>>from >>around the globe. It's the Cube with digital coverage of AWS reinvent 2020 Special coverage sponsored by A. W s Global Partner Network. >>Hello and welcome to the Cube. Virtual in our coverage of AWS reinvent 2020 and our special coverage of a PM partner experience where the Cube virtual and I'm your host, Justin Warren. And today I'm joined by Mike Gill. Fix. Who is the chief product officer for IBM Cloud PACs. Mike, welcome to the Cube. >>Thank you. Thanks for happening. >>Now. Cloud PACs is a new thing from IBM. I'm not particularly familiar with it, but it's it's related to IBM's partnership with with a W s. So maybe you could just start us off quickly by explaining what is cloud packs and what's your role as chief product officer there? >>Well, Klopp acts sort of our next generation platform. What we've been doing is bringing the power of IBM software really across the board and bringing it to a hybrid cloud environments, so make it really easy for our customers to consume it wherever wherever they want, however, they want to choose to do it with a consistent skill set and making it really easy to kind of get those things up and running and deliver value quickly. And this is part of IBM hybrid approach. So what we've seen is organizations that can leverage the same skill set and, you know, basically take those work quotes, make him run where they need thio. Yields about a 2.5 times are y and cloud packs it at the center of that running on the open shift platform so they get consistent security skills and powerful software to run their business running everywhere. And we've been partnering with AWS because we want to make sure that those customers that have made that choice could get access to those capabilities easy and as fast as possible. >>Right? And and the cloud PACs have built on the red hat open. Now let me get this right. It's the open hybrid cloud platform. So is that open shift? >>It is Open shift. Yes. I >>mean, IBM >>is incredibly committed to being thio. Open software and open ship does provide that common layer, and the reason that's important is you want consistent security. You want to avoid lock in, right? That gives you a very powerful platform A fabric, if you will, that can truly run anywhere with any workload. And we've been working very closely with a W s to make sure that is Ah, Premier. First class experience on AWS. >>Yes. So the the open shift on AWS is is relatively new from IBM. So could you explain what is open shift on AWS? And how does that differ from the open shift that people may be already familiar with? >>Well, the Colonel, if you will, is the same. It's the same sort of central open source software, but in working closely with AWS were now making those things available a simple services that you can quickly provisioned and run, and that makes it really easy for people to get started. But again, sort of carrying forward that same sort of skill set. So that's kind of a key way in which we see that you can gain that sort of consistency, you know, no matter where you're running that workflow and we've been investing in that integration, working closely with them Amazon, >>right? And we all know red hats, commitment, thio, open source software and the open ecosystems. Red hat is rightly famous for it, and I I am old enough to remember when it was a brand new thing, particularly in enterprise. Thio allow open source toe to come in and have anything to do with workloads. And now it's It's ALS, the rage, and people are running quite critical workloads on it. So what are you seeing in the adoption within the enterprise off open software? >>The adoption is massive, I think. Well, first, let me describe what's driving it. I mean, people want to tap into innovation and the beauty of open source is your your kind of crowd sourcing, if you will, this massive community of developers that are creating just an incredible amount of innovation and incredible speed, and it's a great way to ensure that you avoid vendor lock in. So enterprises of all types are looking to open solutions as a way both of innovating faster and getting protection. And that commitment is something certainly redheaded tapped into its behind the great success of Red Hat. And it's something that, frankly, is permeating throughout IBM and that we're very committed to driving this sort of open approach. And that means that you know, we need to ensure that people get access to the innovation they need, run it where they want and ensure that they feel that they have choice >>on the choice. I think is a key part of it that isn't really coming through in some of the narrative that there's a lot of discussion about how you should actually, should you go cloud. I remember when it was. Either you should stay on site or should you go, Go to Cloud and we had a long discussion there. Hybrid Cloud really does seem to have come of age where it's it's a a realistic kind of compromise, probably the wrong word, but it's it's a trade off between doing all of one thing or all another. And for most enterprises, that doesn't actually seem to be the choice that that's actually viable for them. So hybrid seems like it's actually just the practical approach. Would that be accurate? >>Well, our studies have shown that if you look statistically at the set of work, oh, that's moved to clouds, you know, something like 20% of workloads have only moved to cloud, meaning the other 80% is experiencing barriers to move >>and some >>of those barriers is figuring out what to do with all this data that's sitting on Prem or, you know, these these applications that have years and years of intelligence baked into them that cannot easily be ported. And so organizations looking to hybrid approaches because they give them more choice. It helps them deal with fragmentation, meaning as I move more workload, I have consistent skill set. It helps me extend my existing investments and bring it into the cloud world. And all those things again are done with consistent security. That's really important, right? Organizations need to make sure they're protecting their assets. Their data throughout, you know, leveraging a consistent platform. So that's really the benefit of the hybrid approach. It essentially is going to enable these organizations unlocked more workload and gain the acceleration and the transformative, effective clouds. And that's why I think they're really That's why it's becoming a necessity, right, because they just can't get that 80% to move. Yah, >>Yeah, I've long said that the cloud is a state of mind rather than a particular location. It's It's more about an operational model of how you do things, so hearing that we've only got 20% of workloads have moved to this new way of doing things does rather suggest that there's a lot more work to be done. What for? Those organizations that are just looking to do this now they've they've done a bit of it and they're looking for those next new workloads. Where do you see customers struggling the most? And where do you think that IBM can help them there? >>Well, um, boy, where they struggling the most? First, I think skills. I mean, they have to figure out a new set of technologies to go and transition from the old World to the new. And at the heart of that is lots of really critical debate. Like, how do they modernize the way that they do software delivery for many enterprises, right. Embrace new ways of doing software delivery. How do they deal with the data issues that arise from where the data sets their obligations for data protection? Um, what happened to the data spans multiple different places, but you have to provide high quality performance and security thes air, all parts of issues that you know, spanned different environments. And so they have to figure out how to manage those kinds of things and make it work in one place. I think the benefit of partnering, you know, with Amazon is clearly there's a huge, you know, customer base. That's interesting. Amazon. I think the benefit of the idea and partnership is you know, we can help to go and unlock some of those new workloads and find ways to get that cloud benefit and help to move them to the cloud faster again with that consistency of experience. And that's why I think it's a good match partnership. We're giving more customers choice. We're helping them to unlock innovation substantially, faster, >>right? And so, for people who might want to just get started without how would they approach this? Do you think people might have some experience with AWS? It's It's almost difficult not to these days, but for those who aren't familiar with the red hat on a W s with open shift on AWS, how would they get started with you? Thio to explore what's possible? >>Well, one of the things that we're offering to our clients is a service that we refer to his I. D. Um garage Z you know, an engagement model, if you will, within IBM, where we work with our clients and we really help them to do co creation. So help to understand their business problem. Or, you know, the target state of where they want their I t to get to. And in working with them in co creation, you know, we help them to affect that transition. Let's say that it's about, you know, delivering business applications faster. Let's say it's about modernizing the applications they have or offering new services new business models again, all in the spirit of co creation. And we found that to be really popular. Um, it's a great way to get started. We we leverage design thinking approach. They can think about the customer experience and their outcome. If they're creating new business, processes, new applications and then really help them toe uplift their skills and, you know, get ready. Thio adopt cloud technology and everything that they dio. >>It sounds like this is, ah, lot of established workloads that people already have in their organizations. It's already there. It's generating real money. It's It's not those experimental workloads that we saw early on which was a well, let's try. This cloud is a fabulous way where we can run some experiments, and if it doesn't work, we just turn it off again. These sound like a lot more workloads, air kind of more important to the business. Is that be true? >>Yeah, I think that's true now. I wouldn't say they're just existing work clothes, because I think there's lots of new business innovation that many of our, you know, clients want to go on launch. And so this gives them an opportunity to do that new innovation but not forget the past, meaning they could bring it forward and bring it forward into an integrated experience. I mean, that's what everyone demands of a true digital business, right? They expect that your experience is integrated, that it's responsive that it's targeted and personalized, and the only way to do that is to allow for experimentation that integrates in with the, you know, standard business processes and things that you did before. And so you need to be able to connect those things together seamlessly, >>right? So it sounds like it's it's a transition more than creating new thing completely from scratch. It's well Look, we've done a lot of innovation over the past decade or so in cloud. We know what works, but we still have workloads that people clearly no one value. How do we put those things together and do it in such a way that we maintain the flexibility to be able to make new changes as we as we learn new things? >>Yeah, leverage what you've got. Play to your strength. I mean, that's that's how you create speed. If you have to reinvent the wheel every time, it's going to be a slow roll. >>Yeah, that does seem like an area where an organization, probably at this point should be looking to partner with other people who have done the hard yards. They've They've already figured this out. What, as you say, Why can't make all of these obvious areas yourself when you're you're starting from scratch? When there's a wealth of experience out there, and particularly this whole ecosystem that exists around around open software? Uh, in fact, maybe you could tell us a little bit about the ecosystem opportunities that are there because red, that's been part of this for a very long time. AWS has a very broad ecosystem is we're all familiar with being here. It reinvent yet again. How does that ecosystem claim toe? What's possible? >>I well, let me explain why I think IBM brings a different dimension to that trio, right? IBM brings the industry expertise. I mean, we've long worked with all of our clients are partners on solving some of the biggest business problems and being embedded in the thing that they do. So we have deep knowledge of their enterprise challenges where they're trying to take them. Deep knowledge of their business processes were ableto bring that that industry know how mixed with, you know, red hats approach to an open, foundational platform coupled with, you know, the great infrastructure you could get from Amazon. And, you know, that's a great sort of powerful combination that we can bring to each of our clients and, you know, maybe just to bring it back a little bit to that idea of Okay, so what's the rolling cloud packs in that? I mean, compact are the kind of software that we've built to enable enterprises to run their essential business processes right in the essential digital operations that they run everything from security to protecting their data or giving them powerful data tools to implement a I and, you know, to implement ai algorithms in the heart of their business or giving them powerful automation capabilities so they can digitize their operations and also make sure those things were going to run effectively. It's those kinds of capabilities that we're bringing in the form of cloud PACs. Think of that is that that substrate that runs a digital business that now could be brought through right running on AWS infrastructure. Good. It's integration that we've done >>right. So basically taking things that as a pre package module that we can just grab that module, drop it in and and start using it rather than having to build it ourselves from scratch. >>That's right. They make them leverage of those powerful capabilities and get focused on innovating the things that matter. Right? So the huge accelerant to getting business value. >>And it does sound a lot easier than trying to learn how to do the complex sort of deep learning and linear algorithms that they're involved in machine learning. I have looked into it a bit and trying to manage that sort of deep maths, and I think I'd much rather just just grab one off the shelf, plug it in and just use it. >>Yeah, It's also better than writing assembler code, which was some of my first programming experiences as well. So I think the software industry has moved on just a little bit since then. >>I think we have to say I do not miss the days of handwriting. Assemble at all, uh, sometimes for nostalgia reasons. But if we want to get things done, I think I'd much rather work in something a little higher level >>specific drinking. >>So thank you so much for my for my guest there. Mike Gill. Fix chief product officer for IBM Cloud PACs from IBM. This has been the cubes coverage off AWS reinvent 2020 and the a p m. Partner experience. I've been your host, Justin Warren. Make sure you come back and join us for more coverage later on

>> Reporter: From around the globe. It's theCUBE with digital coverage of AWS re:Invent 2020. Special coverage sponsored by AWS global partner network. >> Hello, and welcome to theCUBE virtual and our coverage of AWS re:Invent 2020 and our special coverage of APN partner experience. We are theCUBE virtual and I'm your host, Justin Warren. And today I'm joined by Mike Gilfix who is the Chief Product Officer for IBM Cloud Paks. Mike, welcome to theCUBE. >> Thank you. Thanks for having me. Now, Cloud Paks is a new thing from IBM. I'm not particularly familiar with it, but it's related to IBM's partnership with AWS. So maybe you could just start us off quickly by explaining what is Cloud Paks and what's your role as Chief Product Officer there? >> Well, Cloud Paks is sort of our next generation platform. What we've been doing is bringing the power of IBM software really across the board and bringing it to a hybrid cloud environment. So making it really easy for our customers to consume it wherever they want, however, they want to choose to do it with a consistent skillset and making it really easy to kind of get those things up and running and deliver value quickly. And this is part of IBM's hybrid approach. So what we've seen is organizations that can leverage the same skillset and, you know basically take those workloads make them run where they need to yields about a two and a half times ROI and Caltech sit at the center of that running on the OpenShift platform. So they get consistent security, skills and powerful software to run their business running everywhere. And we've been partnering with AWS because we want to make sure that those customers that have made that choice, can get access to those capabilities easy and as fast as possible. >> Right. And the Cloud Paks and Built On the Red Hat open. Now, let me get this right. It's the open hybrid cloud platform. So is that OpenShift? >> It is OpenShift, yes. I mean IBM is incredibly committed to open software and OpenShift does provide that common layer. And the reason that's important is you want consistent security. You want to avoid lock-in, right? That gives you a very powerful platform, (indistinct) if you will, they can truly run anywhere with any workload. And we've been working very closely with AWS to make sure that is a premiere first-class experience on AWS. >> Yes so the OpenShift on AWS is relatively new from IBM. So could you explain what is OpenShift on AWS and how does that differ from the OpenShift that people may be already familiar with? Well, the kernel, if you will, is the same it's the same sort of central open source software but in working closely with AWS we're now making those things available as simple services that you can quickly provision and run. And that makes it really easy for people to get started, but again sort of carrying forward that same sort of skill sets. So that's kind of a key way in which we see that you can gain that sort of consistency, you know, no matter where you're running that workload. And we've been investing in that integration working closely with them, Amazon. >> Yeah, and we all know Red Hat's commitment to open source software in the open ecosystems. Red hat is rightly famous for it. And I am old enough to remember when it was a brand new thing, particularly in enterprise to allow open source to come in and have anything to do with workloads. And now it's all the rage and people are running quite critical workloads on it. So what are you seeing in the adoption within the enterprise of open software? >> The adoption is massive. I think, well first let me describe what's driving it. I mean, people want to tap into innovation and the beauty of open source is you're kind of crowdsourcing if you will, this massive community of developers that are creating just an incredible amount of innovation at incredible speed. And it's a great way to ensure that you avoid vendor lock-in. So enterprises of all types are looking to open solutions as a way, both of innovating faster and getting protection. And that commitment, is something certainly Red Hat has tapped into. It's behind the great success of Red Hat. And it's something that frankly is permeating throughout IBM in that we're very committed to driving this sort of open approach. And that means that, you know, we need to ensure that people can get access to the innovation they need, run it where they want and ensure that they feel that they have choice. >> And the choice I think is a key part of it that isn't really coming through in some of the narrative. There's a lot of discussion about how you should actually pick, should you go cloud? I remember when it was either you should stay on-site or should you go to cloud? And we had a long discussion there. Hybrid cloud really does seem to have come of age where it's a realistic kind of compromise is probably the wrong word, but it's a trade off between doing all the one thing or all another. And for most enterprises, that doesn't actually seem to be the choice that's actually viable for them. So hybrid seems like it's actually just the practical approach. Would that be accurate? >> Well our studies have shown that if you look statistically at the set of workload that's moved to cloud, you know something like 20% of workloads have only moved to cloud meaning the other 80% is experiencing barriers to move. And some of those barriers is figuring out what to do with all this data that's sitting on-prem or you know, these applications that have years and years of intelligence baked into them that can not easily be ported. And so organizations are looking at the hybrid approaches because they give them more choice. It helps them deal with fragmentation. Meaning as I move more workload, I have consistent skillset. It helps me extend my existing investments and bring it into the cloud world. And all those things again are done with consistent security. That's really important, right? Organizations need to make sure they're protecting their assets, their data throughout, you know leveraging a consistent platform. So that's really the benefit of the hybrid approach. It essentially is going to enable these organizations to unlock more workload and gain the acceleration and the transformative effect of cloud. And that's why it's becoming a necessity, right? Because they just can't get that 80% to move yet. >> Yeah and I've long said that the cloud is a state of mind rather than a particular location. It's more about an operational model of how you do things. So hearing that we've only got 20% of workloads have moved to this new way of doing things does rather suggest that there's a lot more work to be done. What, for those organizations that are just looking to do this now or they've done a bit of it and they're looking for those next new workloads, where do you see customers struggling the most and where do you think that IBM can help them there? >> Well,(indistinct) where are they struggling the most? First I think skills. I mean, they have to figure out a new set of technologies to go and transition from this old world to the new and at the heart of that is lots of really critical debates. Like how do they modernize the way that they do software delivery for many enterprises, right? Embrace new ways of doing software delivery. How do they deal with the data issues that arise from where the data sits, their obligations for data protection, what happens if the data spans multiple different places but you have to provide high quality performance and security. These are all parts of issues that, you know, span different environments. And so they have to figure out how to manage those kinds of things and make it work in one place. I think the benefit of partnering, you know, with Amazon is, clearly there's a huge customer base that's interested in Amazon. I think the benefit of the IBM partnership is, you know, we can help to go and unlock some of those new workloads and find ways to get that cloud benefit and help to move them to the cloud faster again with that consistency of experience. And that's why I think it's a good match partnership where we're giving more customers choice. We're helping them to unlock innovation substantially faster. >> Right. And so for people who might want to just get started without it, how would they approach this? People might have some experience with AWS, it's almost difficult not to these days, but for those who aren't familiar with the Red Hat on AWS with OpenShift on AWS, how would they get started with you to explore what's possible? >> Well, one of the things that we're offering to our clients is a service that we refer to as IBM garage. It's, you know, an engagement model if you will, within IBM, where we work with our clients and we really help them to do co-creation so help to understand their business problem or, you know, the target state of where they want their IT to get to. And in working with them in co-creation, you know, we help them to affect that transition. Let's say that it's about delivering business applications faster. Let's say it's about modernizing the applications they have or offering new services, new business models, again all in the spirit of co-creation. And we found that to be really popular. It's a great way to get started. We've leveraged design thinking and approach. They can think about the customer experience and their outcome. If they're creating new business processes, new applications, and then really help them to uplift their skills and, you know, get ready to adopt cloud technology and everything that they do. >> It sounds like this is a lot of established workloads that people already have in their organizations. It's already there, it's generating real money. It's not those experimental workloads that we saw early on which was a, well let's try this. Cloud is a fabulous way where we can run some experiments. And if it doesn't work, we just turn it off again. These sound like a lot more workloads are kind of more important to the business. Is that be true? >> Yeah. I think that's true. Now I wouldn't say they're just existing workloads because I think there's lots of new business innovation that many of our, you know, clients want to go and launch. And so this gives them an opportunity to do that new innovation, but not forget the past meaning they can bring it forward and bring it forward into an integrated experience. I mean, that's what everyone demands of a true digital business, right? They expect that your experience is integrated, that it's responsive, that it's targeted and personalized. And the only way to do that is to allow for experimentation that integrates in with the, you know, standard business processes and things that you did before. And so you need to be able to connect those things together seamlessly. >> Right. So it sounds like it's a transition more than creating new thing completely from scratch. It's well, look, we've done a lot of innovation over the past decade or so in cloud, we know what works but we still have workloads that people clearly know and value. How do we put those things together and do it in such a way that we maintain the flexibility to be able to make new changes as we learn new things. >> Yeah, leverage what you've got play to your strengths. I mean that's how you create speed. If you have to reinvent the wheel every time it's going to be a slow roll. >> Yeah and that does seem like an area where an organization probably at this point should be looking to partner with other people who have done the hard yards. They've already figured this out. Well, as you say, why can't we make all of these obvious areas yourself when you're starting from scratch, when there's a wealth of experience out there and particularly this whole ecosystem that exists around the open software? In fact maybe you could tell us a little bit about the ecosystem opportunities that are there because Red Hat has been part of this for a very long time. AWS has a very broad ecosystem as we're all familiar with being here at re:Invent yet again. How does that ecosystem play into what's possible? >> Well, let me explain why I think IBM brings a different dimension to that trio, right? IBM brings deep industry expertise. I mean, we've long worked with all of our clients, our partners on solving some of their biggest business problems and being embedded in the thing that they do. So we have deep knowledge of their enterprise challenges, deep knowledge of their business processes. deep knowledge of their business processes. We are able to bring that industry know how mixed with, you know, Red Hat's approach to an open foundational platform, coupled with, you know, the great infrastructure you can get from Amazon and, you know, that's a great sort of powerful combination that we can bring to each of our clients. And, you know, maybe just to bring it back a little bit to that idea, okay so what's the role in Cloud Paks in that? I mean, Cloud Paks are the kind of software that we've built to enable enterprises to run their essential business processes, right? In the central digital operations that they run everything from security to protecting their data or giving them powerful data tools to implement AI and you know, to implement AI algorithms in the heart of their business or giving them powerful automation capabilities so they can digitize their operations. And also we make sure those things are going to run effectively. It's those kinds of capabilities that we're bringing in the form of Cloud Paks think of that as that substrate that runs a digital business that now can be brought through right? Running on AWS infrastructure through this integration that we've done. >> Right. So basically taking things as a pre-packaged module that we can just grab that module drop it in and start using it rather than having to build it ourselves from scratch. >> That's right. And they can leverage those powerful capabilities and get focused on innovating the things that matter, right? So the huge accelerant to getting business value. >> And it does sound a lot easier than trying to learn how to do the complex sort of deep learning and linear algorithms that they're involved in machine learning. I have looked into it a bit and trying to manage that sort of deep masses. I think I'd much rather just grab one off the shelf plug it in and just use it. >> Yeah. It's also better than writing assembler code which was some of my first programming experiences as well. So I think the software industry has moved on just a little bit since then. (chuckles) >> I think we have is that I do not miss the days of handwriting assembly at all. Sometimes for this (indistinct) reasons. But if we want to get things done, I think I'd much rather work in something a little higher level. (Mike laughing) So thank you very much for joining me. My guest Mike Gilfix there from IBM, sorry, from IBM cloud. And this has been, sorry, go ahead. We'll cut that. Can we cut and reedit this outro? >> Cameraman: Yeah, you guys can or you can just go ahead and just start over again. >> I'll just do, I'll just do the outro. Try it again. >> Cameraman: Yeah, sounds good. >> So thank you so much for my guests there Mike Gilfix, Chief Product Officer for IBM Cloud Paks from IBM. This has been theCUBES coverage of AWS re:Invent 2020 and the APN partner experience. I've been your host, Justin Warren, make sure you come back and join us for more coverage later on.

>>Live from Miami, Florida. It's the cube covering IBM's data and AI forum brought to you by IBM. >>Welcome back to Miami, everybody. This is the cube, the leader in live tech coverage. We're covering the IBM data and AI forum. Mike Gilfix is here. He's the vice president of digital business automation at IBM. Mike, good to see you again. Good to see you. So your question, what's the difference between a business and an? >>Digital business? Digital business is one that gets digital software scale. So as opposed to traditional business, you know, very manual, very rote. If you want to get software like scale, you need to digitize. >>Okay, that's important. So now, followup question. Uh, you here, I dunno. I think Benioff said every company is a software company or a SAS company. Um, does every company have to be a digital business else? They're toast. >>Uh, I think it's a competitive pressure. I think every business today is looking to get more and more leveraged to stay ahead of their competition. And they're looking to technology to do that. That's actually where we come in because we bring to them automation, technology, automation, technology. They can apply to their business operations that will help them to get that scale. Like you guys got some hard news. Let's get right into it. What do you announce? Sure. So we're announcing a new critical capability. It's part of our cloud pack for automation. It's IBM automation, digital workers. The idea is that you can leverage a digital workforce. You can manage them like people, they can work alongside your people and they can help to free up your people to be that much more productive. They can spend their time on creative things. They can get assistance where they need it all integrated as part of this digital workforce. >>I got a lot of questions, so, so what's a digital worker? Well, it kind of works just like a person does. It can do critical tasks that they need to do, like sift through documents to find out, you know, what to take action on, help with decision making processes, figure out when to act, how to prioritize work. And it can integrate into those people's workflow so they can offload, say, mundane tasks to even more complex tasks where it works alongside them, helps them be more productive. And it sounds a little bit like a software robot, is it? I mean, is it, it is a, it is a form of software robot. You know, the way that we've approached the problem though is we've really approached it from the human aspect. We've looked at the set of things where people spend their time, where they're doing things that they're really not good at. >>For example, we, many organizations actually probably think about even your own job. We spend tons of time sifting through emails, business documents that you're out to turn something to action. It's boring, it's tedious. We're frankly overwhelmed with it. We can use a digital worker to go through those documents, figure out then what to do and then take action on it. Simple example. Um, let's say someone's doing contract analysis. Think about all the time spent going through a contract to figure what's in it, the decision making process. Is it a valid contract? And then determining, you know, who should I get involved when there's a situation so you can bring the right to the right job. >>So is this a a pre-integrated package or do I have to sort of roll my own? How does it, how do I consume it? >>Uh, well that comes as part of our cloud pack, but it comes with a set of tools that you can adapt to your given job roles. So you can describe for example, what's my compliance officer do, what are the set of tasks they do in their day, for example, checking those contracts. And then you can use that to do automation and augmentation where it integrates into the person's workflow and you can manage them just like people. It'll tell you what work they did. And very importantly, we have an element of business controls so that you can trust sort of the work that gets turned over and it'll determine when you have to stage sort of intervention and get a human involved to complete some form of tasks. >>So it sounds like it still sounds a little bit like RPA, but maybe more focused and more specific to certain use cases or tasks. >>Well, if you really look at where RPA is making strides today, it's making strides in data entry and sort of automation of input and data, a lot of back office stuff. But what it doesn't do really well is for example, complex decision making. So consider that compliance officer checking whether something's compliant requires more than simple decision making. It's not excelling today in the area of dealing with unstructured data or figuring out how to integrate into workflows directly. And we've approached this problem from the perspective of the job role. Tell me about the person, not the point thing that I want to get involved. So it's something that can integrate with RPA. It'll extend RPA, but it will really allow you to create a digital worker as in a hybrid workforce management. >>Okay. That's starting to make sense now because you're right, RPA is basically take this, this mundane work process that's very well understood and automated. Sometimes I call it paving the cow path. Um, but, but the, the, to me, the future of RPA is being able to cross that chasm and going into these fuzzy areas that you're describing. Uh, bending into workflows, maybe allowing humans to come into the equation, maybe calling other automations that I can to act on my behalf. >>That's where I think we partner with RPA vendors. We can supply that brain, if you will, that manages the digital worker brain and we can seamlessly integrate it into business processes, many of which actually run on our technology. And so the marriage of those things is effectively really what we've heard clients want. But today struggle to achieve. >>It was interesting because it makes it so you're not trying to replicate RPA, there's not enough vendors out there doing that. You're trying to add value to that in other, I'm sure there are other areas that you can add value to. Um, and are you partnering specifically with RPA vendors? >>We do. We have close partnerships with RPA vendors. Um, you know, one that we've worked very closely with is automation anywhere, but you know, we interoperate and we work with, uh, all the T the the top. >>Okay. So, um, when you think about digital workers, what's the critical issue for customers in terms of enabling >>bullying them? Um, well first a few things. There's a series, there's just a set of trust. You know, if I'm going to turn over work to this digital worker, how do I know that? For example, you know, I don't care what it comes up with. It's not going to sell, uh, inappropriate goods to miners as an example cause it doesn't know, it hasn't been taught those things. So we put some business controls in place that you can specify in natural language so you understand exactly what your digital worker does and it knows then when to get a human involved. Kind of second component is, I think today people want those to be integrated to their workflow. They want to know that it gets you involved, the right person at the right time to take action. And we can integrate that seamlessly into workflow. So that way it's not an isolated thing that just runs as automation. It's truly a synergistic collaboration between both humans and the digital work. >>Great. So what is, what is the cloud pack for automation? We've been talking about the cloud pack for data. What does the cloud pack for automation? >>So it's a set of technologies that digitize what you do in a line of business. So all the technologies in it have a direct analogy to what people do in their workplace. It digitizes your workflow, meaning it coordinates the activities, it digitizes the business data and documents around it and all of the who can see it. Uh, what's the lifecycle? Uh, enables collaboration around those documents. It digitizes decision-making, uh, processing of unstructured data. So really if you think about going to someone who works in a line of business, say they work in supplier onboarding and you ask them what they do, they'll probably describe their day and those kinds of elements and we can digitize that, run it, manage it, and then give you visibility into the. >>How do you, how do you go from what's in the domain experts head to codifying it? Um, is there a, is that a methodology process? Is that services you have tooling to do that? Well, >>yeah. So one of the key ideas behind the technology is it's low code or model driven. So what the thing does is what you see, and that's really important because you can explain to a non technical user essentially what the system is doing so they can check it with you along the way. And we have this methodology that we call playbacks. And the idea is as you kind of elicit requirements from your business user, you put it in the technology at any given point, you can click play, step through your solution, your business user can kind of watch it even if it's incomplete and say, Oh yeah, that's what I had in mind. That isn't what I had in mind. So that's a very powerful technology for doing sort of interactive development between business and it. >>So it's an iterative process where you kind of record the user activity and then show it back, play it back to the user, say, Oh I close. But that's what make this alteration. >>And once you've digitized your operations on it, the automation play is you can integrate things like digital workers or we actually allow you to use the data from your operations to find ways to scale your workforce. Well >>IBM is obviously in addition to a technology company, you're world-class services organization. Um, one of the largest and in, in most capable SIS in the world, global scale with a lot of domain expertise by it, pick an industry, health care, manufacturing, financial services, name it, IBM's got domain expertise there are able to tap that deep domain expertise to drive your business. >>Sure. So first I'm in the software part of IBM. So I support a broad ecosystem, which is inclusive of partners, specific to IBM global services. We actually have an IBM automation practice that, uh, has expertise specifically in the area of how to apply automation technology to business operations. >>Okay. So I love that answer cause basically I'll translate, you said I'm an arms dealer, I'll sell software to my, my colleagues within IBM, but I love all my partners just as well a little more benign than. Yes. Nonetheless. But the point is your, your, your, your, your goal is to scale your software across, uh, many as clients as possible. If they want to use a competitor of IBM global services and that's fine with you, obviously they can yet. Yeah. And so what's that ecosystem look like? I mean, you've got it as a software company, you've got to develop that ecosystem. >>Yeah, we have a massive business partner ecosystem. Um, everything from larger size of course, as you mentioned, but we have lots of regional size. We have a lot of people that have created vertical solutions around our technology. In fact, that's one of the key ways in which we go to market where they've developed something that's specific say to accounts payable or loan processing or you know, health care claims and so on. And so that allows us to extend our reach to niches and it gives them an opportunity to add value add. >>Okay. So I'm going to ask you some thoughts on automation in general. We've seen a lot of text bending, uh, but we haven't seen a productivity boost as a result in the last several years except for this I guess first quarter of 2019, which is the latest data we saw a big uptick. And so a lot of people think we're, we're on the cusp of a productivity boom. Um, that obviously is your business. What are your thoughts? What's your point of view on all that? >>Well, so, uh, we think of ourselves as our mission in life is to bring digital scale to knowledge workers. And let me explain why that's so important. Um, this industry has been talking about digital transformation for a really long time and we've actually been quite successful in digitizing. We're not done, but we've been quite successful in digitizing a huge portion of our business. But the side effect of digitization is that we generated all of this work. You expect that digital business to serve twice as many customers or be that much more responsive and people can't keep up. And what it's done is it's fueled this growth of knowledge work where today we're not doing manual things the way that they were before they were digitized. But instead we're doing them in software. So how do we help people to keep pace? And that's the goal of automation technology. And there's this explosion of knowledge work. To some extent, organizations far and wide are figuring out, okay, how do I get productivity in this new era? That's where we come in. We can help them get that productivity. And we really are in the cusp of people using those techniques now to get that next level of productivity. >>So, and so I've been saying for a while that I feel like there's this huge wave coming in, in, in productivity as a result of things like automation. Um, people don't like to talk about it in the technology community because the sellers especially cause you know, but I think it clearly has to have an impact on jobs. Maybe people don't get fired, but you might hire less people. But that's not really the point I want to make and ask you about. It's the types of jobs that are going to become valuable. We'll shift to these higher value activities. If you're, you know, filling out a form that's going to be less valuable than some of these other more creative, more strategic types of things. What's your point of >>you on that? So, uh, first off, I don't think there's any human that can keep pace with the growth of knowledge work that's getting generated now. So they're going to need help. There's no lack of things to do. So that's kind of my, my, my first thought. I would say my, my second thought in that is, you know, what, if you could use your time differently, I would ask that question to anybody. If you could use your time differently, think about all the value you could go and create. But if you're spending time doing administrivia, is that really the best use of your time? It's clearly not. And so that's where this technology comes into play. The productivity gain is cause you're going to be able to do things that matter the most. Or unleash the creativity of your people. And my experience in working with organizations is exactly that. They leverage automation technology. Now they can do the missions they always wanted to do but never got to in their backlog. >>Yeah. So I guess that my, my take on that, I'd love, I'd love your thoughts. I mean take existing jobs and put a brick wall around them, those existing jobs or are going to change and I think he's going to have a, a negative, you're gonna have job loss, there's no question. And, but then the other jobs are going to be created. My rap on this, people who want to protect the, the past from the future is we basically have 0% unemployment right now. Even in an economic and dramatic economic downturn, we have one 10% unemployment. So if you're, if you're 90% of the people out there, you're going to be able to get a job. Now, nobody likes the economic downturn, but the point is to be competitive as a, as a nation, as a society, you've got to innovate. And automation is part of that innovation. >>Look, I think if you think about the jobs that people want to do, yeah, they're probably not the jobs that are going to be affected by this. And that's what I mean by the evolution. So people can now spend their time on those higher value things. People don't want to do those sets of tasks. Or if you really ask them, think about what they put on the resume, no one puts on their resume today, I'm a great data entry expert. They want to talk about their time with clients, relationship management, making a difference for the business. That's a potential. >>Yeah, but there was a time people would put that on their resume. Punch card, you know, operator. Right. So, right. So we're still, we're still thriving. We're still around. Thanks so much for coming to the queue. It was a great conversation. Thank you. Thanks for hosting me. Pleasure. All right, you're welcome. All right, keep it right there buddy. We'll be back to wrap the IBM data and AI forum from Miami. You're watching the cube. You're right back.

>> Narrator: Live from Las Vegas It's theCUBE covering IBM Think 2018. Brought to you by IBM. >> We're back at Mandalay Bay in Las Vegas. This is IBM Think 2018. This is day three of theCUBE's wall-to-wall coverage. My name is Dave Vellante, I'm here with Peter Burris. You're watching theCUBE, the leader in live tech coverage. Daniel Hernandez is here. He's the Vice President of IBM Analytics, a CUBE alum. It's great to see you again, Daniel >> Thanks >> Dave: Thanks for coming back on >> Happy to be here. >> Big tech show, consolidating a bunch of shows, you guys, you kind of used to have your own sort of analytics show but now you've got all the clients here. How do you like it? Compare and contrast. >> IBM Analytics loves to share so having all our clients in one place, I actually like it. We're going to work out some of the kinks a little bit but I think one show where you can have a conversation around Artificial Intelligence, data, analytics, power systems, is beneficial to all of us, actually. >> Well in many respects, the whole industry is munging together. Folks focus more on workloads as opposed to technology or even roles. So having an event like this where folks can talk about what they're trying to do, the workloads they're trying to create, the role that analytics, AI, et cetera is going to play in informing those workloads. Not a bad place to get that crosspollination. What do you think? >> Daniel: Totally. You talk to a client, there are so many problems. Problems are a combination of stuff that we have to offer and analytics stuff that our friends in Hybrid Integration have to offer. So for me, logistically, I could say oh, Mike Gilfix, business process automation. Go talk to him. And he's here. That's happened probably at least a dozen times so far in not even two days. >> Alright so I got to ask, your tagline. Making data ready for AI. What does that mean? >> We get excited about amazing tech. Artificial intelligence is amazing technology. I remember when Watson beat Jeopardy. Just being inspired by all the things that I thought it could do to solve problems that matter to me. And if you look over the last many years, virtual assistants, image recognition systems that solve pretty big problems like catching bad guys are inspirational pieces of work that were inspired a lot by what we did then. And in business, it's triggered a wave of artificial intelligence can help me solve business critical issues. And I will tell you that many clients simply aren't ready to get started. And because they're not ready, they're going to fail. And so our attitude about things are, through IBM Analytics, we're going to deliver the critical capabilities you need to be ready for AI. And if you don't have that, 100% of your projects will fail. >> But how do you get the business ready to think about data differently? You can do a lot to say, the technology you need to do this looks differently but you also need to get the organization to acculturate, appreciate that their business is going to run differently as a consequence of data and what you do with it. How do you get the business to start making adjustments? >> I think you just said the magic word, the business. Which is to say, at least all the conversations I have with my customers, they can't even tell that I'm from the analytics because I'm asking them about the problems. What do you try to do? How would you measure success? What are the critical issues that you're trying to solve? Are you trying to make money, save money, those kinds of things. And by focusing on it, we can advise them then based on that how we can help. So the data culture that you're describing I think it's a fact, like you become data aware and understand the power of it by doing. You do by starting with the problems, developing successes and then iterating. >> An approach to solving problems. >> Yeah >> So that's kind of a step zero to getting data ready for AI >> Right. But in no conversation that leads to success does it ever start with we're going to do AI or machine learning, what problem are we going to solve? It's always the other way around. And when we do that, our technology then is easily explainable. It's like okay, you want to build a system for better customer interactions in your call center. Well, what does that mean? You need data about how they have interacted with you, products they have interacted with, you might want predictions that anticipate what their needs are before they tell you. And so we can systematically address them through the capabilities we've got. >> Dave, if I could amplify one thing. It makes the technology easier when you put it in these constants I think that's a really crucial important point. >> It's super simple. All of us have had to have it, if we're in technology. Going the other way around, my stuff is cool. Here's why it's cool. What problems can you solve? Not helpful for most of our clients. >> I wonder if you could comment on this Daniel. I feel like we're, the last ten years about cloud mobile, social, big data. We seem to be entering an era now of sense, speak, act, optimize, see, learn. This sort of pervasive AI, if you will. How- is that a reasonable notion, that we're entering that era, and what do you see clients doing to take advantage of that? What's their mindset like when you talk to them? >> I think the evidence is there. You just got to look around the show and see what's possible, technically. The Watson team has been doing quite a bit of stuff around speech, around image. It's fascinating tech, stuff that feels magical to me. And I know how this stuff works and it still feels kind of fascinating. Now the question is how do you apply that to solve problems. I think it's only a matter of time where most companies are implementing artificial intelligence systems in business critical and core parts of their processes and they're going to get there by starting, by doing what they're already doing now with us, and that is what problem am I solving? What data do I need to get that done? How do I control and organize that information so I can exploit it? How can I exploit machine learning and deep learning and all these other technologies to then solve that problem. How do I measure success? How do I track that? And just systematically running these experiments. I think that crescendos to a critical mass. >> Let me ask you a question. Because you're a technologist and you said it's amazing, it's like magic even to you. Imagine non technologists, what `it's like to me. There's a black box component of AI, and maybe that's okay. I'm just wondering if that's, is that a headwind, are clients comfortable with that? If you have to describe how you really know it's a cat. I mean, I know a cat when I see it. And the machine can tell me it's a cat, or not a hot dog Silicon Valley reference. (Peter laughs) But to tell me actually how it works, to figure that out there's a black box component. Does that scare people? Or are they okay with that? >> You've probably given me too much credit. So I really can't explain how all that just works but what I can tell you is how certainly, I mean, lets take regulated industries like banks and insurance companies that are building machine learning models throughout their enterprise. They've got to explain to a regulator that they are offering considerations around anti discriminatory, basically they're not buying systems that cause them to do things that are against the law, effectively. So what are they doing? Well, they're using tools like ones from IBM to build these models to track the process of creating these models which includes what data they used, how that training was done, prove that the inputs and outputs are not anti-discriminatory and actually go through their own internal general counsel and regulators to get it done. So whether you can explain the model in this particular case doesn't matter. What they're trying to prove is that the effect is not violating the law, which the tool sets and the process around those tool sets allow you to get that done today. >> Well, let me build on that because one of the ways that it does work is that, as Ginni said yesterday, Ginni Rometty said yesterday that it's always going to be a machine human component to it. And so the way it typically works is a machine says I think this is a cat and a human validates it or not. The machine still doesn't really know if it's a cat but coming back to this point, one of the key things that we see anyway, and one of the advantages that IBM likely has, is today the folks running Operational Systems, the core of the business, trust their data sources. >> Do they? >> They trust their DB2 database, they trust their Oracle database, they trust the data that's in the applications. >> Dave: So it's the data that's in their Data Lake? >> I'm not saying they do but that's the key question. At what point in time, and I think the real important part of your question is, at what point in time do the hardcore people allow AI to provide a critical input that's going to significantly or potentially dramatically change the behavior of the core operational systems. That seems a really crucial point. What kind of feedback do you get from customers as you talk about turning AI from something that has an insight every now and then to becoming effectively, an element or essential to the operation of the business? >> One of the critical issues in getting especially machine learning models, integrated in business critical processes and workflows is getting those models running where that work is done. So if you look, I mean, when I was here last time I was talking about the, we were focused on portfolio simplification and bringing machine learning where the data was. We brought machine learning to private cloud, we brought it onto Gadook, we brought it on mainframe. I think it is a critical necessary ingredient that you need to deliver that outcome. Like, bring that technology where the data is. Otherwise it just won't work. Why? As soon as you move, you've got latency. As soon as you move, you've got data quality issues you're going to have contending. That's going to exacerbate whatever mistrust you might have. >> Or the stuff's not cheap to move. It's not cheap to ingest. >> Yeah. By the way, the Machine Learning on Z offering that we launched last year in March, April was one of our highest, most successful offerings last year. >> Let's talk about some of the offerings. I mean, at the end of the day you're in the business of selling stuff. You've talked about Machine Learning on Z X, whatever platform. Cloud Private, I know you've got perspectives on that. Db2 Event Store is something that you're obviously familiar with. SPSS is part of the portfolio. >> 50 year, the anniversary. >> Give us the update on some of these products. >> Making data ready for AI requires a design principled on simplicity. We launched in January three core offerings that help clients benefit from the capability that we deliver to capture data, to organize and control that data and analyze that data. So we delivered a Hybrid Data Management offering which gives you everything you need to collect data, it's anchored by Db2. We have the Unified Governance and Integration portfolio that gives you everything you need to organize and control that data as anchored by our information server product set. And we've got our Data Science and Businesses Analytics portfolio, which is anchored by our data science experience, SPSS and Cognos Analytics portfolio. So clients that want to mix and match those capabilities in support of artificial intelligence systems, or otherwise, can benefit from that easily. We just announced here a radical- an even radical step forward in simplification, which we thought that there already was. So if you want to move to the public cloud but can't, don't want to move to the public cloud for whatever reason and we think, by the way, public cloud for workload to like, you should try to run as much as you can there because the benefits of it. But if for whatever reason you can't, we need to deliver those benefits behind the firewall where those workloads are. So last year the Hybrid Integration team led by Denis Kennelly, introduced an IBM cloud private offering. It's basically application paths behind the firewall. It's like run on a Kubernetes environment. Your applications do buildouts, do migrations of existing workloads to it. What we did with IBM Cloud Private for data is have the data companion for that. IBM Cloud Private was a runaway success for us. You could imagine the data companion to that just being like, what application doesn't need data? It's peanut butter and jelly for us. >> Last question, oh you had another point? >> It's alright. I wanted to talk about Db2 and SPCC. >> Oh yes, let's go there, yeah. >> Db2 Event Store, I forget if anybody- It has 100x performance improvement on Ingest relative to the current state of the order. You say, why does that matter? If you do an analysis or analytics, machine learning, artificial intelligence, you're only as good as whatever data you have captured of your, whatever your reality is. Currently our databases don't allow you to capture everything you would want. So Db2 Event Store with that Ingest lets you capture more than you could ever imagine you would want. 250 billion events per year is basically what it's rated at. So we think that's a massive improvement in database technology and it happens to be based in open source, so the programming model is something that developers feel is familiar. SPSS is celebrating it's 50th year anniversary. It's the number one digital offering inside of IBM. It had 510,000 users trying it out last year. We just renovated the user experience and made it even more simple on stats. We're doing the same thing on Modeler and we're bringing SPSS and our data science experience together so that there's one tool chain for data science end to end in the Private Cloud. It's pretty phenomenal stuff. >> Okay great, appreciate you running down the portfolio for us. Last question. It's kind of a, get out of your telescope. When you talk to clients, when you think about technology from a technologist's perspective, how far can we take machine intelligence? Think 20 plus years, how far can we take it and how far should we take it? >> Can they ever really know what a cat is? (chuckles) >> I don't know what the answer to that question is, to be honest. >> Are people asking you that question, in the client base? >> No. >> Are they still figuring out, how do I apply it today? >> Surely they're not asking me, probably because I'm not the smartest guy in the room. They're probably asking some of the smarter guys-- >> Dave: Well, Elon Musk is talking about it. Stephen Hawking was talking about it. >> I think it's so hard to anticipate. I think where we are today is magical and I couldn't have anticipated it seven years ago, to be honest, so I can't imagine. >> It's really hard to predict, isn't it? >> Yeah. I've been wrong on three to four year horizons. I can't do 20 realistically. So I'm sorry to disappoint you. >> No, that's okay. Because it leads to my real last question which is what kinds of things can machines do that humans can't and you don't even have to answer this, but I just want to put it out there to the audience to think about how are they going to complement each other. How are they going to compete with each other? These are some of the big questions that I think society is asking. And IBM has some answers, but we're going to apply it here, here and here, you guys are clear about augmented intelligence, not replacing. But there are big questions that I think we want to get out there and have people ponder. I don't know if you have a comment. >> I do. I think there are non obvious things to human beings, relationships between data that's expressing some part of your reality that a machine through machine learning can see that we can't. Now, what does it mean? Do you take action on it? Is it simply an observation? Is it something that a human being can do? So I think that combination is something that companies can take advantage of today. Those non obvious relationships inside of your data, non obvious insights into your data is what machines can get done now. It's how machine learning is being used today. Is it going to be able to reason on what to do about it? Not yet, so you still need human beings in the middle too, especially when you deal with consequential decisions. >> Yeah but nonetheless, I think the impact on industry is going to be significant. Other questions we ask are retail stores going to be the exception versus the normal. Banks lose control of the payment systems. Will cyber be the future of warfare? Et cetera et cetera. These are really interesting questions that we try and cover on theCUBE and we appreciate you helping us explore those. Daniel, it's always great to see you. >> Thank you, Dave. Thank you, Peter. >> Alright keep it right there buddy, we'll be back with our next guest right after this short break. (electronic music)