(upbeat music) >> Hey everyone, welcome to this event: Build Your Cloud Center of Excellence. I'm your host, Lisa Martin, and I have two guests here with me today to talk about the hybrid cloud, the multi-cloud trends, and specifically the complexity. While we know these trends provide agility and flexibility for customers, they also bring in complexity. And this session is going to focus on exploring that with RBI and HitachiVantara. Please welcome my guests, Adithya Sastry the SVP of Digital Solutions at HitachiVantara and Werner Mayer, head of group core IT and head of group data at RBI International. Guys, welcome to the program. >> Thank you Lisa. Werner, nice to see you again. >> Great to see you both. >> And Werner, we're going to start with you. Talk about RBI. Tell the audience a little bit about what the business is and then we're going to get into your cloud transformation journey over the last couple of years. >> Yes, thank you. So Raiffeisen Bank International is international working banking groups. So our core markets are Central Eastern European, Central Eastern Europe and Austria. And we are serving around 50 million clients in this market. So we active in 13 markets. >> Got it. Talk to me, Werner about the cloud transformation journey that RBI has been on over the last couple of years and some of the complexities that you've experienced as you've launched it. >> Sure. Thank you for the question. So in 2020, we decided that we have to renew our IT strategy. And the aim of the strategy was to change the organization in a way that it can react and adapt fast to the future challenges. So one of the important pillars for us was that we are adapting fast also for new technologies. And this was core pillar in our strategy. So we're searching for technologies which are fit in to our HR transformation. And we found that the cloud and the public cloud environment fits to this venture. So we tested that. We are building up also the competent centers for that and also established the group cloud platform for that. Because our invoice to onboard our international group with the 13 units to this group cloud platform. So that means we have a lot to do to hardening the platforms in terms of security to put in. We have standard for that. We have to introduce large scale programs to train hundreds of engineers. We tested the approach, We convinced the top management and we implemented this, this program. So one of the highlights was, of course, also the the safeguarding of the Ukraine, let's say, banking environment. So we had to lift and shift the complete bank in three months. And it shows that let's say our platforms works. And let's say the approach is proven that we can scale it over the group. >> That's a big challenge. A lot of complexity especially with some of the global things going on. Adithya, these challenges are, are not unique to RBI. A lot of your customers are facing challenges with complexity around cloud management, cloud ops. What can you unpack was the real issue is here? >> Yeah, Lisa, absolutely. And you know, before I answer your question, I do want to, you know, just say a couple of things about Raiffeisen Bank. And you know, we've had the pleasure of working with them for about a year, a little bit more than a year now. And, and, and the way they approach the cloud transformation journey is - should be a template for a lot of the organizations in terms of the preparation in terms of understanding, you know. How other companies have done it and what are the pitfalls. What's worked, and really what's the recipe for their, you know, journey, right? Which is very unique because, you know, you look at you know, being present across 30 different countries within central and eastern Europe as Werner said. And the complexities of dealing with local regulations, GDPR and all these other issues that come with it, right? And not to mention the language variation from country to country. So, you know, phenomenal story there. The journey and the journey still goes, right Werner? It's not complete yet. But Lisa, to your question, you know. When we look at, you know, the complexities of this transformation, that most modern enterprises are going through. It's not very unique, right? What is unique for a Raiffeisen Bank is - has been the preparation. As you get into this journey of moving workloads to cloud, be it refactoring, modernizing, migrating, etc. One of the things that really is often overlooked is: "Are my applications and data workloads resilient on the cloud?" Meaning  how is the performance? Are they just running or are they performing with high availability to meet your customers goals? Is it scalable? And are my cost in line with what I projected when I moved prep. >> Because that's one of the areas we are seeing where you know, what enterprises projected from a cost savings to what they're realizing a year and a half into the journey is a pretty big delta, right? And, and, and a lot of it is dependent on are the cloud - are the applications and the workloads cloud, designed for the cloud? Or are they designed for on-prem which you just move to the cloud. >> So Werner, it sounds like what Adithya said is a compliment to, to you guys and the team at RBI in terms of this being a template for managing complexity. Give us, Werner, your perspective in terms of modern cloud ops. What's in? What's out? What is it that customers really need to be focusing on to be successful? >> Thanks for the compliment, Lisa. And I think this is a great relationship also in the journey. Topic is, is, is a - is a complex program where a lot of things have to fit together. But it was mentioning the resilience. The course, we call it finops, security operations and so on have to come together and have to work on spot. At the end, it's also, let's say, how we are able enabling our teams and how we are ramping out the skills of our teams to deal with these multidimensional, let's say environments. And this is something what we spend a lot of time in order to prepare, but also to bring up the people on a certain level that they can operate at. Because card guard handling is, is different than before. Because beforehand you have central operations team. They do everything for you. But in this world let's say we are also putting the responsibility of the run component of the absent to the - in the tribes and the application teams. And they have to do much more than before. On the other hand, we have first central rules. We have monitoring functions. We have support functions on that in order to best support them in their journey. So this is a hybrid between, let's say, what the teams have to do with the responsibility in the teams, but also with the central functions which are supporting them. And everything have to work together and goes hand in - right, to go hand-in-hand. >> Yeah. Yeah. And if, if I could just add Lisa really quick and and Werner hit the nail on the head, right? Because you cannot look at cloud operation the way we have traditionally looked at managed services. That's the key thing, right? You cannot, you know, traditional managed services you had L1, L2, L3 and then it goes into some sort of a vacuum and then all of a sudden somebody calls you at some point, right? >> Werner: Exactly. >> And it really has flipped, right? To, to Werner's point. And Werner hit that name on the head because you really have to understand. Bring an engineering led approach to make sure that the problems, you know, when you see an issue that you have some level of automation in terms of problem isolation. And then the problem is routed the right individual ie the application engineering team or the data engineering team for resolution in a rapid manner. Right? I think that the key - >> Yes. A very important point with that is said, yeah. So you cannot traditional transport let's say, the operation model what you have now into the cloud because this will not work, yeah. And finally at the end you will not benefit on the technology possibilities there. So super important point. My vision in the cloud and this is also something what we are working on is a sort of zero-ops environment, yeah? Because we're ultimately dealing with the automatization technologies and so on, you can that much - to much more compared to the traditional environment and the benefit of the cloud is: You can test it. You can give it feedback when it is not working, yeah? So it's a completely different operating model. What we try to establish in the cloud environment. >> So really what this seems like guys is is quite a delicate balance that you're solving for. Not the only delicate balance but Werner sticking with you. Talk to us about some of the challenges that you've had around cloud cost management in particular. Help us understand that. >> Thanks for the question. So in principle, we are doing very well on the cost side, surprisingly. And we also started the cloud journey that is said this is not the cost case. Because as I said before, let's say one of the pillars in the strategy strategy was the enablement of technology to the benefit of customer solutions to be adaptive, to be faster. But at the end it turned out that let's say with giving the responsibility of the operation to the dedicated team, they found they - they were working much closer to the cost, and let's say monitoring the cost, then we headed into traditional environments, yeah? I also saw some examples in the group where sort of gamification of the cost were going on. To say who can save more To say who can save more and make more much more out of that what you have in the cloud. And at the end we see that in minimum the cost are balance to the traditional environments in the data centers. But we also saw that let's say, the cost were brought down much more than before. So at the beginning we were relative conservative with the assumptions, yeah? But it turns out that we are really getting the benefit. The things are getting faster and also the costs are going down. And we see this in real cases. >> Yeah. And, and, and Lisa, if I could add something really quick, right? Because - There's been a mad rush to the cloud, right? Everybody kind of, it was, you know, the buzz the buzz was let's get to the cloud. We'll start to realize all these savings. And all of a sudden, everything kind of magically gets better, right? And what we have seen is also, you know, companies or customers or enterprises that have started this journey about 5, 6 years ago and are about, you know, a few years into it. What we are realizing is the cloud costs have increased significantly to what their projections were early on. And the way they're trying to address the cloud cost is by creating a FinOps organization that's looking at, you know, the cost of cloud from a structure standpoint and support as a reactive measure. Saying, "Hey if we move from Azure or one provider to another is there any benefit? If we move certain applications from the cloud back to on-prem, is there any benefit?" When in fact, one of the things that we have noticed really is: The problem needs to shift left to the engineering teams. Because if you are designing the applications and the systems the right way to begin with, then you can manage the data cost issues or the cost overruns, right? So you design for the cloud as opposed to designing and then looking at how do we optimize cloud. >> So Adithya, you talked about the RBI use case as really kind of a template but also some of the challenges with respect to hybrid and multi-cloud are kind of like a chicken and egg scenario. Talk to us kind of like overall about how Hitachi is really helping customers address these challenges and maximize the benefits to get the flexibility to get the agility so that they can deliver what their end user customers are expecting. >> Yeah, yeah. So, so one of the things we are doing, Lisa, when we work with customers, is really trying to understand, you know, look at their entire portfolio of applications, right? And, and look at what the intent of the applications is between customer facing, external customer, internal customer, high availability, production, etc., right? And then we go through a methodology called E3 which is envision, enable and execute. Which is really envision what the end stage should be regardless of what the environment is, right? And then we enable, which is really kind of go through a proof of value to move a few workloads, to modernize, rearchitect, replatform, etc. And look at the benefit of that application on its destination. If it's a cloud - if it's a cloud service provider or if it's another data center, whatever it may be, right? And finally, you know, once we've proven the value and the benefit and and say and kind of monetize the, you know realize the value of it from an agility, from a cost, from security and resilience, etc. Then we go through the execution, which was look we look at the entire portfolio, the entire landscape. And we go through a very disciplined manner working with our customers to roadmap it. And then we execute in a very deliberate manner where you can see value every 2-3 months. Because gone the days when you can do things as a science project that took 2-3 years, right? We, we - Everyone wants to see value, want to see - wants to see progress, and most importantly we want to see cost benefit and agility sooner than later. >> Those are incredibly important outcomes. You guys have done a great job explaining what you're doing together. This sounds like a great relationship. All right, so my last question to both of you is: "If I'm a customer and I'm planning a cloud transformation for my company, what are the two things you want me to remember and consider as I plan this? Werner, we'll start with you. >> I would pick up two things, yeah? The first one is: When you are organizing your company in HR way, then cloud is the HR technology for the HR transformation. Because HR teams needs HR technology. And the second important thing is, what I would say is: Cloud is a large scale and fast moving technology enabler to the company. So if your company is going forward to say: Technology is their enabler tool from a future business then cloud can support this journey. >> Excellent. I'm going to walk away with those. And Adithya, same question to you. I'm a, I'm a customer. I'm at an organization. I'm planning a cloud transformation. Top two things you want me to walk away with. >> Yeah. And I think Werner kind of actually touched on that in the second one, which is: it's not a tech, just an IT or a technology initiative. It is a business initiative, right? Because ultimately what you do from this cloud journey should drive, you know, should lead into business transformation or help your business grow top line or drive margin expansion, etc. So couple of things I would say, right? One is, you know, get Being and prioritize. Work with your business owners, with, you know with the cross-functional team not just the technology team. That's one. The second thing is: as the technology team or the IT team shepherds this journey, you know, keep everyone informed and engaged as you go through this journey. Because as you go through moving workloads modernizing workload, there is an impact to, you know receivables through omnichannel experiences the way customers interact and transact with you, right? And that comes with making making sure your businesses are aware your business stakeholders are aware. So in turn the end customers are aware. So you know, it's not a one and done from an engagement, it's a journey. And bring in the right experts. Talk to people who've done it, done this before, who have kind of stepped in all the pitfalls so you don't have to, right? That's the key. >> That's great advice. That's great advice for anything in life, I think. You talk about the collaboration, the importance of the business and the technology folks coming together. It really has to be - It's a delicate balance as we said before but it really has to be a holistic collaborative approach. Guys, thank you so much for joining me talking through what HitachiVantara and RBI are doing together. It sounds like you're well into this journey and it sounds like it's going quite well. We thank you so much for your insights and your perspectives. >> Thank you, Lisa. Werner, thank you again. >> Good stuff guys. For my guests, I'm Lisa Martin. Thank you so much for watching our event: Build Your Cloud Center of Excellence. (upbeat music)

(upbeat music) >> Hey everyone, welcome to this event: Build Your Cloud Center of Excellence. I'm your host, Lisa Martin, and I have two guests here with me today to talk about the hybrid cloud, the multi-cloud trends, and specifically the complexity. While we know these trends provide agility and flexibility for customers, they also bring in complexity. And this session is going to focus on exploring that with RBI and HitachiVantara. Please welcome my guests, Adithya Sastry the SVP of Digital Solutions at HitachiVantara and Werner Mayer, head of group core IT and head of group data at RBI International. Guys, welcome to the program. >> Thank you Lisa. Werner, nice to see you again. >> Great to see you both. >> And Werner, we're going to start with you. Talk about RBI. Tell the audience a little bit about what the business is and then we're going to get into your cloud transformation journey over the last couple of years. >> Yes, thank you. So Raiffeisen Bank International is international working banking groups. So our core markets are Central Eastern European, Central Eastern Europe and Austria. And we are serving around 50 million clients in this market. So we active in 13 markets. >> Got it. Talk to me, Werner about the cloud transformation journey that RBI has been on over the last couple of years and some of the complexities that you've experienced as you've launched it. >> Sure. Thank you for the question. So in 2020, we decided that we have to renew our IT strategy. And the aim of the strategy was to change the organization in a way that it can react and adapt fast to the future challenges. So one of the important pillars for us was that we are adapting fast also for new technologies. And this was core pillar in our strategy. So we're searching for technologies which are fit in to our HR transformation. And we found that the cloud and the public cloud environment fits to this venture. So we tested that. We are building up also the competent centers for that and also established the group cloud platform for that. Because our invoice to onboard our international group with the 13 units to this group cloud platform. So that means we have a lot to do to hardening the platforms in terms of security to put in. We have standard for that. We have to introduce large scale programs to train hundreds of engineers. We tested the approach, We convinced the top management and we implemented this, this program. So one of the highlights was, of course, also the the safeguarding of the Ukraine, let's say, banking environment. So we had to lift and shift the complete bank in three months. And it shows that let's say our platforms works. And let's say the approach is proven that we can scale it over the group. >> That's a big challenge. A lot of complexity especially with some of the global things going on. Adithya, these challenges are, are not unique to RBI. A lot of your customers are facing challenges with complexity around cloud management, cloud ops. What can you unpack was the real issue is here? >> Yeah, Lisa, absolutely. And you know, before I answer your question, I do want to, you know, just say a couple of things about Raiffeisen Bank. And you know, we've had the pleasure of working with them for about a year, a little bit more than a year now. And, and, and the way they approach the cloud transformation journey is - should be a template for a lot of the organizations in terms of the preparation in terms of understanding, you know. How other companies have done it and what are the pitfalls. What's worked, and really what's the recipe for their, you know, journey, right? Which is very unique because, you know, you look at you know, being present across 30 different countries within central and eastern Europe as Werner said. And the complexities of dealing with local regulations, GDPR and all these other issues that come with it, right? And not to mention the language variation from country to country. So, you know, phenomenal story there. The journey and the journey still goes, right Werner? It's not complete yet. But Lisa, to your question, you know. When we look at, you know, the complexities of this transformation, that most modern enterprises are going through. It's not very unique, right? What is unique for a Raiffeisen Bank is - has been the preparation. But as you get into this journey of moving workloads to cloud, be it refactoring, modernizing, migrating, etc. One of the things that really is often overlooked is: "Are my applications applications and data workloads resilient on, on the, on the cloud?" Meaning are they - How is the performance? Are they just running or are they performing with high availability to meet your customers goals? Is it scalable? And are my cost in line with what I projected when I moved prep, right? Because that's one of the areas we are seeing where you know, what enterprises projected from a cost savings to what they're realizing a year and a half into the journey is a pretty big delta, right? And, and, and a lot of it is dependent on are the cloud - are the applications and the workloads cloud, designed for the cloud? Or are they designed for on-prem which you just move to the cloud. >> So Werner, it sounds like what Adithya said is a compliment to, to you guys and the team at RBI in terms of this being a template for managing complexity. Give us, Werner, your perspective in terms of modern cloud ops. What's in? What's out? What is it that customers really need to be focusing on to be successful? >> Thanks for the compliment, Lisa. And I think this is a great relationship also in the journey. Topic is, is, is a - is a complex program where a lot of things have to fit together. But it was mentioning the resilience. The course, we call it finops, security operations and so on have to come together and have to work on spot. At the end, it's also, let's say, how we are able enabling our teams and how we are ramping out the skills of our teams to deal with these multidimensional, let's say environments. And this is something what we spend a lot of time in order to prepare, but also to bring up the people on a certain level that they can operate at. Because card guard handling is, is different than before. Because beforehand you have central operations team. They do everything for you. But in this world let's say we are also putting the responsibility of the run component of the absent to the - in the tribes and the application teams. And they have to do much more than before. On the other hand, we have first central rules. We have monitoring functions. We have support functions on that in order to best support them in their journey. So this is a hybrid between, let's say, what the teams have to do with the responsibility in the teams, but also with the central functions which are supporting them. And everything have to work together and goes hand in - right, to go hand-in-hand. >> Yeah. Yeah. And if, if I could just add Lisa really quick and and Werner hit the nail on the head, right? Because you cannot look at cloud operation the way we have traditionally looked at managed services. That's the key thing, right? You cannot, you know, traditional managed services you had L1, L2, L3 and then it goes into some sort of a vacuum and then all of a sudden somebody calls you at some point, right? >> Werner: Exactly. >> And it really has flipped, right? To, to Werner's point. And Werner hit that name on the head because you really have to understand. Bring an engineering led approach to make sure that the problems, you know, when you see an issue that you have some level of automation in terms of problem isolation. And then the problem is routed the right individual ie the application engineering team or the data engineering team for resolution in a rapid manner. Right? I think that the key - >> Yes. A very important point with that is said, yeah. So you cannot traditional transport let's say, the operation model what you have now into the cloud because this will not work, yeah. And finally at the end you will not benefit on the technology possibilities there. So super important point. My vision in the cloud and this is also something what we are working on is a sort of zero-ops environment, yeah? Because we're ultimately dealing with the automatization technologies and so on, you can that much - to much more compared to the traditional environment and the benefit of the cloud is: You can test it. You can give it feedback when it is not working, yeah? So it's a completely different operating model. What we try to establish in the cloud environment. >> So really what this seems like guys is is quite a delicate balance that you're solving for. Not the only delicate balance but Werner sticking with you. Talk to us about some of the challenges that you've had around cloud cost management in particular. Help us understand that. >> Thanks for the question. So in principle, we are doing very well on the cost side, surprisingly. And we also started the cloud journey that is said this is not the cost case. Because as I said before, let's say one of the pillars in the strategy strategy was the enablement of technology to the benefit of customer solutions to be adaptive, to be faster. But at the end it turned out that let's say with giving the responsibility of the operation to the dedicated team, they found they - they were working much closer to the cost, and let's say monitoring the cost, then we headed into traditional environments, yeah? I also saw some examples in the group where sort of gamification of the cost were going on. To say who can save more To say who can save more and make more much more out of that what you have in the cloud. And at the end we see that in minimum the cost are balance to the traditional environments in the data centers. But we also saw that let's say, the cost were brought down much more than before. So at the beginning we were relative conservative with the assumptions, yeah? But it turns out that we are really getting the benefit. The things are getting faster and also the costs are going down. And we see this in real cases. >> Yeah. And, and, and Lisa, if I could add something really quick, right? Because - You know, there's been a mad rush to the cloud, right? Everybody kind of, it was, you know, the buzz the buzz was let's get to the cloud. We'll start to realize all these savings. And all of a sudden, everything kind of magically gets better, right? And what we have seen is also, you know, companies or customers or enterprises that have started this journey about 5, 6 years ago and are about, you know, a few years into it. What we are realizing is the cloud costs have increased significantly to what their projections were early on. And the way they're trying to address the cloud cost is by creating a FinOps organization that's looking at, you know, the cost of cloud from a structure standpoint and support as a reactive measure. Saying, "Hey if we move from Azure or one provider to another is there any benefit? If we move certain applications from the cloud back to on-prem, is there any benefit?" When in fact, one of the things that we have noticed really is: The problem needs to shift left to the engineering teams. Because if you are designing the applications and the systems the right way to begin with, then you can manage the data cost issues or the cost overruns, right? So you design for the cloud as opposed to designing and then looking at how do we optimize cloud. >> So Adithya, you talked about the RBI use case as really kind of a template but also some of the challenges with respect to hybrid and multi-cloud are kind of like a chicken and egg scenario. Talk to us kind of like overall about how Hitachi is really helping customers address these challenges and maximize the benefits to get the flexibility to get the agility so that they can deliver what their end user customers are expecting. >> Yeah, yeah. So, so one of the things we are doing, Lisa, when we work with customers, is really trying to understand, you know, look at their entire portfolio of applications, right? And, and look at what the intent of the applications is between customer facing, external customer, internal customer, high availability, production, etc., right? And then we go through a methodology called E3 which is envision, enable and execute. Which is really envision what the end stage should be regardless of what the environment is, right? And then we enable, which is really kind of go through a proof of value to move a few workloads, to modernize, rearchitect, replatform, etc. And look at the benefit of that application on its destination. If it's a cloud - if it's a cloud service provider or if it's another data center, whatever it may be, right? And finally, you know, once we've proven the value and the benefit and and say and kind of monetize the, you know realize the value of it from an agility, from a cost, from security and resilience, etc. Then we go through the execution, which was look we look at the entire portfolio, the entire landscape. And we go through a very disciplined manner working with our customers to roadmap it. And then we execute in a very deliberate manner where you can see value every 2-3 months. Because gone the days when you can do things as a science project that took 2-3 years, right? We, we - Everyone wants to see value, want to see - wants to see progress, and most importantly we want to see cost benefit and agility sooner than later. >> Those are incredibly important outcomes. You guys have done a great job explaining what you're doing together. This sounds like a great relationship. All right, so my last question to both of you is: "If I'm a customer and I'm planning a cloud transformation for my company, what are the two things you want me to remember and consider as I plan this? Werner, we'll start with you. >> I would pick up two things, yeah? The first one is: When you are organizing your company in HR way, then cloud is the HR technology for the HR transformation. Because HR teams needs HR technology. And the second important thing is, what I would say is: Cloud is a large scale and fast moving technology enabler to the company. So if your company is going forward to say: Technology is their enabler tool from a future business then cloud can support this journey. >> Excellent. I'm going to walk away with those. And Adithya, same question to you. I'm a, I'm a customer. I'm at an organization. I'm planning a cloud transformation. Top two things you want me to walk away with. >> Yeah. And I think Werner kind of actually touched on that in the second one, which is: it's not a tech, just an IT or a technology initiative. It is a business initiative, right? Because ultimately what you do from this cloud journey should drive, you know, should lead into business transformation or help your business grow top line or drive margin expansion, etc. So couple of things I would say, right? One is, you know, get Being and prioritize. Work with your business owners, with, you know with the cross-functional team not just the technology team. That's one. The second thing is: as the technology team or the IT team shepherds this journey, you know, keep everyone informed and engaged as you go through this journey. Because as you go through moving workloads modernizing workload, there is an impact to, you know receivables through omnichannel experiences the way customers interact and transact with you, right? And that comes with making making sure your businesses are aware your business stakeholders are aware. So in turn the end customers are aware. So you know, it's not a one and done from an engagement, it's a journey. And bring in the right experts. Talk to people who've done it, done this before, who have kind of stepped in all the pitfalls so you don't have to, right? That's the key. >> That's great advice. That's great advice for anything in life, I think. You talk about the collaboration, the importance of the business and the technology folks coming together. It really has to be - It's a delicate balance as we said before but it really has to be a holistic collaborative approach. Guys, thank you so much for joining me talking through what HitachiVantara and RBI are doing together. It sounds like you're well into this journey and it sounds like it's going quite well. We thank you so much for your insights and your perspectives. >> Thank you, Lisa. Werner, thank you again. >> Good stuff guys. For my guests, I'm Lisa Martin. Thank you so much for watching our event: Build Your Cloud Center of Excellence. (upbeat music)

(upbeat music) >> Hey everyone, welcome to this event: Build Your Cloud Center of Excellence. I'm your host, Lisa Martin, and I have two guests here with me today to talk about the hybrid cloud, the multi-cloud trends, and specifically the complexity. While we know these trends provide agility and flexibility for customers, they also bring in complexity. And this session is going to focus on exploring that with RBI and HitachiVantara. Please welcome my guests, Adithya Sastry the SVP of Digital Solutions at HitachiVantara and Werner Mayer, head of group core IT and head of group data at RBI International. Guys, welcome to the program. >> Thank you Lisa. Werner, nice to see you again. >> Great to see you both. >> And Werner, we're going to start with you. Talk about RBI. Tell the audience a little bit about what the business is and then we're going to get into your cloud transformation journey over the last couple of years. >> Yes, thank you. So Raiffeisen Bank International is international working banking groups. So our core markets are Central Eastern European, Central Eastern Europe and Austria. And we are serving around 50 million clients in this market. So we active in 13 markets. >> Got it. Talk to me, Werner about the cloud transformation journey that RBI has been on over the last couple of years and some of the complexities that you've experienced as you've launched it. >> Sure. Thank you for the question. So in 2020, we decided that we have to renew our IT strategy. And the aim of the strategy was to change the organization in a way that it can react and adapt fast to the future challenges. So one of the important pillars for us was that we are adapting fast also for new technologies. And this was core pillar in our strategy. So we're searching for technologies which are fit in to our HR transformation. And we found that the cloud and the public cloud environment fits to this venture. So we tested that. We are building up also the competent centers for that and also established the group cloud platform for that. Because our invoice to onboard our international group with the 13 units to this group cloud platform. So that means we have a lot to do to hardening the platforms in terms of security to put in. We have standard for that. We have to introduce large scale programs to train hundreds of engineers. We tested the approach, We convinced the top management and we implemented this, this program. So one of the highlights was, of course, also the the safeguarding of the Ukraine, let's say, banking environment. So we had to lift and shift the complete bank in three months. And it shows that let's say our platforms works. And let's say the approach is proven that we can scale it over the group. >> That's a big challenge. A lot of complexity especially with some of the global things going on. Adithya, these challenges are, are not unique to RBI. A lot of your customers are facing challenges with complexity around cloud management, cloud ops. What can you unpack was the real issue is here? >> Yeah, Lisa, absolutely. And you know, before I answer your question, I do want to, you know, just say a couple of things about Raiffeisen Bank. And you know, we've had the pleasure of working with them for about a year, a little bit more than a year now. And, and, and the way they approach the cloud transformation journey is - should be a template for a lot of the organizations in terms of the preparation in terms of understanding, you know. How other companies have done it and what are the pitfalls. What's worked, and really what's the recipe for their, you know, journey, right? Which is very unique because, you know, you look at you know, being present across 30 different countries within central and eastern Europe as Werner said. And the complexities of dealing with local regulations, GDPR and all these other issues that come with it, right? And not to mention the language variation from country to country. So, you know, phenomenal story there. The journey and the journey still goes, right Werner? It's not complete yet. But Lisa, to your question, you know. When we look at, you know, the complexities of this transformation, that most modern enterprises are going through. It's not very unique, right? What is unique for a Raiffeisen Bank is - has been the preparation. But as you get into this journey of moving workloads to cloud, be it refactoring, modernizing, migrating, etc. One of the things that really is often overlooked is: "Are my applications applications and data workloads resilient on, on the, on the cloud?" Meaning are they - How is the performance? Are they just running or are they performing with high availability to meet your customers goals? Is it scalable? And are my cost in line with what I projected when I moved prep, right? Because that's one of the areas we are seeing where you know, what enterprises projected from a cost savings to what they're realizing a year and a half into the journey is a pretty big delta, right? And, and, and a lot of it is dependent on are the cloud - are the applications and the workloads cloud, designed for the cloud? Or are they designed for on-prem which you just move to the cloud. >> So Werner, it sounds like what Adithya said is a compliment to, to you guys and the team at RBI in terms of this being a template for managing complexity. Give us, Werner, your perspective in terms of modern cloud ops. What's in? What's out? What is it that customers really need to be focusing on to be successful? >> Thanks for the compliment, Lisa. And I think this is a great relationship also in the journey. Topic is, is, is a - is a complex program where a lot of things have to fit together. But it was mentioning the resilience. The course, we call it finops, security operations and so on have to come together and have to work on spot. At the end, it's also, let's say, how we are able enabling our teams and how we are ramping out the skills of our teams to deal with these multidimensional, let's say environments. And this is something what we spend a lot of time in order to prepare, but also to bring up the people on a certain level that they can operate at. Because card guard handling is, is different than before. Because beforehand you have central operations team. They do everything for you. But in this world let's say we are also putting the responsibility of the run component of the absent to the - in the tribes and the application teams. And they have to do much more than before. On the other hand, we have first central rules. We have monitoring functions. We have support functions on that in order to best support them in their journey. So this is a hybrid between, let's say, what the teams have to do with the responsibility in the teams, but also with the central functions which are supporting them. And everything have to work together and goes hand in - right, to go hand-in-hand. >> Yeah. Yeah. And if, if I could just add Lisa really quick and and Werner hit the nail on the head, right? Because you cannot look at cloud operation the way we have traditionally looked at managed services. That's the key thing, right? You cannot, you know, traditional managed services you had L1, L2, L3 and then it goes into some sort of a vacuum and then all of a sudden somebody calls you at some point, right? >> Werner: Exactly. >> And it really has flipped, right? To, to Werner's point. And Werner hit that name on the head because you really have to understand. Bring an engineering led approach to make sure that the problems, you know, when you see an issue that you have some level of automation in terms of problem isolation. And then the problem is routed the right individual ie the application engineering team or the data engineering team for resolution in a rapid manner. Right? I think that the key - >> Yes. A very important point with that is said, yeah. So you cannot traditional transport let's say, the operation model what you have now into the cloud because this will not work, yeah. And finally at the end you will not benefit on the technology possibilities there. So super important point. My vision in the cloud and this is also something what we are working on is a sort of zero-ops environment, yeah? Because we're ultimately dealing with the automatization technologies and so on, you can that much - to much more compared to the traditional environment and the benefit of the cloud is: You can test it. You can give it feedback when it is not working, yeah? So it's a completely different operating model. What we try to establish in the cloud environment. >> So really what this seems like guys is is quite a delicate balance that you're solving for. Not the only delicate balance but Werner sticking with you. Talk to us about some of the challenges that you've had around cloud cost management in particular. Help us understand that. >> Thanks for the question. So in principle, we are doing very well on the cost side, surprisingly. And we also started the cloud journey that is said this is not the cost case. Because as I said before, let's say one of the pillars in the strategy strategy was the enablement of technology to the benefit of customer solutions to be adaptive, to be faster. But at the end it turned out that let's say with giving the responsibility of the operation to the dedicated team, they found they - they were working much closer to the cost, and let's say monitoring the cost, then we headed into traditional environments, yeah? I also saw some examples in the group where sort of gamification of the cost were going on. To say who can save more To say who can save more and make more much more out of that what you have in the cloud. And at the end we see that in minimum the cost are balance to the traditional environments in the data centers. But we also saw that let's say, the cost were brought down much more than before. So at the beginning we were relative conservative with the assumptions, yeah? But it turns out that we are really getting the benefit. The things are getting faster and also the costs are going down. And we see this in real cases. >> Yeah. And, and, and Lisa, if I could add something really quick, right? Because - You know, there's been a mad rush to the cloud, right? Everybody kind of, it was, you know, the buzz the buzz was let's get to the cloud. We'll start to realize all these savings. And all of a sudden, everything kind of magically gets better, right? And what we have seen is also, you know, companies or customers or enterprises that have started this journey about 5, 6 years ago and are about, you know, a few years into it. What we are realizing is the cloud costs have increased significantly to what their projections were early on. And the way they're trying to address the cloud cost is by creating a FinOps organization that's looking at, you know, the cost of cloud from a structure standpoint and support as a reactive measure. Saying, "Hey if we move from Azure or one provider to another is there any benefit? If we move certain applications from the cloud back to on-prem, is there any benefit?" When in fact, one of the things that we have noticed really is: The problem needs to shift left to the engineering teams. Because if you are designing the applications and the systems the right way to begin with, then you can manage the data cost issues or the cost overruns, right? So you design for the cloud as opposed to designing and then looking at how do we optimize cloud. >> So Adithya, you talked about the RBI use case as really kind of a template but also some of the challenges with respect to hybrid and multi-cloud are kind of like a chicken and egg scenario. Talk to us kind of like overall about how Hitachi is really helping customers address these challenges and maximize the benefits to get the flexibility to get the agility so that they can deliver what their end user customers are expecting. >> Yeah, yeah. So, so one of the things we are doing, Lisa, when we work with customers, is really trying to understand, you know, look at their entire portfolio of applications, right? And, and look at what the intent of the applications is between customer facing, external customer, internal customer, high availability, production, etc., right? And then we go through a methodology called E3 which is envision, enable and execute. Which is really envision what the end stage should be regardless of what the environment is, right? And then we enable, which is really kind of go through a proof of value to move a few workloads, to modernize, rearchitect, replatform, etc. And look at the benefit of that application on its destination. If it's a cloud - if it's a cloud service provider or if it's another data center, whatever it may be, right? And finally, you know, once we've proven the value and the benefit and and say and kind of monetize the, you know realize the value of it from an agility, from a cost, from security and resilience, etc. Then we go through the execution, which was look we look at the entire portfolio, the entire landscape. And we go through a very disciplined manner working with our customers to roadmap it. And then we execute in a very deliberate manner where you can see value every 2-3 months. Because gone the days when you can do things as a science project that took 2-3 years, right? We, we - Everyone wants to see value, want to see - wants to see progress, and most importantly we want to see cost benefit and agility sooner than later. >> Those are incredibly important outcomes. You guys have done a great job explaining what you're doing together. This sounds like a great relationship. All right, so my last question to both of you is: "If I'm a customer and I'm planning a cloud transformation for my company, what are the two things you want me to remember and consider as I plan this? Werner, we'll start with you. >> I would pick up two things, yeah? The first one is: When you are organizing your company in HR way, then cloud is the HR technology for the HR transformation. Because HR teams needs HR technology. And the second important thing is, what I would say is: Cloud is a large scale and fast moving technology enabler to the company. So if your company is going forward to say: Technology is their enabler tool from a future business then cloud can support this journey. >> Excellent. I'm going to walk away with those. And Adithya, same question to you. I'm a, I'm a customer. I'm at an organization. I'm planning a cloud transformation. Top two things you want me to walk away with. >> Yeah. And I think Werner kind of actually touched on that in the second one, which is: it's not a tech, just an IT or a technology initiative. It is a business initiative, right? Because ultimately what you do from this cloud journey should drive, you know, should lead into business transformation or help your business grow top line or drive margin expansion, etc. So couple of things I would say, right? One is, you know, get Being and prioritize. Work with your business owners, with, you know with the cross-functional team not just the technology team. That's one. The second thing is: as the technology team or the IT team shepherds this journey, you know, keep everyone informed and engaged as you go through this journey. Because as you go through moving workloads modernizing workload, there is an impact to, you know receivables through omnichannel experiences the way customers interact and transact with you, right? And that comes with making making sure your businesses are aware your business stakeholders are aware. So in turn the end customers are aware. So you know, it's not a one and done from an engagement, it's a journey. And bring in the right experts. Talk to people who've done it, done this before, who have kind of stepped in all the pitfalls so you don't have to, right? That's the key. >> That's great advice. That's great advice for anything in life, I think. You talk about the collaboration, the importance of the business and the technology folks coming together. It really has to be - It's a delicate balance as we said before but it really has to be a holistic collaborative approach. Guys, thank you so much for joining me talking through what HitachiVantara and RBI are doing together. It sounds like you're well into this journey and it sounds like it's going quite well. We thank you so much for your insights and your perspectives. >> Thank you, Lisa. Werner, thank you again. >> Good stuff guys. For my guests, I'm Lisa Martin. Thank you so much for watching our event: Build Your Cloud Center of Excellence. (upbeat music)

>>Hey everyone, welcome to this Cube's special program series Women of the Cloud, brought to you by aws. I'm your host for the series, Lisa Martin. Very pleased to be joined by Patty Jordan, the VP of enabling processes and technology at Optimus. My next guest, Patty, welcome to the program. >>Hi Lisa. Thank you for having me. >>Tell me a little bit about yourself, a little bit about your role so the audience gets that understanding of exactly who you are. >>Sure thing. Hi, my name is Patty Jordan. As we mentioned, I am originally from Cameroon, Central Africa, but I was raised in the DC area. I'm called and what you call a bank brat. My father worked for an international organization, the the World Bank. Lived in, like I said, grew up in dc, moved to Austin, Texas about seven years ago. Been with Optum for the last nine years of my working career. And I've had multiple roles, but currently my role as is with the enabling technologies and processes, which means that I manage teams that support the platform of a lot of analytics products in Optum. >>Got it. All right. Bank Brett, that's a new one to me. I hadn't heard that. I love that you're a bank, Brit and proud of it. I can tell. Talk to me a little bit about your, the career path that you have navigated and what are some of your sort of tactical and also strategic recommendations for the audiences looking to grow their career in tech? >>So the interesting thing is, I did not start in tech. My background is as an economist. I have a bachelor's of economics from the women, from the College of Women, Mary. I also have a financial master's in public policy from American University. However, I did take some IT classes and as a kid I'm probably dating myself a little bit, but I programmed in dos, so I, I was always excited by it and I had internships as a programmer that helped me pay for my master's degree in when I graduated. I just felt like I was having fun and I was getting paid very well and I was able to pay off my graduate schools. So I just stayed with tech. >>Love that. But it sounds like you had that interest from when you were quite young and as a lot of us and end up in tech, we didn't start there originally. There's a lot of zigzaggy paths to get there. Sounds like you had that as well. What are some of your recommendations for people, either those that are in tech now or aren't who want to get into it and really expand and climb that ladder? >>So definitely, so one of the things to understand is tech could be many different things. Like one of the things could be programming, which I started doing and now dislike intensely. And then another thing could be like being in the business analyst in tech, getting the business requirements versus product management or even, you know, management. And what I would encourage people to do is really focus on what you feel happy doing, which for me is problem solving and collaborating and getting the right people together to solve very complex problems. And if you focus on that then you'll find your, your the role for you even in tech. >>I love that problem solving is such an important skill to be able to have and to cultivate regardless of the industry that you're in. But I'd love to know a little bit more about some of the successes that you've had helping organizations really navigate their cloud journeys, their migration to cloud as we've seen the last couple of years, a massive acceleration to the cloud that was really born outta the pandemic. Talk to me about some of the successes that you've been able to achieve. >>So the first, I guess most obvious thing is understanding the technology. What do you have at your disposal? What do you need for your team to succeed in the cloud or even OnPrem? But what I've learned most in the last four to five years with the projects that I work on, whether it was migrating from a host data center to one that we owned ourselves or migrating from that data center to AWS recently was you really need to get the business organization engaged. And that's not just getting the sponsorship and getting them this to write that check, but really helping them understand how this journey to the cloud is a combined journey between both organizations, right? And they will be able to be more successful as well with us going to the cloud with improved processing with revenue protection because we, there's more tools available with revenue expansion because now we can now expand faster address client needs faster. And you know, so there's various different aspects of going to cloud that are more than just we're using the coolest technology. >>You're a problem solver, has there. And one of the challenges with organizations and from a cloud migration standpoint that we often talk about is it's a cultural migration as well, which is really challenging to do for any type of organization regardless of industry. Do you have a favorite example where as a, as the problem solver, you came in and really helped the organization, the business side understand, be able to transform their cultural direction, understand why cloud migration can be such a facilitator of the business from the top line in a bottom line perspective. >>So from a bottom line perspective, I think the hardest thing for them to understand or what does not compute for them is you can't give them a set. This is what you're gonna cost in the cloud, right? Because the benefit of being in the cloud is being able to scale shrink, et cetera. So that's one hurdle that we're still fighting to be a hundred percent candid. But from a a top line perspective, what's what's been great is we've been able to ramp up more clients with the same, right? So we haven't had to go out and procure more servers, more storage, hire more staff because we're in the cloud and we've actually been able to scale our teams as well because we incorporated the DevOps functions and we do not need a team to manage a data center anymore. So that they absolutely understood, you know, savings ratified, but really just how do we get to market faster? How do we get to revenue faster and how do we get more revenue with the same pool of resources is something that they've really, really resonated with. >>Well, you're starting to speak their language so that to your point that resonates well, but there's so much productivity improvements, efficiencies to be gained by leveraging cloud computing that that really hit the bottom line of an organization that businesses, if you put it in the right way. And it sounds like as the problem solver you have, they understand the immense value and competitive advantage that cloud can bring to their organization and become sort of a ah, the blinders are off. I get it. >>Exactly. Exactly. You're just not trying to, to play with the latest toys, you are actually solving a business problem even before it happens. >>And that's the key solving business problems before they happen. Being able to predict and forecast is huge for businesses, especially as we've seen the last couple of years. Everybody racing to digital, to to pivot, to survive Now to be competitive. If they don't do that and embrace that emerging technology suite, there's a competitor that's right back here that if they're more culturally willing and able to, to be more agile, they're gonna take the place of a competing organization. So yeah, so it absolutely is a huge differentiator for organizations. And it sounds like you've had some great successes there in helping organizations really navigate the challenges, the cultural challenges, but the benefits of cloud computing. Yes. I do wanna talk to you a little bit about in your expertise, diversity is something that is talked about in every industry. We talk about it in tech all the time, there's still challenges there. What are, what's, what are your thoughts on diversity? What are you seeing and what are some of those challenges that are still sitting on the table? >>So I guess the first thing I would say is there's multiple facets to diversity, right? The first one we always lean to is gender and race, but there's also diversity of thought. And being in the healthcare industry is very important for us to have a diversity of thought and experiences so that we can target a lot of these health equity issues that are, you know, that, that are ongoing. So that's one thing that we've, we've been trying to do is making sure that I don't just have people that think like me on the team. And typically that also means not having people that look like me. So making sure that we have the right pipelines to hire for partnering with our, with some of our vendors. AWS for example, is a good one where they had avenues and they had non-profits that they worked with and they connected us with some of our staff augmentation people also did the same thing, really just expanding the scope of where we're looking for talent and, and that helps also bring that diversity of thought and the diversity of gender race into the, into the full >>It is. And it and, and there's also, there's so much data if we follow the data and of course in tech we're all about data. Every company these days, regardless of industry needs to be a data company. If we follow the data, we can see that organizations with, for example, females within the C-suite are far more profitable than those organizations that don't have that even that element of diversity. So the data is demonstrating there's tremendous business value, tremendous competitive advantage, faster time to market, more products and services that can be delivered if there is thought diversity among the entire organization, not just the C-suite. >>Exactly. And and since we have an impact on what is being delivered as an engineering organization, we also need that in engineering, right? One of the things that's very keen right now is machine language and ai. If we don't have the right models for example, then we either introduced bias or perpetuate by it. So we definitely need people on our teams as well that understand how these technologies work, how we can leverage 'em on our data sets so that we could run counter to this bias >>And countering that bias is incredibly important. Machine learning ai, so driven by data, the volumes of data, but the data needs to be as clean and and non-biased as possible. And that's a big challenge for organizations to undertake. Is there advice that you have for those folks watching who might be, I, I don't see me in this organization, I don't feel represented. How can I change that? >>Well, one would be to speak up, right? Even if you don't see you apply for the job, right? And one of the things that we're trying to address even in the DEI space is making sure that our job descriptions are not introducing any biases so that people will eliminate themselves immediately, right? But really just if you have the skill set and you feel like you can ramp up to the talent, then just apply for the job. Talk to somebody. You do have a network whether you realize it or not. So leverage that network. But really like there's this expression that my kid taught me saying, you miss a hundred percent of the shots you don't take, right? So if you don't try, you're not gonna make it by default. If you do try, there's a chance to make it right. At the very least, you build a connection with someone who can potentially help you down the line. >>That is one of my absolute favorite sayings. You miss a hundred percent of the shots that you don't take. So encouraging people to raise their hand there, there are stats, data, speaking of data we've been talking about that, that demonstrate that women are far less likely to apply for jobs like on LinkedIn for example, unless they need 100% of the job requirements, which we all know are quite stringent and not necessary in a lot of cases. So I love your advice of just try raise your hand, ask the question. All the can say is no. And at the end of the day, what is that? It's a word but can also be directional and and really guiding for people on their journey to wherever that, if it's an engineering, cloud, engineering, DevOps, whatever happen that happens to be, raise your hand the question. And to your point, you have a network, it is there, open that up. There's so much potential for people that just raise, I think that's to raise their hand and ask the question. >>And the corollary to that though is I would also encourage people who are in leader leadership roles to be strong allies, right? Like we need to be aware of what biases we might be introducing or candidates that we might be leaving on the table because we're being too stringent because we're not expanding our, our our search, right? So definitely that's something that I've started doing about five, six years old shortly after I moved to Austin, which I kind of beat myself up about not having done before, is really contributing to that community, helping out, being a mentor, being a coach, being a guide. Sometimes it's just reviewing somebody's resume. Other times it's talking to 'em about a role that I have and helping them map their current state to that role. But really just being an ally to everyone and anyone who wants to come into this space. >>I love that. I, and I have a feeling, Patty, that you're a great mentor and ally for those in your organization across organizations and those out there that may not know yet. Patty can be an ally for me. I'd love to get your take in our final minutes on a couple things. One, the, what's next in cloud from your perspective, the things that you've seen, what you've been able to achieve, and how do you see your role evolving in the industry at Optum? >>So what's next in cloud, and we've talked about that a lot, is data. How do we manage all this data? How do we catalog this data, how to reuse this data, how to reshift this data? We have data in various different environments. We're a multi-cloud company. So how do we make sure that we don't have the same data everywhere? Or even if we do, how do we reconcile that? So data, data, data, right? And from data, get to information so that we can monetize it and we can share it. So that's the, that's for me is really next step. I mean we, we know the applications that we can build, we know the analytics that we can build, but if we don't have the right data, we're limiting ourselves. So that's definitely one aspect that I know that we wanna drive. And as far as my role, I was fortunate enough to be provided with the leadership of development of a platform for analytics, which yes, involves data. >>So I'm very excited about this, right? Cuz that's, that's next level for me. I've been typically in roles that protect revenue in the DevOps and operations role. And now I'm in a revenue generating role and it has a shift in mindset. But I, I really appreciate it and I'm really taking everything I've learned up to now as a DevOps team. I knew when the bad things came. So now I'm trying to prevent, prevent my team from pushing bad things down the pipe, right? So I'm just really excited about what's, what's, what's to come because there's so many opportunities for improving the products that we build. And I'm so excited to be part of this platform. >>There are the, the horizon of opportunities is really endless, which is exciting. And to your point about data, like I mentioned, for every company, whether it's your grocery store, a retailer, the postal service has to become a data driven company. Cuz as consumers we expect that we bring that into our business lives and we expect to be able to transact in business as easily as we do on the consumer side. And that all requires organizations to not just have access to data, but to be able to build the right data infrastructure, toing insights to act on that, to feed the AI and ML models so that products services can get better, more personalized and meet the demands of the ever demanding consumer, which I know I, one of them. I wanna ask you one more final question and that is, what do you think some of the biggest challenges have been with, with respect to tech innovation in the workforce over the past five years? What are some of those things that, that you've seen that you think we're on the right track moving forward to eliminate some of these? >>That is a good question. I think one of the biggest challenges for me has been not to remain in the status quo, right? Like not to do something because it's what we've been doing, but being in the cloud allows us with so many opportunities where we can fail fast. That let's give it a shot, let's do a quick sprint, let's figure out whether it is a possibility or not. Eliminate it if it's not, and then keep moving, right? Like we don't have the same development methodology before that we had to do three months, five months, six months. You can iterate in two week chunks, get it done, confirm your, your statement or not, or negate it, but at the very least have an answer, right? So that for me is the biggest challenge. We're aware of the thinking we're just not doing. So it'd be very exciting when we, when we pivot from that and really start innovating because we have the time >>Innovating because we have the time, as I mentioned, you know, with the demand of consumers, whether it's consumer in, in on the personal side, business side, those demands are there. But the, the exciting thing is to your point, the innovations are there. The capabilities are there, the data is there. We have a lot of what we need to be able to take advantage of that. So it's gonna be exciting to see what happens over the next few years. Patty, it's been such a pleasure having you on the cube today. Thank you so much for joining. You are clearly a, a leader in terms of women in the cloud. We appreciate what you're doing, your insights, your recommendations, and your insights as to what you see in the future. You've been a great guest. Thank you so much for joining me today. >>Thank you for having me Lisa. >>My pleasure For Patty Jordan, I'm Lisa Martin. You're watching The Cubes coverage of Women of the Cloud, brought to you by aws, a special program series. We thank you so much for watching. Take care.

>>Good afternoon, brilliant humans, and welcome back to the Cube. We're live in Detroit, Michigan at Cub Con, and I'm joined by John Furrier. John three exciting days buzzing. How you doing? >>That's great. I mean, we're coming down to the third day. We're keeping the energy going, but this segment's gonna be awesome. The CD foundation's doing amazing work. Developers are gonna be running businesses and workflows are changing. Productivity's the top conversation, and you're gonna start to see a coalescing of the communities who are continuous delivery, and it's gonna be awesome. >>And, and our next guess is an outstanding person to talk about this. We are joined by Stephen Chin, the chair of the CD Foundation. Steven, thanks so much for being here. >>No, no, my pleasure. I mean, this has been an amazing week quote that CubeCon with all of the announcements, all of the people who came out here to Detroit and, you know, fantastic. Like just walking around, you bump into all the right people here. Plus we held a CD summit zero day events, and had a lot of really exciting announcements this week. >>Gotta love the shirt. I gotta say, it's one of my favorites. Love the logos. Love the love the branding. That project got traction. What's the news in the CD foundation? I tried to sneak in the back. I got a little laid into your co-located event. It was packed. Everyone's engaged. It was really looked, look really cool. Give us the update. >>What's the news? Yeah, I know. So we, we had a really, really powerful event. All the key practitioners, the open source leads and folks were there. And one of, one of the things which I think we've done a really good job in the past six months with the CD foundation is getting back to the roots and focusing on technical innovation, right? This is what drives foundations, having strong projects, having people who are building innovation, and also bringing in a new innovation. So one of the projects which we added to the CD foundation this week is called Persia. So it's a, it's a decentralized package repository for getting open source libraries. And it solves a lot of the problems which you get when you have centralized infrastructure. You don't have the right security certificates, you don't have the right verification libraries. And these, these are all things which large companies provision and build out inside of their infrastructure. But the open source communities don't have the benefit of the same sort of really, really strong architecture. A lot of, a lot of the systems we depend upon. It's >>A good point, yeah. >>Yeah. I mean, if you think about the systems that developers depend upon, we depend upon, you know, npm, ruby Gems, Mayn Central, and these systems been around for a while. Like they serve the community well, right? They're, they're well supported by the companies and it's, it's, it's really a great contribution that they give us. But every time there's an outage or there's a security issue, guess, guess how many security issues that our, our research team found at npm? Just ballpark. >>74. >>So there're >>It's gotta be thousands. I mean, it's gotta be a lot of tons >>Of Yeah, >>They, they're currently up to 60,000 >>Whoa. >>Vulnerable, malicious packages in NPM and >>Oh my gosh. So that's a super, that's a jar number even. I know it was gonna be huge, but Holy mo. >>Yeah. So that's a software supply chain in actually right there. So that's, that's open source. Everything's out there. What's, how do, how does, how do you guys fix that? >>Yeah, so per peria kind of shifts the whole model. So when, when you think about a system that can be sustained, it has to be something which, which is not just one company. It has to be a, a, a set of companies, be vendor neutral and be decentralized. So that's why we donated it to the Continuous Delivery Foundation. So that can be that governance body, which, which makes sure it's not a single company, it is to use modern technologies. So you, you, you just need something which is immutable, so it can't be changed. So you can rely on it. It has to have a strong transaction ledger so you can see all of the history of it. You can build up your software, build materials off of it, and it, it has to have a strong peer-to-peer architecture, so it can be sustained long term. >>Steven, you mentioned something I want to just get back to. You mentioned outages and disruption. I, you didn't, you didn't say just the outages, but this whole disruption angle is interesting if something happens. Talk about the impact of the developer. They stalled, inefficiencies create basically disruption. >>No, I mean, if, if, so, so if you think about most DevOps teams in big companies, they support hundreds or thousands of teams and an hour of outage. All those developers, they, they can't program, they can't work. And that's, that's a huge loss of productivity for the company. Now, if you, if you take that up a level when MPM goes down for an hour, how many millions of man hours are wasted by not being able to get your builds working by not being able to get your codes to compile. Like it's, it's >>Like, yeah, I mean, it's almost hard to fathom. I mean, everyone's, It's stopped. Exactly. It's literally like having the plug pulled >>Exactly on whenever you're working on, That's, that's the fundamental problem we're trying to solve. Is it, it needs to be on a, like a well supported, well architected peer to peer network with some strong backing from big companies. So the company is working on Persia, include J Frog, which who I work for, Docker, Oracle. We have Deploy hub, Huawei, a whole bunch of other folks who are also helping out. And when you look at all of those folks, they all have different interests, but it's designed in a way where no single party has control over the network. So really it's, it's a system system. You, you're not relying upon one company or one logo. You're relying upon a well-architected open source implementation that everyone can rely >>On. That's shared software, but it's kind of a fault tolerant feature too. It's like, okay, if something happens here, you have a distributed piece of it, decentralized, you're not gonna go down. You can remediate. All right, so where's this go next? I mean, cuz we've been talking about the role of developer. This needs to be a modern, I won't say modern upgrade, but like a modern workflow or value chain. What's your vision? How do you see that? Cuz you're the center of the CD foundation coming together. People are gonna be coalescing multiple groups. Yeah. >>What's the, No, I think this is a good point. So there, there's a, a lot of different continuous delivery, continuous integration technologies. We're actually, from a Linux Foundation standpoint, we're coalescing all the continued delivery events into one big conference >>Next. You just made an announcement about this earlier this week. Tell us about CD events. What's going on, what's in, what's in the cooker? >>Yeah, and I think one of the big announcements we had was the 0.1 release of CD events. And CD events allows you to take all these systems and connect them in an event scalable, event oriented architecture. The first integration is between Tecton and Capin. So now you can get CD events flowing cleanly between your, your continuous delivery and your observability. And this extends through your entire DevOps pipeline. We all, we all need a standards based framework Yep. For how we get all the disparate continuous integration, continuous delivery, observability systems to, to work together. That's also high performance. It scales with our needs and it, it kind of gives you a future architecture to build on top of. So a lot of the companies I was talking with at the CD summit Yeah. They were very excited about not only using this with the projects we announced, but using this internally as an architecture to build their own DevOps pipelines on. >>I bet that feels good to hear. >>Yeah, absolutely. Yeah. >>Yeah. You mentioned Teton, they just graduated. I saw how many projects have graduated? >>So we have two graduated projects right now. We have Jenkins, which is the first graduated project. Now Tecton is also graduated. And I think this shows that for Tecton it was, it was time, the very mature project, great support, getting a lot of users and having them join the set of graduated projects. And the continuous delivery foundation is a really strong portfolio. And we have a bunch of other projects which also are on their way towards graduation. >>Feels like a moment of social proof I bet. >>For you all. Yeah, yeah. Yeah. No, it's really good. Yeah. >>How long has the CD Foundation been around? >>The CD foundation has been around for, i, I won't wanna say the exact number of years, a few years now. >>Okay. >>But I, I think that it, it was formed because what we wanted is we wanted a foundation which was purpose built. So CNCF is a great foundation. It has a very large umbrella of projects and it takes kind of that big umbrella approach where a lot of different efforts are joining it, a lot of things are happening and you can get good traction, but it produces its own bottlenecks in process. Having a foundation which is just about continuous delivery caters to more of a DevOps, professional DevOps audience. I think this, this gives a good platform for best practices. We're working on a new CDF best practices Yeah. Guide. We're working when use cases with all the member companies. And it, it gives that thought leadership platform for continuous delivery, which you need to be an expert in that area >>And the best practices too. And to identify the issues. Because at the end of the day, with the big thing that's coming out of this is velocity and more developers coming on board. I mean, this is the big thing. More people doing more. Yeah. Well yeah, I mean you take this open source continuous thunder away, you have more developers coming in, they be more productive and then people are gonna even either on the DevOps side or on the straight AP upside. And this is gonna be a huge issue. And the other thing that comes out that I wanna get your thoughts on is the supply chain issue you talked about is hot verifications and certifications of code is such big issue. Can you share your thoughts on that? Because Yeah, this is become, I won't say a business model for some companies, but it's also becoming critical for security that codes verified. >>Yeah. Okay. So I, I think one of, one of the things which we're specifically doing with the Peria project, which is unique, is rather than distributing, for example, libraries that you developed on your laptop and compiled there, or maybe they were built on, you know, a runner somewhere like Travis CI or GitHub actions, all the libraries being distributed on Persia are built by the authorized nodes in the network. And then they're, they're verified across all of the authorized nodes. So you nice, you have a, a gar, the basic guarantee we're giving you is when you download something from the Peria network, you'll get exactly the same binary as if you built it yourself from source. >>So there's a lot of trust >>And, and transparency. Yeah, exactly. And if you remember back to like kind of the seminal project, which kicked off this whole supply chain security like, like whirlwind it was SolarWinds. Yeah. Yeah. And the exact problem they hit was the build ran, it produced a result, they modified the code of the bill of the resulting binary and then they signed it. So if you built with the same source and then you went through that same process a second time, you would've gotten a different result, which was a malicious pre right. Yeah. And it's very hard to risk take, to take a binary file Yep. And determine if there's malicious code in it. Cuz it's not like source code. You can't inspect it, you can't do a code audit. It's totally different. So I think we're solving a key part of this with Persia, where you're freeing open source projects from the possibility of having their binaries, their packages, their end reduces, tampered with. And also upstream from this, you do want to have verification of prs, people doing code reviews, making sure that they're looking at the source code. And I think there's a lot of good efforts going on in the open source security foundation. So I'm also on the governing board of Open ssf >>To Do you sleep? You have three jobs you've said on camera? No, I can't even imagine. Yeah. Didn't >>You just spin that out from this open source security? Is that the new one they >>Spun out? Yeah, So the Open Source Security foundation is one of the new Linux Foundation projects. They, they have been around for a couple years, but they did a big reboot last year around this time. And I think what they really did a good job of now is bringing all the industry players to the table, having dialogue with government agencies, figuring out like, what do we need to do to support open source projects? Is it more investment in memory, safe languages? Do we need to have more investment in, in code audits or like security reviews of opensource projects. Lot of things. And all of those things require money investments. And that's what all the companies, including Jay Frogger doing to advance open source supply chain security. I >>Mean, it's, it's really kind of interesting to watch some different demographics of the developers and the vendors and the customers. On one hand, if you're a hardware person company, you have, you talk zero trust your software, your top trust, so your trusted code, and you got zero trust. It's interesting, depending on where you're coming from, they're all trying to achieve the same thing. It means zero trust. Makes sense. But then also I got code, I I want trust. Trust and verified. So security is in everything now. So code. So how do you see that traversing over? Is it just semantics or what's your view on that? >>The, the right way of looking at security is from the standpoint of the hacker, because they're always looking for >>Well said, very well said, New >>Loop, hope, new loopholes, new exploits. And they're, they're very, very smart people. And I think when you, when you look some >>Of the smartest >>Yeah, yeah, yeah. I, I, I work with, well former hackers now, security researchers, >>They converted, they're >>Recruited. But when you look at them, there's like two main classes of like, like types of exploits. So some, some attacker groups. What they're looking for is they're looking for pulse zero days, CVEs, like existing vulnerabilities that they can exploit to break into systems. But there's an increasing number of attackers who are now on the opposite end of the spectrum. And what they're doing is they're creating their own exploits. So, oh, they're for example, putting malicious code into open source projects. Little >>Trojan horse status. Yeah. >>They're they're getting their little Trojan horses in. Yeah. Or they're finding supply chain attacks by maybe uploading a malicious library to NPM or to pii. And by creating these attacks, especially ones that start at the top of the supply chain, you have such a large reach. >>I was just gonna say, it could be a whole, almost gives me chills as we're talking about it, the systemic, So this is this >>Gnarly nation state attackers, like people who wanted serious >>Damages. Engineered hack just said they're high, highly funded. Highly skilled. Exactly. Highly agile, highly focused. >>Yes. >>Teams, team. Not in the teams. >>Yeah. And so, so one, one example of this, which actually netted quite a lot of money for the, for the hacker who exposed it was, you guys probably heard about this, but it was a, an attack where they uploaded a malicious library to npm with the same exact namespace as a corporate library and clever, >>Creepy. >>It's called a dependency injection attack. And what happens is if you, if you don't have the right sort of security package management guidelines inside your company, and it's just looking for the latest version of merging multiple repositories as like a, like a single view. A lot of companies were accidentally picking up the latest version, which was out in npm uploaded by Alex Spearson was the one who did the, the attack. And he simultaneously reported bug bounties on like a dozen different companies and netted 130 k. Wow. So like these sort of attacks that they're real Yep. They're exploitable. And the, the hackers >>Complex >>Are finding these sort of attacks now in our supply chain are the ones who really are the most dangerous. That's the biggest threat to us. >>Yeah. And we have stacker ones out there. You got a bunch of other services, the white hat hackers get the bounties. That's really important. All right. What's next? What's your vision of this show as we end Coan? What's the most important story coming outta Coan in your opinion? And what are you guys doing next? >>Well, I, I actually think this is, this is probably not what most hooks would say is the most exciting story to con, but I find this personally the best is >>I can't wait for this now. >>So, on, on Sunday, the CNCF ran the first kids' day. >>Oh. >>And so they had a, a free kids workshop for, you know, underprivileged kids for >>About, That's >>Detroit area. It was, it was taught by some of the folks from the CNCF community. So Arro, Eric hen my, my older daughter, Cassandra's also an instructor. So she also was teaching a raspberry pie workshop. >>Amazing. And she's >>Here and Yeah, Yeah. She's also here at the show. And when you think about it, you know, there's always, there's, there's, you know, hundreds of announcements this week, A lot of exciting technologies, some of which we've talked about. Yeah. But it's, it's really what matters is the community. >>It this is a community first event >>And the people, and like, if we're giving back to the community and helping Detroit's kids to get better at technology, to get educated, I think that it's a worthwhile for all of us to be here. >>What a beautiful way to close it. That is such, I'm so glad you brought that up and brought that to our attention. I wasn't aware of that. Did you know that was >>Happening, John? No, I know about that. Yeah. No, that was, And that's next generation too. And what we need, we need to get down into the elementary schools. We gotta get to the kids. They're all doing robotics club anyway in high school. Computer science is now, now a >>Sport, in my opinion. Well, I think that if you're in a privileged community, though, I don't think that every school's doing robotics. And >>That's why Well, Cal Poly, Cal Poly and the universities are stepping up and I think CNCF leadership is amazing here. And we need more of it. I mean, I'm, I'm bullish on this. I love it. And I think that's a really great story. No, >>I, I am. Absolutely. And, and it just goes to show how committed CNF is to community, Putting community first and Detroit. There has been such a celebration of Detroit this whole week. Stephen, thank you so much for joining us on the show. Best Wishes with the CD Foundation. John, thanks for the banter as always. And thank you for tuning in to us here live on the cube in Detroit, Michigan. I'm Savannah Peterson and we are having the best day. I hope you are too.

>>The Cube Presents UI Path Forward five. Brought to you by UI Path. >>Welcome back to the Cube's Coverage of Forward five UI Path Customer event. This is the fourth forward that we've been at. We started in Miami, had some great events. It's all about the customer stories. Dave Valante with Dave Nicholson, Flow Yees here. She's the director of engineering and development at dsu and Kate Hall is to her right. And Kate is the director of Automation Solutions at dsu. Ladies, welcome to the Cube. Thanks so much. Thanks >>You to >>Be here. Tell us about dsu. You guys are huge company, but but give us the focus. >>Yeah, absolutely. Dentsu, it's one of the largest advertising networks out there. One of the largest in the world with over 66,000 employees and we're operating in a hundred plus countries. We're really proud to serve 95% of the Fortune 100 companies. Household names like Microsoft Factor and Gamble. If you seen the Super Bowls ads last year, Larry, Larry Davids ads for the crypto brand. That's a hilarious one for anyone who haven't seen it. So we're just really proud to be here and we really respect the creatives of our company. >>That was the best commercial, the Super Bowl by far. For sure. I, I said at the top of saying that Dave and I were talking UI pass, a cool company. You guys kinda look like cool people. You got cool jobs. Tell, tell us about your respective roles. What do you guys do? Yeah, >>Absolutely, absolutely. Well, I'm the director of engineering and automation, so what I really do is to implement the automation operating model and connecting developers across five continents together, making sure that we're delivering and deploying automation projects up to our best standards setting by the operating model. So it's a really, really great job. And when we get to see all these brilliant minds across the world >>And, And Kate, what's your role? Yeah, >>And the Automation Solutions vertical that I head up, the focus is really on converting business requirements into technical designs for flows, developers to deliver. So making sure that we are managing our pipeline, sourcing the right ideas, prioritizing them according to the business businesses objectives and making sure that we route them to the right place. So is it, does it need to be an automation first? Do we need to optimize the process? Does this make sense for citizen developers or do we need to bring in the professional resources on flow's >>Team? So you're bilingual, you speak, you're like the translator, you speak geek and wall, right? Is that fair? Okay. So take me back to the, let's, let's do a little mini case study here. How did you guys get started? I'm always interested, was this a top down? Is, is is top down required to be successful? Cuz it does feel like you can have bottom up bottoms up with rpa, but, but how did you guys get started? What was the journey like? >>Yeah, we started back in 2017, very traditional top down approach. So we delivered a couple POCs working directly with UiPath. You know, going back those five years, delivered those really highly scalable top down solutions that drove hundreds of thousands of hours of ROI for the business. However, as people kind of began to embrace automation and they learned that this is something that they could, that could help them, it's not something that they should be afraid of to take away their jobs. You know, DSU is a young company with a lot of young, young creatives. They wanna make their lives better. So we were absolutely inundated with all of these use cases of, hey I, I need a bot to do this. I need a bot to do that i's gonna save me, you know, 10 hours a week. It's gonna save my team a hundred hours a month, et cetera, et cetera. All of these smaller use cases that were gonna be hugely impactful for the individuals, their teams, even in entire department, but didn't have that scalable ROI for us to put professional development resources against it. So starting in 2020 we really introduced the citizen development program to put the power into those people's hands so that they could create their own solutions. And that was really just a snowball effect to tackle it from the bottom up as well as the top down. >>So a lot of young people, Dave, they not not threatened by robots that racing it. So >>They've grown up with the technology, they know that they can order an Uber from their phone, right? Why am I, you know, sitting here at MITs typing data from Excel into a program that might be older than some of our youngest employees. >>Yeah. Now, now the way you described it, correct me if I'm wrong, the way you described it, it sounds like there's sort of a gating function though. You're not just putting these tools in the hands of people sitting, especially creatives who are there to create. You're not saying, Oh you want things automated, here are the tools. Go ahead. Automated. We'll we, for those of you who want to learn how to use the tools, we'll have you automate that there. Did I hear that right? You're, you're sort of making decisions about what things will be developed even by citizen developers. >>Let me, Do you wanna talk to them about governance? Yeah, absolutely. >>Yeah, so I think we started out with assistant development program, obviously the huge success, right? Last year we're also here at the Cubes. We're very happy to be back again. But I think a lot, a lot had changed and we've grown a lot since last year. One, I have the joy being a part of this team. And then the other thing is that we really expanded and implemented an automation operating model that I mentioned briefly just earlier. So what that enabled us to do is to unite developers from five continents together organically and we're now able to tap into their talent at a global scale. So we are really using this operating model to grow our automation practice in a scalable and also controlled manner. Okay. What I mean by that is that these developer originally were sitting in 18 plus markets, right? There's not much communication collaboration between them. >>And then we went in and bridged them together. What happened is that originally they were only delivering projects and use cases within their region and sometimes these use cases could be very, very much, you know, small scale and not really maximizing their talent. What we are now able to do is tap into a global automation pipeline. So we connecting these highly skilled people to the pipeline elsewhere, the use cases elsewhere that might not be within their regions because one of our focus, a lot of change I mentioned, right? One thing that will never change with our team, it's used automation to elevate people's potential. Now it's really a win-win situation cuz we are connecting the use cases from different pipelines. So the business is happy cuz we are delivering these high scalable solutions. We also utilizing these developers and they're happy because their skills are being maximized and then at the same time growing our automation program. So then that way the citizen development program so that the lower complexities projects are being delivered at a local level and we are able to innovate at a local level. >>I, I have so many questions flow based on what you just said. It's blowing my mind >>Here. It's a whole cycle. >>So let me start with how do you, you know, one of the, one of the concerns I had initially with RPA, cuz just you're talking about some very narrow use cases and your goal is to expand that to realize the potential of each individual, right? But early days I saw a lot of what I call paving the cow path, taking a process that was not a great process and then automating it, right? And that was limiting the potential. So how do you guys prioritize which processes to focus on and maybe which processes should be rethought, >>Right? Exactly. A lot of time when we do automation, right, we talk about innovations and all that stuff, but innovation doesn't happen with the same people sitting in the same room doing the same thing. So what we are doing now, able to connect all these people, different developers from different groups, we really bring the diversity together. That's diversity D diverse diversity in the mindset, diversity in the skill. So what are we really able to do and we see how we tackle this problem is to, and that's a problem for a lot of business out there is the short-termism. So there's something, what we do is that we take two approaches. One, before we, you know, for example, when we used to receive a use case, right? Maybe it's for the China market involving a specific tool and we just go right into development and start coding and all that good stuff, which is great. >>But what we do with this automation framework, which we think it's a really great service for any company out there that want to grow and mature their automation practice, it's to take a step back, think about, okay, so the China market would be beneficial from this automation. Can we also look at the Philippine market? Can we also look at the Thailand market? Because we also know that they have similar processes and similar auto tools that they use. So we are really able to make our automation in a more meaningful way by scaling a project just beyond one market. Now it's impacting the entire region and benefiting people in the entire region. That is what we say, you know, putting automation for good and then that's what we talked about at dsu, Teaming without limits. And that's a, so >>By taking, we wanna make sure that we're really like taking a step back, connecting all of the dots, building the one thing the right way, the first time. Exactly. And what's really integral into being able to have that transparency, that visibility is that now we're all working on the same platform. So you know, Brian spoke to you last year about our migration into automation cloud, having everything that single pipeline in the cloud. Anybody at DSU can often join the automation community and get access to automation hub, see what's out there, submit their own ideas, use the launchpad to go and take training. Yeah. And get started on their own automation journey as a citizen developer and you know, see the different paths that are available to them from that one central space. >>So by taking us a breath, stepping back, pausing just a bit, the business impact at the tail end is much, much higher. Now you start in 2017 really before you UI path made it's big enterprise play, it acquired process gold, you know, cloud elements now most recently referenced some others. How much of what you guys are, are, are doing is platform versus kind of the initial sort of robot installation? Yeah, >>I mean platforms power people and that's what we're here to do as the global automation team. Whether it's powering the citizen developers, the professional developers, anybody who's interacting with our automations at dsu, we wanna make sure that we're connecting the docs for them on a platform basis so that developers can develop and they don't need to develop those simple use cases that could be done by a citizen developer. You know, they're super smart technical people, they wanna do the cool shit with the new stuff. They wanna branch into, you know, using AI center and doing document understanding. That's, you know, the nature of human curiosity. Citizen developers, they're thrilled that we're making an investment to upscale them, to give them a new capability so that they can automate their own work. And they don't, they, they're the process experts. They don't need to spend a month talking to us when they could spend that time taking the training, learning how to create something themselves. >>How, how much sort of use case runway when you guys step back and look at your business, do you see a limit to the use cases? I mean where are you, if you had on a spectrum of, you know, maturity, how much more opportunity is there for DSU to automate? >>There's so much I think the, you feel >>Like it's limitless? >>No, I absolutely feel like it's limitless because there one thing, it's, there's the use cases and I think it's all about connecting the talent and making sure that something we do really, you know, making sure that we deliver these use cases, invest the time in our people so we make sure our professional developers part of our team spending 10 to 20% of the time to do learning and development because only limitless if our people are getting the latest and the greatest technology and we want to invest the time and we see this as an investment in the people making sure that we deliver the promise of putting people first. And the second thing, it's also investment in our company's growth. And that's a long term goal. And overcoming just focusing on things our short term. So that is something we really focus to do. And not only the use cases we are doing what we are doing as an operating model for automation. That is also something that we really value because then this is a kind of a playbook and a success model for many companies out there to grow their automation practice. So that's another angle that we are also focusing >>On. Well that, that's a relief because you guys are both seem really cool and, and I'm sitting here thinking they don't realize they're working themselves out of a job once they get everything automated, what are they gonna do? Right? But, but so, so it sounds like it's a never ending process, but because you guys are, are such a large global organization, it seems like you might have a luxury of being able to benchmark automations from one region and then benchmark them against other regions that aren't using that automation to be able to see very, very quickly not only realize ROI really quickly from the region where it's been implemented, but to be able to compare it to almost a control. Is that, is that part of your process? Yeah, >>Absolutely. Because we are such a global brand and with the automation, automation operating model, what we are able to do, not only focusing on the talent and the people, but also focusing on the infrastructure. So for example, right, maybe there's a first use case developing in Argentina and they have never done these automation before. And when they go to their security team and asking for an Okta bypass service account and the security team Argentina, like we never heard of automation, we don't know what UiPath is, why would I give you a service account for good reason, right? They're doing their job right. But what we able to do with automation model, it's to establish trust between the developers and the security team. So now we have a set up standing infrastructure that we are ready to go whenever an automation's ready to deploy and we're able to get the set up standing infrastructure because we have the governance to make sure the quality would delivered and making sure anything that we deployed, automation that we deploy are developed and governed by the best practice. So that's how we able to kind of get this automation expand globally in a very control and scalable manner because the people that we have build a relationship with. What are >>The governors to how fast you can adopt? Is it just expertise or bandwidth of that expertise or what's the bottleneck? >>Yeah, >>If >>You wanna talk more about, >>So in terms of the pipeline, we really wanna make sure that we are taking that step back and instead of just going, let's develop, develop, develop, here are the requirements like get started and go, we've prove the value of automation at Densu. We wanna make sure we are taking that step back and observing the pipeline. And it's, it's up to us to work with the business to really establish their priorities and the priorities. It's a, it's a big global organization. There might be different priorities in APAC than there are in EM for a good reason. APAC may not be adopted on the same, you know, e r P system for example. So they might have those smaller scale ROI use cases, but that's where we wanna work with them to identify, you know, maybe this is a legitimate need, the ROI is not there, let's upscale some citizen developers so that they can start, you know, working for themselves and get those results faster for those simpler use cases. >>Does, does the funding come from the line of business or IT or a combination? I mean there are obviously budget constraints are very concerned about the macro and the recession. You guys have some global brands, you know, as, as things ebb and flow in the economy, you're competing with other budgets. But where are the budgets coming from inside of dsu? Is it the business, is it the tech >>Group? Yeah, we really consider our automation group is the cause of doing business because we are here connecting people with bridging people together and really elevating. And the reason why we structure it that way, it's people, we do automation at dsu not to reduce head count, not to, you know, not, not just those matrix number that we measure, but really it's to giving time back to the people, giving time back to our business. So then that way they can focus on their wellbeing and that way they can focus on the work-life balance, right? So that's what we say. We are forced for good and by using automation for good as one really great example. So I think because of this agenda and because DSU do prioritize people, you know, so that's why we're getting the funding, we're getting the budget and we are seeing as a cause of doing business. So then we can get these time back using innovation to make people more fulfilling and applying automation in meaningful ways. >>Kate and Flo, congratulations. Your energy is palpable and really great success, wonderful story. Really appreciate you sharing. Thank you so >>Much for having us today. >>You're very welcome. All keep it right there. Dave Nicholson and Dave Ante. We're live from UI path forward at five from Las Vegas. We're in the Venetian Consent Convention Center. Will be right back, right for the short break.

>> Announcer: theCUBE presents HPE Discover 2022, brought to you by HPE. >> We're back at the formerly the Sands Convention Center, it's called the Venetian Convention Center now, Dave Vellante and John Furrier here covering day three, HPE Discover 2022, it's hot outside, it's cool in here, and we're going to heat it up with Rashmi Kumar, who's the Senior Vice President and CIO of Hewlett Packard Enterprise, great to see you face to face, it's been a while. >> Same here, last couple of years, we were all virtual. >> Yeah, that's right. So we've talked before about sort of your internal as-a-service transformation, you know, we do call it dog fooding, everybody likes to course correct and say, no, no, it's drinking your own champagne, is it really that pretty? >> It is, and the way I put it is, no pressure to my product teams, it's being customer zero. >> Right, take us through the acceleration on how everything's been going with you guys, obviously, the pandemic was an impact to certainly the CIO role and your team but now you've got GreenLake coming in and Antonio's big statement before the pandemic, by 2022 everything will be as a service and then everything went remote, VPNs and all this new stuff, how's it going? >> Yeah, so from business perspective, that's a great point to start that, right? Antonio promised in 2019 that HPE will be Everything-as-a-Service company and he had no view of what's going to happen with COVID. But guess what? So many businesses became digital and as-a-service during those two years, right? And now we came back this year, it was so exciting to be part of Discover when now we are Everything-as-a-Service. So great from business perspective but, when I look at our own transformation, behind the scene, what IT has been busy with and we haven't caught a breadth because of pandemic, we have taken care of all that change, but at the same time have driven our transformation to make HPE, edge to cloud platform as a service company. >> You know, I saw a survey, I referenced it earlier today, it was a survey, I think it was been by Couchbase, it was a CIO survey, so they asked, who was responsible at your organization for the digital transformation? And overwhelming, like 75% said, CIO, which surprised me 'cause, you know, in line with the business and so forth but in fact I thought, well, maybe, because of the forced march to digital that's what was top of their mind, so who is responsible for, and I know it's not just one person, for the digital transformation? Describe that dynamic. >> Yeah, so definitely it's not one person, but you do need that whole accountable, responsible, informed, right, in the context of digital transformation. And you call them CIO, you call them CDIO or CDO and whatnot but, end of the day, technology is becoming an imperative for a business to be successful and COVID alone has accelerated it, I'm repeating this maybe millions time if you Google it but, CIOs are best positioned because they connect the dots across organization. In my organization at HPE, we embarked upon this large transformation where we were consolidating 10 different ERPs, multiple master data system into one and it wasn't about doing digital which is e-commerce website or one technology, it was creating that digital foundation for the company then to transform that entire organization to be a physical product company to a digital product company. And we needed that foundation for us to get that code to cash experience, not only in our traditional business, but in our as-a-service company. >> So maybe that wasn't confirmation bias, I want to ask you about, we've been talking a lot about sustainability and I've made the comment that, if you go back, you know, 10, 12 years and you were CIO IT at that time, CIO really didn't care about the energy bill, that was paid for by facilities, they really didn't talk to each other much and that's completely changed, why has it changed? How should a CIO, how do your your peers think about energy costs today? >> Yeah, so, at some point look, ESG is the biggest agenda for companies, regulators, even kind of the watchers of ISS and Glass Lewis type thing and boards are becoming aware of it. If you look at 2-4% of greenhouse emission comes from infrastructure, specifically technology infrastructure, as part of this transformation within HPE, I also did what I call private cloud transformation. Remember, it's not data center transformation, it's private cloud transformation. And if you can take your traditional workload and cloudify it which runs on a GreenLake type platform, it's currently 30% more efficient than traditional way of handling the workload and the infrastructure but, we recently published our green living progress report and we talk about efficiency, by 2020 if you have achieved three times, the plan is to get to 30 times by 2050 where, infrastructure will not contribute to energy bill in turn the greenhouse emission as well. I think CIOs are responsible multifold on the sustainability piece. One is how they run their data center, make it efficient with GreenLake type implementations, demand from your hyperscaler to provide that, what Fidelma just launched, sustainability scorecard of the infrastructure, second piece is, we are the data gods in the company, right? We have access to all kinds of data, provide that to the product teams and have them, if we cannot measure, we cannot improve. So if you work with your product team, work with your BU leader, provide them data around greenhouse gas and how they're impacting a mission through their products and how can they make it better going forward, and that can be done through technology, right? All the measurements come from technology. So what technology we need to provide to our manufacturing lines so that they can monitor and improve on the sustainability front as well. >> You mentioned data, I wanted to bring that up 'cause I was going to bring that up in another top track here, data as an asset now is at play, so I get the data on the sustainability, feed that in, but as companies go to the cloud operating model, they go, hey, I got the hyperscalers, you call microscale, Amazon for instance, and you got on-premises data center, which is a large edge and you got the edge, the data control plane, and then the control plane and the data plane are always seem to be like the battle ground, I want to control the data plane, will customers own the data plane or will the infrastructure providers control that data plane? And how do you see that? Because we want to power the machine learning, so data plane control plane, it seems to be like the new middleware, what's your view on that? How do you look at that holistically? >> Yeah, so I'll start based on the hyperscaler conversation, right? And I had this conversation with one of the very big ones recently, or even our partner, SAP, when they talk about RISE, data center and how I host my application infrastructure, that's the lowest common denominator of our job. When I talk about CIOs being responsible for digital transformation, that means how do I make my business process more innovative? How do I make my data more accessible, right? So, if you look at data as an asset for the company, it's again, they're responsible, accountable. As CIO, I'm responsible to have it managed, have it on a technology platform, which makes it accessible by it and our business leader accountable to define the right metrics, right kind of KPIs, drive outcome from that data. IT organization, we are also too busy driving a lot of activities and today's world is going to bad business outcome. So with the data that I'm collecting, how do I enable my business leader to be able to drive business outcome through the use of the data? That's extremely important, and at HPE, we have achieved it, there are two ways, right? Now I have one single ERP, so all the data that I need for what I call operational reporting, get hindsight and insight is available at one place and they can drive their day to day business with that, but longer term, what's going to happen based on what happened, which I call insight to foresight comes from a integrated data platform, which I have control of, and you know, we are fragmenting it because companies now have Databox, Snowflake, AWS data analytics tool, Azure data analytics tool, I call it data torture. CIOs should get control of common set of data and enable their businesses to define better measurements and KPIs to be able to drive the data. >> So data's a crown jewel then, it's crown jewel not-- >> Can we double-click on that because, okay, so you take your ERP system, the consumers of data in the ERP system, they have the context that we've kind of operationalized those systems. We haven't operationalized our analytics systems in the same way, which is kind of a weird dynamic, and so you, right, I think correctly noted Rashmi that, we are creating all these stove pipes. Now, think I heard from you, you're gaining control of those stove pipes, but then how do you put data back in the hands of those line of business users without having to go through a hyper specialized analytics team? And that's a real challenge I think for data. >> It is challenge and I'll tell you, it's messy even in my world but, I have dealt with data long enough, the value lies in how do I take control of all stove pipes, bring it all together, but don't make it a data lake which is built out of multiple puddles, that data lake promise hasn't delivered, right? So the value lies in the conformed layer which then it's easier for businesses to access and run their analytics from, because they need a playground because all the answers they don't have, on the operation side, as you mentioned, we got it, right? It'll happen, but on the fore site side and deeper insight side based on driving the key metrics, two challenges; understanding what's the key metrics in KPI, but the second is, how to drive visibility and understanding of it. So we need to get technology out of the conversation, bring in understanding of the data into the conversation and we need to drive towards that path. >> As a business, you know, line of business person putting that hat on, I would love to have this conversation with my CIO because I would say, I just want self-service infrastructure and I want to have access to the data that I need, I know what metrics I need to run my business so now I want the technology to be just a technical detail, you take care of that and then somebody in the organization, probably not the line of business person wants to make sure that that data is governed and secure. So there's somebody else and that maybe is your responsibility, so how do you handle that real problem? So I think you're well on the track with GreenLake for self-serve infrastructure, right, how do you handle the sort of automated governance piece of it, make that computational? Yeah, so one thing is technology is important because that's bringing all the data together at one place with single version of truth. And then, that's why I say my sons are data scientist, by the way, I tell them that the magic happens at the intersection of technology knowledge, data knowledge, and business knowledge, and that's where the talent, which is very hard to find who can connect dots across these three kind of circles and focus on that middle where the value lies and pushing businesses to, because, you know, business is messy, I've worked on pharma companies, utilities, now technology, order does not mean revenue, right? There's a lot more that happen and pricing or chargeback, rebates, all that things, if somebody can kind of make sense out of it through incremental innovation, it's not like a big bang I know it all, but finding those areas and applying what you said, I call it the G word, governance, to make sure your source is right and then creating that conform layer then makes into the dashboard the right information about those types of metrics is extreme. >> And then bringing that to the ecosystem, now I just made it 10 times more complicated. >> Yeah, this is a great conversation, we on theCUBE interview one time we're talking about the old software days where shrink-wrap software be on the shelf, you wouldn't know if was successful until you looked at the sales data, well after the fact, now everything's instrumented, SaaS companies, you know exactly what the adoption is, either people like it or they don't, the data doesn't lie. So now companies are realizing, okay, I got data, I can instrument everything, your customers are now saying, I can get to the value fast now. So knowing what that value is is what everyone's talking about. How do you see that changing the data equation? >> Yeah, that's so true even for our business, right? If you talk to Fidelma today, who is our CTO, she's bringing together the platform and multiple platforms that we had so far to go to as-a-service business, right? Infosite, Aruba Central, GLCP, or now we call it it's all HPE GreenLake, but now this gives us the opportunity to really be a alongside customer. It's no more, I sold a box, I'll come back to you three years later for a refresh, now we are in touch with our customer real time through Telemetry data that's coming from our products and really understanding how our customers are reacting with that, right? And that's where we instantiated what we call is a federated data lake where, marketing, product, sales, all teams can come together and look at what's going on. Customer360, right? Data is locked in Salesforce from opportunity, leads, codes perspective, and then real time orders are locked in S4. The challenge is, how do we bring both together so that our sales people have on their fingertip whats the install base look like, how much business that we did and the traditional side and the GreenLake side and what are the opportunities here to support our customers? >> Real quick, I know we don't have a lot of time left, but I want to touch on machine learning, which basically feeds AI, machine learning, AI go together, it's only as good as the data you can provide to it. So to your point about exposing the data while having the stove pipes for compliance and governance, how do you architect that properly? You mentioned federated data lake and earlier you said the data lake promise hasn't come back, is it data meshes? What is the architecture to have as much available data to be addressed by applications while preserving the protection? >> Yeah, so, machine learning and AI, I will also add chatbots and conversational AI, right? Because that becomes the front end of it. And that's kind of the automation process promise in the data space, right? So, the point is that, if we talk about federated data lake around one capability which I'm talking about GreenLake consumption, right? So one piece is around, how do I get data cleanly? How do I relate it across various products? How do I create metrics out of it? But how do I make it more accessible for our users? And that's where the conversational AI and chatbot comes in. And then the opportunity comes in is around not only real time, but analytics, I believe Salesforce had a pitch called customer insight few years ago, where they said, we have so many of you on our platform, now I can combine all the data that I can access and want to give you a view of how every company is interacting with their customer and how you can improve it, that's where we want to go. And I completely agree, it ends up being clean data, governed data, secure data, but having that understanding of what we want to project out and how do I make it accessible for our users very seamlessly. >> Last question, what's your number one challenge right now in this post isolation world? >> Talent, we haven't talked about that, right? >> Got to get that out there. >> All these promises, right, the entire end to end foundational transformation, as-a-service transformation, talking about the promise of data analytics, we talked about governance and security, all that is possible because of the talent we have or we will have, and our ability to attract and retain them. So as CIO, I personally spend a lot of time, CEO, John Schultz, Antonio, very, very focused on creating that employee experience and what we call everything is edge for us, so edge to office initiative where we are giving them hybrid work capabilities, people are very passionate about purpose, so sustainability, quality, all these are big deal for them, making sure that senior leadership is focused on the right thing, so, hybrid working capability, hiring the right set of people with the right skill set and keeping them excited about the work we are doing, having a purpose, and being honest about it means I haven't seen a more authentic leader than Antonio, who opens up his keynote for this type of convention, with the purpose that he's very passionate about in current environment. >> Awesome, Rashmi, always great to have you on, wonderful to have you face to face, such a clear thinker in bringing your experience to our audience, really appreciate it. >> Thank you, I'm a big consumer of CUBE and look forward to having-- >> All right, and keep it right there, John and I will be back to wrap up with Norm Follett, from HPE discover 2022, you're watching theCUBE. 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>>The cube presents HPE discover 2022 brought to you by HPE. >>Welcome back to the Venetian convention center. You're watching the Cube's coverage of HPE discover 2022. The first discover live discover in three years, 2019 was the last one. The cube we were just talking about. This has been at H HP discover. Now HPE since 2011, my co-host John furrier. We're pleased to welcome Phil Maru. Who's the executive vice president and general manager of HPE Aruba. And he's joined by David Hughes, the chief product and technology officer at HPE Aruba gentleman. Welcome to the cube. Good to see you. Thank you. Thank >>You. >>Okay, so you guys talk a lot, Phil, about the intelligent edge. Yep. Okay. What do you, what do you mean by that? >>Yeah, so we, well, we're kind of focused on, is providing technology to customers that sits out at the edge and typically the edge would be, uh, any location out of the data center or out of the cloud. So for the most part, our customers would deploy our technology either in their office premises or maybe retail premises shops, uh, maybe deploying out of the home where their employees are on a factory floor. And we're really talking about technology to connect both people and devices back to, um, systems and technology throughout an organization. So, but >>I, I, you know, sometimes I call it the near edge and the far edge yeah. Near, near edge. Maybe as we saw home Depot up on the stage yesterday far, Edge's like space. Right. You're including all of that. Right. That's >>Edge. >>Yeah. And actually we, we, we, you know, we've got a broad range of technology that actually works within the data center as well. So, you know, what we are focused on is providing, uh, network technology, software and services. And, you know, for the most part, our heritage is at the edge, but it's more pervasive than that. So >>If you have the edge, you got connectivity and power, that's an edge. How much, um, is the physical world being connected now you're seeing robotics automation. Yeah. Ex and with machine learning specifically in compute, really driving a new acceleration at the edge. What you, how do you guys view that? What's your reaction? Yeah. >>I think, look, it, I think as connectivity is improving and that's both in terms of wifi connectivity, so, you know, wifi technology continues to, uh, advance and also you've got this new kind of private 5g area, just generally connectivity is becoming more pervasive and that's helping some industries that haven't previously embraced it. And I think industrial is, is one of the big ones. So, you know, historically it was difficult for kind of car manufacturers to really enable a factory floor. But now the connectivity is connectivity is better. That gives them the opportunity to be able to really change how they do things. So >>David, if you do take an outside in view, mm-hmm <affirmative>, uh, and, and, and when you talk to customers, what are they telling you and how is that informing your product strategy? >>Yeah, well, you >>Know, I think there's, there's several themes we hear. One is, you know, it's really important, better work from anywhere they wanna enable their employees, um, to get the same experience, whether they're at home or on the road or in their branch office or at headquarters. Um, you know, people are also concerned that as they deploy, deploy all of this IOT and pursuit of digital transformation, they don't want those devices to be a weak point where someone breaks into one device and moves naturally, um, across the network. So they want to have this great experience for their customers and their users, but they wanna make sure that they're not compromising security, um, in any way. And so it's about getting that balance between ease of use and, and security. That's one of the primary things we hear, >>You know, Dave, one of the things we talked about many, many years ago was when hybrid and was starting to come out multi-cloud was on the, on the table early on. Uh, we were, we were saying, Hey, the data center is just a big edge, right? I mean, if you have cloud operations and you see what's going on with GreenLake here now, the momentum hybrid cloud is cloud operations, right? An edge off data centers to a big edge on premises. And you got the edge as you have cloud operations, like say GreenLake, plugging in partners and diverse environments. You're connecting, not just branch offices that are per perimeter based. You have no perimeter and you have now other companies connecting mm-hmm <affirmative> so you got data and you got network. How do you guys see that transition as GreenLake has a very big ecosystem part of it, partners and whatnot. >>Yeah. So, you know, I think for us, um, the ecosystem of partners that we have is critical in terms of delivering what our customers need. And, you know, I think one of the really important areas is around verticals. So, um, you know, when you think about different verticals, they have similar problems, but you need to tailor the solutions. Um, to each of those, you know, we are talking a bit about devices and people. When you look at say a healthcare environment, there can be 30 devices there for each patient. And, um, so there's connecting all those devices securely, but we have partners that will help pull all of that together that may be focused on, um, you know, medical environment that may focused on stadiums. They may be focused on industrial. Um, so having partners that understand those verticals and working closely with them to deliver solutions is important in our go to market. >>So another kind of product question and related to what you just said, David, I got connectivity, speed, reliability, cost security, or maybe a missing something. But you, you said earlier, you gonna gotta balance those. How do you do that? And do you do that for the specific use cases? Like for instance, you just mentioned stadiums and 81 and how do you balance those and, and do you tailor those for the use cases? >>Yeah, well, I think it depends on the customer and different people have different views about where they need to be. So some people are, are so afraid about security. They wanna be air gapped and completely separate than the internet. That would be one extreme mm-hmm <affirmative> other people, you know, look at it and see what's happening with COVID with everyone working from home with people being able to work from Starbucks or the airport. And they're beginning to think, well, why is the branch that much different? And so what I think we are seeing is, you know, a reevaluation of how people connect to, um, the apps they're using and, uh, you know, you, you, you've probably for sure heard people talking about zero trust, talking about micro segmentation. You know, I think what we we see is that people wanna be able to build a network in a way where rather than any device being able to talk to any device or any person, which is where the internet started, we wanna build to build networks where people or devices can only talk to the destinations that are necessary for them to do their job. >>And so a lot of the technology that we are building into the network is really about making security intrinsic by limiting what can talk to what that's >>Actually micro, micro segmentations, zero trust, um, these all point to a modern, the modern network, as you say, Antonio Neri was just on the cube, talking about programmability, substrate, the words like that come to mind, what is the modern network look like? I mean, you have to be agile. You have to be programmable. You have to have security. Can you describe in your words, what does the modern network these days need to look like? How should customers think about architecting them? What are some of the table stakes and what are some of the differentiators that customers need to do to have a modern network? >>Yeah, well, you covered off a coup a few quarter, one there with clarity and so on. So let me pick one that you didn't mention. And, and I, you know, I think we are seeing, you know, a lot of interest around network as a service. And, you know, when we think about network as a service, we think about it broadly, um, you know, for consumers, we're getting more and more used to buying things as a service versus buying a thing. When you, when you get Alexa, you care about how well she answers your questions, you don't care about what CPU is or how much Ram Alexa has. And likewise with networking, people are caring about the outcomes of keeping their employees connected, keeping their, their devices and systems running. And so what for us, what NASA is all about is that shift of thinking about a network as being a collection of devices that get managed to being a framework for connectivity and running it from the point of view of those outcomes. >>And so whether, you know, it's about CapEx versus OPEX or about do it yourself, managing the network yourself versus outsourcing that, um, or it's about the, you know, Greenfield versus brownfield, each of our customers has got a different starting point, but they're all getting heading towards this destination of being able to treat their network as a service. And so that is, you know, a key area of innovation for us and whether it's big customers like home Depot that you heard about yesterday, um, where we kind of manage everything for them on a, as on a store basis, um, for connectivity, um, or, you know, the recent, um, skew based nest that we launched, which is a really scalable foundation for our partners to build nest offerings around. Um, we see this as a key part of network modernization. Yeah. >>And one of the things, again, that's great stuff. Uh, infrastructure is code, which was really kind of pioneer the DevOps movement in cloud kind of as platform level. And you got data ops now and AI at the top of the stack, we were always wondering when network as code was gonna come, uh, and where you actually have it, where it's programmable. I mean, we all know what policies do do. They're good. That's all great network as code. >>Yeah. >>And that's the concept that's like DevOps, it's like, make it work just seamlessly, just be always on. And >>Yeah. And smart, you know, people are always looking for the, for the easy button. Um, and so they want, they want things to operate easily. They want it to be easy to manage. And, you know, I actually think there's a little bit of a, um, a conflict between networkers code and the easy button, right? So it depends on the class of customers. Some customers like financials, for instance, have a huge software development organizations that are extremely capable that could, that can go with program ability that want things as code. But the majority of the, of, of the verticals that we deal with, um, don't have those big captive software organizations. And so they're really looking for automation and simplicity and they wanna outsource that problem. So in Aruba central, we have invested a lot to make it really easy for our customers to, um, get what they need, you know, is that movement of zero code. It's more like zero code. They want, they want something packaged now >>The headless networks. Yeah. Low code, no code >>Kind of thing. Yeah, that's right. And, you know, obviously for people that have the sophistication that want to, um, do the most advanced things, we have APIs. And so we support that kind of programmable way of doing things. But I'd say that that's that's, those are more specialized customers. So >>Phil, yeah. Uh, is that the strategy? I mean, David listed off a number of, of factors here is that Aruba's strategy to modernize networks to actually create the easy button through network as a service is as simple as dial tone. Is that how we >>Should think? I mean, the way I think about the strategy is I think about it as a triangle, really, along the bottom, we've got the products and services that we offer and we continue to add more products and services. We either buy companies such as silver peak a couple of years ago, or we build, uh, additional products and by, and by the way, that's in response to customers who are frustrated with some other suppliers and wanna move on mass over to, uh, companies like ourselves. So at the bottom layer of the product and services, and then the other side of the triangle one would be NAS, which we talked about, which is kind of move to buying network and as a service. And then the other side of the triangle is the platform, which for us is river central, which is part of HP GreenLake. And that's really all about, you know, kind of making it easy for customers to manage networks and Aruba central right now has got about 120,000 live customers on it. It connects to about 2 million devices and it's collecting a lot of data as well. So we anonymously collect data from all of our customers. We've got one and a half billion data points in the platform. And what we do is we let that data kind of look for anomalies and spot problems on the network before they happen for customers. >>So Aruba central predated, uh, uh, GreenLake GreenLake. Yeah. And, and so did you write to GreenLake through GreenLake APIs? How, what was the engineering work to accomplish that? >>Yeah, so really, um, Aruba central is kind of the Genesis of the GreenLake platform. So we took Aruba central and made it more generic okay. To build the GreenLake cloud platform. And you know, what we've done very recently is bring, bring Aruba into that unified infrastructure, along with storage and compute. So the same sign-on applies across all of HP's, um, products, the same way of managing licenses, managing devices. And so it provides us, uh, great foundation going forwards to, um, solve more comprehensively. Our customers automation requires. >>So, so just a quick follow. So Aruba actually was the main spring of GreenLake from the standpoint of okay. Sing, like you said, single sign on a platform that could evolve and become more, more generic. Yes. So, okay. So that was a nice little, um, bonus of the acquisition, you know, it's now the whole company >><laugh> Aruba taking over. >>Yeah. There's been a lot of work to, to, uh, you know, make it generic and, and widely applicable. Right. Yeah. Um, so, but >>You were purpose >>Built for yeah. Well it's foundational. Yes. So foundational for GreenLake, they built on top of it. Yeah. So you mentioned the data points, billions of data points. So I gotta ask you, cuz we're seeing this, um, copy more and more with machine learning, driving a lot of acceleration, cuz you can do simulations with machine learning and compute. We had Neil McDonal done earlier. He's a compute guy, you got networking. So with all this, um, these services and devices being put on and off the network humans, can't actually figure this out. You can discover what's on the network. How are you guys viewing the discovery and monitoring because there's no perimeter okay. On the network anymore. So I want to know what's out there. Um, how do you get through it? How does machine learning and AI play into this? >>Yeah. I mean, what we are trying to do is obviously flag trends for customers and say, Hey look, you know, we can either see something happening with your network. So there's a particular issue over here and we need to, I dunno, free up more capacity to solve that. Or we're looking at how their network is running and then comparing that with anonymized data from all of our other customers as well. So we're just helping find those problems. But yeah, you're right. I mean, I think it is becoming more of an issue for organizations, you know, how do you manage the network, >>But you see machine learning and AI playing a big part. >>Yeah, yeah. Yeah. I think, uh, AI massively and, and other technology advances as well that we make. So recently we, uh, also announced the availability of location awareness within our access points. And that might sound like a simple thing. But when network, when companies build out their networks, they often lose or they potentially could lose the records as to, well, where were the access points that we laid out and actually where are they not within, you know, 20 feet, but where actually are they? So we introduced kind of location, finding technology as well into our, uh, access points to make it easy for >>Customers. So Aruba one of the best, if not the best acquisition. I think that HP E has made, um, it's made by three par was, you know, good. It saved the storage business. Okay. That was more of a defensive play. Uh, but to see Aruba, it's a growth business. You guys report on it every quarter. Yeah. It's obviously a key ingredient to enable uh, uh, GreenLake and, and a that's another example, nimble was similar. We're much smaller sort of more narrow, but taking the AI ops piece and bringing it over. So it's, it was great to see HPE executing on some of its M and a as opposed to just leaving them alone and not really leveraging 'em. So guys, yeah. Congratulations really appreciate you guys coming on and explaining that. Congratulations on all the, all the great work and thanks for coming on the cube. Okay. >>Thank you guys. Yeah. Thanks for having us. >>All right, John, and I'll be back right after this short break. You're watching the cube, the leader in enterprise tech coverage from HPE Las Vegas, 2022. We'll be right back.

(soft bright music) (logo swooshing) (crowd murmuring) >> Hey everyone, welcome to Las Vegas! Lisa Martin here on the ground with theCUBE about Coupa Inspire 2022. And can you hear the buzz behind me? It is so great to be in person. Nick Banich joins me, the Chief Revenue Officer and Global Partnership Manager for the Coupa Alliance at Miebach Consulting. Nick, it's great to have you on the program. >> Thanks for having me, Lisa. First time here at Inspire and it's exciting. >> Is it exciting? It's great to see this room packed. >> It is! It feels, like, the pandemic is finally- >> It does. >> Maybe behind us. >> Right, fingers crossed. (Nick chuckles) So talk to us a little bit about Miebach Consulting and a little bit about the Coupa Partnership, so the audience gets that understanding of what you guys do. >> Yeah, guess, we're kind of new to the Coupa ecosystem. You could say, we came as part of the acquisition of LLamasoft. So Miebach is a supply chain focus, advisory, consultancy, engineering firm. So we have three different business lines. Supply chain strategy, where we do things like supply chain design and the Coupa platform, planning, inventory, engineering, automation studies, and distribution centers, with the labor crunch that we're facing right now. As well as we have a digital transformation group that works on getting the decision-making as a supply chain industry into the digital realm and away from Microsoft Excel. >> Let's talk about the digitization of the supply chain. You know, one of the things that we've seen in the last couple of years is this massive acceleration to digital because businesses in every industry had no choice. But where are, what are the current trends from a digital supply chain perspective? >> You know, I think the, kind of the integration of the compression of the decision-making cycle has really gotten companies to not look at strategic decisions then operational decisions and tactical decisions in execution. That all has to be compressed now with the volatility we've all been exposed to. I mean, basically, for the past 20 years, we took the supply chain and turned it into a Swiss watch. It was very long, very well orchestrated. But with the volatility, with labor issues, with the land war in Europe, this volatility and change is requiring companies to be much more adaptive. And they've had to compress that decision cycle down and the Coupa platform, certainly, from a supply chain standpoint, absolutely helps infuse that process to shorten time from question to answer and allow you to address strategic and tactical topics in parallel to one another and not kind of waterfall down over the decision making product. >> That's important, 'cause these days, there is no time for waterfalls. So let's unpack the Coupa supply chain design platform. Talk to me about it, what it does and how it is helping that acceleration? >> Yeah, so it's incredibly powerful. And what it allows you to do is create that digital representation. We can take a three dimensional world and put it into a two dimensional linear program. And within the same platform we can optimize strategically and take a look at end to end type of supply chain decisions, nearshoring, onshoring, supplier diversification, and risk aspects. We can look at it more operationally. We're actually looking at which manufacturing plans should make what? What distribution centers should serve what customers? How do I segment my products? How do I segment my customers? Then within the same modules, you can use and go to your inventory optimization, not only optimize inventory, but also simulate it, which gives you phenomenal power in a world where there is so much uncertainty. You can apply risk in those questions of what if, so you're ready. So that way, when the thing happens, you're not that scrambling to have analysts crunch Excel files to see what do you do to normalize inventory levels or normalize your supplier base. You're able to be more proactive with the predictive and prescriptive analytics that the full suite provides for you. >> That is essential. If that's one of the lessons we've learned in the last couple of years, not if, but when. >> Nick: Yes. >> Talk to me about customers that are using the platform. What are some of the, using it well. What are some of the things that they have in common? >> You know, I think the organizations that are implementing it well, look for it. They view it as a real platform. You know, historically, supply chain design, network optimization, was seen as a tool, and companies implement it as a tool. You purchase licenses, you assign a couple of people to work on it from your analytical department and you just went with it. This is a very powerful platform to completely revolutionize how you make decisions within your supply chain. And you need to approach it the same way you approach a new warehouse management system, a new planning platform, a new labor management system, the change management aspects, the organizational aspects, the education of stakeholders on what is this, demystifying it. So it's not a black box and everybody knows what it can and should do and how best to utilize it. So those organizations that view it as more than a distribution network tool, "Hey, where do I put my new warehouse? Hey, this lease is coming up in Central Europe. It's coming up in Ohio. Do I extend the lease? Do I need to move?" That's, like, a level zero maturity on our maturity graph. The very mature companies are using it and infusing it both strategically, operational, technically, and are using it for distribution decisions, transportation decisions around mode selection, production footprint decisions. You have the capability to have a digital twin. And by having, the other thing companies struggle with is, they just build one model. >> Uh-hmm. >> I start out, I buy the product. You know, I get it built in, I move everything to the cloud and then I do a distribution solve for the U.S. And then the European group says, "Hey, that was great. That was insightful. Can we do the same thing in Europe?" And you take that model and then you add Europe into it. And then the production group says, "Hey, you know, we're thinking about changing some of our make-buy decisions. Can you model what the effect would be on total cost if we did do some nearshoring?" And all of a sudden, you turn your one model that you had built for a specific purpose into this Christmas tree where everybody's hanging their ornaments. And what you really need to do is having a modeling strategy. What type, you should have a volume, a portfolio of models you can pull from and say, "Hey, here's our strategic end to end model. Hey, here's our tactical Asian production models. Hey, here's our total landed cost for top 15% of our customers." And having that set of models, so you have right models, the right questions. >> Uh-hmm. >> That's what the companies that are really scaling this and really excelling. And you'll notice a pattern. The companies that are excelling that have the Coupa platform, typically, you'll find them on list, like, Gartner's Top 25 and things along those lines. Because it is a very powerful platform when you unlock the art of the possible with it. >> Sounds, like, those are companies that are very innovative. But where does the company, that maybe isn't there yet? How do they start? 'Cause it sounds, like, there's a tremendous wealth of potential and opportunities that the technology can deliver. Do they have to start with executive buy-in? What do you see as kind of, like, some of those early steps? >> This is a change management exercise from the very beginning. So creating that sense of urgency, creating your powerful coalition. You have to start with that. If you view this as, "Hey, we're going to have a tool, we're going to use this once, and then our supply chain's fixed for the next 10 years." I mean, I think most leaders are realizing that those days are long gone. That supply chain design has to be a continual topic at the top levels. You know, supply chain is on the lips of every politician and every (chuckles) board member right now. So this is a wonderful moment for those supply chain leaders that have wanted to infuse a greater level of digital decision-making. This is the perfect opportunity. You can get buy-in, like, you never had before. Your CFO is probably analyzing labor inflation, fuel inflation rates, disruptions on supply base, and you're probably having to deal with more pressure out of the CFO and its department than you ever had to in the past. We see it with our clients. The pressure is on with those leaders. And this allows you to very quickly be much more holistic in that decision-making. You're not relying on how good was the analyst, that made this Excel file that told you to open up this plan, move this distribution center, serve this customer base in this way. It's not based on how that data looks and how good that analyst was, you're infusing an entire practice into your organization. >> That's critical, because every company these days is a data company. If they're not, they're not going to be around. It's about the ability to have visibility extract the value from the data to make those data-driven decisions, because we don't have time. We heard a lot about that from a real-time perspective and the keynote this morning that's table stakes run any organization. >> Yeah, and with the move of the platform to the cloud, as part of the Coupa ecosystem, with the DDM, with the rapid model builder, and all those things that come along with it, it will significantly squash the amount out of time you have from question to answer. Because the first time you do this, it probably takes four months. And of that four months to ask that question, and get an answer, build your model, you know, replicate the 3D world in that 2D environment. Over half of that time is spent on cleaning data, building the baseline model, aligning with finance, they peanut butter spread certain aspects of cost onto the onto SKUs and really getting correct cost allocations for A, B, and C SKUs. You spend half your time just playing around with your data to get the model to work right now. Once you add that model, next time, question and answer infinitely quicker. But you have to have a good data strategy. You have to have the right data architecture. If you don't have that specific to supply chain, leaders really need to get on that. Because what we see a lot of times is organizations will have an enterprise data strategy. >> Uh-hmm. >> And they're going to build a data warehouse or a data lake, you know, whatever, I'm a consultant, so I'm also guilty of the buzz words. But, we kind of call it the supply chain data plan. You don't need to wait for the whole enterprise to get ready to have all of your data sorted out in a single instance, homogenize. Start collecting that supply chain data, have a data strategy around it. So that way, you can start replicating these things then you can feed it back into the enterprise data strategy. But you have to get your data right. It's the old adage garbage in garbage out. >> Right. >> It's still true to this day. No matter how powerful the analytical tools are, we're infusing machine learning, artificial intelligence into some of the solves in the platform. But if you don't have that good data, you're going to struggle. So that's a key piece to it, getting that executive buy-in and having that right data strategy will set you on a much smoother path to success than if you don't do those things. >> Right, the data strategy is critical. If not, one of the biggest competitive differentiators these days. Where is the chief data officer, the chief digital officer, the chief information officer, in these conversations that Miebach is having with customers? >> Too often, not at the forefront enough. >> Lisa: Really? >> Those clients that have that group, have that organization, and they have influencing power, those programs go much quicker, much simpler. The rate of adoption, the scalability of the program. All of a sudden, you're not thinking about, "What am I going to do with one or two analysts interacting with the product?" You're now developing apps. You have your planners interfacing with it. You have capacity managers interacting with the digital model. Those that don't have that, do have much more impetus, because it's always the adage of, "Oh, IT, what do we do? And our data's a mess. We have this data program and our IT resources are super constrained." So you have to bring those people to the table. You have to have them part of the conversation, 'cause they can be an incredible enabler if you bring them and get them bought in. >> That's a great point of those enablers. And especially, given the fact that nobody has extra time to waste here. This is a, everything is so fast moving. You mentioned supply chain being on the lips of every politician. Everybody's lips, everybody's expecting some delivery that is delayed for whatever reason. >> I mean, 12 years ago when I started with the firm, and people, "Oh, what does the firm do?" I'm like, "Oh we're a global supply chain consultancy." And they're like, "What?" >> Yeah. (laughs) >> You know, now everybody knows. And they're like, "Oh, yeah!" It's amazing that the revolution, I mean, the pandemic has been incredibly unfortunate with all the hardships and deaths and everything and still dealing with hotspots and things. I think it did bring supply chain, supply chain was struggling for a while to get a seat at the table. Organizations started having chief supply chain officers. You know, that was a new thing not that long ago. This has brought table stakes to the supply chain organization. My challenge back to us is what do we do with this now? >> Right. >> For years, as an industry, we've asked to be at the table, we're here now, spotlight's on us. It's time for us to deliver. Things like the Coupa platform are an incredible enabler of that. But you got to get it right when you roll it out. >> The spotlight's on you, but there's also a skill shortage. Talk to me about that. I just saw you do a big sigh. How can Miebach and Coupa with this platform help to mitigate some of the supply chain skills gap that organizations in every industry are facing? >> You know, it really comes down to the human element and when people talk a lot about sustainability, they talk about environmental conditions. There's a human sustainability topic we have to cover. Nobody likes being assigned to be a data analyst on a transformational project. And you're crunching Excel spreadsheets and running it sequel coding. No, no, that's not an enjoyable fulfilling task for many people. >> Lisa: No. >> There are special people that it is, and God bless (chuckles) them. So with things, like, the apps, with things, like, building out, so that way, we can take the people that you do have and have them making decisions, driving discussions around the insights the platform's giving versus just crunching numbers and building models. This is where you're going to have a much higher retainment. People are going to be excited about the job. They're going to have fun at the job because you do see a turnover of organizations that don't get the data strategy right, that people don't like being in a supply chain center of excellence in perpetuity. Again, there are certain people that are, but a lot of times, once the people get this analytical insight to how strategically the design of the company is set up, business units will grab them and give them a significant role. And then you're continually churning and replacing your COE talent. So having a talent strategy for your COE and having a strategy of how you're going to leverage, you know, we're in a world where my first grader's are learning coding, right? Like, you need to have a data strategy. So that way, that becomes your people strategy as well. And too many times, people think, "Hey, I buy the platform. I need a project strategy. What are the projects we're going to do?" And not often enough, do they talk about the people element of it to really make this work. And it absolutely has to be part of the discussion as you're setting up your center of excellence, it's people, it's processes and it's technology. >> Absolutely! >> You got to bring those three together or you real struggle a bit. >> You do. And then change management is not an easy thing to do for anybody. But one of the things you talked about, this is the pandemic as an accelerator of getting the supply chain folks to the table, being able to accelerate, getting data into the hands of people that can actually take in clean insights and make decisions based on that. So if you look into a crystal ball, what's the future of supply chain design? Where is it going? >> I believe we're going to see a lot more of movement towards applications and infusing of artificial intelligence and machine learning. It's there. It's ready to go. What a lot of companies are lacking and it goes back to what we already talked about is the data piece of it. I mean, we have been developing algorithms in a machine learning environment for three, four years now. It goes back to garbage in, and garbage out. So I think it's going to be a big element of supply chain talent, securing that, figuring out with robotic product process automation and things like that. How do you take non-value added work so you can take the talent you do have and give them more fulfilling work? I think companies are going to need to have data strategies and all that unlocks applications and things. So you can democratize, right? You have this digital twin in the cloud. How many people within the organization cross-functionally have questions about the supply chain? >> Right. >> What if this happens? What if that happens? Hey, if we do this, what does it effect upstream downstream? >> Right. >> So once you build that cloud, develop the applications that allow the entire enterprise to interface with this digital representation to play around and see what the effect is to then make better, more informed, more holistic decisions, drive more conversational, cross functionally amongst leaders, and even below the top leadership level. I think this is really where we're going to go and the companies that don't just survive, but thrive in this new normal, whatever that's going to be, is going to be the companies that get that right. >> They have to embrace that. There's no doubt. >> Nick: Have to embrace it. >> Nick, it's been great having you on the program, talking about supply chain, what's going on there, the accelerators, but also the opportunities. Thank you so much for sharing your insights. >> I appreciate the opportunity. So it's been a great conversation. I look forward to the rest of the event! >> I agree. For Nick Banich, I'm Lisa Martin on the ground in Las Vegas at Coupa Inspire 2022. Stick around, I'll be back with my next guest shortly. (bright music)

>>Hi, everyone. Welcome to the cube and unstoppable domain, special showcase women of web three or well, three I'm super excited for this season. We have three great guests, Sandy Carter, the SVP and channel chief of unstoppable domains. Noel Bailey managing director for the entertainment, AKA disco leper. That's her handle NFT handle. We'll talk more about that. And Kristen Mirabella, Bella director of business development, Gemini all in the web three world here for women of web three. Welcome to the show. So what a great announcement, Sandy? What is the wow three women of web three. And why did you announce it on stumbled domains? Web three. >>Awesome. Well, thanks John. So today we are so excited to announce unstoppable women of web three. And one of the things that we noticed ourselves plus 60 plus companies is that we need more diversity in the web three space. So our mission is to make web three more accessible for everyone to help women with that first step and be very action oriented. So we're going to launch education, networking and events as we move forward. And we're real excited to start today, March 8th, we've got a 24 hour Twitter space. We have a YouTube live. We're going to be auction and off some NFTs to donate to girls in tech, a not-for-profit who is also going to launch a mentoring platform for women in web three. We'll also be announcing a hundred inspirational women's and Webster, and I can take up the entire time talking about all we have in store to make web three accessible to everyone. >>That's awesome. We're going to unpack that lot of things to talk about there. I'm really looking forward to it, neural, your, you got a great story here. What are the lazy lions and, and the queen so to speak and what are you guys doing? And tell us about your handle. >>That's a lot of questions there. John, why don't we start with that? So, I mean, I started my NFT journey about six months ago only, and I got really lucky in entering into the space for the lazy lions to start with and the Kings and existing Queens that were kind of in that space to begin were incredibly welcoming. I literally like, I love being the person in the room that asked the dumb question, because if I, if I can ask it, then, you know, there's, there's a hundred other people there that aren't asking that question. And so when I stepped into the, you know, the pride space with Twitter and discord, getting to know the lazy lions before I even got into my first project, they were incredibly welcoming. Like any question that I asked they had an answer for. And so, you know, why we're kind of wondering with unstoppable and supporting that? >>Well, one, once we, once through that space, I got introduced to queen Sandy as well. You know, she's part of the pride and, and one of the lazy lions and again, yeah, it's that whole symbiotic relationship where you've got, you know, Kings and Queens, men and women kind of in the pride, but it's not just about men and women either. It's the diversity aspect where it's people from all different cultures, backgrounds all around the world. And so, you know, getting in and learning and growing together in this brand new space that we're all part of creating. And then Unstoppables a huge part of that with the gateway to allowing people to kind of get into it, to begin. So it just all makes sense. We're going to expense. >>Okay, we're going to unpack that in a minute, but Kristen w what's going on with Gemini and web three, what's going on in the ecosystem there? How are you supporting the women of web three initiative? >>Really excited. Gemini is an exchange and custodian. We offer access to cryptocurrencies. We are your access points. We're the access point for women who are trying to embrace their own financial freedom and build their own story, be economically empowered and interacting with web three in a way that's going to be increasingly necessary. As, as this continues to build, Gemini is really excited to be able to provide a platform for education for anyone and especially women who are looking to build their knowledge base around what's happening in cryptocurrency. How can they interact with it? How can they make really good financial decisions as they look to interact with networks, you know, within defy, what tokens do they want to be able to, you know, purchase, move off of a centralized platform like Geminis. We are very regulated. We're very secure as an access point to be able to interact with cryptocurrencies and use crypto to interact with this ecosystem that's growing. You can, you know, as a woman decide on a really good idea on how you want to embrace that financial freedom of interacting with the protocol that might unlock your potential to be more financially independent, make really good decisions about the future of what your, your family might need economically, you know, in Gemini as an access point for that, as far as crypto and other digital assets go is where we were really proud that we can power that network. >>So we have to chip and I got the lazy lions. You have the unstoppable, all three of you guys are in the middle of all the action and it's super game-changing. It's also a cultural shift. You seeing a lot of young, the young generation, as well as senior experienced people coming in, certainly technologists are coming in, business leaders are coming in and it just feels like a whole nother cultural shift. So we have to ask you, what are you guys most excited for in this roadmap for women of web three what's on your mind? What do you guys see? What's the vision? >>Well, I'll start first. You know, one of the things that I'm really excited about is getting women to experience web three, not just book learning, but really get in there and interact and play with it. So for example, John, there is a game called de-central land. They sell land. And what they're going to help us do is to build a virtual women of web three headquarters inside of the game. And as women go there, they're going to experience, you know, logging in, they're going to experience crypto, like Kristin does talked about they'll experience. NFT is like disco, just talked about. And so it won't just be book smart. They'll be able to get in there and do and see and play, which I think is the best way to learn about web three. >>For me, I'd say, I mean, honestly, I'm most excited about getting it started. There's been so much work kind of going into this to begin with. And, and this space is, is also new and constantly growing and kind of evolving, changing as we go because we're pioneers kind of in this space, really. Like we all have web three. And so getting it started and it continues to grow and evolve from there, which is, you know, a lot to do with kind of community driven initiatives what's happening in the market and the space at the time as well. So super get it started, build it. And it keeps growing from there. >>Christine, what's your vision to what, how do you see this evolving what's what do you hope for and what are some of the things you're excited about? >>I couldn't agree more. What I think is really exciting is that again, if you're looking to learn about this, you know, Sandy you're so right, you're not gonna learn about really how to unlock the potential of this ecosystem by reading about it. You have to get in there, find crypto, come to Geminis platform, open an account, understand what it means to buy cryptocurrency, buy Bitcoin, understand what you're comfortable with. Use resources like our crypto pedia, to understand the differences between tokens, the differences between layers. Why would you buy this token and transfer it off of the platform where you're looking to interact with three, maybe you're looking at these web three applications and you want to understand what generating income through one of these looks like you really got to start with the basics, but start here, purchase something, move it off. You know, test it, use little, little amounts. >>You don't have to buy a full Bitcoin. I think that that's a common misconception with people who are really starting to get interested in the space, especially as they start to learn about cryptocurrency, buy a tiny piece, you know, you don't need to sell the farm, move it off the platform, learn a little bit about how you can interact, build a community around yourself. There are a lot of women who are learning how to do this and through NFTs and through other interests that you might naturally have, you can really embrace the technology and understand what it can do for you. >>You know, you, you mentioned that in the early days of Bitcoin, even a theory of giving it away was a big part of that kind of early days of community. And Earl, you mentioned the word pride as part of the lazy lions community is a big part of this. Sandy, you know, this you've seen communities develop over the years, this new kind of community dynamic is a network effect, but it's also people centric. It's also about reputation. So it's about being open and collaborative. I mean, it sounds like a bunch of cliches jammed together, but this is kind of the world we're in for web three. Can you guys share your thoughts on that and get a reaction to that? >>Yeah. And I just wanted to jump on kind of what Kristin was mentioning there as well. You know, like, and Sandy, like get in there, get started, like have a little taste, have a little of this watch learn and then kind of tying into your community aspect there, ask the questions, get into, and you know, the two, the couple of main spaces, there are discord and Twitter, which, and again, I signed up my Twitter account in 2014 and I pretty much didn't touch it, like from 2015 kind of onwards, like now learning and getting in and growing with this space, that's kind of where the mediums are to start with with that. So yeah. Get in and get started and, and ask the questions on the way >>Sandy, you see Twitter and discord as the primary. >>Yeah. Yeah. There's so many this guy, right. Because you know, I'm on, I'm now on telegram. I'm on disbarred, I'm on Twitter, I'm on signal. I just got invited to signal groups. So this is one of the areas that we need to work on for web three. I think all of us would agree is just that interface. Part of the reason that we're launching this is because it is hard today, right? Web three is hard. And so there's multiple communications channels, you know, and that's why we love, you know, partners like Jim and I, who are making it easier and lazy lions who are setting up these communities. You know, when you buy in it of T you're really not, I guess you are buying the NFT for value, but you're also buying into the community disco. And I have been meeting actually every Saturday night for a while now with the rest of the Queens, planning out women of web three, Kristin and Jim and I, and I have been meeting together it's about the people and the networking and the tribe that you're part of as well. You really nailed it on the community piece. >>You know, ever since we started talking about it unstoppable, I got to say, I've been wanting to get the cube and FTS going because it is a community dynamic, but it's also this got practical usage of is there's data behind it. There's actually real use cases. Can you guys share your thoughts on how you see the use cases being applied specifically to the world, but also to, to women of web three to Wasn't go first. >>Yeah. We're also polite. We're all quite polite. And do you want to go first? You're one of our partners, we'll let you start us off. >>Sorry. I didn't want to and want to jump in there and they want to get started a real applications of, of what this looks like. I think goes back to an idea I had at the top of the call as there's clarity, as that continues to emerge as web three continues to build. And we understand what this really means. I think many would say that there's, you know, lack of clarity around what web three means. Maybe there are some platforms that are slightly more centralized than others. If we think of what web three in general represents, you know, it's this idea of decentralization empowering you through ownership of your data, empowering you through the ability to do things in a decentralized way, but you're not able to do on web two. And I think the real application of transition of where we are today into what this becomes is, you know, I think we keep nailing it on the head. >>You really have to get out there and practice. You have to understand what this transition means for you and what does it mean for what you're trying to achieve? So if my personal stance is, is really solid in where, you know, your financial future is rooted. And if we're talking about cryptocurrency in your ability to interact with these networks, like we've been saying, you have to practice, you have to understand and learn what you're getting yourself into. But I also think there's this element of being okay with making mistakes, but you are talking about your financial future. You're talking about something that's there really high stakes around making mistakes means starting with really good partners. You can start with platforms like Gemini. You can start with platforms like unstoppable domains and know that the foundation has been laid for you to be able to test these grounds. >>I think that what this becomes and what is really important here is knowing that there are going to be a few centralized points that are your access to this web of three, to this broader ecosystem. But being able to trust that these platforms have security in mind. So the security first mindset that empowers you to then go be in charge of data, privacy, being able to take charge of really what your interaction with the rest of this world means. And being, being able to trust that the foundational layer that you're entering that world through is one that can be trusted. I think that as we look at the real world application of this finding that right starting point is really important. >>Yeah. And I w I would just add John to, to what Kristen just said. There are also B2B use cases here. So we want to make sure that, you know, there's a lot of consumer work, but there's also B to B as well. So, you know, imagine you're in decentral land or you're in sandbox a game. If you're a retailer or in a consumer business, you can place your products or your portfolio inside of that game, there is now decentralized finance that's out there. How does that play a role in your company and the way that you're financing for your company? Not just for yourself, like Kristin mentioned, but also for your company. And then dowels, of course, fractional ownership of different things. We're seeing, you know, funding change. SPACs turning into dowels, all of this. If you look at our 24 hour Twitter space, I'm S I can't wait. I think I'm going to actually do a 24 hour bins for myself because >>That's a college come on. We gotta do. >>Right. I know this guy will be with me. Right. And just that last time I did, that was new. Yeah. >>Well, super exciting. I mean, wow, wow. Three could be a doubt. I mean, the vision here is really amazing. I am so impressed. I think this is a great thing because it could go anywhere. What do you guys see at Dow in the future merging communities and merging tribes together? How do you guys have you guys talked about that? What's the, what's the thought process there? >>We actually did talk about doing a Dow. We decided to kick off first and get everybody up to speed on what it was before we jumped into a doubt, which I think is pretty advanced and sophisticated. And so, you know, part of what we also see is if you look at part of the membership, you'll see women of blockchain, women of data BFF. I mean, all these women's groups coming together to unite as long with, along with a lot of major companies, web to companies, Google Deloitte I'll chair, with the who's, who of web three, you've got Gemini, you've got, you know, consensus, you've got blockchain.com. So, you know, I love this because we are coming together for a movement, not for individual companies, but to have an impact on the industry to really educate women. And John, I forgot one of the really cool things we're also announcing today is our first 100 inspirational women of web three. In fact, disco helped me come up with the name of that, because we do want to highlight as examples, all of these great women that are in the space so that we each can reach back and pull others forward. >>Okay, now we've got to get into the, the disco leopard, let's put the lower third up there so we can see it. And the name that's tell us about the story here. And what does it mean to you? Take us through the thought process, the experience and how you envision this unfolding. Cause it's an NFT. You have one it's >>Yeah, totally. I guess. I mean, starting with, so the disco leopard kind of piece to it as well, like in this new space, in the, in the web space, first of all, you get to like, come up with your own identity. So I got to pick this go leopard, like if he doesn't want to be a disco leopard. And so even just coming up with the journey of like, what is your identity with that? And then, you know, you go through that path of being doxed, meaning being revealed, people kind of know who you are or not, or keeping it, you know, kind of a name on the side, that's all. Okay. Like it's all part of that whole decentralized space, which is super exciting. So just so you know, like the disco leper feeds, you know, optimist glass, half full, you know, pessimist, glass, half empty. And then the third piece to that was disco leopard equals. Awesome. And that's where I saw it. And I'm like, that's me a hundred percent. I'm >>Trying to get your lower third, had your name next to it, >>But that's okay. I'm all right with that. I don't mind. So, you know, getting, getting into that to start with, and then, you know, when we were talking about partners and coming into this safe space as well, and yeah, absolutely kind of technology based partners infrastructure to make sure that we're, we're safe and we've got a smooth gateway kind of coming in, but I'm also gonna put communities into partnerships as well, because there are so many NFT projects, you know, defy gaming projects, et cetera, finding your people, finding the community that resonates with you and it's different for everyone. And that's a beautiful thing, but you get to kind of find like-minded people and join them. >>You know, I've been thinking this for about a long, long time, and I thought I was just weird, but now that it's happening, you guys are in the middle of it. The, your identity is so important now, and you could have a community and tribe to belong to, but yet traverse other tribes and move around. This is kind of the whole prospect of unstoppable, right? So Sandy, this is like a great future. You can be protected in a trusted tribe or community, and then still move around to others and engage. It's almost like a packet moving around a network. It's really about people too, on the internet. This is a total complete game changer. It wasn't really, it's not really possible prior to this. >>Yeah. I mean, if you look at all the members, you can move from a metaverse, you can move into gaming, you can go into defy, we've got NFT communities. And, and I love, you know, like you said, traversing, those communities, like we're going to do an auction and we've had donated NFTs. So disco and lazy lions, the queen of lazy lions are donating a lazy lion. Crypto chicks are gonna donate something. If you don't know what these are, these are all NFT communities that have their own identities as well. We have Deadheads NILAH and the long neck ladies, which is started by a 13 year old girl, who's going to talk on one of our Twitter spaces about how she had 13 earned millions of dollars and became times first artist in residence. So there's just, I mean, there's so much potential here and just look at all these amazing women on the screen. You know, I think web three, the face of web three is female. >>That's awesome. Any final thoughts for you guys and, and the session here, it's amazing. First of all, I'm so excited to, to have this conversation and be included and be included into the group here. Thank you for having me closing thoughts on women of web three, how people can get involved, what you guys aspire to be, what are some of the goals can take us through that? >>I guess for me looking at, you kind of asked the question of, you know, what we're most excited about with what's coming up with the international women's day. And, and, you know, what's beyond that. I'm really excited about what unstoppable are doing in introducing the gateway from web two to web three, because that whole 24, the, the events that we have coming on today is, you know, information, education, openness, how to use it, but what's coming beyond there. And it is that transition from web to, and how to, how do we even, like, I'm about to learn that as well. And as I said, I've been in that, in this NMT journey for six months learning thus far, but what does it look like to get into a web three experience and the web page and that design and look and feel so that next step of learning and getting into it. And again, anyone that's kind of being involved in this conversation now you'll be the first people stepping into that space as web three really comes to life. And it is the new web. Very exciting, >>Great. >>I couldn't agree more neural. What I think excites us the most is the level of interest and the level of engagement that we're seeing an unprecedented levels. These and what's coming next is that you're going to see more and more women and more, more people as part of these communities, as we've talked about wanting to learn, wanting to engage and wanting to be part of this and numbers that we really haven't even seen still yet. We've just scratched the surface. And what I want to ask everyone to do is not to wait not to wait until you feel like you're behind. Take action. Now go to our crypto pedia page, open an account at Gemini, start to interact with cryptocurrencies, understand what it means to take, you know, a crypto or digital asset off of a platform and interact with some of these networks, understand what it means to own, and then empty look at unstoppable domains and understand how you can start to dip your toe in. We really want to empower everyone with the knowledge of what you can do here, and we couldn't be more excited about the future >>Also Sandy final word. >>Yes. So I'm excited about a new world where diversity helps shape the next movement. You know, we've seen web one and web two shaped by, you know, homogeneous groups. And what I'm looking forward to is the future, because we know that innovation is driven by diversity of thought. And so for me, I'm really excited about today international women's day, where we're launching all these educational sessions, you know, Kristen mentioned don't wait, get involved, disco, you know, talked a lot about the potential of going from web two to web three. We hope to see tons of women learning from the web to world. And then I just have to say, I mean, if we could get this across in the virtual world, we're then going to also host an in real life I R L event at south by Southwest. So I'm real excited to be back in person to John so that I can actually give my, my fellow colleagues hugs as well. >>I can't wait to be in person. Thank you so much for coming on this. A great program today is international women's day, but every day is women of web three day. Thanks for sharing great insight. I'm looking forward to more conversations and seeing what happens and participating in any way that I can. And thanks for having me and including me in the conversation. Thank you. Thank you. Okay. This is the cubes conversations here in the showcase women of web three. I'm John for your host. Thanks for watching.

(upbeat music) >> Welcome to this CUBE Conversation. This is part of the second season of the AWS startup showcase, season two, episode one. I'm Dave Nicholson, and I am joined with a very special guest, CEO and co-founder of Tidelift, Mr. Donald Fischer. Donald, welcome to the CUBE. >> Thanks David. Really glad to be here. >> So, first and foremost, tell us about Tidelift. >> Happy to, yeah, so, at Tidelift we're on a mission. Our mission is to make open source software work better for everyone, and when we say that, we mean, make it work better for all the organizations and governments and everybody that depends on open source software to build the applications that we all rely on. But also part of our mission, is making open source work better for the creators of open source. The independent open source maintainers, who are behind so many of those building blocks, technology building blocks that our commerce industry and society is comprised of these days. They've got a hard task to hold up all of that stuff and make sure that it meets, you know, professional grade standards and that we can all rely on it. And so, we want to do our part to help both sides of that equation. >> Fantastic, well, I want to double click on a few of the things that you said, but I think I want to format this by starting out with a little role play between the two of us, if you don't mind. I know you're CEO, but for the sake of this, you're going to be the CIO and I'm going to be the CEO, and we're going to play off some recent events here. So, hey Donald, come on in, sit down. Listen, I want to talk to you about this whole log shell, log for something, or another thing that's going on. So, let me get this straight. Our multinational Fortune 500 company is dependent upon software, that's free, and somehow we've been running this and the people who maintain it, do it for free, we don't pay for it, but somehow this has opened us up to a threat from people who can log into a system we're using to keep track of stuff, and then, what's going on? By the way, you're fired, but I want to know if, I want to know if you can stay on for the next 90 days to train your replacement, but, explain to me what's going on with this whole open-source nonsense? >> Yeah. Don't panic boss. Only about 70 or 80% of the software in our enterprise that is third-party open source software. So, there's definitely, like 20 or 30% that's not, and we're on top of it. Now, yeah, I think it's a, you know, you're right to say, we are completely dependent on this software, that's being created by these, you know, amazing folks on the internet. Boss, you told me that we had to have a global corporation here with modern digital customer experience. We're not going to be able to do it using Microsoft front page from 1997, and there's no other path to take than to build with modern building blocks. And today in, you know, the modern era, that means building on open source packages and technologies across a whole slew of language, ecosystems, like JavaScript and Java PHP, Ruby, Python, .NET, Rust, Go, we use all of it here, boss, and, we don't get to have a business unless we do. >> Okay, so, I didn't understand a word that you just said, but it was enough to convince me to let you keep your job. So, end-scene, we're not getting paid scale wages to do this, Donald, so I think we can go back to our normal personas. So, how does Tidelift play into all of this? I'd really want to hear about this concept of what an open source maintainer is, because these are largely volunteers, aren't they, in terms of the maintenance that they're doing? >> Yeah, so, I mean, open source, there's a lot of different models for open source software development. There certainly are a number of foundational open source projects, certainly at the infrastructure level, like operating systems, databases and things like that, that tend to be, you know, predominantly driven by vendors, software vendors, you know, like you can think of Red Hat, VMware organizations like that. But when you get up to the application development world, teams, building, you know, websites, web applications, mobile applications, most of the building blocks at that tier in these a programming language ecosystems, most of the software there is actually being created, that enterprise organizations use, is being created by individual, independent, open source maintainers, where it's not their day job, it's a side hustle for them. And it's a really interesting question, like, how did we get here? You know, why are these folks doing it? It sort of rhymes with the question I asked myself years ago, like, who's typing all this stuff into Wikipedia, and why? Like, it's amazing resource, I'm so glad it's there, but why are they doing this, right? And it turns out that there's a bunch of motivations there's some cynical motivations for the open source maintainers that people attribute that are practical too, you know, people say your GitHub repository is your resume in as a modern developer, things like that helps you get a reputation, you can use that to get a job. But, when we've talked to the maintainers of the most widely used open source packages, and by that, I mean, thousands of packages that every major organization that builds software relies on, the main reason why they do it is actually impact. We find we've actually done direct surveys of this audience and the reason why they spend their nights and weekends and carve out time, where they could be, you know, getting paid to do something else or going skiing or going to the beach, is it really feels good to have this activity that they put out into the world, and, you know, they know that folks use this stuff and rely on it, and there's a pride in their work and the impact that they're making. But the challenge with this model is that when it's only an impact and pride, and sort of a, you know, a good feeling driven effort, it means that maybe all of the things that organizations might want their standards that organizations might want their software to meet doesn't get done, right? Like it's one thing, if you've got a job as a software engineer, building corporate software, or even as a, you know, a maintainer at a corporate open source company, and you have a checklist of, you know, standard enterprise software development, commercial grade software development tasks that you need to be completing, if you're doing it as a side hustle for good reasons, like impact and, you know, releasing your creative juice, you might not get to some of the more boring aspects of commercial software engineering, like security engineering and some of the documentation and release engineering and, you know, making sure there's structured metadata around all the elements of it. And then that's the gap that we're really trying to fill at Tidelift, by connecting these two audiences. >> Yeah. How? How? You want to fill the gap, you want to connect the audiences, but, how do you do that? >> Yeah, perfect, so, we do it by paying the maintainers, paying the open source maintainers, actual dollars, or the currency of their preference, and what we're paying them for is not just to sort of hack on their projects, or hack on their projects more, we're asking them to help us ensure that the software that the organizations that we work with depend on meets certain specific concrete enterprise standards, and those standards fall into three categories, security, licensing, and maintenance. So, on the security front, you know, a baseline standard, there is making sure that we have known versions of the open source packages that are free of known defects, right? So there's like a catalog of known security defects that the industry uses called the National Vulnerability Database, you may have seen the terminology CVE referred to in passing, that's the identifier for these things. So, we work with the open-source maintainers to make sure that we've figured out, mapped out, which versions of software packages are impacted by known security vulnerabilities. And then we also look forward and make sure that we have a plan in place for what happens in the future when there are security vulnerabilities. So, you know, traditional commercial software, there's a security response team, who's kind of standing by 24/7, ready to respond, and then there's a defined protocol of what's going to happen, in terms of what's called responsible disclosure, telling the right folks in the right sequence, that there is a vulnerability causing there to be a patch version of the software available, communicating that through, you know, traditional commercial software vendors for, you know, years have been doing that internally, that doesn't exist by default for volunteer, you know, part-time open source, independent open source maintainers. So we fill that gap and we pre-wire that with them to make sure that that first track security is can be buttoned up. >> So, you're paying them, are you and your co-founders wealthy philanthropists that are just doing this, or what's the business model here? Now you're pulling these people who were doing it for free, they're happy, but how does that translate into a business model for Tidelift. >> Perfect, so, the work that they're doing, you know, I talked a little bit about security, we also do similar things on those other attributes, like licensing, making sure that the licenses are completely accurate, and we kind of know who wrote the software, et cetera, and then maintenance, is it being proactively cared for going forward? Is somebody still on the case with these projects? Now, the result of all of that work, is we create a vetted catalog of known good open source releases that we've vetted with the experts, often the individuals and teams that wrote the code in the first place, usually, we vet that it meets these enterprise standards. That's a really useful tool for organizations that are building with that. So, the way that we convey that to organizations that are building software in a useful way is we have a SAS service software, that as a service platform, that's what Tidelift is, and basically, the teams that use this stuff, they plug us into their software development process, typically alongside other tools that they might have, like CI/CD tools that are running tests on their application logic, they'll plug in Tidelift into their release process to ensure that those, the 70 or 80% of the software that they ship, that comes from GitHub, comes from the Python package index, or NPM, or the Maven Central Repository for Java, we're vetting that that meets their enterprise standards and ensuring that the ingredients, the building blocks that go into their applications are known good and vetted to these concrete standards. And they are, you know, this is an unsolved problem for almost every serious organization. There's a couple of, you know, over-performing organizations, like Google has done some amazing internal work on this, Amazon has an incredible dedicated team that does this internally for Amazon developers, very few other organizations, even some of the largest multinational companies have a dedicated internal function doing this comprehensively and systematically. Tidelift is that function that these organizations can use. They can work with us and our network, our unique network of hundreds of these independent open source maintainers, to ensure that there is a feed of known good vetted packages to go into their applications. >> So, were maintainers going in and auditing, and editing, and vetting software that was essentially created by others? That's one question, and then the other question that kind of goes along with that is, are you vetting a gold copy of something and saying, this software meets certain criteria, you should feel okay using it, that's one thing. Validating that the actual distribution, you know, the actual code that's being executed in their enterprise is secure and hasn't been tampered with is another thing. So where do you sit in that distribution channel or that supply chain? >> Sure, so, on the distribution front, you can think of us, we're sort of a GPS system that your application developers can use to know which versions of software are going to meet your enterprise standards. We don't create a separate world where we have our own, you know, side copy of the entire development ecosystem. It's not what these organizations want. They don't want to use some weird enterprise world set of open source packages, they want to just, you know, type NPM install have the, you know, software flow into their organization, but they also want it to not have no insecurity vulnerabilities in it, and they don't want to get bitten two weeks or two years later with a license violation, because there was kind of fuzzy, or incomplete data around the open source license. So what we do is, we help them consume the open source software, you know, knowing that it's been vetted to these standards. And then we also work with the open source community to cause the software to be changed to meet those standards, right? So back to the first part of your question, We work with a lot of projects with the prime maintainers, often the authors, as I said, and we've actually been extending our model over the years to work with these open source maintainers to cover not just their own project, but, some of those neighboring projects, right? Like the core projects that their project depends on, other projects that are co-used with them, they have a lot of expertise, and also, you know, relationships with the surrounding open source community there. So, they're working with us as curators, if you will, our ambassadors that help us get on the community and cover as much of the landscape as possible. >> And, so, what's the relationship with AWS? This is, you know, we're talking here as part of the AWS startup showcase season two, episode one, which is, that's actually pretty cool. So we need to, you know, the challenge here is, season one was awesome, much like Ted Lasso, season two, we have big shoes to fill here, Donald. So, what's the-- >> We got to up our game. >> (laughs) What's the relationship with AWS? And, I mean, why would they call you out as someone interesting for us to talk to? >> Yeah, so, we've had a great relationship that we've been investing in, and working on together with AWS. So, every one of AWS's customers faces this challenge around the software workloads that they're deploying on AWS. You know, it's just, you can't argue against the fact that the vast majority of the application software in the modern world is comprised majority of this third-party open source software. And so, it's really important whether it's running on a device, you know, an Edge device, or whether it's running in a Cloud data center, that those applications meet these standards, especially on the security front. So, AWS recognizes this need and opportunity for their customers, and so we've been working really well jointly with them. We're glad to say that we're an ISV, and AWS ISV accelerate partner now, which gives us the ability to co-engage with AWS and work together to solve mutual customers challenges, and we've had a great time working with the AWS team to help scale up our efforts to get the word word out around this important area, and then more importantly, give organizations the tools to address it and make sure that they have a comprehensive strategy for managing their open source in place. >> Fantastic, Donald, we're up against time, but I do have a 10 second answer I'd like from you. Tidelift, is that a reference to a rising tide lifting all boats, or is it an admonishment not to build a house on the beach in Malibu? >> It's the former, you know, think about this network of independent open source maintainers, working together, a rising tide lifts all boats. >> Eight seconds, that was like four seconds. Perfect. Donald Fischer, from Tidelift, thank you so much. For me, Dave Nicholson here at the CUBE. This has been a CUBE Conversation, as part of AWS's startup showcase, season two, episode one. Come to the CUBE for the best in tech coverage. (soft music)

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

>>Hey, welcome back to the cubes. Continuing coverage of AWS reinvent 2021. I'm your host, Lisa Martin. This is day two, our first full day of coverage. But day two, we have two life sets here with AWS and its ecosystem partners to remote sets over a hundred guests on the program. We're going to be talking about the next decade of cloud innovation, and I'm pleased to welcome back to cube alumni to the program. Justin Borkman is here, the co-founder and CEO of Starburst and Teresa Tung, the cloud first chief technologist at Accenture guys. Welcome back to the queue. Thank you. Thank you for having me. Good to have you back. So, so Teresa, I was doing some research on you and I see you are the most prolific prolific inventor at Accenture with over 220 patents and patent applications. That's huge. Congratulations. Thank you. Thank you. And I love your title. I think it's intriguing. I'd like to learn a little bit more about your role cloud-first chief technologist. Tell me about, >>Well, I get to think about the future of cloud and if you think about clouded powers, everything experiences in our everyday lives and our homes and our car in our stores. So pretty much I get to be cute, right? The rest of Accenture's James Bond >>And your queue. I like that. Wow. What a great analogy. Just to talk to me a little bit, I know service has been on the program before, but give me a little bit of an overview of the company, what you guys do. What were some of the gaps in the markets that you saw a few years ago and said, we have an idea to solve this? Sure. >>So Starburst offers a distributed query engine, which essentially means we're able to run SQL queries on data anywhere, uh, could be in traditional relational databases, data lakes in the cloud on-prem. And I think that was the gap that we saw was basically that people had data everywhere and really had a challenge with how they analyze that data. And, uh, my co-founders are the creators of an open source project originally called Presto now called Trino. And it's how Facebook and Netflix and Airbnb and, and a number of the internet companies run their analytics. And so our idea was basically to take that, commercialize that and make it enterprise grade for the thousands of other companies that are struggling with data management, data analytics problems. >>And that's one of the things we've seen explode during the last 22 months, among many other things is data, right? In every company. These days has to be a data company. If they're not, there's a competitor in the rear view rear view mirror, ready to come and take that place. We're going to talk about the data mesh Teresa, we're going to start with you. This is not a new car. This is a new concept. Talk to us about what a data mesh is and why organizations need to embrace this >>Approach. So there's a canonical definition about data mesh with four attributes and any data geek or data architect really resonates with them. So number one, it's really routed decentralized domain ownership. So data is not within a single line of business within a single entity within a single partner has to be across different domains. Second is publishing data as products. And so instead of these really, you know, technology solutions, data sets, data tables, really thinking about the product and who's going to use it. The third one is really around self-service infrastructure. So you want everybody to be able to use those products. And finally, number four, it's really about federated and global governance. So even though their products, you really need to make sure that you're doing the right things, but what's data money. >>We're not talking about a single tool here, right? This is more of a, an approach, a solution. >>It is a data strategy first and foremost, right? So companies, they are multi-cloud, they have many projects going on, they are on premise. So what do you do about it? And so that's the reality of the situation today, and it's first and foremost, a business strategy and framework to think about the data. And then there's a new architecture that underlines and supports that >>Just didn't talk to me about when you're having customer conversations. Obviously organizations need to have a core data strategy that runs the business. They need to be able to, to democratize really truly democratized data access across all business units. What are some of the, what are some of your customer conversations like are customers really embracing the data strategy, vision and approach? >>Yeah, well, I think as you alluded to, you know, every business is data-driven today and the pandemic, if anything has accelerated digital transformation in that move to become data-driven. So it's imperative that every business of every shape and size really put the power of data in the hands of everyone within their organization. And I think part of what's making data mesh resonates so well, is that decentralization concept that Teresa spoke about? Like, I think companies acknowledge that data is inherently decentralized. They have a lot of different database systems, different teams and data mesh is a framework for thinking about that. Then not only acknowledges that reality, but also braces it and basically says there's actually advantages to this decentralized approach. And so I think that's, what's driving the interest level in the data mesh, uh, paradigm. And it's been exciting to work with customers as they think about that strategy. And I think that, you know, essentially every company in the space is, is in transition, whether they're moving from on cloud to the prem, uh, to, uh, sorry, from on-prem to the cloud or from one cloud to another cloud or undergoing that digital transformation, they have left behind data everywhere. And so they're, they're trying to wrestle with how to grasp that. >>And there's, we know that there's so much value in data. The, the need is to be able to get it, to be able to analyze it quickly in real time. I think another thing we learned in the pandemic is it real-time is no longer a nice to have. It is essential for businesses in every organization. So Theresa let's talk about how Accenture and servers are working together to take the data mesh from a concept of framework and put this into production into execution. >>Yeah. I mean, many clients are already doing some aspect of the data mesh as I listed those four attributes. I'm sure everybody thought like I'm already doing some of this. And so a lot of that is reviewing your existing data projects and looking at it from a data product landscape we're at Amazon, right? Amazon famous for being customer obsessed. So in data, we're not always customer obsessed. We put up tables, we put up data sets, feature stores. Who's actually going to use this data. What's the value from it. And I think that's a big change. And so a lot of what we're doing is helping apply that product lens, a literal product lens and thinking about the customer. >>So what are some w you know, we often talk about outcomes, everything being outcomes focused and customers, vendors wanting to help customers deliver big outcomes, you know, cost reduction, et cetera, things like that. How, what are some of the key outcomes Theresa that the data mesh framework unlocks for organizations in any industry to be able to leverage? >>Yeah. I mean, it really depends on the product. Some of it is organizational efficiency and data-driven decisions. So just by the able to see the data, see what's happening now, that's great. But then you have so beyond the, now what the, so what the analytics, right. Both predictive prescriptive analytics. So what, so now I have all this data I can analyze and drive and predict. And then finally, the, what if, if I have this data and my partners have this data in this mesh, and I can use it, I can ask a lot of what if and, and kind of game out scenarios about what if I did things differently, all of this in a very virtualized data-driven fashion, >>Right? Well, we've been talking about being data-driven for years and years and years, but it's one thing to say that it's a whole other thing to actually be able to put that into practice and to use it, to develop new products and services, delight customers, right. And, and really achieve the competitive advantage that businesses want to have. Just so talk to me about how your customer conversations have changed in the last 22 months, as we've seen this massive acceleration of digital transformation companies initially, really trying to survive and figure out how to pivot, not once, but multiple times. How are those customer conversations changing now is as that data strategy becomes core to the survival of every business and its ability to thrive. >>Yeah. I mean, I think it's accelerated everything and, and that's been obviously good for companies like us and like Accenture, cause there's a lot of work to be done out there. Um, but I think it's a transition from a storage centric mindset to more of an analytics centric mindset. You know, I think traditionally data warehousing has been all about moving data into one central place. And, and once you get it there, then you can analyze it. But I think companies don't have the time to wait for that anymore. Right there, there's no time to build all the ETL pipelines and maintain them and get all of that data together. We need to shorten that time to insight. And that's really what we, what we've been focusing on with our, with our customers, >>Shorten that time to insight to get that value out of the data faster. Exactly. Like I said, you know, the time is no longer a nice to have. It's an absolute differentiator for folks in every business. And as, as in our consumer lives, we have this expectation that we can get whatever we want on our phone, on any device, 24 by seven. And of course now in our business lives, we're having the same expectation, but you have to be able to unlock that access to that data, to be able to do the analytics, to make the decisions based on what the data say. Are you, are you finding our total? Let's talk about a little bit about the go to market strategy. You guys go in together. Talk to me about how you're working with AWS, Theresa, we'll start with you. And then Justin we'll head over to you. Okay. >>Well, a lot of this is powered by the cloud, right? So being able to imagine a new data business to run the analytics on it and then push it out, all of that is often cloud-based. But then the great thing about data mesh it's it gives you a framework to look at and tap into multi-cloud on-prem edge data, right? Data that can't be moved because it is a private and secure has to be at the edge and on-prem so you need to have that's their data reality. And the cloud really makes this easier to do. And then with data virtualization, especially coming from the digital natives, we know it scales >>Just to talk to me about it from your perspective that the GTL. >>Yeah. So, I mean, I think, uh, data mesh is really about people process and technology. I think Theresa alluded to it as a strategy. It's, it's more than just technology. Obviously we bring some of that technology to bear by allowing customers to query the data where it lives. But the people in process side is just as important training people to kind of think about how they do data management, data analytics differently is essential thinking about how to create data as a product. That's one of the core principles that Theresa mentioned, you know, that's where I think, um, you know, folks like Accenture can be really instrumental in helping people drive that transformational change within their organization. And that's >>Hard. Transformational change is hard with, you know, the last 22 months. I've been hard on everyone for every reason. How are you facilitating? I'm curious, like to get Theresa, we'll start with you, your perspectives on how our together as servers and Accenture, with the power of AWS, helping to drive that cultural change within organizations. Because like we talked about Justin there, nobody has extra time to waste on anything these days. >>The good news is there's that imperative, right? Every business is a digital business. We found that our technology leaders, right, the top 10% investors in digital, they are outperforming are the laggards. So before pandemic, it's times to post pep devek times five, so there's a need to change. And so data is really the heart of the company. That's how you unlock your technical debt into technical wealth. And so really using cloud and technologies like Starburst and data virtualization is how we can actually do that. >>And so how do you, Justin, how does Starburst help organizations transfer that technical debt or reduce it? How does the D how does the data much help facilitate that? Because we talk about technical debt and it can, it can really add up. >>Yeah, well, a lot of people use us, uh, or think about us as an abstraction layer above the different data sources that they have. So they may have legacy data sources today. Um, then maybe they want to move off of over time, um, could be classical data, warehouses, other classical, uh, relational databases, perhaps they're moving to the cloud. And by leveraging Starburst as this abstraction, they can query the data that they have today, while in the background, moving data into the cloud or moving it into the new data stores that they want to utilize. And it sort of hides that complexity. It decouples the end user experience, the business analyst, the data scientists from where the data lives. And I think that gives people a lot of freedom and a lot of optionality. And I think, you know, the only constant is change. Um, and so creating an architecture that can stand the test of time, I think is really, really important. >>Absolutely. Speaking of change, I just saw the announcement about Starburst galaxy fully managed SAS platform now available in all three major clouds. Of course, here we are at AWS. This is a, is this a big directional shift for servers? >>It is, you know, uh, I think there's great precedent within open source enterprise software companies like Mongo DB or confluent who started with a self managed product, much the way that we did, and then moved in the direction of creating a SAS product, a cloud hosted, fully managed product that really I think, expands the market. And that's really essentially what we're doing with galaxy galaxy is designed to be as easy as possible. Um, you know, Starburst was already powerful. This makes it powerful and easy. And, uh, and, and in our view, can, can hopefully expand the market to thousands of potential customers that can now leverage this technology in a, in a faster, easier way, >>Just in sticking with you for a minute. Talk to me about kind of where you're going in, where services heading in terms of support for the data mesh architecture across industries. >>Yeah. So a couple of things that we've, we've done recently, and whether we're doing, uh, as we speak, one is, uh, we introduced a new capability. We call star gate. Now star gate is a connector between Starburst clusters. So you're going to have a Starbucks cluster, and let's say Azure service cluster in AWS, a Starbucks cluster, maybe an AWS west and AWS east. And this basically pushes the processing to where the data lives. So again, living within this construct of, uh, of decentralized data that a data mesh is all about, this allows you to do that at an even greater level of abstraction. So it doesn't even matter what cloud region the data lives in or what cloud entirely it lives in. And there are a lot of important applications for this, not only latency in terms of giving you fast, uh, ability to join across those different clouds, but also, uh, data sovereignty constraints, right? >>Um, increasingly important, especially in Europe, but increasingly everywhere. And, you know, if your data isn't Switzerland, it needs to stay in Switzerland. So starting date as a way of pushing the processing to Switzerland. So you're minimizing the data that you need to pull back to complete your analysis. And, uh, and so we think that's a big deal about, you know, kind of enabling a data mash on a, on a global scale. Um, another thing we're working on back to the point of data products is how do customers curate and create these data products and share them within their organization. And so we're investing heavily in our product to make that easier as well, because I think back to one of the things, uh, Theresa said, it's, it's really all about, uh, making this practical and finding quick wins that customers can deploy, deploy in their data mess journey, right? >>This quick wins are key. So Theresa, last question to you, where should companies go to get started today? Obviously everybody has gotten, we're still in this work from anywhere environment. Companies have tons of data, tons of sources of data, did it, infrastructure's already in place. How did they go and get started with data? >>I think they should start looking at their data projects and thinking about the best data products. I think just that mindset shift about thinking about who's this for what's the business value. And then underneath that architecture and support comes to bear. And then thinking about who are the products that your product could work better with just like any other practice partnerships, like what we have with AWS, right? Like that's a stronger together sort of thing, >>Right? So there's that kind of that cultural component that really strategic shift in thinking and on the architecture. Awesome guys, thank you so much for joining me on the program, coming back on the cube at re-invent talking about data mesh really help. You can help organizations and industry put that together and what's going on at service. We appreciate your time. Thanks again. All right. For my guests, I'm Lisa Martin, you're watching the cubes coverage of AWS reinvent 2021. The cube is the leader in global live tech coverage. We'll be right back.

>>Welcome back to the cubes, continuous coverage of HP es latest Green Lake announcement firehose of innovation. We're seeing a >>cadence >>that HP is delivering in cloud services. Daniel Newman is here, he's the principal analyst at the tour, um, extraordinary research company. Daniel great to see you how you doing man. >>Dave Great to, great to be in person again six ft and safe. But it's good to be back. >>Yeah, it really is uh, been a blur. Right? So we're gonna talk about the pivot to cloud based services. We're seeing that everybody is sort of leaning in HP es all in. I want to talk about value and what this all means to investors. We talk about data, but let me start with the whole as a service move. As I said, everybody's doing it. You see it virtually every companies. Hp was certainly the first to say we're all in, It communicated very well to Wall Street. Everybody's in a debate. No, we were first. No, we were first, but you gotta evaluate based upon the actions that they're taking. How do you look at the trends in this space and how do you look at H. P. S performance? >>Yeah, I admired and Antonio's early pivot, you know, when he got on stage and he said, We're gonna move everything to as a service. I believe that was about two years ago now and the ambition was to have it by 2022. It immediately stood out to me because the momentum, the momentum was behind public cloud, you would have believed three years ago that every workload was going to be in the public cloud and unfortunately guys like us knew that wasn't true. But what we did know was the customers, the enterprise, we're all becoming very comfortable and preference was starting to be shown with that consumption of it meaning subscription based, moving from Capex to apex. That to me was a signal that the timing was right now. Once they got the timing right, it was really about how does this all happened right? It's not necessarily just, we're gonna flip a switch and we're going to start to offer everything as a subscription as a service. There's a lot of standing up those services, putting all that compute all that network, all that storage into a data center, making sure that you have a way to accurately price it and make it quickly consumable, which is something by the way I've admired over the past couple of years, watching the evolution of the software that HP has been rolling. Whether that's Green Lake Central as moral, is that, you know, whether that's kubernetes in the orchestration of hybrid cloud using containers or that's just the ability to spin up a single compute workload in a timely fashion. That's the attraction to public cloud. So, you know, take H P E and its strategy aside and what we have now is you have all of the traditional big iron I T O E M all moving in this direction concurrently. They all understand from both evaluation standpoint meeting Wall Street and also meeting the customer where they are, they have to step up. They had to, uh, whether that was what I was doing with apex Cisco with plus iBMS acquisition of red hat. All these companies were going from, you know, public to private, private to public and then of course you gotta go horizontal from edge to cloud as well. It's a lot to undertake Dave but it's an exciting time and knowing that hybrid is the answer the data is proving that it puts a lot of these companies in a good position to compete. >>Now you mentioned that is the customer preference for good reason. Right? That gives them more flexibility but there's also Wall Street's preference, right? You see that, you know, huge valuations companies like snowflake data, dog elastic. It's that annual recurring revenue that is appealing. They want that they want growth. We saw Q3 hp that did a beaten raise I think 1100 customers for green lake, they announced the orders were up well over 40%. I think revenue was up 30 30 plus percent. So those are the kind of metrics that Wall Street wants to see interestingly though Daniel of course the shift to an A. R. R. Model hurts the income statement but it makes it more predictable and that's what investors today want, what your thoughts. >>Absolutely. I had a chance to speak multiple times over the past few years with the leadership at HP. And it was the exact thing. David that I that I raised, I said you realize that it might be a sidestep or even a half a step backwards before you start to gain momentum. And the real problem with Wall Street is there's no patients. So you mentioned a couple of names like data dog and snowflake. These companies have exponential valuations to earnings because they don't earn anything yet. But most of the market is forward looking and the market tries to anticipate where growth is going to come and saAS companies tend to drive fast growth and fast multiples. This is also left for somewhat slow growth evaluation for companies like HP. Despite the fact that it's doing a lot of the right things you mentioned of course mid double digit growth in green lake, large customer growth numbers. You know, I believe you're serving a billion dollars in revenue or in subscription dollars. Um, fact check that on their >>way to a billion on their way to be honest. I think >>it's booked maybe over >>700 million in revenue that way. >>And so as all those, the confluence of all those events, the market has to be able to basically cherry pick though a part of the business. And I think that's been a little bit of a problem. Not just for HP, but just for all these companies that are, that are struggling with smaller multiples of their P. E ratios. This is true for Cisco? This is true for IBM this is true for for HP and I'll kind of close my thought here. But as the company continues to talk about green Lake and it continues to lean into this, this is the part that has to rise to the front front of the Wall Street investor of the business media to say that existing part of the business is stable, It's solid. They have great customers. However, concurrently the part of the business that is the future, the subscription part that attaches to the public cloud that is enabling companies to grow. That is where they're at. And that is why we see more value. There's a lot of value to unlock and it's because, you know, these small multiples and the business is heading in what I believe is the right >>direction. And HPV last quarter cited, they hit almost 35% gross margin, which is, which is a high mark, high water mark for them if you extract VM ware out of Dell there in the mid twenties. So these are two different businesses and I think that's a big reason why Dell's moving into the space. I almost think like the board conversation at HP was, hey, let's, let's not keep thinking about building boxes. Let's build services and let's add value to those services that are software based and then we can kind of control our own destiny as opposed to kind of intel getting all the margins and or M. D. Or whatever it is. So so that so how do you see as a service driving value for H. P. E. It's customers and ultimately what do they have to do to convince Wall street >>recurring revenue companies drive higher multiples? It's not even a debate and companies that have a large percentage of their business as recurring tend to drive much higher evaluation and tend to also be more beloved by shareholders. The performance of HP has been good, it's been solid, it's been in the right place especially given the circumstances of the pandemic and the impact of on prem it we all saw the explosion of SAS the explosion of cloud, you know, SAS and chips are hot, they're always hot. But everything that was sort of sandwiched in the middle became a little bit more murky throughout the pandemic times. And the ability for HP. And these companies that are in this space are operating to be able to bridge this gap. The companies have 25 or so percent of workload during the public cloud. That means the rest need services from companies like HP. So the tam is growing because the overall size of the workload, the volumes of data are all growing exponentially and that's an opportunity but the market wants to see fast growth. Dave I mean they're not going to accept the single digit overall growth if you want to get the kind of multiples of a, you know, even a Microsoft at a 40 or a sales force at 100. But HPV with its software is starting to play in those spaces where investors in the market maybe can start to recognize that it is undervalued. >>So we live in a data centric world, Antonio talks about this all the time and we're seeing HP makes some moves in terms of data data management, you see what they're doing with his moral and that's a big part of the software place. So to the extent that you can lean into that wave have a higher contribution from software, higher margin business obviously and a more predictable revenue stream. That seems to be the right direction in my view. Um it's gonna take some time to play out. They're not gonna overnight, you know, they don't have a green sheet of paper, they clean sheet of paper, they have a business that they have to manage and they have to service their customers. But to the extent that the majority of their business over time can become as a service, shouldn't that confer higher margins and and greater value to investors? Yeah, it's sticky >>for enterprise users when you move to that subscription model, it's not as easy as just lifting and shifting you build your entire business process around these investments in these technologies. Software. It's sticky, it's organizationally complex because where HP sits in the stack, where their analytic solutions and software help you more successfully deploy S. A. P type workloads. The entire company runs on that. So the involvement and the importance of the role that HP is playing is huge. The challenge for customers isn't as big customers get this, the enterprise users, the C I O. S. They get the importance Wall Street though it's a little harder for them sometimes to digest. Whereas they might be looking at something like a snowflake that you mentioned. That's fairly straightforward. Almost all of its revenue is pure subscription and it's looked at as 20 years in a perpetuity where people are still trying to wonder is HP gonna be sticky? Are these customers not only going to keep with HP but are they going to increase? Right. Is that net revenue expansion going to take place across the portfolio? And HP rolls out more services right. Started with storage and then it moves to compute and then it adds edge layer services. Are people going to buy the whole stack? Because that of course, also as we've seen with some of the bigger players can be an extremely attractive value proposition. >>Well, I also think as they move into cloud, HP has always been about optionality. So I feel as though with their day to play, for example, they can get deeper into data management but they can also partner with others, you're leaning into open source so that means you can expand your portfolio that's kind of what the cloud game is is you know, here's the cloud, we got all these different options, choose what you want, we'll manage it for you, charge you for that but we'll take away that headache. That's a good business, >>choose your own cloud adventure last week oracle reported. Um and I'm only pointing this out because you know, you look at the company and everybody was what's with their i as number? Why is it not big or smaller? Why don't we know right. But over the last couple of years we've realized that it's no longer little seeing big see little C which I would call infrastructure as a service no longer exists. Cloud is one big number. So H P E being in the cloud through its hybrid services, its software, its platform support is just as much about being in the cloud is a company that offers I. S. Or company that offers SAs however convincing the market that this is the case is the trick. We're starting to see companies because you you hear when IBM reports how their numbers are, you know, they're they're tying in all kinds of global business services and they're tying in you know, red hat numbers and they're telling in their public cloud numbers but what I'm saying is up to this point, a lot of these hybrid services are kind of not necessarily being bucket ID like this big sea of cloud but it really is the entire stack of of infrastructure platform software and then of course all those attached services for companies to deploy this that equal a cloud number. And so the subscription number grows. Green Lakes customer account grows. And I think convincing the street and everybody in between that this is a cloud number and not a on prem or a attached to the cloud number is going to really help boomer boom, the overall value that people see and what HP is doing. >>And I think not only H P E but I think others are I think finally they're starting to realize that wow, you know, we all know everything is not going to public cloud. We understand it's a hybrid world Public cloud spend a company's the hyper scale is collectively spent $100 billion dollars last year on Capex. That's like a gift to a company like HP that can connect the dots and create that abstraction layer that hides the underlying complexity. We'll take care of that for you will make everything cloud native. We can bring cloud native on prem and go out to the edge, which is like the Wild West that is a that's a trillion dollar opportunity that there's no limit to market potential for companies out there and HP specifically. >>Well the edges a massive opportunity and that's what I said, you know, a lot of us are and we do this ourselves as both analysts and sometimes media personalities is we like to debate how big the opportunity of cloud is. And of course there are some firms that try to market size this, but I actually think it's extraordinarily difficult to market sizes, especially because of the edge. You talk about data and analytics. I recently attended the a event. It's a car event in Munich and you just look at the amount of data that vehicles are going to be creating in the in the coming years. They're basically massive rolling data centers full of chips, compute networking storage. This is all going to take significant infrastructure investments at scale and it's creating this humongous opportunity at the edge and you look at five Gs impact and as we roll out five G it's scale. Every one of these things brings more data connects, more devices and all that intelligence needs infrastructure, It needs software, it needs services. So the overall tam Dave is going to continue to grow and I think if anything it tends to be underestimated because it's really hard to define just how big the data equation is actually going to be in the market. >>Digital changes the equation. It's not, it's no longer servers, storage, networking database, its cloud services that are enabling digital transformations. I'll give you one more >>thing that just crossed my mind. But I think is important is if you even look at the the S. G. And sustainability efforts that most companies are going to be taking the amount of investment in trying to capture, comprehend manage just the data and analytics to understand your footprint and understand how you are going to achieve carbon neutrality and how you're going to do this up and down. And I mean that's just one thing and of course that's a, I wouldn't call it table stakes at this point, the market expects every company to be making this kind of investment well, when you run a multi national global enterprise that has edge, that has data centers that has manufacturing facilities, there is just unbelievable requirements on technology. And again, we've got to connect that public cloud somehow. So we can't ignore the fact that those public cloud players are all addressing this, they're all bringing solutions out. But companies like HP, this is where their sweet spot is, and this is where I believe they're going to have to compete very aggressively and efficiently to show we are a great partner to the public cloud, but our legacy and our capabilities mean we understand this part of the business, we believe we're the right fit and trust me, the Azure and AWS are, they're not going to make this easy, they're going to be competitive but they're also going to going to be very cooperative >>well, and they're coming into the home court of the on prem vendors. So that's gonna be interesting to see how that plays out as an observer, as an analyst, what do you want to see from HP, Green Lake cloud services? What are the, what are the areas that you're gonna be watching that could serve as indicators of success and momentum? >>Well, we didn't even talk because we did talk about some of that, but we didn't even talk about aI and amount for instance, all this data itself has to be managed and processed. So the fact that you're getting to that data management at scale, the fact that you're building out orchestration for containers. Well this is because of that data delusion conundrum, whatever word we want to use for it. But the best companies in the world are going to find a way to extract more value from that data and that's going to be through the application of aI of ml of neural networks, deep learning and other important capabilities. Having a foot into that Dave is something I want to see HP and it already does, but I want to see the participation there. This is an area that I think public cloud is doing really well there. They really made big investments both with homegrown chips with partnering with the likes of videos and intel to, to offer a lot of enhancement acceleration, um Ml and AI services. I think this is gonna be an area that on prem and through hybrid offerings. We're gonna want to see the company compete. Uh and then of course, I think back to the one thing Dave, I'll just kind of wrap on this, is that that customer growth, I mean you talked about how to get evaluation, how to get the street up, people get excited about overall growth. They need to get that narrative carved out about green, like about the subscription growth, the service growth point next and all that stuff, but all that has to start to equate to overall growth. Um you know, I think it needs to be made at least single high digits, single overall percentage growth, especially because the whole portfolio supposed to be there. You know, companies get those big multiples are growing >>fast growth on, on that large of a base would get people's attention. You mentioned custom chips, H P >>E, you >>know, H P S H P S heritage and HP. They have chops in custom silicon. So be interesting to see if, if you know the future, you talk about ai inference at the edge, huge disruptive potential opportunities and I'm really curious as to see how that plays out because that is another trillion dollar market opportunity. Daniel, thanks so much for coming to the cubes. Great to have you looking forward to working with you in the future. >>Yeah, it's great to be here. And sorry, we didn't get to those chips earlier. We could have gone down a whole, another whole, another >>half hour. Great, great to talk to you. All right, thank you for watching everybody. This is the cubes, continuous coverage of HBs, Big Green Lake announcement. Keep it right there for more, great content. Mhm.

(intro music) >> We're back on theCUBE unpacking HPE's GreenLake announcements. I'm here with Keith Townsend, the CTO advisor. Keith, always awesome to see you, man. >> Good to be back on theCUBE. >> So, let's talk about these announcements. Let's break it down. Where do you want to start? >> So-- >> Cloud services? >> Cloud services, one of the things that we've gone back and forth with HPE over the past few years is that I don't understand GreenLake. Like, is it a financial scheme? Is it a cloud services? And I think data services, the data services announcement around Zirdle and Marketplace really elevates GreenLake to a cloud service. Kind of on par with some of the hyperscalers on how they think about architectures around data centers and, and fabrics and services to enterprise customers. >> When you say on, par in what regard? >> So, one of the things I didn't get, separate to the GreenLake announcement, we've heard a lot about HPE's containers services, Ezmeral, and they have a data fabric and it does things that the storage solutions does. Okay. That seems like a marketplace upon itself. And then the data services with the Zirdle acquisition, completely different marketplace? No, HPE is bringing all of that together, logically. So a cloud architect, similar to how they could go to AWS's console, select some services, deploy those services in their AWS VPC. Now, I can conceptually do that with HPE. I can go to HPE's GreenLake console, choose the services I need to build my app, and deploy it. That is something new within all these traditional OEM providers. >> Because of the cloud nativeness on-prem, bringing that capability. >> So, bringing the Aruba Central concepts, you know, Aruba Central, I think I read a stat, a hundred thousand customers on Aruba Central with a million interactions an hour. So this scale is hyperscale scale. This base to have a centralized marketplace and have those on those cloud-like services, but on-premises or in Niccolo, I think puts HPE near the top, if not the top for building private cloud services on-premises. >> Lets say you're a CTO at an organization that's an HPE customer or an architect. You're all in, on HPE, been working with the company for a long, long time. Wouldn't you want a view of your estate, your applications and workloads, where you could manage on-prem, Cloud, whether it's AWS, Azure, Google, take advantage of the cloud native, go across cloud, abstract all that complexity away, maybe eventually go out to the edge. Is that what you want? >> That's what I want, it's aspirational. No one between Microsoft to HPE, no one is able to give me that today. So as a CTO, I'm looking at platforms and seeing is the building blocks there. We talked to the HP storage team of how they're building the abstractions, that they can take anything from their ProLiant line, build the necessary storage underlay, and then abstract that away with a GreenLake. You can do that with AWS EBC, Azure storage. It really doesn't matter because they're building that abstractions. So, aspirationally they're there, they have the right vision. It's about excecution. >> Okay, so that is the right direction in your view, you, I mean, I think that that is clearly where customers want to go. >> A lot of work >> Keith: A lot of work. to get there, and it's a race, right? I mean, that's, you know, I feel as though, as a service is good starting point, but there's, there's a long way to go. And, so how do you feel about HPE's chances there, how they're positioning relative to not only the, there other sort of on-prem competitors, but public cloud players. >> So they're asking the right questions. They're asking the right questions of the right players. It's about relationships. Dave, you know this more than anyone that if you don't have the right relationships inside of the customers, you're not going to get there. And I think that's HPE's number one struggle. The, no slant to the VP of operations, but the VP of operations doesn't want to change his operations. He doesn't want disruption. What COO was coming to you and saying, "I want to be disruptive." Same thing in VP of operations, IT operations, they don't want disruption, but this has been HPE's traditional customer. HPE needs to get into the chief data officers, the chief marketing officers' office, and have these very difficult conversations in sales so that they can eventually show that they can't execute. I think that's the one of their primary challenges. >> So, okay that's good. I'm glad you brought that up because I think Ezmeral starts to go in that direction, it feels as though the first phase is let's pick off analytics. Let's make analytics on-prem as attractive and simple as it is in the cloud. And then, beyond that, let's support this notion of decentralized data and federated governance. And that is aspirational today. But no, as to your point, nobody really has that. AWS really, you know, they're not going after that, across clouds at this point in time, Microsoft is with arc, I guess, and Google kind of has Anthos and they're kind of doing it, but, but yeah, I'm not sure you're going to trust your cloud provider to be that player. So it's kind of like jump ball here, isn't it? >> You know, AWS make a strategic partnership with one of HP's primary competitors, because there was a gap. We know Andy Jassy, former president and CEO of AWS, doesn't typically partner with traditional OEMs, unless there's a real gap in his portfolio that he needed to do and he did it with VMware and he did it with HPE's primary competitor in storage and one of their primary competitors in storage. HPE sees the opportunity. The question is, do they have the workforce? Do they have the field teams, the field CTOs, the solution architects that can go and talk the talk to these customers and this new audience that they need to convince that HPE is just as, as respected a snowflake in these, in this data area. >> Can partners fill that gap? >> Partners definitely can fill that gap, but HPE still has the same challenge for partners: transforming partners from speaking boxes to solutions. I've spent a short stint at VMware. I was surprised at how rigid the channel is and these large organizations and making that transition. >> The other thing, when you think about it as a service that at least that I look for when, if you could comment is the pace, you know, we all would go to, we go to these events, go to re-invent and it's just this fire hose of announcements. We're seeing HPE on a cadence. You know, it's not like a once a year dealio with GreenLake. We're seeing, you know, some stuff with HPC. We're seeing the acquisition of Zerto of the, the DR services, the data protection as a service, Ezmeral. Do you feel like that pace is accelerating? And is it fast enough? >> You know what, I famously said on theCUBE that VMware moves at the pace of the CIO. HPE needs to move a little bit faster than the CIO because the CIO isn't their only customer. They have the opportunity to get customers outside of the CIO and I think they're moving fast enough. This is really hard stuff. Especially when you start to deal with data and the most valuable asset of an organization. Can you move too fast? You absolutely can. One of the other analysts said that you don't want to become the, the forgotten about data services company of the other, of the two thousands. You don't want to make that mistake in the twenties. So I, right now, I think I feel as if HPE is making the right cadence, bringing along their old customers, new customers. Challenge of all of the big OEMs is how do you not erode your base customer base and, but still move fast enough to satisfy the move fast break stuff crowd. >> Keep close to your customers. Keith, we got to leave it there. Thanks so much for coming back on theCUBE. >> I'd love to have you back. >> As always, Dave, great time. All right. And thank you for watching. Keep it right there for more great content from HPE GreenLake announcements. You're watching theCUBE.