>> Live from Washington, DC, it's theCUBE, covering AWS Public Sector Summit. Brought to you by Amazon Web Services. >> Welcome back everyone to theCUBE's live coverage of the AWS Public Sector Summit, here in our nation's capital. I'm your host, Rebecca Knight, co-hosting with John Furrier. We have two guests for this segment, we have George Gagne, he is the Chief Information Officer at Defense POW/MIA Accounting Agency. Welcome, George. And we have Christopher McDermott, who is the CDO of the POW/MIA Accounting Agency. Welcome, Chris. >> Thank you. >> Thank you both so much for coming on the show. >> Thank you. >> So, I want to start with you George, why don't you tell our viewers a little bit about the POW/MIA Accounting Agency. >> Sure, so the mission has been around for decades actually. In 2015, Secretary of Defense, Hagel, looked at the accounting community as a whole and for efficiency gains made decision to consolidate some of the accounting community into a single organization. And they took the former JPAC, which was a direct reporting unit to PACOM out of Hawaii, which was the operational arm of the accounting community, responsible for research, investigation, recovery and identification. They took that organization, they looked at the policy portion of the organization, which is here in Crystal City, DPMO and then they took another part of the organization, our Life Sciences Support Equipment laboratory in Dayton, Ohio, and consolidated that to make the defense POW/MIA Accounting Agency, Under the Office of Secretary Defense for Policy. So that was step one. Our mission is the fullest possible accounting of missing U.S. personnel to their families and to our nation. That's our mission, we have approximately 82,000 Americans missing from our past conflicts, our service members from World War II, Korea War, Korea, Vietnam and the Cold War. When you look at the demographics of that, we have approximately 1,600 still missing from the Vietnam conflict. We have just over a 100 still missing from the Cold War conflict. We have approximately 7,700 still missing from the Korean War and the remainder of are from World War II. So, you know, one of the challenges when our organization was first formed, was we had three different organizations all had different reporting chains, they had their own cultures, disparate cultures, disparate systems, disparate processes, and step one of that was to get everybody on the same backbone and the same network. Step two to that, was to look at all those on-prem legacy systems that we had across our environment and look at the consolidation of that. And because our organization is so geographically dispersed, I just mentioned three, we also have a laboratory in Offutt, Nebraska. We have detachments in Southeast Asia, Thailand, Vietnam, Laos, and we have a detachment in Germany. And we're highly mobile. We conduct about, this year we're planned to do 84 missions around the world, 34 countries. And those missions last 30 to 45 day increments. So highly mobile, very globally diverse organization. So when we looked at that environment obviously we knew the first step after we got everybody on one network was to look to cloud architectures and models in order to be able to communicate, coordinate, and collaborate, so we developed a case management system that consist of a business intelligence software along with some enterprise content software coupled with some forensics software for our laboratory staff that make up what we call our case management system that cloud hosted. >> So business challenges, the consolidation, the reset or set-up for the mission, but then the data types, it's a different kind of data problem to work, to achieve the outcomes you're looking for. Christopher, talk about that dynamic because, >> Sure. >> You know, there are historical different types of data. >> That's right. And a lot of our data started as IBM punchcards or it started from, you know, paper files. When I started the work, we were still looking things up on microfiche and microfilm, so we've been working on an aggressive program to get all that kind of data digitized, but then we have to make it accessible. And we had, you know as George was saying, multiple different organizations doing similar work. So you had a lot of duplication of the same information, but kept in different structures, searchable in different pathways. So we have to bring all of that together and make and make it accessible, so that the government can all be on the same page. Because again, as George said, there's a large number of cases that we potentially can work on, but we have to be able to triage that down to the ones that have the best opportunity for us to use our current methods to solve. So rather than look for all 82,000 at once, we want to be able to navigate through that data and find the cases that have the most likelihood of success. >> So where do you even begin? What's the data that you're looking at? What have you seen has had the best indicators for success, of finding those people who are prisoners of war or missing in action? >> Well, you know, for some degrees as George was saying, our missions has been going on for decades. So, you know, a lot of the files that we're working from today were created at the time of the incidents. For the Vietnam cases, we have a lot of continuity. So we're still working on the leads that the strongest out of that set. And we still send multiple teams a year into Vietnam and Laos, Cambodia. And that's where, you know, you try to build upon the previous investigations, but that's also where if those investigations were done in the '70s or the '80s we have to then surface what's actionable out of that information, which pathways have we trod that didn't pay off. So a lot of it is, What can we reanalyze today? What new techniques can we bring? Can we bring in, you know, remote sensing data? Can we bring GIS applications to analyze where's the best scenario for resolving these cases after all this time? >> I mean, it's interesting one of the things we hear from the Amazon, we've done so many interviews with Amazon executives, we've kind of know their messaging. So here's one of them, "Eliminate the undifferentiated heavy lifting." You hear that a lot right. So there might be a lot of that here and then Teresa had a slide up today talking about COBOL and mainframe, talk about punch cards >> Absolutely. >> So you have a lot of data that's different types older data. So it's a true digitization project that you got to enable as well as other complexity. >> Absolutely, when the agency was formed in 2015 we really begin the process of an information modernization effort across the organization. Because like I said, these were legacy on-prem systems that were their systems' of record that had specific ways and didn't really have the ability to share the data, collaborate, coordinate, and communicate. So, it was a heavy lift across the board getting everyone on one backbone. But then going through an agency information modernization evolution, if you will, that we're still working our way through, because we're so mobilely diversified as well, our field communications capability and reach back and into the cloud and being able to access that data from geographical locations around the world, whether it's in the Himalayas, whether it's in Vietnam, whether it's in Papua New Guinea, wherever we may be. Not just our fixed locations. >> George and Christopher, if you each could comment for our audience, I would love to get this on record as you guys are really doing a great modernization project. Talk about, if you each could talk about key learnings and it could be from scar tissue. It could be from pain and suffering to an epiphany or some breakthrough. What was some of the key learnings as you when through the modernization? Could you share some from a CIO perspective and from a CDO perspective? >> Well, I'll give you a couple takeaways of what I thought I think we did well and some areas I thought that we could have done better. And for us as we looked at building our case management system, I think step one of defining our problem statement, it was years in planning before we actually took steps to actually start building out our infrastructure in the Amazon Cloud, or our applications. But building and defining that problem statement, we took some time to really take a look at that, because of the different in cultures from the disparate organizations and our processes and so on and so forth. Defining that problem statement was critical to our success and moving forward. I'd say one of the areas that I say that we could have done better is probably associated with communication and stakeholder buy-in. Because we are so geographically dispersed and highly mobile, getting the word out to everybody and all those geographically locations and all those time zones with our workforce that's out in the field a lot at 30 to 45 days at a time, three or four missions a year, sometimes more. It certainly made it difficult to get part of that get that messaging out with some of that stakeholder buy-in. And I think probably moving forward and we still deal regarding challenges is data hygiene. And that's for us, something else we did really well was we established this CDO role within our organization, because it's no longer about the systems that are used to process and store the data. It's really about the data. And who better to know the data but our data owners, not custodians and our chief data officer and our data governance council that was established. >> Christopher you're learnings, takeaways? >> What we're trying to build upon is, you define your problem statement, but the pathway there is you have to get results in front of the end users. You have get them to the people who are doing the work, so you can keep guiding it toward the solution actually meets all the needs, as well as build something that can innovate continuously over time. Because the technology space is changing so quickly and dynamically that the more we can surface our problem set, the more help we can to help find ways to navigate through that. >> So one of the things you said is that you're using data to look at the past. Whereas, so many of the guests we're talking today and so many of the people here at this summit are talking about using data to predict the future. Are you able to look your data sets from the past and then also sort of say, And then this is how we can prevent more POW. Are you using, are you thinking at all, are you looking at the future at all with you data? >> I mean, certainly especially from our laboratory science perspective, we have have probably the most advanced human identification capability in the world. >> Right. >> And recovery. And so all of those lessons really go a long ways to what what information needs to be accessible and actionable for us to be able to, recover individuals in those circumstances and make those identifications as quickly as possible. At the same time the cases that we're working on are the hardest ones. >> Right. >> The ones that are still left. But each success that we have teaches us something that can then be applied going forward. >> What is the human side of your job? Because here you are, these two wonky data number crunchers and yet, you are these are people who died fighting for their country. How do you manage those two, really two important parts of your job and how do you think about that? >> Yeah, I will say that it does amp up the emotional quotient of our agency and everybody really feels passionately about all the work that they do. About 10 times a year our agency meets with family members of the missing at different locations around the country. And those are really powerful reminders of why we're doing this. And you do get a lot of gratitude, but at the same time each case that's waiting still that's the one that matters to them. And you see that in the passion our agency brings to the data questions and quickly they want us to progress. It's never fast enough. There's always another case to pursue. So that definitely adds a lot to it, but it is very meaningful when we can help tell that story. And even for a case where we may never have the answers, being able to say, "This is what the government knows about your case and these are efforts that have been undertaken to this point." >> The fact there's an effort going on is really a wonderful thing for everybody involved. Good outcomes coming out from that. But interesting angle as a techy, IT, former IT techy back in the day in the '80s, '90s, I can't help but marvel at your perspective on your project because you're historians in a way too. You've got type punch cards, you know you got, I never used punch cards. >> Put them in a museum. >> I was the first generation post punch cards, but you have a historical view of IT state of the art at the time of the data you're working with. You have to make that data actionable in an outcome scenario workload work-stream for today. >> Yeah, another example we have is we're reclaiming chest X-rays that they did for induction when guys were which would screen for tuberculosis when they came into service. We're able to use those X-rays now for comparison with the remains that are recovered from the field. >> So you guys are really digging into history of IT. >> Yeah. >> So I'd love to get your perspective. To me, I marvel and I've always been critical of Washington's slowness with respect to cloud, but seeing you catch up now with the tailwinds here with cloud and Amazon and now Microsoft coming in with AI. You kind of see the visibility that leads to value. As you look back at the industry of federal, state, and local governments in public over the years, what's your view of the current state of union of modernization, because it seems to be a renaissance? >> Yeah, I would say the analogy I would give you it's same as that of the industrial revolutions went through in the early 20th century, but it's more about the technology revolution that we're going through now. That's how I'd probably characterize it. If I were to look back and tell my children's children about, hey, the advent of technology and that progression of where we're at. Cloud architecture certainly take down geographical barriers that before were problems for us. Now we're able to overcome those. We can't overcome the timezone barriers, but certainly the geographical barriers of separation of an organization with cloud computing has certainly changed. >> Do you see your peers within the government sector, other agencies, kind of catching wind of this going, Wow, I could really change the game. And will it be a step function into your kind of mind as you kind of have to project kind of forward where we are. Is it going to a small improvement, a step function? What do you guys see? What's the sentiment around town? >> I'm from Hawaii, so Chris probably has a better perspective of that with some of our sister organizations here in town. But, I would say there's more and more organizations that are adopting cloud architectures. It's my understanding very few organizations now are co-located in one facility and one location, right. Take a look at telework today, cost of doing business, remote accessibility regardless of where you're at. So, I'd say it's a force multiplier by far for any line of business, whether it's public sector, federal government or whatever. It's certainly enhanced our capabilities and it's a force multiplier for us. >> And I think that's where the expectation increasingly is that the data should be available and I should be able to act on it wherever I am whenever the the opportunity arises. And that's where the more we can democratize our ability to get that data out to our partners to our teams in the field, the faster those answers can come through. And the faster we can make decisions based upon the information we have, not just the process that we follow. >> And it feeds the creativity and the work product of the actors involved. Getting the data out there versus hoarding it, wall guarding it, asylumming it. >> Right, yeah. You know, becoming the lone expert on this sack of paper in the filing cabinet, doesn't have as much power as getting that data accessible to a much broader squad and everyone can contribute. >> We're doing our part. >> That's right, it's open sourcing it right here. >> To your point, death by PowerPoint. I'm sure you've heard that before. Well business intelligence software now by the click of a button reduces the level of effort for man-power and resources to put together slide decks. Where in business intelligence software can reach out to those structured data platforms and pull out the data that you want at the click of a button and build those presentations for you on the fly. Think about, I mean, if that's our force multiplier in advances in technology of. I think the biggest thing is we understand as humans how to exploit and leverage the technologies and the capabilities. Because I still don't think we fully grasp the potential of technology and how it can be leveraged to empower us. >> That's great insight and really respect what you guys do. Love your mission. Thanks for sharing. >> Yeah, thanks so much for coming on the show. >> Thank you for having us. >> I'm Rebecca Knight for John Ferrer. We will have much more coming up tomorrow on the AWS Public Sector Summit here in Washington, DC. (upbeat music)