(bright upbeat music) >> Well, hello everybody. John Walls is here on "the CUBE". Great to have you with us as we continue our series here at the AWS Executive Summit sponsored by Accenture. And today we're talking about public service and not just a little slice of public service but probably the largest public sector offering in the UK and for with us or with us. Now to talk about that is Lianne Anderton, who is in with the Intelligent Automation Garage Delivery Lead at the UK Department of Work and Pension. Lianne, good to see you today. Thanks for joining us here on "the CUBE". >> Hi, thanks for having me. >> And also with this us is Amar Narayan, who is a Manager Director at Accenture the AWS Business Group for the Lead in Health and Public Sector, also UK and Ireland. And Amar, I think, you and Lianne, are in the same location, Newcastle, I believe in the UK, is that right? >> Yeah, absolutely. Yep, yeah, we're, here in the northeast of UK. >> Well, thank you for being with us. I appreciate the time. Lianne, let's talk about what you do, the Department of Work and Pension, the famous DWP in England. You have influence or certainly touchpoints with a huge amount of the British population. In what respects, what are you doing for the working class in England and what does technology have to do with all that? >> Sure, so for the Department for Work and Pensions I think the pensions bit is fairly self explanatory so anybody who is over state pension age within the UK. for the work part of that we also deal with people of working age. So, these are people who are either in employment and need additional help through various benefits we offer in the UK. Those people who are out of work. And we also deal with health related benefits as well. And we are currently serving over 20 million claimants every year at this moment in time. So, we're aware of a huge part of the UK government. >> All right, so say that number again. How many? >> 20 million claimants every year. >> Million with an M, right? >> Yeah. >> So, and that's individuals. And so how many transactions, if you will, how many do you think you process in a month? How, much traffic basically, are you seeing? >> An extraordinary amount? I'm not even, I don't think I even know that number. (Lianne laughing) >> Mind blowing, right? So, it's- >> A huge, huge amount. >> Mind blowing. >> Yeah, so, basically the we kind of keep the country going. So, you know, if the department for Work and Pensions kind of didn't exist anymore then actually it would cause an infinite number of problems in society. We, kind of help and support the people who need that. And, yeah, so we play a really vital role in kind of you know, social care and kind of public service. >> So, what was your journey to Accenture then? What, eventually led you to them? What problem were you having and how have you collaborated to solve that? >> So, in terms of how we work with Accenture. So, we had in around 2017 DWP was looking at a projected number of transactions growing by about 210 million which was, you know, an extraordinary amount. And, you know, I think as we've kind of covered everything that we do is on a massive scale. So, we as DWP as an organization we had absolutely no idea how we were going to be able to handle such a massive increase in the transactions. And actually, you know, after kind of various kind of paths and ideas of how we were going to do that, automation, was actually the answer. But the problem that we have with that is that we have, like many governments around the world, we have really older legacy systems. So, each of these benefits that we deal with are on legacy systems. So, whatever we were going to develop had to, you know, connect to all of these, it had to ingest and then process all of these pieces of data some of which, you know, given the fact that a lot of these systems have a lot of manual input you have data issues there that you have to solve and whatever we did, you know, as we've talked about in terms of volumes has to scale instantly as well. So, it has to be able to scale up and down to meet demand and, you know, and that down scaling is also equally as important. So yeah, you've got to be able to scale up to meet the volumes but also you've got to be able to downscale when when it's not needed. But we had nothing that was like that kind of helped us to meet that demand. So, we built our own automation platform, The Intelligent Automation Garage and we did that with Accenture. >> So Amar, I'd like you to chime in here then. So, you're looking at this client who has this massive footprint and obviously vital services, right? So, that's paramount that you have to keep that in mind and the legacy systems that Lianne was just talking about. So, now you're trying to get 'em in the next gen but also respecting that they have a serious investment already in a lot of technology. How do you approach that kind of problem solving, those dynamics and how in this case did you get them to automation as the solution? >> Sure, so I think I think one of the interesting things, yeah as Lianne has sort of described it, right? It's effectively like, you know the department has to have be running all of the time, right? They can't, you know, they can't effectively stop and then do a bunch of IT transformation, you know it's effectively like, you know, changing the wheels of a jumbo jet whilst it's taking off, right? And you've got to do all of that all in one go. But what I think we really, really liked about the situation that we were in and the client relationship we had was that we knew we had to it wasn't just a technology play, we couldn't just go, "All right, let's just put some new technology in." What we also needed to do was really sort of create a culture, an innovation culture, and go, "Well how do we think about the problems that we currently have and how do we think about solving them differently and in collaboration, right?" So, not just the, "Let's just outsource a bunch of technology for to, you know, to Accenture and build a bunch of stuff." So, we very carefully thought about, well actually, the unique situation that they're in the demands that the citizens have on the services that the department provide. And as Lianne mentioned, that technology didn't exist. So, we fundamentally looked at this in a different way. So, we worked really closely with the department. We said, Look, actually what we ultimately need is the equivalent of a virtual workforce. Something where if you already, you know all of a sudden had a hundred thousand pension claims that needed to be processed in a week that you could click your fingers and, you know in a physical world you'd have another building all of your kits, a whole bunch of trained staff that would be able to process that work. And if in the following week you didn't need that you no longer needed that building that stuff or the machinery. And we wanted to replicate that in the virtual world. So, we started designing a platform we utilized and focused on using AWS because it had the scalability. And we thought about, how were we going to connect something as new as AWS to all of these legacy systems. How are we going to make that work in the modern world? How are we going to integrate it? How we going to make sure it's secure? And frankly, we're really honest with the client we said, "Look, this hasn't been done before. Like, nowhere in Accenture has done it. No one's done it in the industry. We've got some smart people, I think we can do it." And, we've prototyped and we've built and we were able to prove that we can do that. And that in itself just created an environment of solving tricky problems and being innovative but most importantly not doing sort of proof of concepts that didn't go anywhere but building something that actually scaled. And I think that was really the real the start of what was has been the Garage. >> So, And Lianne, you mentioned this and you just referred to it Amar, about The Garage, right? The Intelligent Automation Garage. What exactly is it? I mean, we talked about it, what the needs are all this and that, but Lianne, I'll let you jump in first and Amar, certainly compliment her remarks, but what is the IAG, what's the... >> So, you know, I think exactly what kind of Amar, has said from a from a kind of a development point of view I think it started off, you know, really, really small. And the idea is that this is DWP, intelligent automation center of excellence. So, you know, it's aims are that, you know, it makes sure that it scopes out kind of the problems that DWP are are facing properly. So, we really understand what the crux of the problem is. In large organizations It's very easy, I think to think you understand what the problem is where actually, you know, it is really about kind of delving into what that is. And actually we have a dedicated design team that really kind of get under the bonnet of what these issues really are. It then kind of architects what the solutions need to look like using as Amar said, all the exciting new technology that we kind of have available to us. That kind of sensible solution as to what that should look like. We then build that sensible solution and we then, you know as part of that, we make sure that it scales to demand. So, something that might start out with, I dunno, you know a few hundred claimants or kind of cases going through it can quite often, you know, once that's that's been successful scale really, really quickly because as you know, we have 20 million claimants that come through us every year. So, these types of things can grow and expand but also a really key function of what we do is that we have a fully supported in-house service as well. So, all of those automations that we build are then maintained and you know, so any changes that kind of needed to be need to be made to them, we have all that and we have that control and we have our kind of arms wrapped around all of those. But also what that allows us to do is it allows us to be very kind of self-sufficient in making sure that we are as sufficient, sorry, as efficient as possible. And what I mean by that is looking at, you know as new technologies come around and they can allow us to do things more effectively. So, it allows us to kind of almost do that that kind of continuous improvement ourselves. So, that's a huge part of what we do as well. And you know, I think from a size point of view I said this started off really small as in the idea was this was a kind of center of excellence but actually as automation, I think as Amar alluded to is kind of really started to embed in DWP culture what we've started to kind of see is the a massive expansion in the types of of work that people want us to do and the volume of work that we are doing. So, I think we're currently running at around around a hundred people at the moment and I think, you know we started off with a scrum, a couple of scrum teams under Amar, so yeah, it's really grown. But you know, I think this is here to stay within DWP. >> Yeah, well when we talk about automation, you know virtual and robotics and all this I like to kind of keep the human element in mind here too. And Amar, maybe you can touch on that in certain terms of the human factors in this equation. 'Cause people think about, you know, robots it means different things to different people. In your mind, how does automation intersect with the human element here and in terms of the kinds of things Lianne wants to do down the road, you know, is a road for people basically? >> Oh yeah, absolutely. I think fundamentally what the department does is support people and therefore the solutions that we designed and built had to factor that in mind right? We were trying to best support and provide the best service we possibly can. And not only do we need to support the citizens that it supports. The department itself is a big organization, right? We're up to, we're talking between sort of 70 and 80,000 employees. So, how do we embed automation but also make the lives of the, of the DWP agents better as well? And that's what we thought about. So we said, "Well look, we think we can design solutions that do both." So, a lot of our automations go through a design process and we work closely with our operations team and we go, well actually, you know in processing and benefit, there are some aspects of that processing that benefit that are copy and paste, right? It doesn't require much thought around it, but it just requires capturing data and there's elements of that solution or that process that requires actual thought and understanding and really empathy around going, "Well how do I best support this citizen?" And what we tended to do is we took all of the things that were sort of laborious and took a lot of time and would slow down the overall process and we automated those and then we really focused on making sure that the elements that required the human, the human input was made as user friendly and centric as we possibly could. So, if there's a really complex case that needs to be processed, we were able to present the information in a really digestible and understandable way for the agents so that they could make a informed and sensible decision based around a citizen. And what that enabled us to do is essentially meet the demands of the volumes and the peaks that came in but also maintain the quality and if not improve, you know the accuracy of the claims processing that we had. >> So, how do you know, and maybe Lianne, you can address this. How do you know that it's successful on both sides of that equation? And, 'cause Amar raised a very good point. You have 70 to 80,000 employees that you're trying to make their work life much more efficient, much simpler and hopefully make them better at their jobs at the end of the day. But you're also taking care of 20 million clients on the, your side too. So, how do you, what's your measurement for success and what kind of like raw feedback do you get that says, "Okay, this has worked for both of our client bases, both our citizens and our employees?" >> Yeah, so we can look at this both from a a quantitative and a qualitative point of view as well. So, I think from a let take the kind figures first. So we are really hot on making sure that whatever automations we put in place we are there to measure how that automation is working what it's kind of doing and the impact that it's having from an operational point of view. So I think, you know, I think the proof of the fact that the Intelligent Automation Garage is working is that, you know, in the, in its lifetime, we've processed over 20 million items and cases so far. We have 65 scaled and transitioned automations and we've saved over 2 million operational hours. I was going to say that again that's 2 million operational hours. And what that allows us to do as an organization those 2 million hours have allowed us to rather than people as Amar, said, cutting and pasting and doing work that that is essentially very time consuming and repetitive. That 2 million hours we've been able to use on actual decision making. So, the stuff that you need as sentient human being to make judgment calls on and you know and kind of make those decisions that's what it's allowed us as an organization to do. And then I think from a quality point of view I think the feedback that we have from our operational teams is, you know is equally as as great. So, we have that kind of feedback from, you know all the way up from to the director level about, you know how it's kind of like I said that freeing up that time but actually making the operational, you know they don't have an easy job and it's making that an awful lot easier on a day to day basis. It has a real day to day impact. But also, you know, there are other things that kind of the knock on effects in terms of accuracy. So for example, robot will do is exactly as it's told it doesn't make any mistakes, it doesn't have sick days, you know, it does what it says on the tin and actually that kind of impact. So, it's not necessarily, you know, counting your numbers it's the fact that then doesn't generate a call from a customer that kind of says, "Well you, I think you've got this wrong." So, it's all that kind of, these kind of ripple effects that go out. I think is how we measure the fact that A, the garage is working and b, it's delivering the value that we needed to deliver. >> Robots, probably ask better questions too so yeah... (Lianne laughing) So, real quick, just real quick before you head out. So, the big challenge next, eureka, this works, right? Amar, you put together this fantastic system it's in great practice at the DWP, now what do we do? So, it's just in 30 seconds, Amar, maybe if you can look at, be the headlights down the road here for DWP and say, "This is where I think we can jump to next." >> Yeah, so I think, what we've been able to prove as I say is that is scaled innovation and having the return and the value that it creates is here to stay, right? So, I think the next things for us are a continuous expand the stuff that we're doing. Keeping hold of that culture, right? That culture of constantly solving difficult problems and being able to innovate and scale them. So, we are now doing a lot more automations across the department, you know, across different benefits across the digital agenda. I think we're also now becoming almost a bit of the fabric of enabling some of the digital transformation that big organizations look at, right? So moving to a world where you can have a venture driven architectures and being able to sort of scale that. I also think the natural sort of expansion of the team and the type of work that we're going to do is probably also going to expand into sort of the analytics side of it and understanding and seeing how we can take the data from the cases that we're processing to overall have a smoother journey across for our citizens. But it's looking, you know, the future's looking bright. I think we've got a number of different backlogs of items to work on. >> Well, you've got a great story to tell and thank you for sharing it with us here on "the CUBE", talking about DWP, the Department of Work and Pensions in the UK and the great work that Accenture's doing to make 20 million lives plus, a lot simpler for our friends in England. You've been watching ""the CUBE"" the AWS Executive Summit sponsored by Accenture. (bright upbeat music)

(bright upbeat music) >> Well, hello everybody. John Walls is here on "the CUBE". Great to have you with us as we continue our series here at the AWS Executive Summit sponsored by Accenture. And today we're talking about public service and not just a little slice of public service but probably the largest public sector offering in the UK and for with us or with us. Now to talk about that is Lianne Anderton, who is in with the Intelligent Automation Garage Delivery Lead at the UK Department of Work and Pension. Lianne, good to see you today. Thanks for joining us here on "the CUBE". >> Hi, thanks for having me. >> And also with this us is Amar Narayan, who is a Manager Director at Accenture the AWS Business Group for the Lead in Health and Public Sector, also UK and Ireland. And Amar, I think, you and Lianne, are in the same location, Newcastle, I believe in the UK, is that right? >> Yeah, absolutely. Yep, yeah, we're, here in the northeast of UK. >> Well, thank you for being with us. I appreciate the time. Lianne, let's talk about what you do, the Department of Work and Pension, the famous DWP in England. You have influence or certainly touchpoints with a huge amount of the British population. In what respects, what are you doing for the working class in England and what does technology have to do with all that? >> Sure, so for the Department for Work and Pensions I think the pensions bit is fairly self explanatory so anybody who is over state pension age within the UK. for the work part of that we also deal with people of working age. So, these are people who are either in employment and need additional help through various benefits we offer in the UK. Those people who are out of work. And we also deal with health related benefits as well. And we are currently serving over 20 million claimants every year at this moment in time. So, we're aware of a huge part of the UK government. >> All right, so say that number again. How many? >> 20 million claimants every year. >> Million with an M, right? >> Yeah. >> So, and that's individuals. And so how many transactions, if you will, how many do you think you process in a month? How, much traffic basically, are you seeing? >> An extraordinary amount? I'm not even, I don't think I even know that number. (Lianne laughing) >> Mind blowing, right? So, it's- >> A huge, huge amount. >> Mind blowing. >> Yeah, so, basically the we kind of keep the country going. So, you know, if the department for Work and Pensions kind of didn't exist anymore then actually it would cause an infinite number of problems in society. We, kind of help and support the people who need that. And, yeah, so we play a really vital role in kind of you know, social care and kind of public service. >> So, what was your journey to Accenture then? What, eventually led you to them? What problem were you having and how have you collaborated to solve that? >> So, in terms of how we work with Accenture. So, we had in around 2017 DWP was looking at a projected number of transactions growing by about 210 million which was, you know, an extraordinary amount. And, you know, I think as we've kind of covered everything that we do is on a massive scale. So, we as DWP as an organization we had absolutely no idea how we were going to be able to handle such a massive increase in the transactions. And actually, you know, after kind of various kind of paths and ideas of how we were going to do that, automation, was actually the answer. But the problem that we have with that is that we have, like many governments around the world, we have really older legacy systems. So, each of these benefits that we deal with are on legacy systems. So, whatever we were going to develop had to, you know, connect to all of these, it had to ingest and then process all of these pieces of data some of which, you know, given the fact that a lot of these systems have a lot of manual input you have data issues there that you have to solve and whatever we did, you know, as we've talked about in terms of volumes has to scale instantly as well. So, it has to be able to scale up and down to meet demand and, you know, and that down scaling is also equally as important. So yeah, you've got to be able to scale up to meet the volumes but also you've got to be able to downscale when when it's not needed. But we had nothing that was like that kind of helped us to meet that demand. So, we built our own automation platform, The Intelligent Automation Garage and we did that with Accenture. >> So Amar, I'd like you to chime in here then. So, you're looking at this client who has this massive footprint and obviously vital services, right? So, that's paramount that you have to keep that in mind and the legacy systems that Lianne was just talking about. So, now you're trying to get 'em in the next gen but also respecting that they have a serious investment already in a lot of technology. How do you approach that kind of problem solving, those dynamics and how in this case did you get them to automation as the solution? >> Sure, so I think I think one of the interesting things, yeah as Lianne has sort of described it, right? It's effectively like, you know the department has to have be running all of the time, right? They can't, you know, they can't effectively stop and then do a bunch of IT transformation, you know it's effectively like, you know, changing the wheels of a jumbo jet whilst it's taking off, right? And you've got to do all of that all in one go. But what I think we really, really liked about the situation that we were in and the client relationship we had was that we knew we had to it wasn't just a technology play, we couldn't just go, "All right, let's just put some new technology in." What we also needed to do was really sort of create a culture, an innovation culture, and go, "Well how do we think about the problems that we currently have and how do we think about solving them differently and in collaboration, right?" So, not just the, "Let's just outsource a bunch of technology for to, you know, to Accenture and build a bunch of stuff." So, we very carefully thought about, well actually, the unique situation that they're in the demands that the citizens have on the services that the department provide. And as Lianne mentioned, that technology didn't exist. So, we fundamentally looked at this in a different way. So, we worked really closely with the department. We said, Look, actually what we ultimately need is the equivalent of a virtual workforce. Something where if you already, you know all of a sudden had a hundred thousand pension claims that needed to be processed in a week that you could click your fingers and, you know in a physical world you'd have another building all of your kits, a whole bunch of trained staff that would be able to process that work. And if in the following week you didn't need that you no longer needed that building that stuff or the machinery. And we wanted to replicate that in the virtual world. So, we started designing a platform we utilized and focused on using AWS because it had the scalability. And we thought about, how were we going to connect something as new as AWS to all of these legacy systems. How are we going to make that work in the modern world? How are we going to integrate it? How we going to make sure it's secure? And frankly, we're really honest with the client we said, "Look, this hasn't been done before. Like, nowhere in Accenture has done it. No one's done it in the industry. We've got some smart people, I think we can do it." And, we've prototyped and we've built and we were able to prove that we can do that. And that in itself just created an environment of solving tricky problems and being innovative but most importantly not doing sort of proof of concepts that didn't go anywhere but building something that actually scaled. And I think that was really the real the start of what was has been the Garage. >> So, And Lianne, you mentioned this and you just referred to it Amar, about The Garage, right? The Intelligent Automation Garage. What exactly is it? I mean, we talked about it, what the needs are all this and that, but Lianne, I'll let you jump in first and Amar, certainly compliment her remarks, but what is the IAG, what's the... >> So, you know, I think exactly what kind of Amar, has said from a from a kind of a development point of view I think it started off, you know, really, really small. And the idea is that this is DWP, intelligent automation center of excellence. So, you know, it's aims are that, you know, it makes sure that it scopes out kind of the problems that DWP are are facing properly. So, we really understand what the crux of the problem is. In large organizations It's very easy, I think to think you understand what the problem is where actually, you know, it is really about kind of delving into what that is. And actually we have a dedicated design team that really kind of get under the bonnet of what these issues really are. It then kind of architects what the solutions need to look like using as Amar said, all the exciting new technology that we kind of have available to us. That kind of sensible solution as to what that should look like. We then build that sensible solution and we then, you know as part of that, we make sure that it scales to demand. So, something that might start out with, I dunno, you know a few hundred claimants or kind of cases going through it can quite often, you know, once that's that's been successful scale really, really quickly because as you know, we have 20 million claimants that come through us every year. So, these types of things can grow and expand but also a really key function of what we do is that we have a fully supported in-house service as well. So, all of those automations that we build are then maintained and you know, so any changes that kind of needed to be need to be made to them, we have all that and we have that control and we have our kind of arms wrapped around all of those. But also what that allows us to do is it allows us to be very kind of self-sufficient in making sure that we are as sufficient, sorry, as efficient as possible. And what I mean by that is looking at, you know as new technologies come around and they can allow us to do things more effectively. So, it allows us to kind of almost do that that kind of continuous improvement ourselves. So, that's a huge part of what we do as well. And you know, I think from a size point of view I said this started off really small as in the idea was this was a kind of center of excellence but actually as automation, I think as Amar alluded to is kind of really started to embed in DWP culture what we've started to kind of see is the a massive expansion in the types of of work that people want us to do and the volume of work that we are doing. So, I think we're currently running at around around a hundred people at the moment and I think, you know we started off with a scrum, a couple of scrum teams under Amar, so yeah, it's really grown. But you know, I think this is here to stay within DWP. >> Yeah, well when we talk about automation, you know virtual and robotics and all this I like to kind of keep the human element in mind here too. And Amar, maybe you can touch on that in certain terms of the human factors in this equation. 'Cause people think about, you know, robots it means different things to different people. In your mind, how does automation intersect with the human element here and in terms of the kinds of things Lianne wants to do down the road, you know, is a road for people basically? >> Oh yeah, absolutely. I think fundamentally what the department does is support people and therefore the solutions that we designed and built had to factor that in mind right? We were trying to best support and provide the best service we possibly can. And not only do we need to support the citizens that it supports. The department itself is a big organization, right? We're up to, we're talking between sort of 70 and 80,000 employees. So, how do we embed automation but also make the lives of the, of the DWP agents better as well? And that's what we thought about. So we said, "Well look, we think we can design solutions that do both." So, a lot of our automations go through a design process and we work closely with our operations team and we go, well actually, you know in processing and benefit, there are some aspects of that processing that benefit that are copy and paste, right? It doesn't require much thought around it, but it just requires capturing data and there's elements of that solution or that process that requires actual thought and understanding and really empathy around going, "Well how do I best support this citizen?" And what we tended to do is we took all of the things that were sort of laborious and took a lot of time and would slow down the overall process and we automated those and then we really focused on making sure that the elements that required the human, the human input was made as user friendly and centric as we possibly could. So, if there's a really complex case that needs to be processed, we were able to present the information in a really digestible and understandable way for the agents so that they could make a informed and sensible decision based around a citizen. And what that enabled us to do is essentially meet the demands of the volumes and the peaks that came in but also maintain the quality and if not improve, you know the accuracy of the claims processing that we had. >> So, how do you know, and maybe Lianne, you can address this. How do you know that it's successful on both sides of that equation? And, 'cause Amar raised a very good point. You have 70 to 80,000 employees that you're trying to make their work life much more efficient, much simpler and hopefully make them better at their jobs at the end of the day. But you're also taking care of 20 million clients on the, your side too. So, how do you, what's your measurement for success and what kind of like raw feedback do you get that says, "Okay, this has worked for both of our client bases, both our citizens and our employees?" >> Yeah, so we can look at this both from a a quantitative and a qualitative point of view as well. So, I think from a let take the kind figures first. So we are really hot on making sure that whatever automations we put in place we are there to measure how that automation is working what it's kind of doing and the impact that it's having from an operational point of view. So I think, you know, I think the proof of the fact that the Intelligent Automation Garage is working is that, you know, in the, in its lifetime, we've processed over 20 million items and cases so far. We have 65 scaled and transitioned automations and we've saved over 2 million operational hours. I was going to say that again that's 2 million operational hours. And what that allows us to do as an organization those 2 million hours have allowed us to rather than people as Amar, said, cutting and pasting and doing work that that is essentially very time consuming and repetitive. That 2 million hours we've been able to use on actual decision making. So, the stuff that you need as sentient human being to make judgment calls on and you know and kind of make those decisions that's what it's allowed us as an organization to do. And then I think from a quality point of view I think the feedback that we have from our operational teams is, you know is equally as as great. So, we have that kind of feedback from, you know all the way up from to the director level about, you know how it's kind of like I said that freeing up that time but actually making the operational, you know they don't have an easy job and it's making that an awful lot easier on a day to day basis. It has a real day to day impact. But also, you know, there are other things that kind of the knock on effects in terms of accuracy. So for example, robot will do is exactly as it's told it doesn't make any mistakes, it doesn't have sick days, you know, it does what it says on the tin and actually that kind of impact. So, it's not necessarily, you know, counting your numbers it's the fact that then doesn't generate a call from a customer that kind of says, "Well you, I think you've got this wrong." So, it's all that kind of, these kind of ripple effects that go out. I think is how we measure the fact that A, the garage is working and b, it's delivering the value that we needed to deliver. >> Robots, probably ask better questions too so yeah... (Lianne laughing) So, real quick, just real quick before you head out. So, the big challenge next, eureka, this works, right? Amar, you put together this fantastic system it's in great practice at the DWP, now what do we do? So, it's just in 30 seconds, Amar, maybe if you can look at, be the headlights down the road here for DWP and say, "This is where I think we can jump to next." >> Yeah, so I think, what we've been able to prove as I say is that is scaled innovation and having the return and the value that it creates is here to stay, right? So, I think the next things for us are a continuous expand the stuff that we're doing. Keeping hold of that culture, right? That culture of constantly solving difficult problems and being able to innovate and scale them. So, we are now doing a lot more automations across the department, you know, across different benefits across the digital agenda. I think we're also now becoming almost a bit of the fabric of enabling some of the digital transformation that big organizations look at, right? So moving to a world where you can have a venture driven architectures and being able to sort of scale that. I also think the natural sort of expansion of the team and the type of work that we're going to do is probably also going to expand into sort of the analytics side of it and understanding and seeing how we can take the data from the cases that we're processing to overall have a smoother journey across for our citizens. But it's looking, you know, the future's looking bright. I think we've got a number of different backlogs of items to work on. >> Well, you've got a great story to tell and thank you for sharing it with us here on "the CUBE", talking about DWP, the Department of Work and Pensions in the UK and the great work that Accenture's doing to make 20 million lives plus, a lot simpler for our friends in England. You've been watching ""the CUBE"" the AWS Executive Summit sponsored by Accenture. (bright upbeat music)

>> Live from Washington DC, it's theCUBE. Covering AWS Public Sector Summit 2018. Brought to you by Amazon Web Services and its ecosystem partners. >> Hello everyone, welcome back. It's theCUBE's exclusive coverage. We're here in Washington, D.C. for live coverage of theCUBE here at Amazon Web Services, AWS Public Sector Summit. This is the re-invent for the global public sector. Technically they do a summit but it's really more of a very focused celebration and informational sessions with customers from Amazon Web Services, GovCloud, and also international, except China, different world. John Furrier, Dave Vellante here for our third year covering AWS Public Sector Summit and again our next guest is Max Peterson, the Vice President of International Sales Worldwide for public sector data, Max, good to see you, thanks for coming back. >> It's good to see you again, John, thank you. >> So, we saw you at dinner last night, great VIP Teresa Carlson dinner last night, it's a who's who in Washington, D.C., but also international global public sector. >> Absolutely. >> And so, I want to get your thoughts on this, because AWS is not just in D.C. for GovCloud, there's a global framework here. What's goin' on, what's your take on how this cloud is disrupting the digital nations, and obviously here at home in D.C.? >> Well, John, so first of all, I love your description of this as a celebration, because really that's one of the things that we do, is we celebrate customer success, and so when you look at AWS around the world, we've got customers that are delivering solutions for citizens, new solutions for healthcare, a great solution to education all around the world. In Europe, we serve all those customers from London, Ireland, Germany, Frankfurt, Paris, all open regions, and we're bringing two new regions that we've announced, in the Middle East, which is an exciting part of the Europe, Middle East, and Africa business, and then also up in the Nordics, with Sweden. >> Yeah, so I want to ask you about EMEA, Europe, Middle East and Africa, it's the acronym for essentially international. Huge growth, obviously Europe is a mature set of countries, and it has its own set of issues, but in the Middle East and outside of Europe there's a huge growing middle class of digital culture. >> Yes. >> You're seeing everything from cryptocurrency booming, blockchain, you're seeing kind of the financial industries changing, obviously mobile impact, you got a new revolution going on with digital. You guys have to kind of thread the needle on that. What are you guys doing to support those regions? Obviously, you got to invest, got GDP always in the headlines >> Right. >> Recently, that's Europe's issue, and globally, but you got Europe, and you got outside of Europe. Two different growth strategies, how is AWS investing, what are some of the things you guys are doing? >> Sure, let me try and get all of those questions >> (laughs) Just start them one at a time >> That was very good, yeah. So, let's do the invest and grow piece. Digital skills are critical, and that's one of the challenges with the overall digital transformation, and, by the way, that's not just EMEA, that's all around the world, right? Including the U.S., and so we're doing a lot of things to try to address the digital skills requirement, a program that we've got called AWS Educate just yesterday announced the Cloud Academy Course. So, career colleges, technical colleges will be able to teach a two-year course specifically on cloud, right? For traditional university education, we provide this thing called AWS Educate. We, in the UK, we started a program over 18 months ago called Restart, where we focus on military leavers, spouses, and disadvantaged youth through the prince's trust, and we're training a thousand people a year on AWS cloud computing and digital skills. Taking them, in this case, out of military, or from less advantaged backgrounds and bringin' 'em into tech. And then, finally in April of this year, at our Brussels public sector summit, a celebration of customers in EMEA, we announced that we're going to be training 100,000 people across Europe, Middle East and Africa, with a combination of all of these programs, so skills is absolutely top in terms of getting people on to the cloud, right, and having them be digitally savvy, but the other part that you talked about is really the generational and cultural changes. People expect service when they touch a button on the phone. And that's not how most governments work, it's not how a lot of educational institutions work, and so we're helping them. And so, literally now, across the region, we've got governments that are delivering online citizen services at the touch of a button. Big organizations, like the UK Home Office, like the Department for Wealth and Pensions, like the Ministry of Justice. And then, I think the other thing that you asked about was GDPR. >> Yeah. (laughs) >> Am I covering all the bases? >> You're doing good Max. >> You keep it rollin'. >> You're a clipping machine, here. >> So, GDPR might be thought of as a European phenomenon, but my personal opinion is that's going to set the direction for personal data privacy around the world, and we're seeing the implementation happen in Europe, but we're seeing also customers in the Middle East, in Asia, down in Latin America going, "Hey, that's a good example." And I think you'll see people adopt it, much like people have adopted the NIST definition of cloud computing. Why re-invent it? If there's something that's good, let's adopt it and go, and Amazon understood that that was coming, although some people act like it's a surprise. >> Yeah. >> Did your e-mail box get flooded with e-mail? >> Oh, Gosh. >> God, tons Well the day >> Day before. >> Yes! >> (laughs) >> Yes, day before! Acting like this was, like a surprise. It started two years before, so Amazon actually started our planning so that when the day arrived for it to be effective, AWS services were GDPR compliant so that customers could build GDPR compliant solutions on top of the cloud. >> So, I mean generally I know there's a lot of detail there, but what does that mean, GDPR compliant? 'Cause I like having my data in the cloud with GDPR, 'cause I can push a lot of the compliance onto my cloud provider, so what does that really mean, Max? >> Yeah, well fundamentally, GDPR gives people control of their information. An example is the right to be forgotten, right? Many companies, good companies were already doing that. This makes it a requirement across the entire EU, right? And so, what it means to be compliant is that companies, governments, people need to have a data architecture. They really have to understand where their data is, what information they're collecting, and they have to make the systems follow the rules for privacy protection. >> So how does AWS specifically help me as a customer? >> Right, so our customers around Europe, in fact, around the world build their solutions on top of Amazon. The Amazon services do things that are required by GDPR like encryption, alright? And so, you're supposed to encrypt and protect private data. In Amazon, all you do is click a button, and no matter where you store it, it's encrypted and protected. So a lot of organizations struggled to implement some of these basic protections. Amazon's done it forever, and under GDPR, we've organized those so that all of our services act the same. >> Max, this brings up security questions, 'cause, you know obviously we hear a lot of people use the cloud, as an example, for getting things stood up quickly, >> Yep. >> Whether it's an application in the past, and then say a data warehouse, you got redshifts, and kinesis, and at one point was the fastest growing service, as Andy Jassy said, now that's been replaced by a bunch of other stuff. You got SageMaker around the corner, >> SageMaker's awesome. >> So you got that ability, but also data is not just a data warehouse question. It's really a central value proposition, whether you're talking about in the cloud or IOT, so data becomes the center of the value proposition. How are you guys ensuring security? What are some of the conversations, because it certainly differs on a country by country basis. You got multiple regions developing, established and developing new ones for AWS. How do you look at that? How do you talk to customers and say, "Okay, here's our strategy, and here's what we're doing to secure your data, here's how you can go faster (laughs), keep innovating, because you know they don't want to go slower, because it's complicated. To do a GDPR overhaul, for some customers, is a huge task. How do you guys make it faster, while securing the data? >> Yeah, so first of all, your observation about data, having gravity, is absolutely true. What we've struggled with, with government customers, with healthcare and commercial enterprise, is people have their data locked up in little silos. So the first thing that people are doing on the cloud, is they're taking all that and putting it into a data warehouse, a data repository. Last night we heard from NASA, and from Blue Origin about the explosion in data, and in fact, what they said, and we believe, is that you're going to start bringing your compute to the data because the amount of information that you've got, when you've got billions of sensors, IOT, billions of these devices that are sending information or receiving information, you have to have a cloud strategy to store all that information. And then secondly, you have to have a cloud compute strategy to actually make use of that information. You can't download it anymore. If you're going to operate in real time, you've got to run that machine learning, right, in real time, against the data that's coming in, and then you've got to be able to provide the information back to an application or to people that makes use of it. So you just can't do it in-house anymore. >> You mentioned the talk last night as part of the Earth and Science Program, which you guys did, which by the way, I thought was fabulous. For the folks watching, they had a special inaugural event, before this event around earth and space, Blue Origin was there, Jet Propulsion Lab, much of the NASA guys, a lot of customers. But the interesting thing he said also, was is that they look at the data as a key part, and then he called himself a CTO, Chief Toy Officer. And he goes, "you got to play with the toys before they become too old," but that was a methodology that he was talking about how they get involved in using the tooling. Tooling becomes super important. You guys have a set of services, AWS, Amazon Web Services, which essentially are tools. >> Yeah. >> Collectively tools, you know global, you end up generalizing it, but this is important because now you can mix and match. Talk about how that's changed the customer mindset and how they roll out technology because they got to play, they got to experiment, as Andy Jassy would say, but also, also put the tools into production. How is it changing the face of your customer base? >> Sure, well, one of the things that customers love, is the selection of tools, but one of the most important things we actually do with customers, is help them to solve their problems. We have a professional service organization, we have what we call Envision Engineering, which is a specialized team that goes in and develops prototypes with customers, so that they understand how they can use these different tools to actually get their work done. One quick example: in the UK, the NHS had to implement a new program for people calling in to understand health benefits. And they could've done this in a very traditional fashion, it would've taken months and months to set up the call center and get everything rolling. Fortunately, they worked with one of our partners, and they understood that they could use new speech and language processing tools like Lex, and Amazon's in-the-cloud call center tools, like Connect. In two weeks, they were able to develop the application that handled 42% of the inbound call volume entirely automated, with speech and text processing, so that the other 52% could go to live operators where they had a more complex problem. That was prototyped in two weeks, it was implemented in three more weeks, a total of five weeks from concept to operation of a call center receiving thousands and thousands of inbound calls on the cloud. >> Max, can you paint a picture of the EMEA customer base, how it sort of compares to the US, the profile? I mean, obviously here, in the United States, you got a healthy mix of customers. You got startups, you're announcing enterprises, you got IOT use cases. I imagine a lot of diversity in EMEA, but how does it compare with the US, how would you describe it? Paint a picture for us. >> Yeah sure, candidly, we see the same exact patterns all around the world. Customers are in different stages of readiness, but across Europe, we have central governments that are bringing online, mission systems to the cloud. I mentioned Home Office, I mentioned DWP, I mentioned Her Majesty Revenue and Customs, HMRC. They're bringing real mission systems to the cloud now because they laid the right foundations, right? They've got a cloud native policy, and that's what directs government, that says stop building legacy systems and start building for the future by using the cloud. Educational institutions across the board are using AWS. Science and research, like the European Space Agency is using AWS, so we see, really, just the same pattern going on. Some areas of the world are newer to the cloud, so in the Middle East, we're seeing that sort of startup phase, where startup companies are gettin' onto the cloud. Some of 'em are very big. Careem is a billion dollar startup running on AWS, right. But we're helping startups just do the basics on the cloud. In Bahrain, which is a small country in the Middle East, they realized the transformative opportunity with cloud computing, and they decided to take the lead. They worked with AWS, they produced a national cloud policy, their CIO said we will move to the cloud, and that's key. Leadership is absolutely key. And then they put in place a framework, and they very systematically identified those applications that were ready, and they moved those first. Then they tackled the ones that weren't quite ready, and they moved those. They moved 450 applications in a matter of three months, to the cloud, but it was by having a focused program, top-level leadership, the right policy, and then we provided technical resources to help them do it. >> Max, I want to get one last question before the time comes up, but I want to put you on the spot here. >> Oh good. >> In the United States, Amazon Web Services public sector has really kind of changed the game. You saw the CIA deal that you guys did years ago, the Department of Defense is all in the news, obviously it's changing the ecosystem. How is that dynamic happening in Europe? You said the patterns are the same. Take a minute to just quickly describe, what's going on in the ecosystem? What's the partner profile look like? You've got a great partner ecosystem, and there are different partners. You mentioned Bahrain, Digital Nation, changing the game. You guys seem to attract kind of a new guard, a new kind of thinking, partners. What is the ecosystem partnerships look like for you guys, internationally, and is there the same dynamic going on that's happening in the US with the CIA, and DOD leaders around changing the narrative, changing the game, with technology? >> Sure, good questions. We wouldn't be able to deliver the solutions that we deliver to customers without our partner ecosystem. And sometimes, they're small, born in the cloud partners, the same sort of phenomenon that we have in the US. The example with the National Health Service was delivered by a expert consulting partner called Arcus Global, about a hundred person strong consulting organization that just knows cloud and makes it their business. And we see those throughout Europe, Middle East, and into Africa. We have our large global partners, Capgemini, Accenture, and then I think the other thing that's really important, is the regional partners. So what's happening is we're seeing those regional partners, partners like Everee, or Dee-Ecto, or SCC. We're seeing them now realize that their customers want to be agile, they want to be innovative, they want to be fast, and it doesn't hurt that they're going to save some money. And so we're seeing them change their business model, to adopt cloud computing, and that's the tipping point. When that middle, that trusted middle of partners, starts to adopt cloud and help the customers, that's when it really swings the other direction. >> It's great growth, and new growth brings new partners, new profiles, new brands, new names, and specialty is key. Max, thanks for coming on the CUBE. Really appreciate you taking the time. International, we're riding the wave of home sector with CUBE here in the US, soon we'll see you in some international summits. >> I'm looking forward, >> Alright. >> John, Dave, it was awesome to talk to you. >> Thanks Max. >> Alright, we are here live in Washington, D.C., for Amazon Web Services, AWS, Public Sector Summit 2018, we are in Washington, I'm John Furrier, Dave Vellante, and also Stu Miniman is here, the whole CUBE team is here, unpacking the phenomenon that is AWS, rocking the government and digital nations around the world. We're back with more, after this short break. (upbeat techno music)