Pentagon Turns to DAVE for More Efficient Buying
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By
Frank Konkel
The API-driven acquisition systems helps the Defense Department shift data from more than 450 sources.
The Defense Department is known as the biggest spender among agencies in the federal government, but it’d like to be known as one of the more efficient agencies at some point.
For that to happen, the Pentagon has to better use mission-driven analytics, according to Mark Krzysko, deputy director of acquisition resources and analysis within DOD’s Office of the Under Secretary of Defense for Acquisition, Technology and Logistics.
The department and military branch partners produce and collect growing amounts of data—everything from unstructured data sets to traditional business process information. The department’s focus, however, should be on how the data pertains to mission, Krzysko said.
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“It’s not about the data; it’s about mission,” Krzysko said Tuesday, speaking at an analytics forum hosted by FCW. “If you don’t understand how it’s fitting into your mission area, you might go awry.”
Krzysko helps oversee a $1.7 trillion portfolio that includes anything DOD buys, from paperclips to planes, collecting data from more than 450 disparate places in an effort to make sense of it. The undersecretary then uses that data to oversee programs, make decisions on them and report to Congress various spending data, Krzysko said.
Recently, however, the Pentagon has received some help from DAVE. That’s not a person—it’s the Defense Acquisition Visibility Environment, an API-driven and analytics-fueled acquisition reporting system. DAVE is the framework that covers the classification, business rules, sourcing and security around data, as well as the laws, policies and regulations that apply to it.
DAVE’s API-driven nature “gives us the ability to move that data around” and ultimately provide better spending information to program managers and senior executives across the Pentagon. More accurate spending statistics ought to lead to better oversight and return on investment.
“You need a strong foundation and framework,” Krzysko said. “That translates to a data management framework and infrastructure together that can support what you’re trying to do.”