>> Announcer: 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,
>> Christopher: 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.
>> Rebecca: 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)