboard can sort of wire up a model, it gives you an example of what type of predictions or what type of data you need. >> True, in the Splank case, I think it is more of BI tool actually supporting a level of data science moral support on the back. I do not know, maybe I have to look at this but in our case we have a complete data science experience where you actually start from the minute the data gets ingested, you can actually start the storage, the transformation, the analytics and all of that can be done in less than 10 lines of coding. You can just actually do the whole thing. You just call those functions then it will the right there in front of you. So in twin you can do that. That I think is much more powerful and there are tools, there are many many tools today. >> So you're saying that data science experience is an enter in pipeline and therefore can integrate what were boundaries between separate products. >> The boundary is becoming narrower and narrower in some sense. You can go all the way from data ingestion to the analytics in just few clicks or few lines of course. That's what's happening today. Integrated experience if you will. >> That's different from the specialized skills where you might have a tri-factor, prexada or something similar as for the wrangling and then something else for sort of the the visualizations like Altracks or Tavlo and then into modeling. >> A year or so ago, most of data scientists try to spend a lot of time doing data wrangling because some of the models, they can actually call very directly but the wrangling is actually where they spend their time. How do you get the data crawl the data, cleanse the data, etc. That is all now part of our data platform. It is already integrated into the platform so you don't have to go through some of these things. >> Where are you finding the first success for that tool suite? >> Today it is almost integrated with, for instance, I had a case where we exchange the data we integrate that into what's in the Watson data platform and the Watson APIs is a layer above us in the platform where we actually use the analytics tools, more advanced AI tools but the simple machinery models and so on and so forth is already integrated into as part of the Watson data platform. It is going to become an integrated experience through and through. >> To connect data science experience into eWatson IoT platform and maybe a little higher at this quasi-solution layer. >> Correct, exactly. >> Okay, interesting. >> We are doing that today and given the fact that we have so much happening on the edge side of things which means mission critical systems today are expecting stream analysts to get to get insights right there and then be able to provide the outcomes at the edge rather than pushing all the data up to your cloud and then bringing it back down. >> Let's talk about edge versus cloud. Obviously, we can't for latency and band width reasons we can't forward all the data to the cloud, but there's different use cases. We were talking to Matasa Harry at Sparks Summit and one of the use cases he talked about was video. You can't send obviously all the video back and you typically on an edge device wouldn't have heavy-duty machine learning, but for video camera, you might want to learn what is anomalous or behavior call out for that camera. Help us understand some of the different use cases and how much data do you bring back and how frequently do retrain the models? >> In the case of video, it's so true that you want to do a lot of any object ignition and so on and so forth in the video itself. We have tools today, we have cameras outside where if a van goes it detect the particular object in the video live. Realtime streaming analytics so we can do that today. What I'm seeing today in the market is, in the transaction between the edge and the cloud. We believe edge is an extension of the cloud, closer to the asset or device and we believe that models are going to get pushed from the cloud, closer to the edge because the compute capacity and storage and the networking capacity are all improving. We are pushing more and more computing to their devices. >> When you talk about pushing more of the processing. you're talking more about predicts and inferencing then the training. >> Correct. >> Okay. >> I don't think I see so much of the training needs to be done at the edge. >> George: You don't see it. >> No, not yet at least. We see the training happening in the cloud and then once a train, the model has been trained, then you come to a steady, steady model and then that is the model you want to push. When you say model, it could be a bunch of coefficients. That could be pushed onto the edge and then when a new data comes in, you evaluate, make decisions on that, create insights and push it back as actions to the asset and then that data can be pushed back into the cloud once a day or once in a week, whatever that is. Whatever the capacity of the device you have and we believe that edge can go across multiple scales. We believe it could be as small with 128 MB it could be one or two which I see sitting in your local data center on the premise. >> I've had to hear examples of 32 megs in elevators. >> Exactly. >> There might be more like a sort of bandwidth and latency oriented platform at the edge and then throughput and an volume in the cloud for training. And then there's the issue of do you have a model at the edge that corresponds to that instance of a physical asset and then do you have an ensemble meaning, the model that maps to that instance, plus a master canonical model. Does that work for? >> In some cases, I think it'll be I think they have master canonical model and other subsidiary models based on what the asset, it could be a fleet so you in the fleet of assets which you have, you can have, does one asset in the fleet behave similar to another asset in the fleet then you could build similarity models in that. But then there will also be a model to look at now that I have to manage this fleet of assets which will be a different model compared to action similarity model, in terms of operations, in terms of optimization if I want to make certain operations of that asset work more efficiently, that model could be completely different with when compared to when you look at similarity of one model or one asset with another. >> That's interesting and then that model might fit into the information technology systems, the enterprise systems. Let's talk, I want to go get a little lower level now about the issue of intellectual property, joint development and sharing and ownership. IBM it's a nuanced subject. So we get different sort of answers, definitive answers from different execs, but at this high level, IBM says unlike Google and Facebook we will not take your customer data and make use of it but there's more to it than that. It's not as black-and-white. Help explain that for so us. >> The way you want to think is I would definitely paired back what our chairman always says customers' data is customers' data, customer insights is customer insights so they way we look at it is if you look at a black box engine, that could be your analytics engine, whatever it is. The data is your inputs and the insights are our outputs so the insights and outputs belong to them. we don't take their data and marry it with somebody else's data and so forth but we use the data to train the models and the model which is an abstract version of what that engine should be and then more we train the more better the model becomes. And then we can then use across many different customers and as we improve the models, we might go back to the same customers and hey we have an improved model you want to deploy this version rather than the previous version of the model we have. We can go to customer Y and say, here is a model which we believe it can take more of your data and fine tune that model again and then give it back to them. It is true that we don't actually take their data and share the data or the insights from one customer X to another customer Y but the models that make it better. How do you make that model more intelligent is what out job is and that's what we do. >> If we go with precise terminology, it sounds like when we talk about the black box having learned from the customer data and the insights also belonging to the customer. Let's say one of the examples we've heard was architecture engineering consulting for large capital projects has a model that's coming obviously across that vertical but also large capital projects like oil and gas exploration, something like that. There, the model sounds like it's going to get richer with each engagement. And let's pin down so what in the model is sort of not exposed to the next customer and what part of the model that has gotten richer does the next customer get the balance of? >> When we actually build a model, when we pass the data, in some cases, customer X data, the model is built out of customer X data may not sometimes work with the customer Y's data so in which case you actually build it from scratch again. Sometimes it doesn't. In some case it does help because of the similarity of the data in some instance because if the data from company X in oil gas is similar to company Y in oil gas, sometimes the data could be similar so in which case when you train that model, it becomes more efficient and the efficiency goes back to both customers. we will do that but there are places where it would really not work. What we are trying to do is. We are in fact trying to build some kind of knowledge bundles where we can actually what used to be a long process to train the model can ow shortened using that knowledge bundle of what we have actually gained. >> George: Tell me more about how it works. >> In retail for instance, when we actually provide analytics, from any kind of IoT sense, whatever sense of data this comes in we train the model, we get analytics used for ads, pushing coupons, whatever it is. That knowledge, what you have gained off that retail, it could be models of models, it could be metamodels, whatever you built. That can actually serve many different customers but the first customer who is trying to engage with us, you don't have any data to the model. It's almost starting from ground zero and so that would actually take a longer time when you are starting with a new industry and you don't have the data, it'll take you a longer time to understand what is that saturation point or optimization point where you think the model cannot go any further. In some cases, once you do that, you can take that saturated model or near saturated model and improve it based on more data that actually comes from different other segments. >> When you have a model that has gotten better with engagements and we've talked about the black box which produces the insights after taking in the customer data. Inside that black box there's like at the highest level we might call it the digital twin with the broad definition that we started with, then there's a data model which a data model which I guess could also be incorporated into the knowledge graft for the structure and then would it be fair to call the operational model the behavior? >> Yes, how does the system perform or behave with respect the data and the asset itself. >> And then underpinning that, the different models that correspond to the behaviors of different parts of this overall asset. So if we were to be really precise about this black box, what can move from one customer to the next and what what won't? >> The overall model, supposing I'm using a random data retrieval model, that remains but actual the coefficients are the feature rector, or whatever I use, that could be totally different for customers, depending on what kind of data they actually provide us. In data science or in analytics you have a whole platora of all the way from simple classification algorithms to very advanced predictive modeling algorithms. If you take the whole class when you start with a customer, you don't know which model is really going to work for a specific user case because the customer might come and can say, you might get some idea but you will not know exactly this is the model that will work. How you test it with one customer, that model could remain the same kind of use case for some of other customer, but that actual the coefficients the degree of the digital in some cases it might be two level decision trees, in others case it might be a six level decision tree. >> It is not like you take the model and the features and then just let different customers tweak the coefficients for the features. >> If you can do that, that will be great but I don't know whether you can really do it the data is going to change. The data is definitely going to change at some point of time but in certain cases it might be directly correlated where it can help, in certain cases it might not help. >> What I'm taking away is this is fundamentally different from traditional enterprise applications where you could standardize business processes and the transactional data that they were producing. Here it's going to be much more bespoke because I guess the processes, the analytic processes are not standardized. >> Correct, every business processes is unique for a business. >> The accentures of the world we're trying to tell people that when SAP shipped packaged processes, which were pretty much good enough, but that convince them to spend 10 times as much as the license fee on customization. But is there a qualitative difference between the processes here and the processes in the old ERP era? I think it's kind of different in the ERP era and the processes, we are more talking about just data management. Here we're talking about data science which means in the data management world, you're just moving data or transforming data and things like that, that's what you're doing. You're taking the data. transforming to some other form and then you're doing basic SQL queries to get some response, blah blah blah. That is a standard process that is not much of intelligence attached to it but now you are trying to see from the data what kind of intelligence can you derive by modeling the characteristics of the data. That becomes a much tougher problem so it now becomes one level higher of intelligence that you need to capture from the data itself that you want to serve a particular outcome from the insights you get from is model. >> This sounds like the differences are based on one different business objectives and perhaps data that's not as uniform that you would in enterprise applications, you would standardize the data here, if it's not standardized. >> I think because of the varied the disparity of the businesses and the kinds of verticals and things like that you're looking at, to get complete unified business model, is going to be extremely difficult. >> Last question, back-office systems the highest level they got to were maybe the CFO 'cause you had a sign off on a lot of the budget for the license and a much much bigger budget for the SI but he was getting something that was like close you quarter in three days or something instead of two weeks. It was a control function. Who do you sell to now for these different systems and what's the message, how much more strategic how do you sell the business impact differently? >> The platforms we directly interact with the CIO and CTOs or the head of engineering. And the actual solutions or the insights, we usually sell it to the COOs or the operational folks. So because the COO is responsible for showing you productivity, efficiency, how much of savings can you do on the bottom line top line. So the insights would actually go through the COOs or in some sense go through their CTOs to COOs but the actual platform itself will go to the enterprise IT folks in that order. >> This sounds like it's a platform and a solution sell which requires, is that different from the sales motions of other IBM technologies or is this a new approach? >> IBM is transforming on its way. The days where we believe that all the strategies and predictives that we are aligned towards, that actually needs to be the key goal because that's where the world is going. There are folks who, like Jeff Boaz talks about in the olden days you need 70 people to sell or 70% of the people to sell a 30% product. Today it's a 70% product and you need 30% to actually sell the product. The model is completely changing the way we interact with customers. So I think that's what's going to drive. We are transforming that in that area. We are becoming more conscious about all the strategy operations that we want to deliver to the market we want to be able to enable our customers with a much broader value proposition. >> With the industry solutions group and the Global Business Services teams work on these solutions. They've already been selling, line of business CXO type solutions. So is this more of the same, it's just better or is this really higher level than IBM's ever gotten in terms of strategic value? >> This is possibly in decades I would say a high level of value which come from a strategic perspective. >> Okay, on that note Veeru, we'll call it a day. This is great discussion and we look forward to writing it up and clipping all the videos and showering the internet with highlights. >> Thank you George. Appreciate it. >> Hopefully I will get you back soon. >> I was a pleasure, absolutely. >> With that, this George Gilbert. We're in our Palo Alto studio for wiki bond and theCUBE and we've been talking to Veeru Ramaswamy who's VP of Watson IoT platform and we look forward to coming back with Veeru sometime soon. (upbeat music)

Published Date : Aug 23 2017

SUMMARY :

and he's here to fill us in and the club ration or the social integration. the next work station and he talked about into the to the digital world, the way a normal person looks at a physical object? and represent the digital twin on a physical world and the pulleys and the panels for operating it. that becomes a critical part of the twin. in the digital world, then that gives you the ability in that you could program the real world. that comes from the sensors, once you model it Okay, so it's a structured way of interacting Okay, so it's not the narrow definition What are some of the business impacts and then be able to have different business models in the sense that IBM's customers become in the way Correct so the way we want think about is, someone's modeling and risk from you the supplier I'm pretty sure we have a lot of financial risk modeling if that's the right word. are engineered to order instead of make to stock. and you bring your billion devices and connect but you take a few use cases and then generalize so most of the time you get 80% of your asset management sort of the hot topic and in the states, and then you want to bring your similation models and behavior, is that what makes it simulation ready? That's the graph that holds the relation between nodes that maybe the lower level operation systems. and the availability of the existing assets with you. Okay that's where you translate essentially I remember in the Munich event, of some of the most successful engagements the way you can definitely see success It sounds like in the chip industry Moore's law is going to depend on how do you build this ecosystem And all the way up to the guys who are going to and all of that to make the connections. And how much is the solution builder and software developers to come and sit together and the automotive customer brings in We always by the way believe he sort of set the path for modern computing someone on the IBM side might be talking the standard what do you call In terms of getting the customer organization and then you have a GBS which actually or an existing application that needs customization. analytics and so on and so forth that goes along with that. and then how do different members of the ecosystem and AI specialists distributed across the globe. like a BI person all the way to people who can build then we have our data signs experience it's naturally that talent has to be much more the pool talent you have. and then you also need the domestics There's the issue of, and resources to work with. how to build a platform from a Kosera. that had the people to operate that stuff and the other aspect is, So what does that look like? and charts that comes out of the data in and intend, integrated to like pentaho and be able to call the data what type of data you need. the data gets ingested, you can actually start the storage, can integrate what were boundaries You can go all the way from data ingestion sort of the the visualizations like Altracks It is already integrated into the platform and the Watson APIs is a layer above us a little higher at this quasi-solution layer. and given the fact that we have and one of the use cases he talked about was video. and so on and so forth in the video itself. When you talk about pushing more of the processing. needs to be done at the edge. Whatever the capacity of the device you have and then do you have an ensemble meaning, so you in the fleet of assets which you have, about the issue of intellectual property, and share the data or the insights from There, the model sounds like it's going to get richer and the efficiency goes back to both customers. and you don't have the data, it'll take you a longer time incorporated into the knowledge graft for the structure Yes, how does the system perform or behave that correspond to the behaviors of different parts and can say, you might get some idea It is not like you take the model and the features the data is going to change. and the transactional data that they were producing. is unique for a business. and the processes, we are more talking about This sounds like the differences are based on and the kinds of verticals the highest level they got to were maybe the CFO So because the COO is responsible for showing you in the olden days you need 70 people to sell and the Global Business Services teams a high level of value which come from and showering the internet with highlights. Thank you George. and we look forward to coming back

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Bruce Tyler, IBM & Fawad Butt | IBM CDO Strategy Summit 2017


 

(dramatic music) >> Narrator: Live from Fisherman's Wharf in San Francisco. It's theCube. Covering IBM Chief Data Officer Strategy Summit Spring 2017. Brought to you by IBM. >> Hey, welcome back, everybody. Jeff Frank here with theCube. We are wrapping up day one at the IBM CEO Strategy Summit Spring 2017 here at the Fisherman's Wharf Hyatt. A new venue for us, never been here. It's kind of a cool venue. Joined by Peter Burris, Chief Research Officer from Wikibon, and we're excited to have practitioners. We love getting practitioners on. So we're joined by this segment by Bruce Tyler. He's a VP Data Analytics for IBM Global Business Services. Bruce, nice to see you. >> Thank you. >> And he's brought along Fawad Butt, the Chief Data Governance Officer for Kaiser Permanente. Welcome. >> Thank you, thank you. >> So Kaiser Permanente. Regulated industry, health care, a lot of complex medical issues, medical devices, electronic health records, insurance. You are in a data cornucopia, I guess. >> It's data heaven all the way. So as you mentioned, Kaiser is a vertically integrated organization, Kaiser Permanente is. And as such the opportunity for us is the fact that we have access to a tremendous amount of data. So we sell insurance, we run hospitals, medical practices, pharmacies, research labs, you name it. So it's an end to end healthcare system that generates a tremendous amount of dataset. And for us the real opportunity is to be able to figure out all the data we have and the best uses for it. >> I guess I never really thought of it from the vertical stack perspective. I used to think it was just the hospital, but the fact that you have all those layers of the cake, if you will, and can operate within them, trade data within them, and it gives you a lot of kind of classic vertical stack integration. That fits. >> Very much so. And I didn't give you the whole stack. I mean, we're actually building a medical school in Southern California. We have a residency program in addition to everything else we've talked about. But yeah, the vertical stack does provide us access to data and assets related to data that are quite unique. On the one side, it's a great opportunity. On the other side, it has to be all managed and protected and served in the best interest of our patrons and members. >> Jeff: Right, right. And just the whole electronic health records by themselves that people want access to that, they want to take them with. But then there's all kinds of scary regulations around access to that data. >> So the portability, I think what you're talking about is the medical record portability, which is becoming a really new construct in the industry because people want to be able to move from practitioner to practitioner and have that access to records. There are some regulation that provide cover at a national scale but a lot of this also is impacted by the states that you're operating in. So there's a lot of opportunities where I can tell some of the regulation in this space over time and I think that will, then we'll see a lot more adoption in terms of these portability standards which tend to be a little one off right now. >> Right, right. So I guess the obvious question is how the heck do you prioritize? (laughter) You got a lot of things going on. >> You know, I think it's really the standard blocking/tackling sort of situation, right? So one of the things that we've done is taken a look at our holistic dataset end to end and broken it down into pieces. How do you solve this big problem? You solve it by piecing it out a little bit. So what we've done is that we've put our critical dataset into a set of what we call data domains. Patient, member, providers, workers, HR, finance, you name it. And then that gives us the opportunity to not only just say how good is our data holistically but we can also go and say how good is our patient data versus member data versus provider data versus HR data. And then not only just know how good it is but it also gives us the opportunity to sort of say, "Hey, there's no conceivable way we can invest "in all 20 of these areas at any given point." So what's the priority that aligns with business objectives and goals? If you think about corporate strategy in general, it's based on customers and demand and availability and opportunities but now we're adding one more tool set and giving that to our executives. As they're making decisions on investments in longer term, and this isn't just KP, it's happening across industries, is that the data folks are bringing another lens to the table, which is to say what dataset do we want to invest in over the course of the next five years? If you had to choose between 20, what are the three that you prioritize first versus the other. So I think it's another lever, it's another mechanism to prioritize your strategy and your investments associated with that. >> But you're specifically focused on governance. >> Fawad: I am. >> In the health care industry, software for example is governed by a different set of rules as softwares in other areas. Data is governed by a different set of rules than data is governed in most other industries. >> Fawad: Correct. >> Finance has its own set of things and then some others. What does data governance mean at KP? Which is a great company by the way. A Bay Area company. >> Absolutely. >> What does it mean to KP? >> It's a great question, first of all. Every data governance program has to be independent and unique because it should be trying to solve for a set of things that are relevant in that context. For us at KP, there are a few drivers. So first is, as you mentioned, regulation. There's increased regulation. There's increased regulatory scrutiny in pressure. Some things that have happened in financial services over the last eight or ten years are starting to come and trickle in to the healthcare space. So there's that. There's also a changing environment in terms of how, at least from an insurance standpoint, how people acquire health insurance. It used to be that your employer provided a lot of that, those services and those insurances. Now you have private marketplaces where a lot of people are buying their own insurance. And you're going from a B2B construct to a B2C construct in certain ways. And these folks are walking around with their Android phones or their iPhones and they're used to accessing all sorts of information. So that's the customer experience that you to to deliver to them. So there's this digital transformation that's happening that's driving some of the need around governance. The other areas that I think are front and center for us are obviously privacy and security. So we're custodians of a lot of datasets that relate to patients' health information and their personal information. And that's a great responsibility and I think from a governance standpoint that's one of the key drivers that define our focus areas in the governance space. There are other things that are happening. There's obviously our mission within the organization which is to deliver the highest coverage and care at the lowest cost. So there's the ability for us to leverage our data and govern our data in a way which supports those two mission statements, but the bigger challenge in nuts and bolts terms for organizations like ours, which are vertically integrated, is around understanding and taking stock of the entire dataset first. Two, protecting it and making sure that all the defenses are in place. But then three, figuring out the right purposes to use this, to use the data. So data production is great but data consumption is where a lot of the value gets captured. So for us some of the things that data governance facilitates above all is what data gets shared for what purposes and how. Those are things that an organization of our size deliver a tremendous amount of value both on the offensive and the defensive side. >> So in our research we've discovered that there are a lot of big data functions or analytic functions that fail because they started with the idea of setting up the infrastructure, creating a place to put the data. Then they never actually got to the use case or when they did get to the use case they didn't know what to do next. And what a surprise. No returns, lot of costs, boom. >> Yep. >> The companies that tend to start with the use case independently individual technologies actually have a clear path and then the challenge is to accrete knowledge, >> Yes. >> accrete experience and turn it into knowledge. So from a governance standpoint, what role do you play at KP to make sure that people stay focused in use cases, that the lessons you learn about pursuing those use cases then turn to a general business capability in KP. >> I mean, again, I think you hit it right on the head. Data governance, data quality, data management, they're all great words, right? But what do they support in terms of the outcomes? So from our standpoint, we have a tremendous amount of use cases that if we weren't careful, we would sort of be scatterbrained around. You can't solve for everything all at once. So you have to find the first set of key use cases that you were trying to solve for. For us, privacy and security is a big part of that. To be able to, there's a regulatory pressure there so in some cases if you lose a patient record, it may end up costing you $250,000 for a record. So I think it's clear and critical for us to be able to continue to support that function in an outstanding way. The second thing is agility. So for us one of the things that we're trying to do with governance and data management in general, is to increase our agility. If you think about it, a lot of companies go on these transformation journeys. Whether it's transforming HR or trying to transform their finance functions or their business in general, and that requires transforming their systems. A lot of that work, people don't realize, is supported and around data. It's about integrating your old data with the new business processes that you're putting out. And if you don't have that governance or that data management function in place to be able to support that from the beginning or have some maturity in place, a lot of those activities end up costing you a lot more, taking a lot longer, having a lower success rate. So for us delivering value by creating additional agility for a set of activities that as an organization, we have committed to, is one for of core use cases. So we're doing a transformation. We're doing some transformation around HR. That's an area where we're making a lot of investments from a data governance standpoint to be able to support that as well as inpatient care and membership management. >> Great, great lessons. Really good feedback for fellow practitioners. Bruce, I want to get your perspective. You're kind of sitting on the other side of the table. As you look at the experience at Kaiser Permanente, how does this equate with what you're seeing with some of your other customers, is this leading edge or? >> Clearly on point. In fact, we were talking about this before we came up and I'm not saying that you guys led, we led the witness here but really how do you master around the foundational aspects around the data, because at the end of the day it's always about the data. But then how do you start to drive the value out of that and go down that cognitive journey that's going to either increase value onto your insights or improve your business optimization? We've done a healthy business within IBM helping customers go through those transformation processes. I would say five years ago or even three years ago we would start big. Let's solve the data aspect of it. Let's build the foundational management processes around there so that it ensures that level of integrity and trusted data source that you need across an organization like KP because they're massive because of all the different types of business entities that they have. So those transformation initiatives, they delivered but it was more from an IT perspective so the business partners that really need to adopt and are going to get the value out of that were kind of in a waiting game until that came about. So what we're seeing now is looking at things around from a use case-driven approach. Let's start small. So whether you're looking at trying to do something within your call center and looking at how to improve automation and insights in that spec, build a proof of value point around a subset of the data, prove that value, and those things can typically go from 10 to 12 weeks, and once you've demonstrated that, now how do can you scale? But you're doing it under your core foundational aspects around the architecture, how you're going to be able to sustain and maintain and govern the data that you have out there. >> It's a really important lesson all three of you have mentioned now. That old method of let's just get all the infrastructure in place is really not a path to success. You getting hung up, spend a lot of money, people get pissed off and oh by the way, today your competitors are transforming right around you while you're >> Unless they're also putting >> tying your shoes. >> infrastructure. >> Unless they're also >> That's right. (laughter) >> tying their shoes too. >> Build it and they will come sounds great, but in the data space, it's a change management function. One of my favorite lines that I use these days is data management is a team sport. So this isn't about IT, or this isn't just about business, and can you can't call business one monolith. So it's about the various stakeholders and their needs and your ability to satisfy them to the changes you're about to implement. And I think that gets lost a lot of times. It turns into a technical conversation around just capability development versus actually solving and solutioning for that business problem set that are at hand. >> Jeff: Yeah. >> Peter: But you got to do both, right? >> You have to. >> Bruce: Absolutely, yeah. >> Can I ask you, do we have time for another couple of questions? >> Absolutely. >> So really quickly, Fawad, do you have staff? >> Fawad: I do. >> Tell us about the people on your staff, where they came from, what you're looking for. >> So one of the core components of data governance program are stewards, data stewards. So to me, there are multiple dimensions to what stewards, what skills they should have. So for stewards, I'm looking for somebody that has some sort of data background. They would come from design, they would come from architecture, they would come from development. It doesn't really matter as long as they have some understanding. >> As long as you know what a data structure is and how you do data monitoring. >> Absolutely. The second aspect is that they have to have an understanding of what influence means. Be able to influence outcomes, to be able to influence conversations and discussions way above their pay grade, so to be able to punch above your weight so to speak in the influence game. And that's a science. That's a very, very definitive science. >> Yeah, we've heard many times today that politics is an absolute crucial game you have to play. >> It is part of the game and if you're not accounting for it, it's going to hit you in the face when you least expect it. >> Right. >> And the third thing is, I look for people that have some sort of an execution background. So ability to execute. It's great to be able to know data and understand data and go out and influence people and get them to agree with you, but then you have to deliver. So you have to be able to deliver against that. So those are the dimensions I look at typically when I'm looking at talent as it relates particularly to stewardship talent. In terms of where I find it, I try to find it within the organization because if I do find it within the organization, it gives me that organizational understanding and those relationship portfolios that people bring to the table which tend to be part of that influence-building process. I can teach people data, I can teach them some execution, I can't teach them how to do influence management. That just has to-- >> You can't teach them to social network. >> Fawad: (laughing) That's exactly right. >> Are they like are the frustrated individuals that have been seen the data that they're like (screams) this is-- >> They come from a lot of different backgrounds. So I have a steward that is an attorney, is a lawyer. She comes from that background. I have a steward that used to be a data modeler. I have a steward that used to run compliance function within HR. I have a steward that comes from a strong IT background. So it's not one formula. It's a combination of skills and everybody's going to have a different set of strengths and weaknesses and as long as you can balance those out. >> So people who had an operational role, but now are more in an execution setup role. >> Fawad: Yeah, very much so. >> They probably have a common theme, though, across them that they understand the data, they understand the value of it, and they're able to build consensus to make an action. >> Fawad: That's correct. >> That's great. That's perfect close. They understand it and they can influence, and they can get to action. Pretty much sums it up, I think so. All right. >> Bruce: All right thank you. >> Well, thanks a lot, Bruce and Fawad for stopping by. Great story. Love all the commercials on the Warriors, I'm a big fan and watch KNBR. (laughter) But really a cool story and thanks for sharing it and continued success. >> Thank you for the opportunity. >> Absolutely. All right, with Peter Burris, I'm Jeff Frank. You're watching theCube from the IBM Chief Data Officer Strategy Summit Spring 2017 from Fisherman's Wharf, San Francisco. We'll be right back after this short break. Thanks for watching. (electronic music)

Published Date : Mar 30 2017

SUMMARY :

Brought to you by IBM. Bruce, nice to see you. the Chief Data Governance Officer for Kaiser Permanente. So Kaiser Permanente. So it's an end to end healthcare system but the fact that you have all those layers of the cake, On the other side, it has to be all managed And just the whole electronic health records and have that access to records. how the heck do you prioritize? and giving that to our executives. In the health care industry, software for example Which is a great company by the way. So that's the customer experience the infrastructure, creating a place to put the data. that the lessons you learn about pursuing those use cases So you have to find the first set of key use cases You're kind of sitting on the other side of the table. and I'm not saying that you guys led, in place is really not a path to success. That's right. So it's about the various stakeholders and their needs Tell us about the people on your staff, So to me, there are and how you do data monitoring. so to be able to punch above your weight is an absolute crucial game you have to play. for it, it's going to hit you in the face So you have to be able to deliver against that. So I have a steward that is an attorney, So people who had an operational role, and they're able to build consensus to make an action. and they can get to action. Love all the commercials on the Warriors, I'm a big fan from the IBM Chief Data Officer Strategy Summit Spring 2017

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Cortnie Abercrombie & Caitlin Halferty Lepech, IBM - IBM CDO Strategy Summit - #IBMCDO - #theCUBE


 

>> Announcer: Live from Fisherman's Wharf in San Francisco, it's theCUBE, covering IBM Chief Data Officer Strategy Summit Spring 2017. Brought to you by IBM. >> Hey, welcome back, everybody. Jeff Frick here with theCUBE. We're at Fisherman's Wharf in San Francisco at the IBM Chief Data Officer Strategy Summit Spring 2017. It's a mouthful, it's 170 people here, all high-level CXOs learning about data, and it's part of an ongoing series that IBM is doing around chief data officers and data, part of a big initiative with Cognitive and Watson, I'm sure you've heard all about it, Watson TV if nothing else, if not going to the shows, and we're really excited to have the drivers behind this activity with us today, also Peter Burris from Wikibon, chief strategy officer, but we've got Caitlin Lepech who's really driving this whole show. She is the Communications and Client Engagement Executive, IBM Global Chief Data Office. That's a mouthful, she's got a really big card. And Cortnie Abercrombie, who I'm thrilled to see you, seen her many, many times, I'm sure, at the MIT CDOIQ, so she's been playing in this space for a long time. She is a Cognitive and Analytics Offerings leader, IBM Global Business. So first off, welcome. >> Thank you, great to be here. >> Thanks, always a pleasure on theCUBE. It's so comfortable, I forget you guys aren't just buddies hanging out. >> Before we jump into it, let's talk about kind of what is this series? Because it's not World of Watson, it's not InterConnect, it's a much smaller, more intimate event, but you're having a series of them, and in the keynote is a lot of talk about what's coming next and what's coming in October, so I don't know. >> Let me let you start, because this was originally Cortnie's program. >> This was a long time ago. >> 2014. >> Yeah, 2014, the role was just starting, and I was tasked with can we identify and start to build relationships with this new line of business role that's cropping up everywhere. And at that time there were only 50 chief data officers worldwide. And so I-- >> Jeff: 50? In 2014. >> 50, and I can tell you that earnestly because I knew every single of them. >> More than that here today. >> I made it a point of my career over the last three years to get to know every single chief data officer as they took their jobs. I would literally, well, hopefully I'm not a chief data officer stalker, but I basically was calling them once I'd see them on LinkedIn, or if I saw a press announcement, I would call them up and say, "You've got a tough job. "Let me help connect you with each other "and share best practices." And before we knew, it became a whole summit. It became, there were so many always asking to be connected to each other, and how do we share best practices, and what do you guys know as IBM because you're always working with different clients on this stuff? >> And Cortnie and I first started working in 2014, we wrote IBM's first paper on chief data officers, and at the time, there was a lot of skepticism within our organization, why spend the time with data officers? There's other C-suite roles you may want to focus on instead. But we were saying just the rise of data, external data, unstructured data, lot of opportunity to rise in the role, and so, I think we're seeing it reflected in the numbers. Again, first summit three years ago, 30 participants. We have 170 data executives, clients joining us today and tomorrow. >> And six papers later, and we're goin' strong still. >> And six papers later. >> Exactly, exactly. >> Before we jump into the details, some of the really top-level stuff that, again, you talked about with John and David, MIT CDOIQ, in terms of reporting structure. Where do CDOs report? What exactly are they responsible for? You covered some of that earlier in the keynote, I wonder if you can review some of those findings. >> Yeah, that was amazing >> Sure, I can share that, and then, have Cortnie add. So, we find about a third report directly to the CEO, a third report through the CIO's office, sort of the traditional relationship with CIOs, and then, a third, and what we see growing quite a bit, are CXOs, so functional or business line function. Originally, traditionally it was really a spin-off of CIO, a lot of technical folks coming up, and we're seeing more and more the shift to business expertise, and the focus on making sure we're demonstrating the business impact these data programs are driving for our organization. >> Yeah, it kind of started more as a data governance type of role, and so, it was born out of IT to some degree because, but IT was having problems with getting the line of business leaders to come to the table, and we knew that there had to be a shift over to the business leaders to get them to come and share their domain expertise because as every chief data officer will tell you, you can't have lineage or know anything about all of this great data unless you have the experts who have been sitting there creating all of that data through their processes. And so, that's kind of how we came to have this line of business type of function. >> And Inderpal really talked about, in terms of the strategy, if you don't start from the business strategy-- >> Inderpal? >> Yeah, on the keynote. >> Peter: Yeah, yeah, yeah, yeah. >> You are really in big risk of the boiling the ocean problem. I mean, you can't just come at it from the data first. You really have to come at it from the business problem first. >> It was interesting, so Inderpal was one of our clients as a CEO three times prior to rejoining IBM a year ago, and so, Cortnie and I have known him-- >> Express Scripts, Cambia. >> Exactly, we've interviewed him, featured him in our research prior, too, so when he joined IBM in December a year ago, his first task was data strategy. And where we see a lot of our clients struggle is they make data strategy an 18-month, 24-month process, getting the strategy mapped out and implemented. And we say, "You don't have the time for it." You don't have 18 months to come to data, to come to a data strategy and get by and get it implemented. >> Nail something right away. >> Exactly. >> Get it in the door, start showing some results right away. You cannot wait, or your line of business people will just, you know. >> What is a data strategy? >> Sure, so I can say what we've done internally, and then, I know you've worked with a lot of clients on what they're building. For us internally, it started with the value proposition of the data office, and so, we got very clear on what that was, and it was the ability to take internal, external data, structured, unstructured, and pull that together. If I can summarize it, it's drive to cognitive business, and it's infusing cognition across all of our business processes internally. And then, we identified all of these use cases that'll help accelerate, and the catalyst that will get us there faster. And so, Client 360, product catalog, et cetera. We took data strategy, got buy-in at the highest levels at our organization, senior vice president level, and then, once we had that support and mandate from the top, went to the implementation piece. It was moving very quickly to specify, for us, it's about transforming to cognitive business. That then guides what's critical data and critical use cases for us. >> Before you answer, before you get into it, so is a data strategy a means to cognitive, or is it an end in itself? >> I would say it, to be most effective, it's a succinct, one-page description of how you're going to get to that end. And so, we always say-- >> Peter: Of cognitive? >> Exactly, for us, it's cognitive. So, we always ask very simple question, how is your company going to make money? Not today, what's its monetization strategy for the future? For us, it's coming to cognitive business. I have a lot of clients that say, "We're product-centric. "We want to become customer, client-centric. "That's our key piece there." So, it's that key at the highest level for us becoming a cognitive business. >> Well, and data strategies are as big or as small as you want them to be, quite frankly. They're better when they have a larger vision, but let's just face it, some companies have a crisis going on, and they need to know, what's my data strategy to get myself through this crisis and into the next step so that I don't become the person whose cheese moved overnight. Am I giving myself away? Do you all know the cheese, you know, Who Moved My Cheese? >> Every time the new iOS comes up, my wife's like-- >> I don't know if the younger people don't know that term, I don't think. >> Ah, but who cares about them? >> Who cares about the millenials? I do, I love the millenials. But yes, cheese, you don't want your cheese to move overnight. >> But the reason I ask the question, and the reason why I think it's important is because strategy is many things to many people, but anybody who has a view on strategy ultimately concludes that the strategic process is what's important. It's the process of creating consensus amongst planners, executives, financial people about what we're going to do. And so, the concept of a data strategy has to be, I presume, as crucial to getting the organization to build a consensus about the role the data's going to play in business. >> Absolutely. >> And that is the hardest. That is the hardest job. Everybody thinks of a data officer as being a technical, highly technical person, when in fact, the best thing you can be as a chief data officer is political, very, very adept at politics and understanding what drives the business forward and how to bring results that the CEO will get behind and that the C-suite table will get behind. >> And by politics here you mean influencing others to get on board and participate in this process? >> Even just understanding, sometimes leaders of business don't articulate very well in terms of data and analytics, what is it that they actually need to accomplish to get to their end goal, and you find them kind of stammering when it comes to, "Well, I don't really know "how you as Inderpal Bhandari can help me, "but here's what I've got to do." And it's a crisis usually. "I've got to get this done, "and I've got to make these numbers by this date. "How can you help me do that?" And that's when the chief data officer kicks into gear and is very creative and actually brings a whole new mindset to the person to understand their business and really dive in and understand, "Okay, this is how "we're going to help you meet that sales number," or, "This is how we're going to help you "get the new revenue growth." >> In certain respects, there's a business strategy, and then, you have to resource the business strategy. And the data strategy then is how are we going to use data as a resource to achieve our business strategy? >> Cortnie: Yes. >> So, let me test something. The way that we at SiliconANGLE, Wikibon have defined digital business is that a business, a digital business uses data as an asset to differentially create and keep customers. >> Caitlin: Right. >> Does that work for you guys? >> Cortnie: Yeah, sure. >> It's focused on, and therefore, you can look at a business and say is it more or less digital based on how, whether it's more or less focused on data as an asset and as a resource that's going to differentiate how it's business behaves and what it does for customers. >> Cortnie: And it goes from the front office all the way to the back. >> Yes, because it's not just, but that's what, create and keep, I'm borrowing from Peter Drucker, right. Peter Drucker said the goal of business is to create and keep customers. >> Yeah, that's right. Absolutely, at the end of the day-- >> He included front end and back end. >> You got to make money and you got to have customers. >> Exactly. >> You got to have customers to make the money. >> So data becomes a de-differentiating asset in the digital business, and increasingly, digital is becoming the differentiating approach in all business. >> I would argue it's not the data, because everybody's drowning in data, it's how you use the data and how creative you can be to come up with the methods that you're going to employ. And I'll give you an example. Here's just an example that I've been using with retailers lately. I can look at all kinds of digital exhaust, that's what we call it these days. Let's say you have a personal digital shopping experience that you're creating for these new millenials, we'll go with that example, because shoppers, 'cause retailers really do need to get more millenials in the door. They're used to their Amazon.coms and their online shopping, so they're trying to get more of them in the door. When you start to combine all of that data that's underlying all of these cool things that you're doing, so personal shopping, thumbs up, thumb down, you like this dress, you like that cut, you like these heels? Yeah, yes, yes or no, yes or no. I'm getting all this rich data that I'm building with my app, 'cause you got to be opted in, no violating privacy here, but you're opting in all the way along, and we're building and building, and so, we even have, for us, we have this Metro Pulse retail asset that we use that actually has hyperlocal information. So, you could, knowing that millenials like, for example, food trucks, we all like food trucks, let's just face it, but millenials really love food trucks. You could even, if you are a retailer, you could even provide a fashion truck directly to their location outside their office equipped with things that you know they like because you've mined that digital exhaust that's coming off the personal digital shopping experience, and you've understood how they like to pair up what they've got, so you're doing a next best action type of thing where you're cross-selling, up-selling. And now, you bring it into the actual real world for them, and you take it straight to them. That's a new experience, that's a new millennial experience for retail. But it's how creative you are with all that data, 'cause you could have just sat there before and done nothing about that. You could have just looked at it and said, "Well, let's run some reports, "let's look at a dashboard." But unless you actually have someone creative enough, and usually it's a pairing of data scientist, chief data officers, digital officers all working together who come up with these great ideas, and it's all based, if you go back to what my example was, that example is how do I create a new experience that will get millenials through my doors, or at least get them buying from me in a different way. If you think about that was the goal, but how I combined it was data, a digital process, and then, I put it together in a brand new way to take action on it. That's how you get somewhere. >> Let me see if I can summarize very quickly. And again, just as an also test, 'cause this is the way we're looking at it as well, that there's human beings operate and businesses operate in an analog world, so the first test is to take analog data and turn it into digital data. IOT does that. >> Cortnie: Otherwise, there's not digital exhaust. >> Otherwise, there's no digital anything. >> Cortnie: That's right. >> And we call it IOT and P, Internet of Things and People, because of the people element is so crucial in this process. Then we have analytics, big data, that's taking those data streams and turning them into models that have suggestions and predictions about what might be the right way to go about doing things, and then there's these systems of action, or what we've been calling systems of enactment, but we're going to lose that battle, it's probably going to be called systems of action that then take and transduce the output of the model back into the real world, and that's going to be a combination of digital and physical. >> And robotic process automation. We won't even introduce that yet. >> Which is all great. >> But that's fun. >> That's going to be in October. >> But I really like the example that you gave of the fashion truck because people don't look at a truck and say, "Oh, that's digital business." >> Cortnie: Right, but it manifested in that. >> But it absolutely is digital business because the data allows you to bring a more personal experience >> Understand it, that's right. >> right there at that moment, and it's virtually impossible to even conceive of how you can make money doing that unless you're able to intercept that person with that ensemble in a way that makes both parties happy. >> And wouldn't that be cheaper than having big, huge retail stores? Someone's going to take me up on that. Retailers are going to take me up on this, I'm telling you. >> But I think the other part is-- >> Right next to the taco truck. >> There could be other trucks in that, a much cleaner truck, and this and that. But one thing, Cortnie, you talk about and you got to still have a hypothesis, I think of the early false promises of big data and Hadoop, just that you throw all this stuff in, and the answer just comes out. That just isn't the way. You've got to be creative, and you have to have a hypothesis to test, and I'm just curious from your experience, how ready are people to take in the external data sources and the unstructured data sources and start to incorporate that in with the proprietary data, 'cause that's a really important piece of the puzzle? It's very different now. >> I think they're ready to do it, it depends on who in the business you are working with. Digital offices, marketing offices, merchandising offices, medical offices, they're very interested in how can we do this, but they don't know what they need. They need guidance from a data officer or a data science head, or something like this, because it's all about the creativity of what can I bring together to actually reach that patient diagnostic, that whatever the case may be, the right fashion truck mix, or whatever. Taco Tuesday. >> So, does somebody from the chief data office, if you will, you know, get assigned to, you're assigned to marketing and you're assigned to finance, and you're assigned to sales. >> I have somebody assigned to us. >> To put this in-- >> Caitlin: Exactly, exactly. >> To put this in kind of a common or more modern parlance, there's a design element. You have to have use case design, and what are we going, how are we going to get better at designing use cases so we can go off and explore the role that data is going to play, how we're going to combine it with other things, and to your point, and it's a great point, how that turns into a new business activity. >> And if I can connect two points there, the single biggest question I get from clients is how do you prioritize your use cases. >> Oh, gosh, yeah. >> How can you help me select where I'm going to have the biggest impact? And it goes, I think my thing's falling again. (laughing) >> Jeff: It's nice and quiet in here. >> Okay, good. It goes back to what you were saying about data strategy. We say what's your data strategy? What's your overarching mission of the organization? For us, it's becoming cognitive business, so for us, it's selecting projects where we can infuse cognition the quickest way, so Client 360, for example. We'll often say what's your strategy, and that guides your prioritization. That's the question we get the most, what use case do I select? Where am I going to have the most impact for the business, and that's where you have to work with close partnership with the business. >> But is it the most impact, which just sounds scary, and you could get in analysis paralysis, or where can I show some impact the easiest or the fastest? >> You're going to delineate both, right? >> Exactly. >> Inderpal's got his shortlist, and he's got his long list. Here's the long term that we need to be focused on to make sure that we are becoming holistically a cognitive company so that we can be flexible and agile in this marketplace and respond to all kinds of different situations, whether they're HR and we need more skills and talent, 'cause let's face it, we're a technology company who's rapidly evolving to fit with the marketplace, or whether it's just good old-fashioned we need more consultants. Whatever the case may be. >> Always, always. >> Yes! >> I worked my business in. >> More consultants! >> Alright, we could go, we could go and go and go, but we're running out of time, we had a full slate. >> Caitlin: We just started. >> I know. >> I agree, we're just starting this convers, I started a whole other conversation to him. We haven't even hit the robotics yet. >> We need to keep going, guys. >> Get control. >> Cortnie: Less coffee for us. >> What do people think about when they think about this series? What should they look forward to, what's the next one for the people that didn't make it here today, where should they go on the calendar and book in their calendars? >> So, I'll speak to the summits first. It's great, we do Spring in San Francisco. We'll come back, reconvene in Boston in fall, so that'll be September, October frame. I'm seeing two other trends, which I'm quite excited about, we're also looking at more industry-specific CDO summits. So, for those of our friends that are in government sectors, we'll be in June 6th and 7th at a government CDO summit in D.C., so we're starting to see more of the industry-specific, as well as global, so we just ran our first in Rio, Brazil for that area. We're working on a South Africa summit. >> Cortnie: I know, right. >> We actually have a CDO here with us that traveled from South Africa from a bank to see our summit here and hoping to take some of that back. >> We have several from Peru and Mexico and Chile, so yeah. >> We'll continue to do our two flagship North America-based summits, but I'm seeing a lot of growth out in our geographies, which is fantastic. >> And it was interesting, too, in your keynote talking about people's request for more networking time. You know, it is really a sharing of best practices amongst peers, and that cannot be overstated. >> Well, it's community. A community is building. >> It really is. >> It's a family, it really is. >> We joke, this is a reunion. >> We all come in and hug, I don't know if you noticed, but we're all hugging each other. >> Everybody likes to hug their own team. It's a CUBE thing, too. >> It's like therapy. It's like data therapy, that's what it is. >> Alright, well, Caitlin, Cortnie, again, thanks for having us, congratulations on a great event, and I'm sure it's going to be a super productive day. >> Thank you so much. Pleasure. >> Thanks. >> Jeff Frick with Peter Burris, you're watchin' theCUBE from the IBM Chief Data Officer Summit Spring 2017 San Francisco, thanks for watching. (electronic keyboard music)

Published Date : Mar 29 2017

SUMMARY :

Brought to you by IBM. and we're really excited to have the drivers It's so comfortable, I forget you guys and in the keynote is a lot of talk about what's coming next Let me let you start, because this was and start to build relationships with this new Jeff: 50? 50, and I can tell you that and what do you guys know as IBM and at the time, there was a lot of skepticism and we're goin' strong still. You covered some of that earlier in the keynote, and the focus on making sure the line of business leaders to come to the table, I mean, you can't just come at it from the data first. You don't have 18 months to come to data, Get it in the door, start showing some results right away. and then, once we had that support and mandate And so, we always say-- So, it's that key at the highest level so that I don't become the person the younger people don't know that term, I don't think. I do, I love the millenials. about the role the data's going to play in business. and that the C-suite table will get behind. "we're going to help you meet that sales number," and then, you have to resource the business strategy. as an asset to differentially create and keep customers. and what it does for customers. Cortnie: And it goes from the front office is to create and keep customers. Absolutely, at the end of the day-- digital is becoming the differentiating approach and how creative you can be to come up with so the first test is to take analog data and that's going to be a combination of digital and physical. And robotic process automation. But I really like the example that you gave how you can make money doing that Retailers are going to take me up on this, I'm telling you. You've got to be creative, and you have to have because it's all about the creativity of from the chief data office, if you will, assigned to us. and to your point, and it's a great point, is how do you prioritize your use cases. How can you help me and that's where you have to work with and respond to all kinds of different situations, Alright, we could go, We haven't even hit the robotics yet. So, I'll speak to the summits first. to see our summit here and hoping to take some of that back. We'll continue to do our two flagship And it was interesting, too, in your keynote Well, it's community. We all come in and hug, I don't know if you noticed, Everybody likes to hug their own team. It's like data therapy, that's what it is. and I'm sure it's going to be a super productive day. Thank you so much. Jeff Frick with Peter Burris,

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Inderpal Bhandari & Jesus Mantas | IBM CDO Strategy Summit 2017


 

(inspiring piano and string music) >> Announcer: Live from Fisherman's Wharf in San Francisco, it's theCUBE, covering IBM Chief Data Officer Strategy Summit Spring 2017. Brought to you by IBM. >> Hey, welcome back, everybody. Jeff Frick here with theCUBE. We're in downtown San Francisco at the IBM Chief Data Officer Strategy Summit Spring 2017. That's a mouthful, but it's important because there's a series of these strategy summits that are happening not only in the United States, but they're expanding it all over the world, and it's really a chance for practitioners to come together, the chief data officers, to share best practices, really learn from the best, and as we love to do on theCUBE, we get the smartest people we can find, and we have them here. So first off, let me introduce Peter Burris, Chief Research Officer from Wikibon, but from IBM coming right off the keynote-- >> The smart people. >> The smart people, Inderpal Bhandari, he is the IBM Global Chief Data Officer, which is a short title and a big job, and Jesus Mantas, he's the General Manager, Cognitive Transformation, IBM Global Business Services. First off, gentlemen, welcome. >> Thank you. >> Thank you. >> It's really interesting how this chief data officer space has evolved. We've been watching it for years, back to some of the MIT CDOIQ, I think like three or four years ago nobody knew who they were, who were they going to report to, what are they going to do, what's the scope of the job. That's changed dramatically, and it really says something to IBM's credit that they just went out and got one to help really to refine and define for your customers where this is going. So first off, welcome, and let's get into it. How is the role starting to solidify as to what do chief data officers do? >> So, I'll take that. In terms of chief data officers, if you think in terms of the advent of the position, when it started out, I was one of the earliest in 2006, and I've done the job four times, and it has been continuously evolving ever since. When the job was first, in my very first job, I actually had to create the job because there was a company very interested in recruiting me, and they said they sensed that data was critical. It was a company in pharmaceutical insurance, so really very data based, right, everything is driven through data. And so, they had a sense that data was going to be extremely important, extremely relevant, but they didn't really have the position, or they didn't coin the phrase. And I suggested that there were three other chief data officers at that time in the U.S., and so, I became the fourth. At that time, it had to do with, essentially aligning data with strategy, with the strategy of the company, which means how is the company actually planning to monetize itself? Not its data, but itself. And then, essentially make sure that the data is now fit for purpose, to help them with that monetization. And so, that's all about aligning with the corporate strategy, and you have to have an officer who's capable of doing that and has that focus and is able to push that because then, once you start with that strategy, and then, there are plenty of different branches that shoot off, like governance, centralization of data, analytics, data science, and so on and so forth, and then, you have to manage that process. >> And data used to be kind of a liability, hard to think today looking back, 'cause you had to buy servers and storage, and it was expensive, and what do you do with it all? You can't analyze it. Boy, how the world has flipped. Now, data is probably one of your most important assets, but then, the big question, right, what do you do with it to really make it an asset? >> It is, it is, and it's actually fascinating to see here in the summit how even the role that was created in a few years, chief data officer, is coupled with this change in the nature of the value of that role has changed. To your point, I remember meeting some CIO friends 10 years ago that they were telling me how they were deleting data because it was too costly to have it. Now, those same CIOs would give whatever they could have to get that data back and have that history and be able to monetize the data. Because of the evolution of computing, and because now, not only the portion of the physical world that we've been able to represent with data for the last 50 years with information technology, but we're adding to that space all of this 80% of the data that even if digitized we were unable to use in processes, in decision making, in manufacturing. Now we have cognitive technology that can actually use that data, the role of the chief data officer is actually expanding significantly from what used to be the element of data science, of data governance, of data sovereignty, of data security, to now this idea of value creation with basically five times more categories of data, and it actually is a dialogue that we're having here at the summit that is the fascinating from the people who are doing this job every day. >> If you think about the challenges associated with the chief data officer, it's a job that's evolving, but partly one of the reasons why the chief data officer job is evolving is the very concept of the role that data plays in business is evolving, and that's forcing every job in business to evolve. So, the CMO's job's evolving, the CEO's job's evolving, and the CIO's job is evolving. How are you navigating this interesting combination of forces on the role of the CDO as you stake out, this is the value I'm going to bring to the business, even as other jobs start to themselves change and respond to this concept of the value of data? >> People ask me to describe my job, and there are just two words that I use to describe it. It's change agent, and that's exactly how a CDO needs to be, needs to look at their job, and also, actually act on that. Because to your point, it's not just the CDO job is evolving, it's all these other jobs are all evolving simultaneously, and there are times when I'm sitting at the table, it appears that, well, you don't really own anything because everybody else owns all the processes in the business. On the other hand, sometimes you're sitting there, and you're thinking, no, you actually own everything because the data that feeds those processes or comes out of those process is not coming back to you. I think the best way to think about the CDO job is that of a change agent. You are essentially entrusted with creating value from the data, as Jesus said, and then, enabling all the other jobs to change, to take advantage of this. >> 'Cause it's the enablement that that's where you bring the multiplier effect, it's the democratization of the data across the organization, across business roles, across departments is where you're going to get this huge multiplier. >> Yeah, and I think the role of one of the things that we're seeing and the partnership that Inderpal and I have in the way that we do this within IBM, but also, we do it for the rest of our clients is that change agency element of it is the constant infusion of design. Chief data officers were very well-known for the data science elements of it, but part of the constraint is actually no longer the computing capability or the algorithms themselves or the access to the data, which solved those constraints, is now actually preparing the business leaders to consume that and to actually create value, which changes the nature of their job as well, and that's the resistance point where embedding these technologies in the workflows, in a way that they create value in the natural flow of what these jobs actually do is extremely important. Otherwise, I mean, we were having a fascinating discussion before this, even if the data is correct, many business leaders will say, "Well, I don't believe it." And then, if you don't adopt it, you don't get the value. >> You guys are putting together this wonderful community of CDOs, chief data officers, trying to diffuse what the job is, how you go about doing the job. If you're giving advice and counsel to a CEO or board of directors who are interested in trying to apply this role in their business, what should they be looking for? What type of person, what type of background, what type of skills? >> I'll take it, and then, you can. I think it's almost what I would call a new Da Vinci. >> Peter: A new Da Vinci? >> A new Da Vinci is the Renaissance of someone that is, he's got a technology background, because you need to actually understand the mathematical and the data and the technology co-engineering aspect. >> So, if not an IT background, at least a STEM background. >> Exactly, it's a STEM background, but combined with enough knowledge of business architecture. So I call it Da Vinci because if you see the most remarkable paintings and products of Da Vinci was the fusion of mathematics and arts in a way that hadn't been done before. I think the new role of a data science is someone that can be in the boardroom elegantly describing a very sophisticated problem in a very easy to understand manner, but still having the depth of really understanding what's behind it and drawing the line versus what's possible and what's likely to happen. >> I think that's right on. I think the biggest hurdle for a chief data officer is the culture change, and to do that, you actually have to be a Da Vinci, otherwise, you really can't pull that off. >> Peter: You have to be a Da Vinci? >> You have to be a Da Vinci to pull that off. It's not just, you have to appreciate not just the technology, but also the business architecture as well as the fact that people are used to working in certain ways which are now changing on them, and then, there is an aspect of anxiety that goes with it, so you have to be able to understand that, and actually, perhaps even harness that to your advantage as you move forward as opposed to letting that become some kind of a threat or counterproductive mechanism as you move forward. >> I've done a fair amount of research over the years on the relationship between business model, business model design profitability, and this is, there's a lot of different ways of attacking this problem, I'm not going to tell you I have the right answer yet, but one of the things that I discovered when talking to businesses about this is that often it fails when the business fails to, I'm going to use the word secure, but it may not be the right word, secure the ongoing rents or value streams from the intellectual property that they create as part of the strategy. Companies with great business model design also find ways to appropriate that value from what they're doing over an extended period of time, and in digital business, increasingly that's data. That raises this interesting question, what is the relationship between data, value streams over time, ownership, intellectual property? Do you have any insight into that? It's a big question. >> Yeah, no no, I mean, I think we touched on it also in the discussion, both Jesus and I touched on that. We've staked out a very clear ground on that, and when I say we, I mean IBM, the way we are defining that is we are pretty clear that for all the reasons you just outlined, the client's data has to be their data. >> Peter: Has to be? >> Has to be their data. It has to be their insight because otherwise, you run into this notion of, well, whose intellectual property is it, whose expertise is it? Because these systems learn as they go. And so, we're architecting towards offerings that are very clear on that, that we're going to make it possible for a client that, for instance, just wants to keep their data and derive whatever insight they can from that data and not let anybody else derive that insight, and it'll be possible for them to do that. As well as clients where they're actually comfortable setting up a community, and perhaps within an industry-specific setup, they will allow insights that are then shared across that. We think that's extremely important to be really clear about that up front and to be able to architect to support that, in a way that that is going to be welcomed by the business. >> Is that part of the CDO's remit within business to work with legal and work with others to ensure that the rules and mechanisms to sustain management of intellectual property and retain rents out of intellectual property, some call it the monetization process, are in place, are enforced, are sustained? >> That's always been part of the CDO remit, right. I mean, in the sense that even before cognition that was always part of it, that if we were bringing in data or if data was leaving the company that we wanted to make sure that it was being done in the right way. And so, that partnership not just with legal but also with IT, also with the business areas, that we had to put in place, and that's the essence of governance. In the broadest sense, you could think of governance as doing that, as protecting the data asset that the company has. >> They have the derivatives now, though. You're getting stacked derivatives. >> Inderpal: It's much more complicated. >> Of data, and then insight combined, so it's not just that core baseline data anymore. >> And I like to make it an element. You've heard us say for the last five years we believe that data has become the new natural resource for the business. And when you go back to other natural resources, and you see what happened with people that were in charge of them, you can kind of predict a little bit that evolution on the chief data officer role. If you were a landowner in Texas when there was no ability to basically either extract or decline petroleum, you were not preoccupied with how would you protect land rights under the line that you can see. So, as a landowner you have a job, but you were basically focused on what's over the surface. Once actually was known that below the surface there was massive amount of value that could be obtained, suddenly that land ownership expanded in responsibility. You then have to be preoccupied, "Okay, wait a minute, who owns those land rights "to actually get that oil, and who's going to do that?" I think you can project that to the role of the chief data officer. If you don't have a business model that monetizes data, you are not preoccupied to actually figure out how to govern it or how to monetize it or how to put royalties on it, you are just preoccupied with just making sure that the data you have, it was well-maintained and it could be usable. The role's massively expanding to this whole below the line where not only the data is being used for internal purposes, but it's becoming a potential element of a strategy that is new. >> The value proposition, simply stated. >> Jesus: Value proposition, exactly. >> But you're right, so I agree with that, but data as an asset has different characteristics than oil as an asset, or people as an asset. People can effectively be applied to one thing at a time. I mean, we can multitask, but right now, you're having a conversation with us, and so, IBM is not seeing you talk to customers here at the show, for example. Data does not follow the economics of scarcity. >> Jesus: Right. >> It follows a new economics, it's easy to copy, it's easy to share. If it's done right, it's easy to integrate. You can do an enormous number of things with data that you've never been able to do with any other asset ever, and that's one of the reasons why this digital transformation is so interesting and challenging, and fraught with risk, but also potentially rewarding. So, as you think about the CDO role and being the executive in the business that is looking at taking care of an asset, but a special type of asset, how that does change the idea of taking care of the energy or the oil to now doing it a little bit differently because it can be shared, because it can be combined. >> I mean, I think in the way as technology has moved from being a mechanism to provide efficiency to the business to actually being core to defining what the business is, I think every role related to technology is following that theme, so I would say, for example, Inderpal and I, when we're working with clients or on our models, he's not just focused on the data, he's actually forming what is possible for the business to do. What should be the components of the new business architecture? It's this homogenized role, and that's why I kept saying it's like, you could have been one of those Da Vincis. I mean, you get to do it every day, but I don't know if you want to comment on that. >> I think that's exactly right. You are right in the sense that it is a different kind of asset, it has certain characteristics which are different from what you'd find in, say, land or oil or something like a natural resource, but in terms of, and you can create a lot of value at times by holding onto it, or you could create a lot of value by sharing it, and we've seen examples of both metaphors. I think as part of being the CDO, it's being cognizant that there is going to be a lot of change in this role as data is changing, not just in its nature in the sense that now you have a lot more unstructured data, many different forms of data, but also in terms of that's application within the business, and this expansion to changing processes and transforming processes, which was never the case when I first did the job in 2006. It was not about process transformation. It was about a much more classic view of an asset where it's, we create this data warehouse, that becomes the corporate asset, and now, you generate some insights from it, disseminate the insights. Now it's all about actually transforming the business by changing the processes, reimagining what they could be, because the nature of data has changed. >> I have one quick question. >> Last one. >> Very quickly, well, maybe it's not a quick question, so if you could just give me a quick answer. A couple times you both have mentioned the relationship between the CDO and business architecture. Currently, there's a relationship between the CIO and IT architecture, even the CIO and data architecture at a technical level. At IBM, do you actually have staff that does business architecture work? Is there someone, is that a formal, defined set of resources that you have, or should CDOs have access to a group of people who do business architecture? What do you think? >> We've traditionally had business architects at IBM, I think for a long time, that predates me. But again, as Jesus said, their role is also evolving. As it becomes much more about process transformation, it's different than it was before. I mean, this is much more now about a collaborative effort where you essentially sit down in a squad in an agile setting, and you're working together to redesign and reinvent the process that's there. And then, there's business value. It's less about creating large monolithic architectures that span an entire enterprise. It's all about being agile, data-driven, and reacting to the changes that are happening. >> So, turning strategy into action. >> Yes. >> And I think, again, in IBM, one of the things that we have done, our CIO, that is the organization that actually is the custodian of this cognitive enterprise architecture of which Inderpal actually is part of. So, we are actually putting it all together. It used to be an organization. Most COOs have evolved from running operations to defining shared services to now have to figure out what is the digital services version of the enterprise they need to implement, and they can't do that without a CDO in place, they just can't. >> Alright, gentlemen. Unfortunately, we'll have to leave it there. For viewers at home, tune into season two with Inderpal and Jesus. Really a great topic. Congratulations on the event, and we look to forward to the next time. >> Thank you. >> Thank you very much. >> Absolutely. With Peter Burris, I'm Jeff Frick. You're watching theCUBE from the IBM Chief Data Officer Strategy Summit Spring 2017. Be right back with more after this short break. Thanks for watching. (electronic keyboard music)

Published Date : Mar 29 2017

SUMMARY :

Brought to you by IBM. that are happening not only in the United States, and Jesus Mantas, he's the General Manager, How is the role starting to solidify the corporate strategy, and you have to have an officer and it was expensive, and what do you do with it all? and because now, not only the portion of the physical world of forces on the role of the CDO as you stake out, and then, enabling all the other jobs to change, it's the democratization of the data or the access to the data, which solved those constraints, to a CEO or board of directors I'll take it, and then, you can. and the data and the technology co-engineering aspect. is someone that can be in the boardroom is the culture change, and to do that, and actually, perhaps even harness that to your advantage of attacking this problem, I'm not going to tell you the client's data has to be their data. and to be able to architect to support that, and that's the essence of governance. They have the derivatives now, though. so it's not just that core baseline data anymore. that the data you have, Data does not follow the economics of scarcity. and being the executive in the business for the business to do. in the sense that now you have the relationship between the CDO and business architecture. and reacting to the changes So, turning strategy that is the organization that actually Congratulations on the event, Be right back with more after this short break.

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Jamie Alexander, Sensibill - IBM Interconnect 2017 - #ibminterconnect - #theCUBE


 

>> Announcer: Live from Las Vegas. It's theCUBE. Covering InterConnect 2017. Brought to you by IBM. >> You're a startup, growing. >> Jamie Alexander: Absolutely. >> You're working with big banks. This is not easy. >> Jamie Alexander: It is not easy. >> Normally they don't work with startups at all. >> Jamie Alexander: It's not easy at all. >> And Thintek is exploding as a very big growth area. Cloud enables this. Take us through some of the key points in your journey. As CTO, you've nailed some big wins with some big, established financial institutions, how'd you pull it off, what's the formula? >> Yeah, actually you could come and see my talk on Wednesday. I actually do that in detail. But I could give you a quick summary. So there's really, all along the way from the initial pre-sales to the pitch sessions with the customers, to the pilots, there are kind of learnings all along the way of the process and I think the number one thing is white glove service. So, typically, from a scalability perspective, startups are being trained to make it self-service, API, there's a developer portal, people can go in-- >> John: Move fast and break stuff. >> But actually, especially for the first set of customers, the white glove service is absolutely essential and really establishing the relationships at the ground level, so not just on the business side, that's a given, but also with the technical folks, the people at the banks that are doing the integrations, they can kill your projects. And so, really, giving them a bit of a taste of our culture I think, actually, really excites them. >> The white glove service, though, if I hear this correctly, it's not just being kind and holding their hand, there's some technical table stakes. >> Absolutely. >> What are those table stakes? 'Cause that seems to be the enterprise readiness matrix. >> Yeah, that's a great question. So I think the key is making tools that are very simple for developers to use, have developers love using your product, because, ultimately, it's a technical integration, and so one of the things that we did is we created an SDK both for iOS and Android and it's not just service connectivity, but it's also the full user experience around receipt capture. And what that did is it precluded the need for the banks to go and build all the screens and all the workflows. We could come in and say right away, here, we have it for you, you can customize it, configure it to make it look like your banking application to add your brand elements to it. But, ultimately, it allowed them, in a very short period of time, to bring on that new feature. The end user has no idea about Sensibill, there might be a little logo at the bottom of the receipt that says it's powered by Sensibill but other than that, it very much fits in with the existing banking application. And that's really important because receipts aren't their space, we want them to, right out of the gate, have a receipt capture application that's intuitive for end users. And this allows us to put it in their hand and just make it work for them. So that's really a big part of the success for them. >> And you've overcome that startup fear. >> Jamie: Absolutely. How have you done that? >> So I think the advantage for me is did spend my early career with IBM. So I spent about the first 13 years, >> Dave: So you were trained by IBM. So you kind of know. (laughs) >> And so I was both in software groups or working on e-commerce implementations but sort of the middle part after that, was in global services where I got to work with people in enterprise but across various sectors. And so that gave me they confidence and really allows me to think in the same way that enterprise folks think. Because we're not a startup that's selling, that has a platform where people are sharing pictures of sneakers, I mean this is serious business, and not to belittle other-- >> And their brand. Your customer's brand is on the line here. >> Absolutely, and so it really impacts everything we do. Who we hire, the culture we try to build, how we present ourselves to our customers. I mean it's across the board. Many considerations. But I think also, like me personally, I've always had that entrepreneurial spirit. So I've always been hacking things together on the side, and, actually, around 2010 when I left IBM, I had a previous startup, so this is number two for me. In fact, at IBM, I tried to, actually, do something intrapreneurial. But for me, actually, B to B, especially Business to Enterprise is for me really the sweet spot in terms of my skills and it's hard, so I like that. I like a hard problem and I would prefer that there's more barriers and it shows in the interest from our investors as well. You want a business with moats around it, and certainly financial institutions like banks, can take two years to close a deal. It's a really long sales cycle. >> John: So you're up for the challenge. >> Absolutely. >> So other than your past with IBM, what's the other IBM connection? You're running this on Bluemix, and IBM Cloud? >> Yeah, so we're running the solution on Bluemix. So we chose IBM for a number of reasons. One was their global footprints, in terms of their data centers. Our customers have certain SLAs they expect us to uphold. They require that we have disaster recovery in place. And so SoftLayer was very early, in terms of, bringing their data centers into Canada. So they recognize the opportunity there. And so we were both in Toronto and Montreal data centers. On top of that, as well, we've been part of the IBM Global Entrepreneurship Program. That's given us some mentoring around how to scale our business. Gave us some financial incentives as well. On top of that, there are other relationships that we've explored with the services business at IBM. so could, theoretically, IBM be a preferred vendor for, or integrator for our technology, and so there's a number of fronts that we're working with IBM and I think also, partly, because my former relationship, I was an employee at IBM. >> Dave: In Canada or in the U.S.? >> In Canada. So even our CEO for example, she was also at IBM. So bringing the best talents that I can find. People that want a change in their career and move from a large enterprise to a small company, we look for those people. >> And you were in the software labs up there, and then in the services group you got the financial services domain expertise and brought the software and FS together, wallah. >> Yeah and I, certainly, would not have predicted all the excitement around Thintek when I started. I'm really pleased that I, magically, threw horse shoes in luck and ended up in the right place at the right time. Even from three years ago-- >> When you tackle hard problems, usually, you end up in a good spot. >> Absolutely, yeah. >> So the hard question I want to ask you, this is a tough question, so be ready. Canadians or The Maple Leafs? >> (laughs) I'd have to say the Maple Leafs, to be honest, I'm from Toronto so. (laughing) >> Unless the Maple Leafs lose and then the Canadians over the Bruins, obviously. >> Hey, if there's a Canadian team, I'll be rooting for them. >> I love the hockey in Canada, being from the Boston area. Alright now, I want to ask you something more sentimental about the culture. You mentioned culture which you were talking about, your company culture. What's the cultural shift that you're seeing in the market place? Because we're talking about you're a start up that has cracked the code on a very hard problem with banks getting a customer. So kudos and props for that. But also, there's a whole dev ops movement that's going, now, to data. Where we heard some of the IBM execs pointing out the counter culture that's developing. The younger generation, they don't want things the old way. They're doing things much different. Can you comment about what your observations are around this cultural shift? >> Yeah, for sure. I think we've spent a bit too long, in general, paying lip service to the word innovation and I think, finally, it's, really, coming to fruition. Like real innovation not innovation just for the sake of marketing but, really, being able to innovate. Because a sub set of the millennials that are coming up, they really have, the culture of innovation has, really, been infused into their entire upbringing. And then they're, really, showing that in the work place. You see, over the last say, five, six years, the rise of hack days and these kind of things. People that are also interested in solving problems that don't just have commercial outcomes to them. What you find is, that if you can align people's passions and interests and have them understand that if you go after this thing, your career will be set. That's some of the things we try to do with our more junior resources. Is let them know that if there's something that they're interested in, a problem they want to tackle. It's aligned with where we're going from corporate objectives. Go after that because you will get what you want at Sensibill. We want those kind of people that don't just pay lip service to innovation but, really, see something and are self starting and can go after things on their own. I think there's, also, a big aspect of social awareness. There's people on our team and rightly so that are concerned about ethical use of data. So we're, at Sensibill, drafting up a policy just so, internally, we know that we can agree, collectively, on how we intend too use our data. It's, certainly, not malicious purposes. We're not selling individual user data. Now the banks do have access, the data collected through their systems is theirs. But, ultimately, in terms of how we plan to monetize the insights which is the next, really, interesting thing and things that I'm working on in 2017, really making sure it's done in an ethical way. >> That's your next moon shot is to, really, crack the code on the governance and the management of the data? >> But I think to get the right people, you also have to have to consider the social implications of using the data. People have to feel good about the work they do. There can be a lot of sensitivity around the type of data that we collect. >> Well Jamie, congratulations on the financing of your start up. Jamie Alexander, who's the co-founder and CTO of Sensibill. Check em out. If you're a big bank, not many of them, it's mostly potential customers. Congratulations on winning the big deal as a start up, that's great news. >> Thanks so much. Thanks for coming on the CUBE and sharing your start up story. I'm John Furrier with Dave Vellante. Keep watching it here. Stay with us for more coverage from Las Vegas after this short break. (lively music)

Published Date : Mar 22 2017

SUMMARY :

Brought to you by IBM. This is not easy. Normally they don't how'd you pull it off, what's the formula? the customers, to the pilots, and really establishing the relationships and holding their hand, 'Cause that seems to be the and so one of the things that we did How have you done that? So I spent about the first 13 years, Dave: So you were trained by IBM. but sort of the middle part after that, Your customer's brand is on the line here. I mean it's across the board. the solution on Bluemix. So bringing the best the software and FS together, wallah. at the right time. When you tackle hard problems, So the hard question I want to ask you, to say the Maple Leafs, Unless the Maple Leafs Hey, if there's a Canadian team, that has cracked the code showing that in the work place. the type of data that we collect. on the financing Thanks for coming on the CUBE and sharing

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Robbie Strickland, IBM - Spark Summit East 2017 - #SparkSummit - #theCUBE


 

>> Announcer: Live from Boston Massachusetts this is theCube. Covering Spark Summit East 2017, brought to you by Databricks. Now here are your hosts Dave Vellante and George Gilbert. >> Welcome back to theCube, everybody, we're here in Boston. The Cube is the worldwide leader in live tech coverage. This is Spark Summit, hashtag #SparkSummit. And Robbie Strickland is here. He's the Vice President of Engines & Pipelines, I love that title, for the Watson Data Platform at IBM Analytics, formerly with The Weather Company that was acquired by IBM. Welcome to you theCube, good to see you. >> Thank you, good to be here. >> So, it's my standing tongue-in-cheek line is the industry's changing, Dell buys EMC, IBM buys The Weather Company. [Robbie] That's right. >> Wow! That sort of says it all, right? But it was kind of a really interesting blockbuster acquisition. Great for the folks at The Weather Company, great for IBM, so give us the update. Where are we at today? >> So, it's been an interesting first year. Actually, we just hit our first anniversary of the acquisition and a lot has changed. Part of my role, new role at IBM, having come from The Weather Company, is a byproduct of the two companies bringing our best analytics work and kind of pulling those together. I don't know if we have some water but that would be great. So, (coughs) excuse me. >> Dave: So, let me chat for a bit. >> Thanks. >> Feel free to clear your throat. So, you were at IBM, the conference at the time was called IBM Insight. It was the day before the acquisition was announced and we had David Kenny on. David Kenny was the CEO of The Weather Company. And I remember we were talking, and I was like, wow, you have such an interesting business model. Off camera, I was like, what do you want to do with this company, you guys are like prime. Are you going public, you going to sell this thing, I know you have an MBA background. And he goes, "Oh, yeah, we're having fun." Next day was the announcement that IBM bought The Weather Company. I saw him later and I was like, "Aha!" >> And now he's the leader of the Watson Group. >> That's right. >> Which is part of our, The Weather Company joined The Watson Group. >> And The Cloud and analytics groups have come together in recognition that analytics and The Cloud are peanut butter and jelly. >> Robbie: That's absolutely right. >> And David's running that organization, right? >> That is absolutely right. So, it's been an exciting year, it's been an interesting year, a lot of challenges. But I think where we are now with the Watson Data Platform is a real recognition that the use dase where we want to try to make data and analytics and machine learning and operationalizing all of those, that that's not easy for people. And we need to make that easy. And our experience doing that at The Weather Company and all the challenges we ran into have informed the organization, have informed the road map and the technologies that we're using to kind of move forward on that path. >> And The Watson Data Platform was announced in, I believe, October. >> Robbie: That's right. >> You guys had a big announcement in New York City. And you took many sort of components that were viewed as individual discreet functions-- >> Robbie: That's right. >> And brought them together in a single data pipeline. Is that right? >> Robbie: That's right. >> So, maybe describe that a little bit for our audience. >> So, the vision is, you know, one of the things that's missing in the market today is the ability to easily grab data from some source, whether it's a database or a Kafka stream, or some sort of streaming data feed, which is actually something that's often overlooked. Usually you have platforms that are oriented around streaming data, data feeds, or oriented around data at rest, batch data. One of the things that we really wanted to do was sort of combine those two together because we think that's really important. So, to be able to easily acquire data at scale, bring it into a platform, orchestrate complex workflows around that, with the objective, of course, of data enrichment. Ultimately, what you want to be able to do is take those raw signals, whatever they are, and turn that into some sort of enriched data for your organization. And so, for example, we may take signals in from a mobile app, things like beacons, usage beacons on a mobile app, and turn that into a recommendation engine so we can feed real time content decisions back into a mobile platform. Well, that's really hard right now. It requires lots of custom development. It requires you to essentially stitch together your pipeline end to end. It might involve a machine learning pipeline that runs a training pipeline. It might involve, it's all batch oriented, so you land your data somewhere, you run this machine learning pipeline maybe in Spark or ADO or whatever you've got. And then the results of that get fed back into some data store that gets merged with your online application. And then you need to have a restful API or something for your application to consume that and make decisions. So, our objective was to take all of the manual work of standing up those individual pieces and build a platform where that is just, that's what it's designed to do. It's designed to orchestrate those multiple combinations of real time and batch flows. And then with a click of a button and a few configuration options, stand up a restful service on top of whatever the results are. You know, either at an interim stage or at the end of the line. >> And you guys gave an example. You actually showed a demo at the announcement. And I think it was a retail example, and you showed a lot of what would traditionally be batch processes, and then real time, a recommendation came up and completed the purchase. The inference was this is an out of the box software solution. >> Robbie: That's right. >> And that's really what you're saying you've developed. A lot of people would say, oh, it's IBM, they've cobbled together a bunch of their old products, stuck them together, put an abstraction layer on, and wrapped a bunch of services around it. I'm hearing from you-- >> That's exactly, that's just WebSphere. It's WebSphere repackaged. >> (laughing) Yeah, yeah, yeah. >> No, it's not that. So, one of the things that we're trying to do is, if you look at our cloud strategy, I mean, this is really part and parcel, I mean, the nexus of the cloud strategy is the Watson Data Platform. What we could have done is we could have said let's build a fantastic cloud and compete with Amazon or Google or Microsoft. But what we realized is that there is a certain niche there of people who want to take individual services and compose them together and build an application. Mostly on top of just raw VMs with some additional, you know, let's stitch together something with Lambda or stitch together something with SQS, or whatever it may be. Our objective was to sort of elevate that a bit, not try to compete on that level. And say, how do we bring Enterprise grade capabilities to that space. Enterprise grade data management capabilities end-to-end application development, machine learning as a first class citizen, in a cohesive experience. So that, you know, the collaboration is key. We want to be able to collaborate with business users, data scientists, data engineers, developers, API developers, the consumers of the end results of that, whether they be mobile developers or whatever. One of the things that is sort of key, I think, to the vision is that these roles that we've traditionally looked at. If you look at the way that tool sets are built, they're very targeted to specific roles. The data engineer has a tool, the data scientist has a tool. And what's been the difficult part is the boundaries between those have been very firm and the collaboration has been difficult. And so, we draw the personas as a Venn diagram. Because it's very difficult, especially if you look at a smaller company, and even sometimes larger companies, the data engineer is the data scientist. The developer who builds the mobile application is the data scientist. And then in some larger organizations, you have very large teams of data scientists that have these artificial barriers between the data scientist and the data engineer. So, how do we solve both cases? And I think the answer was for us a platform that allows for seamless collaboration where there is not these clean lines between the personas, that the tool sets easily move from one to the other. And if you're one of those hybrid people that works across lines, that the tool feels like it's one tool for you. But if you're two different teams working together, that you can easily hand off. So, that was one of the key objectives we're trying to answer. >> Definitely an innovative component of the announcement, for sure. Go ahead, George. >> So, help us sort of bracket how mature this end-to-end tool suite is in terms of how much of the pipeline it addresses. You know, from the data origin all the way to a trained model and deploying that model. Sort of what's there now, what's left to do. >> So, there are a few things we've brought to market. Probably the most significant is the data science experience. The data science experience is oriented around data science and has, as its sort of central interface, Jupyter Notebooks. Now, as well as, we brought in our studio, and those sorts of things. The idea there being that we'll start with the collaboration around data scientists. So, data scientists can use their language of choice, collaborate around data sets, save out the results of their work and have it consumed either publicly by some other group of data scientists. But the collaboration among data scientists, that was sort of step one. There's a lot of work going on that's sort of ongoing, not ready to bring to market, around how do we simplify machine learning pipelines specifically, how do we bring governance and lineage, and catalog services and those sorts of things. And then the ingest, one of the things we're working on that we have brought to market is our product called Lift which connects, as well. And that's bringing large amounts of data easily into the platform. There are a few components that have sort of been brought to market. dashDB, of course, is a key source of data clouded. So, one of the things that we're working on is some of these existing technologies that actually really play well into the eco system, trying to tie them well together. And then add the additional glue pieces. >> And some of your information management and governance components, as well. Now, maybe that is a little bit more legacy but they're proven. And I don't know if the exits and entries into those systems are as open, I don't know, but there's some capabilities there. >> Speaking of openness, that's actually a great point. If you look at the IIG suite, it's a great On-Premise suite. And one of the challenges that we've had in sort of past IBM cloud offerings is a lot of what has been the M.O. in the past is take a great On-Prem solution and just try to stand it up as a service in the cloud. Which in some cases has been successful, in other cases, less so. One of the things we're trying to look at with this platform is how do we leverage (a) open source. So that whatever you may already be running open source on, Prem or in some other provider, that it's very easy to move your workloads. So, we want to be able to say if you've got 10,000 lines of fraud detection code to map produce. You don't need to rewrite that in anything. You can just move it. And the other thing is where our existing legacy tech doesn't necessarily translate well to the cloud, our first strategy is see if there's any traction around an existing open source project that satisfies that need, and try to see if we can build on that. Where there's not, we go cloud first and we build something that's tailor made to come out. >> So, who's the first one or two customers for this platform? Is it like IBM Global Business Services where they're building the semi-custom industry apps? Or is it the very, very big and sophisticated, like banks and Telcos who are doing the same? Or have you gotten to the point where you can push it out to a much wider audience? >> That's a great question, and it's actually one that is a source of lots of conversation internally for us. If you look at where the data science experience is right now, it's a lot of individual data scientists, you know, small companies, those sorts of things coming together. And a lot of that is because some of the sophistication that we expect for Enterprise customers is not quite there yet. So, we wouldn't expect Enterprise customers to necessarily be onboarded as quickly at the moment. But if we look at sort of the, so I guess there's maybe a medium term answer and a long term answer. I think the long term answer is definitely the Enterprise customers, you know, leveraging IBM's huge entry point into all of those customers today, there's definitely a play to be made there. And one of the things that we're differentiating, we think, over an AWS or Google, is that we're trying to answer that use case in a way that they really aren't even trying to answer it right now. And so, that's one thing. The other is, you know, going beta with a launch customer that's a healthcare provider or a bank where they have all sorts of regulatory requirements, that's more complicated. And so, we are looking at, in some cases, we're looking at those banks or healthcare providers and trying to carve off a small niche use case that doesn't actually fall into the category of all those regulatory requirements. So that we can get our feet wet, get the tires kicked, those sorts of things. And in some cases we're looking for less traditional Enterprise customers to try to launch with. So, that's an active area of discussion. And one of the other key ones is The Weather Company. Trying to take The Weather Company workloads and move The Weather Company workloads. >> I want to come back to The Weather Company. When you did that deal, I was talking to one of your executives and he said, "Why do you think we did the deal?" I said, "Well, you've got 1500 data scientists, "you've got all this data, you know, it's the future." He goes, "Yeah, it's also going to be a platform "for IOT for IBM." >> Robbie: That's right. >> And I was like, "Hmmm." I get the IOT piece, how does it become a platform for IBM's IOT strategy? Is that really the case? Is that transpiring and how so? >> It's interesting because that was definitely one of the key tenets behind the acquisition. And what we've been working on so hard over the last year, as I'm sure you know, sometimes boxes and arrows on an architecture diagram and reality are more challenging. >> Dave: (laughing) Don't do that. >> And so, what we've had to do is reconcile a lot of what we built at The Weather Company, existing IBM tech, and the new things that were in flight, and try to figure out how can we fit all those pieces together. And so, it's been complicated but also good. In some cases, it's just people and expertise. And bringing those people and expertise and leaving some of the software behind. And other cases, it's actually bringing software. So, the story is, obviously, where the rubber meets the road, more complicated than what it sounds like in the press release. But the reality is we've combined those teams and they are all moving in the same direction together with various bits and pieces from the different teams. >> Okay, so, there's vision and then the road map to execute on that, and it's going to unfold over several years. >> Robbie: That's right. >> Okay, good. Stuff at the event here, I mean, what are you seeing, what's hot, what's going on with Spark? >> I think one of the interesting things with what's going on with Spark right now is a lot of the optimizations, especially things around GPUs and that. And we're pretty excited about that, being a hardware manufacturer, that's something that is interesting to us. We run our own cloud. Where some people may not be able to immediately leverage those capabilities, we're pretty excited about that. And also, we're looking at some of those, you know, taking Spark and running it on Power and those sorts of things to try to leverage the hardware improvements. So, that's one of the things we're doing. >> Alright, we have to leave it there, Robbie. Thanks very much for coming on theCube, really appreciate it. >> Thank you. >> You're welcome. Alright, keep it right there, everybody. We'll be right back with our next guest. This is theCube. We're live from Spark Summit East, hashtag #SparkSummit. Be right back. >> Narrator: Since the dawn of The Cloud, theCube.

Published Date : Feb 9 2017

SUMMARY :

brought to you by Databricks. The Cube is the worldwide leader in live tech coverage. is the industry's changing, Dell buys EMC, Great for the folks at The Weather Company, is a byproduct of the two companies And I remember we were talking, and I was like, Which is part of our, And The Cloud and analytics groups have come together is a real recognition that the use dase And The Watson Data Platform was announced in, And you took many sort of components that were And brought them together in a single data pipeline. So, the vision is, you know, one of the things And I think it was a retail example, And that's really what you're saying you've developed. That's exactly, that's just WebSphere. So, one of the things that we're trying to do is, of the announcement, for sure. You know, from the data origin all the way to So, one of the things that we're working on And I don't know if the exits and entries One of the things we're trying to look at with this platform And a lot of that is because some of the sophistication and he said, "Why do you think we did the deal?" Is that really the case? one of the key tenets behind the acquisition. and the new things that were in flight, to execute on that, and it's going to unfold Stuff at the event here, I mean, So, that's one of the things we're doing. Alright, we have to leave it there, Robbie. This is theCube.

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Mike Gualtieri, Forrester Research - Spark Summit East 2017 - #sparksummit - #theCUBE


 

>> Narrator: Live from Boston, Massachusetts, this is the Cube, covering Spark Summit East 2017, brought to you by Databricks. Now, here are your hosts, Dave Vellante and George Gilbert. >> Welcome back to Boston, everybody, where the town is still euphoric. Mike Gualtieri is here, he's the principal analyst at Forrester Research, attended the parade yesterday. How great was that, Mike? >> Yes. Yes. It was awesome. >> Nothing like we've ever seen before. All right, the first question is what was the bigger shocking surprise, upset, greatest win, was it the Red Sox over the Yankees or was it the Superbowl this weekend? >> That's the question, I think it's the Superbowl. >> Yeah, who knows, right? Who knows. It was a lot of fun. So how was the parade yesterday? >> It was magnificent. I mean, it was freezing. No one cared. I mean--but it was, yeah, it was great. Great to see that team in person. >> That's good, wish we could talk, We can, but we'll get into it. So, we're here at Spark Summit, and, you know, the show's getting bigger, you're seeing more sponsors, still heavily a technical audience, but what's your take these days? We were talking off-camera about the whole big data thing. It used to be the hottest thing in the world, and now nobody wants to have big data in their title. What's Forrester's take on that? >> I mean, I think big data-- I think it's just become mainstream, so we're just back to data. You know, because all data is potentially big. So, I don't think it's-- it's not the thing anymore. I mean, what do you do with big data? You analyze it, right? And part of what this whole Spark Summit is about-- look at all the sessions. Data science, machine learning, streaming analytics, so it's all about sort of using that data now, so big data is still important, but the value of big data comes from all this advanced analytics. >> Yeah, and we talked earlier, I mean, a lot of the value of, you know, Hadoop was cutting costs. You know, you've mentioned commodity components and reduction in denominator, and breaking the need for some kind of big storage container. OK, so that-- we got there. Now, shifting to new sources of value, what are you spending your time on these days in terms of research? >> Artificial intelligence, machine learning, so those are really forms of advanced analytics, so that's been-- that's been very hot. We did a survey last year, an AI survey, and we asked a large group of people, we said, oh, you know, what are you doing with AI? 58% said they're researching it. 19% said they're training a model. Right, so that's interesting. 58% are researching it, and far fewer are actually, you know, actually doing something with it. Now, the reality is, if you phrase that a little bit differently, and you said, oh, what are you doing with machine learning? Many more would say yes, we're doing machine learning. So it begs the question, what do enterprises think of AI? And what do they think it is? So, a lot of my inquiries are spent helping enterprises understand what AI is, what they should focus on, and the other part of it is what are the technologies used for AI, and deep learning is the hottest. >> So, you wrote a piece late last year, what's possible today in AI. What's possible today in AI? >> Well, you know, before understanding was possible, it's important to understand what's not possible, right? And so we sort of characterize it as there's pure AI, and there's pragmatic AI. So it's real simple. Pure AI is the sci-fi stuff, we've all seen it, Ex Machina, Star Wars, whatever, right? That's not what we're talking about. That's not what enterprises can do today. We're talking about pragmatic AI, and pragmatic AI is about building predictive models. It's about conversational APIs, to interact in a natural way with humans, it's about image analysis, which is something very hot because of deep learning. So, AI is really about the building blocks that companies have been using, but then using them in combination to create even more intelligent solutions. And they have more options on the market, both from open source, both from cloud services that-- from Google, Microsoft, IBM, and now Amazon, at their re-- Were you guys at their reinvent conference? >> I wasn't, personally, but we were certainly there. >> Yeah, they announced the Amazon AI, which is a set of three services that developers can use without knowing anything about AI or being a data scientist. But, I mean, I think the way to think about AI is that it is data science. It requires the expertise of a data scientist to do AI. >> Following up on that comment, which was really interesting, is we try and-- whereas vendors try and democratize access to machine learning and AI, and I say that with two terms because usually the machine learning is the stuff that's sort of widely accessible and AI is a little further out, but there's a spectrum when you can just access an API, which is like a pre-trained model-- >> Pre-trained model, yep. >> It's developer-accessible, you don't need to be a data scientist, and then at the other end, you know, you need to pick your algorithms, you need to pick your features, you need to find the right data, so how do you see that horizon moving over time? >> Yeah, no, I-- So, these machine learning services, as you say, they're pre-trained models, totally accessible by anyone, anyone who can call an API or a restful service can access these. But their scope is limited, right? So, if, for example, you take the image API, you know, the imaging API that you can get from Google or now Amazon, you can drop an image in there and it will say, oh, there's a wine bottle on a picnic table on the beach. Right? It can identify that. So that's pretty cool, there might be a lot of use cases for that, but think of an enterprise use case. No. You can't do it, and let me give you this example. Say you're an insurance company, and you have a picture of a steel roof that's caved in. If you give that to one of these APIs, it might say steel roof, it may say damage, but what it's not going to do is it's not going to be able to estimate the damage, it's not going to be able to create a bill of materials on how to repair it, because Google hasn't trained it at that level. OK, so, enterprises are going to have to do this themselves, or an ISV is going to have to do it, because think about it, you've got 10 years worth of all these pictures taken of damage. And with all of those pictures, you've got tons of write-ups from an adjuster. Whoa, if you could shove that into a deep learning algorithm, you could potentially have consumers take pictures, or someone untrained, and have this thing say here's what the estimate damage is, this is the situation. >> And I've read about like insurance use cases like that, where the customer could, after they sort of have a crack up, take pictures all around the car, and then the insurance company could provide an estimate, tell them where the nearest repair shops are-- >> Yeah, but right now it's like the early days of e-commerce, where you could send an order in and then it would fax it and they'd type it in. So, I think, yes, insurance coverage is taking those pictures, and the question is can we automate it, and-- >> Well, let me actually iterate on that question, which is so who can build a more end-to-end solution, assuming, you know, there's a lot of heavy lifting that's got to go on for each enterprise trying to build a use case like that. Is it internal development and only at big companies that have a few of these data science gurus? Would it be like an IBM Global Services or an EXIN SURE, or would it be like a vertical ISV where it's semi-custom, semi-patent? >> I think it's both, but I also think it's two or three people walking around this conference, right, understanding Spark, maybe understanding how to use TensorFlow in conjunction with Spark that will start to come up with these ideas as well. So I think-- I think we'll see all of those solutions. Certainly, like IBM with their cognitive computing-- oh, and by the way, so we think that cognitive computing equals pragmatic AI, right, because it has similar characteristics. So, we're already seeing the big ISVs and the big application developers, SAP, Oracle, creating AI-infused applications or modules, but yeah, we're going to see small ISVs do it. There's one in Austin, Texas, called InteractiveTel. It's like 10 people. What they do is they use the Google-- so they sell to large car dealerships, like Ernie Boch. And they record every conversation, phone conversation with customers. They use the Google pre-trained model to convert the speech to text, and then they use their own machine learning to analyze that text to find out if there's a customer service problem or if there's a selling opportunity, and then they alert managers or other people in the organization. So, small company, very narrowly focused on something like car buying. >> So, I wonder if we could come back to something you said about pragmatic AI. We love to have someone like you on the Cube, because we like to talk about the horses on the track. So, if Watson is pragmatic AI, and we all-- well, I think you saw the 60 Minutes show, I don't know, whenever it was, three or four months ago, and IBM Watson got all the love. They barely mentioned Amazon and Google and Facebook, and Microsoft didn't get any mention. So, and there seems to be sentiment that, OK, all the real action is in Silicon Valley. But you've got IBM doing pragmatic AI. Do those two worlds come together in your view? How does that whole market shake up? >> I don't think they come together in the way I think you're suggesting. I think what Google, Microsoft, Facebook, what they're doing is they're churning out fundamental technology, like one of the most popular deep learning frameworks, TensorFlow, is a Google thing that they open sourced. And as I pointed out, those image APIs, that Amazon has, that's not going to work for insurance, that's not going to work for radiology. So, I don't think they're in-- >> George Gilbert: Facebook's going to apply it differently-- >> Yeah, I think what they're trying to do is they're trying to apply it to the millions of consumers that use their platforms, and then I think they throw off some of the technology for the rest of the world to use, fundamentally. >> And then the rest of the world has to apply those. >> Yeah, but I don't think they're in the business of building insurance solutions or building logistical solutions. >> Right. >> But you said something that was really, really potentially intriguing, which was you could take the horizontal Google speech to text API, and then-- >> Mike Gualtieri: And recombine it. >> --put your own model on top of that. And that's, techies call that like ensemble modeling, but essentially you're taking, almost like an OS level service, and you're putting in a more vertical application on top of it, to relate it to our old ways of looking at software, and that's interesting. >> Yeah, because what we're talking about right now, but this conversation is now about applications. Right, we're talking about applications, which need lots of different services recombined, whereas mostly the data science conversation has been narrowly about building one customer lifetime value model or one churn model. Now the conversation, when we talk about AI, is becoming about combining many different services and many different models. >> Dave Vellante: And the platform for building applications is really-- >> Yeah, yeah. >> And that platform, the richest platform, or the platform that is, that is most attractive has the most building blocks to work with, or the broadest ones? >> The best ones, I would say, right now. The reason why I say it that way is because this technology is still moving very rapidly. So for an image analysis, deep learning, very good for image, nothing's better than deep learning for image analysis. But if you're doing business process models or like churn models, well, deep learning hasn't played out there yet. So, right now I think there's some fragmentation. There's so much innovation. Ultimately it may come together. What we're seeing is, many of these companies are saying, OK, look, we're going to bring in the open source. It's pretty difficult to create a deep learning library. And so, you know, a lot of the vendors in the machine learning space, instead of creating their own, they're just bringing in MXNet or TensorFlow. >> I might be thinking of something from a different angle, which is not what underlying implementation they're using, whether it's deep learning or whether it's just random forest, or whatever the terminology is, you know, the traditional statistical stuff. The idea, though, is you want a platform-- like way, way back, Windows, with the Win32 API had essentially more widgets for helping you build graphical applications than any other platform >> Mike Gualtieri: Yeah, I see where you're going. >> And I guess I'm thinking it doesn't matter what the underlying implementation is, but how many widgets can you string together? >> I'm totally with you there, yeah. And so I think what you're saying is look, a platform that has the most capabilities, but abstracts, the implementations, and can, you know, can be somewhat pluggable-- right, good, to keep up with the innovation, yeah. And there's a lot of new companies out there, too, that are tackling this. One of them's called Bonsai AI, you know, small startup, they're trying to abstract deep learning, because deep learning right now, like TensorFlow and MXNet, that's a little bit of a challenge to learn, so they're abstracting it. But so are a lot of the-- so is SAS, IBM, et cetera. >> So, Mike, we're out of time, but I want to talk about your talk tomorrow. So, AI meets Spark, give us a little preview. >> AI meets Spark. Basically, the prerequisite to AI is a very sophisticated and fast data pipeline, because just because we're talking about AI doesn't mean we don't need data to build these models. So, I think Spark gives you the best of both worlds, right? It's designed for these sort of complex data pipelines that you need to prep data, but now, with MLlib for more traditional machine learning, and now with their announcement of TensorFrames, which is going to be an interface for TensorFlow, now you've got deep learning, too. And you've got it in a cluster architecture, so it can scale. So, pretty cool. >> All right, Mike, thanks very much for coming on the Cube. You know, way to go Pats, awesome. Really a pleasure having you back. >> Thanks. >> All right, keep right there, buddy. We'll be back with our next guest right after this short break. This is the Cube. (peppy music)

Published Date : Feb 8 2017

SUMMARY :

brought to you by Databricks. Mike Gualtieri is here, he's the principal analyst It was awesome. All right, the first question is So how was the parade yesterday? Great to see that team in person. and, you know, the show's getting bigger, I mean, what do you do with big data? what are you spending your time on Now, the reality is, if you phrase that So, you wrote a piece late last year, So, AI is really about the building blocks It requires the expertise of a data scientist to do AI. So, if, for example, you take the image API, of e-commerce, where you could send an order in assuming, you know, there's a lot of heavy lifting and the big application developers, SAP, Oracle, We love to have someone like you on the Cube, that Amazon has, that's not going to work for insurance, Yeah, I think what they're trying to do Yeah, but I don't think they're in the business and you're putting in a more vertical application Yeah, because what we're talking about right now, And so, you know, a lot of the vendors you know, the traditional statistical stuff. and can, you know, can be somewhat pluggable-- So, Mike, we're out of time, So, I think Spark gives you the best of both worlds, right? Really a pleasure having you back. This is the Cube.

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