DLA News Archive

News | June 17, 2022

DLA expanding use of DOD advanced analytics tool

By DLA Information Operations

The Defense Logistics Agency Chief Data and Analytics Office hosted Advana/DLA Day June 9 to discuss the data platform’s capabilities and security features.

DLA senior leaders attended along with representatives from the Office of the Under Secretary of Defense for Acquisition and Sustainment, OUSD Comptroller, Joint Staff, U.S. Transportation Command and Advana. 

Advana, a mashup of the words “Advancing Analytics,” is a Defense Department platform that pulls data from hundreds of business systems to make it discoverable, understandable, and usable for advanced analytics. The platform organizes data and depicts it in filterable dashboards. It also provides decision makers and analysts access to enterprise data and structured analytics in a scalable, reliable, and secure environment. 

DLA is working to expand its use of Advana to make data-driven business decisions.

“We want to ensure that DLA is both a good teammate and consumer of data but also a contributor to the overall data landscape,” DLA Deputy Director Brad Bunn said.  

Expanded use of the Advana platform supports the department’s goal to become a data-centric organization.

Greg Little, OUSD Deputy Comptroller for Enterprise Data and Business Performance, underscored the importance of a shared approach to using the platform, emphasizing how Advana combines data from multiple functional areas and organizations to provide leaders with the whole picture.

“We want to see all of the dots connected within that picture and that’s really what we’re trying to achieve with Advana,” Little said.

Logisticians from Transcom, the Joint Staff and other organizations provided Advana demonstrations. Attendees also discussed opportunities to leverage DLA’s data along with external data from vendors and other federal agencies.

DLA Chief Data and Analytics Officer Lindsey Saul urged agency senior leaders to consider future use of the Advana platform and how it will affect DLA’s data architecture.

“The questions [we need to answer in DLA] are what is the universe of data that we need and what data do we want to bring in externally? What type of analytics do we want to do? These questions will drive decisions for our to-be data architecture,” Saul said.