CAPE EVAMOSC Platform Support

WEBVTT
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Have you ever like bought something really expensive, uh, maybe like a car, and you just feel that immediate wave of buyer's remorse.
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Absolutely.
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The second you drive it off the lot.
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Right.
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You save up all the money, you negotiate the price, you sign that uh that endless stack of papers, and you drive it off feeling fantastic.
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But then, you know, a year goes by.
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And then the reality of owning it sets in.
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Exactly.
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You suddenly have to pay for comprehensive insurance, routine oil changes, maybe a whole new set of tires, or I mean, there's that weird rattling noise in the engine that costs a thousand bucks just for a mechanic to diagnose.
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Aaron Powell Yeah, because the initial acquisition, that's visible.
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It's a one-time transaction.
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But the operating and support costs, the fuel, the maintenance, the human labor, that firms a massive ongoing financial commitment.
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Trevor Burrus, Jr.: Yeah, and it often just completely dwarfs the original purchase price.
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Suddenly you realize the sticker price was just, well, the opening bid, the upkeep is what actually drains your bank account.
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So I want you to imagine that exact scenario.
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But instead of just a single commuter car, you're managing a massive global fleet of military helicopters, heavily armored tanks, precision missile systems.
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Trevor Burrus, Jr.
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Which is a logistical nightmare, honestly.
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Yeah, right.
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And instead of draining your personal bank account, the upkeep is pulling from a multi-billion dollar military budget.
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You would assume, right, that the entity paying those bills knows exactly where every single dollar is going.
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Aaron Powell Well, you would assume that.
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But the reality of enterprise-scale government accounting is um it's far more convoluted.
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Trevor Burrus, Jr.
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It always is.
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Yeah.
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The sheer volume of transactions and you know the legacy systems tracking them, it creates this environment where the true granular cost of operating a specific weapon system becomes incredibly difficult to pin down.
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Aaron Powell, which brings us to today.
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Welcome to today's deep dive.
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We are looking at how the U.S.
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Department of Defense is attempting to solve this colossal multi-billion dollar blind spot regarding exactly how much its major weapons systems actually cost to operate and maintain.
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And our grounding material for this exploration is uh it's a stack of highly detailed U.S.
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government contracting documents.
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Aaron Powell The fun stuff.
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Oh, very dense reading.
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Specifically, we're looking at a request for proposal number, HQ00342000079, along with two performance work statements or PWS documents.
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Aaron Powell And these outline a massive data integration project known as EVAM OC, right?
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Exactly.
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EVAM OC.
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So the mission of this deep dive is to basically decode this dense contracting material.
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Because if you look past the bureaucratic formatting and the, you know, the endless acronyms.
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There's so many acronyms.
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So many.
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But what you find is this genuinely fascinating story about advanced fita science, government bureaucracy, and what it actually takes to build a 100-terabyte system capable of tracking every drop of aviation fuel and like every spare tank tread across the entire military.
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Aaron Powell To really understand the solution here, we first have to fully grasp the problem, which is highlighted right at the top of these sources.
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Right.
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Despite having the largest military budget in the world, the documents flatly state that the DOD lacks complete, accurate, and granular data on the operating and support costs.
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Aaron Powell They call those OS costs, right?
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Yeah, ONS costs.
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And they lack this data for many of their major acquisition programs.
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Okay, let's unpack this.
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Because to the average listener, it sounds completely absurd that the military wouldn't already track this stuff.
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But if you break down the mechanics of a massive organization, it sort of starts to make sense.
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Aaron Powell It does.
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It's an enterprise problem.
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Right.
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So think of it like trying to run a massive Fortune 500 delivery company.
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The HR department is meticulously tracking all the truck driver salaries in one specialized software system.
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Sure.
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Then the mechanics down the garage, they have a completely different database where they log replacement brake pads and tires.
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And a third, entirely separate logistics department tracks fuel consumption at the pumps.
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And they don't talk to each other.
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Exactly.
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Everyone is doing their job perfectly, but the databases are completely siloed.
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So the CEO sitting at the top has absolutely no idea if delivery truck number 42 is actually profitable to keep on the road because all that cost data is just fractured across three different departments.
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If we connect this to the bigger picture, the stakes here are significantly higher than a delivery company.
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I mean, obviously, yeah.
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The sources point out that this fractured data environment isn't just an administrative annoyance, it's actually a legal liability.
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Wait, really?
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A legal liability?
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Yes.
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There is a specific statutory mandate driving this entire project.
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The documents reference Title 10 of the U.S.
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Code, Section 2337A.
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Okay.
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It's a federal law concerning guidance on life cycle management.
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So Congress actually had to put it in writing and like pass a law demanding accountability for these operating costs.
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Pretty much.
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Congress recognized the blind spot.
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This law legally requires the Director of Cost Assessment and Program Evaluation, an office known as OSD KPE, to develop and maintain a centralized database on these actual realized operating and support costs.
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OSD CAPES.
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So they're the ones on the hook for this.
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Right.
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KPE acts as the internal auditors and prognosticators of the DoD.
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They have this strict statutory requirement from Congress, but the enterprise database they need to fulfill it.
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It literally does not exist yet across this sprawling DoD infrastructure.
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Wow.
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And just as a reminder to you listening, we're simply unpacking the goals stated in these government documents.
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The text itself, driven by Congress, explicitly argues that without this centralized data, the government just can't achieve savings for the taxpayer or control these massive sustainment budgets.
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Exactly.
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We're looking at the mechanism they are building to attempt that goal, regardless of the broader politics surrounding military spending.
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Aaron Powell Right, because without data-driven insight, you just can't improve life cycle cost estimates for future programs.
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You're basically flying blind in the sustainment phase, which is where the vast majority of a weapon system's lifetime cost actually occurs.
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Aaron Powell, which is exactly why solving a structural problem of this magnitude requires a massive framework and frankly serious technological investment.
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Yet this isn't cheap.
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No, not at all.
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And that leads us directly to the financial architecture of the request for proposal.
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The government isn't just cutting a single check, they're utilizing an indefinite delivery, indefinite quantity contract.
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An IDIQ.
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Yes, an IDIQ.
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And the maximum value on this IDIQ is a staggering$100 million.
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It's massive, but the IDIQ format is crucial here.
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It basically tells the contractor look, we have a massive complex integration problem up to this$100 million ceiling, but we can't predict every single data hurdle on day one.
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Aaron Powell Because it's too big to map out entirely in advance.
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Exactly.
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So they say we will issue specific task orders as we define the exact requirements over time.
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And the overarching umbrella for all this work is that EVAMAAC system.
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Right.
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Enterprise visibility and management of operating and support cost, EVAAC.
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Aaron Powell And the technical scale detailed in the performance work statement is huge.
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It requires the contractor to design a secure, scalable repository that can handle up to 100 terabytes of data.
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Aaron Powell Wait, let me push back on that for a second.
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Sure.
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Because 100 terabytes, I mean, in the era of massive cloud computing, 100 terabytes is practically nothing.
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Uh-huh.
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No, seriously, Netflix streams that in a fraction of a second globally, right?
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You can buy a desktop hard drive with a huge chunk of that capacity for just a few hundred bucks.
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So why is this a$100 million problem if the storage footprint is that relatively small?
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Because it is a structural relational data problem, not a storage volume problem.
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We aren't talking about storing massive 4K video files or high-resolution images, which, you know, chew up terabytes quickly.
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Right.
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Video is huge.
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You're talking about text.
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Millions upon millions of individual transaction rows.
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The sources explicitly state that the data acquisition and preparation task is the most challenging aspect of the work.
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Oh, okay.
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And it represents the greatest value to the government.
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The contractor has to pull data from over 75 disparate legacy source systems.
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75?
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Wow, that is the core of the friction right there.
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Because these 75 systems cover everything from financial management to logistics, maintenance, human resources, property, and the documents note that absolutely none of those upstream data systems were designed or implemented to support cost mapping to individual weapons.
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Yeah, they were just built to pay people or order parts.
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Right.
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So the mechanism of this challenge is what justifies the$100 million ceiling.
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The contractor's real job is complex data cleansing and wrangling.
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Think of it this way: imagine you're trying to calculate the true cost of a decade of family dinners.
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Okay, I'm tracking.
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But your receipts are from 75 different grocery stores.
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Some receipts measure ingredients in weight, some in volume, some are in different currencies, even.
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And half the receipts are from like 1998.
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And none of them say dinner on Tuesday.
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They just list a raw ingredient, like flour or tomatoes.
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Aaron Powell Precisely.
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So the contractor has to build algorithms that grab those raw ingredients and turn them into a cohesive meal.
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Man, that sounds impossible.
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It's incredibly complex.
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They have to build automated business rules that map general ledger transactions, so raw accounting data over to the highly structured Cape Cost estimating structure.
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Aaron Powell And to highlight the sheer mechanical difficulty of that, the sources mention that all incoming data expressed in dollars are in then year dollars.
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Aaron Powell Which is a huge headache.
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Aaron Powell Meaning the cost is recorded exactly as it was on the day of the transaction, completely unadjusted for inflation.
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Yes.
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So the algorithms have to grab a supply invoice from, say, 2004, explicitly identify the economic index for that specific base year, apply the exact inflation conversion rate to normalize it into current year dollars.
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Wow.
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And then trace that specific expenditure to the engine of one specific vehicle.
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It is automated forensic accounting on just a staggering scale.
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And obviously, you can't test a highly experimental 100-terabyte data model on the entire military at once without causing absolute chaos.
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You need a sandbox, right?
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A massive self-contained data ecosystem to prove the concept actually works.
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Exactly.
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And that logic dictates the strategy behind Task Order One.
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Right.
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Task Order One, this is the proof of concept.
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It focuses primarily on U.S.
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Army weapons systems, starting specifically with the ground vehicle commodity group.
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Though the documents do note that future task orders will expand to address the Navy, Air Force, and Marines, but the Army provides the perfect testing ground.
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And the hardware they're tracking in this first phase, it really grounds this abstract data project in heavy reality.
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They are mapping costs for M1 Abrams tanks, Apache and Blackhawk helicopters, striker vehicles, javelin missiles, and the MQ-1C Grey Eagle drones.
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It's a massive fleet.
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Yeah.
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And they aren't just tracking the broad category of Abrams tanks.
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Right, because the variations matter.
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The system has to handle type model series or mission description series derivatives.
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Yes, the data has to differentiate between a base M182 and M1A2 SEP or an upgraded M182 SCP-3.
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And the MQ1C Grey Eagle, I mean, that isn't just a drone flying in the air.
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Tracking its cost means tracking the ground control stations, the satellite links, the specific maintenance crew hours.
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The data granularity has to be flawless.
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So to achieve that granularity, we have to look at the alphabet soup of legacy feeder systems this new platform is forced to ingest.
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The sources list systems like FedLog.
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Right, FedLog.
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This is the Federal Logistics Data System.
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It's essentially a massive parts catalog where they pull prices for consumable repair parts.
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But then FedLog has to talk to FMD, Fuel Manager Defense, which is run by the Defense Logistics Agency.
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Aaron Powell And this is where the systems clash spectacularly.
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FMD measures fuel transactions in volume, so gallons on hand and gallons pumped.
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But the SVPE database doesn't care about gallons, right?
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They need to report to Congress in dollars.
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Aaron Ross Powell Exactly.
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So the automated business rules have to grab a transaction from FMD in gallons, ping another database to find the exact price per gallon on that specific day.
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Oh my gosh.
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Convert it into dollars, and then somehow link that fuel burn back to an Apache helicopter's tail number, not just the military base's general operating fund.
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It requires just relentless calculation.
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And then you also have TAMIS, the training ammunition management information system, which tracks missiles in single units, and Syncata, a third-party payment system used to track transportation costs in flat monetary fees.
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Trevor Burrus, Jr.
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Gallons, units, and fees.
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All of it has to be converted, standardized, and mapped.
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The complexity of normalizing that data just cannot be overstated.
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But here's where it gets really interesting to me.
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Okay.
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We are talking about pulling an incredible amount of sensitive readiness and cost data into one centralized location.
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If an adversary gains access to this database, they don't just see a budget, right?
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They see exactly how much fuel we have, how many replacement parts are moving, and the exact operational readiness of our tank fleets.
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The gold mine of strategic intelligence.
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Exactly.
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So how does the government architect this to keep the data safe while actually letting analysts use it?
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That's a great question.
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The sources outline a very distinct two-platform architecture to solve that exact security puzzle.
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The actual EVAMP OSC backend, the engine room where all this messy data ingestion, wrangling, and storage happens, is hosted securely on Amazon GovCloud.
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Okay, Amazon GovCloud.
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Yes.
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And it is designated at Impact Level 4.
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Let's define that for the listener real quick.
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Impact Level 4 is a specific DoD security standard for controlled unclassified information.
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It means the data won't like reveal nuclear launch codes, but aggregated together, it reveals critical troop readiness, supply chain vulnerabilities, and strategic posture.
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Right.
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So the impact level four environment is the vault.
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Yeah.
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It is strictly controlled, meant primarily for the highly cleared CPE analysts who are managing the platform and writing the algorithms.
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But the broader DOD community still needs to see the results, right?
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You do.
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So to share this data safely, EDMPOPAS packages up the finished, sanitized cost profiles and pushes them over to a completely separate public-facing platform called Advana.
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Advana is like the storefront.
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The back-end factory makes the product and Advana puts it in the display window.
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Exactly.
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Advana hosts what the documents call the common Vemise tool.
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This separation of duties is really a brilliant administrative move.
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Because of the authority to operate, right?
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Yes.
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The authority to operate, which is the military's strict, formalized cybersecurity permission slip to plug a system into the network is a massive hurdle.
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By separating the platforms, the Bacape team doesn't have to manage the authority to operate or grant user access for every single military commander who just wants to view a readiness analytics dashboard.
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Oh, that's smart.
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Right.
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Advantage handles all the public-facing security protocols while the AvAMSE backend remains hidden, just quietly feeding it the clean processed data.
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But building a secure bridge between 75 siloed legacy systems and a modern cloud-based analytics platform, I mean, that requires an incredibly specialized workforce.
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You cannot just hire a standard Silicon Valley software development team to execute this.
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The intense human requirements outlined in this contract are a testament to how difficult this is.
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The government is incredibly rigid about the key personnel required to run this project.
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For instance, the product manager must have a minimum of 10 years of experience relating to major program management.
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And the senior cost analyst requirement is even more intense.
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They need a master's degree in a math-heavy field like operations research, applied mathematics, industrial engineering, or economics.
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Plus, they need five years of experience specifically in DOD business cost analysis.
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What's fascinating here is the specific fusion of skills the government is demanding.
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Yeah.
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They need top-tier software engineers who understand how to build automated data pipelines in an Amazon GovCloud environment.
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But those engineers are useless unless they're paired with analysts who hold degrees in operations research.
00:16:12.879 --> 00:16:15.600
Which is the mathematical study of logistics and efficiency.
00:16:16.000 --> 00:16:16.240
Right.
00:16:16.399 --> 00:16:22.799
They need people who fundamentally understand army logistics, inflation indices, and cost estimating methodologies.
00:16:23.039 --> 00:16:30.720
Because if the engineers don't understand the mechanics of army supply chains, the automated business rules they code will output completely flawed data.
00:16:31.039 --> 00:16:31.919
Wow, yeah.
00:16:32.080 --> 00:16:38.960
And the physical working conditions for this team, they really reflect the extreme sensitivity of the project.
00:16:39.200 --> 00:16:44.000
The physical security requirements in this contract keep this from feeling like a normal tech job.
00:16:44.320 --> 00:16:45.039
Oh, absolutely.
00:16:45.279 --> 00:16:50.000
Contractor employees are strictly forbidden from wearing clothing with their company logos, for example.
00:16:50.320 --> 00:16:51.679
No casual startup hoodies.
00:16:51.919 --> 00:16:52.240
Nope.
00:16:52.480 --> 00:17:04.240
They have to maintain a neat business casual appearance that blends in, ensuring they don't create the impression that they are government officials while walking the halls of the Pentagon or associated DOD facilities.
00:17:04.640 --> 00:17:11.039
And they all have to maintain secret facility clearances, which is a rigorous background check process.
00:17:11.279 --> 00:17:18.000
But the detail in the contract that really highlights the reality of government security work is the section on key control.
00:17:18.240 --> 00:17:19.039
Oh, the keys.
00:17:19.279 --> 00:17:20.160
It's wild.
00:17:20.400 --> 00:17:24.559
The contract explicitly states that contractors cannot duplicate keys.
00:17:24.720 --> 00:17:35.839
But if a contractor loses a master key, the government will step in, replace the entire lock system for that area, and deduct the total cost of replacing all those locks directly from the contractor's monthly payment.
00:17:36.160 --> 00:17:37.519
Which is incredibly expensive.
00:17:37.759 --> 00:17:38.000
Right.
00:17:38.319 --> 00:17:44.000
It proves that in the era of a hundred terabyte cloud architecture, the biggest vulnerability to the U.S.
00:17:44.079 --> 00:17:48.559
military is still a contractor misplacing a physical brass key.
00:17:48.880 --> 00:17:55.839
It's an absolute zero-tolerance policy for security breaches, whether they are digital intrusions or physical lapses.
00:17:56.000 --> 00:18:01.200
A compromised physical lock is treated with the exact same severity as a compromised cloud server.
00:18:01.519 --> 00:18:02.880
So what does this all mean?
00:18:03.039 --> 00:18:07.599
Why spend an entire deep dive dissecting a government request for proposal?
00:18:07.839 --> 00:18:19.119
Because whether you are a data scientist dealing with integration challenges, a project manager battling scope creep, or just someone fascinated by massive logistical puzzles, this Eve Ame document is a masterclass.
00:18:19.359 --> 00:18:19.839
It really is.
00:18:20.000 --> 00:18:29.359
It provides a real-time mechanical look at how a massive enterprise attempts to wrangle decades of fractured digital chaos into centralized, actionable intelligence.
00:18:29.680 --> 00:18:32.799
We've basically traced the complete operational journey today.
00:18:32.960 --> 00:18:37.200
It begins with a legal mandate from Congress demanding accountability for billions of dollars.
00:18:37.440 --> 00:18:37.599
Yep.
00:18:37.839 --> 00:18:45.279
That mandate spawns a hundred million dollar contractual framework designed to build a highly secure 100-terabyte relational database.
00:18:45.440 --> 00:19:00.319
And it culminates with elite data scientists writing complex algorithms to pull unadjusted ammunition and fuel receipts out of 75 different aging databases, normalizing the inflation rates and mapping them to specific M1 Abrams tanks.
00:19:06.400 --> 00:19:10.079
It is an unbelievable logistical and technical mountain to climb.
00:19:10.240 --> 00:19:12.079
But it leaves me with one final thought.
00:19:12.319 --> 00:19:18.880
We talked at the beginning about the true ongoing cost of owning a car, the oil, the tires, the unpredictable upkeep.
00:19:19.119 --> 00:19:19.200
Right.
00:19:19.440 --> 00:19:39.519
If the Evan Mosi project actually succeeds, and the DOD can instantly accurately track the exact true cost of every single bullet, every gallon of aviation fuel, and every mechanical repair hour tied to a specific vehicle, how might that unprecedented level of financial transparency fundamentally change the way future conflicts are budgeted, planned, and fought?
00:19:39.839 --> 00:19:49.039
When you remove the blind spot and eliminate the true cost of sustaining a military force, the strategic decisions regarding what equipment to buy and how to deploy it will inevitably shift.
00:19:49.359 --> 00:19:54.880
The lingering question to chew on as data continues to rewrite the rules of modern administration.
00:19:55.119 --> 00:19:57.279
Thank you for joining us on this deep dive.
00:19:57.519 --> 00:20:02.799
Keep exploring the hidden systems and massive databases that run our world, and we'll catch you next time.