Objective & Overview
The baseline performance of the Marine Corps’ Afloat Spares Packages (ASPs) has provided limited effectiveness in attaining a Full Mission Capable (FMC) aircraft deployed. USMC desires to increase effectiveness by influencing the type, range, and depth of the parts within these packages.
SteerBridge is utilizing Artificial Intelligence and Machine Learning to reduce customer wait time and increase squadron readiness. Our effort enhances cost efficiencies by providing a roadmap for algorithms using transactional data to forecast a more accurate mix of high and low-demand parts per aircraft.
The project is currently in Phase I which deals with data discovery and developing an algorithmic framework. We are also engaged in the ongoing development of cloud dashboards to visualize ASP data. Following an agile approach, USMC internal evaluation of prototype and feedback is ongoing so that the project best serves the end user.
Objective & Overview
U.S. Department of Veterans Affairs (VA) began transforming the education benefits of the GI Bill more than a decade ago with the passage of the Post-9/11 Veterans Educational Assistance Act of 2008. VA has determined there remains a need to modernize and improve GI Bill claims processing for veterans, service members and their dependents. This effort continues SteerBridge’s work in support of VA, including IT updates to implement the Harry W. Colmery Educational Assistance Act of 2017 and support to VA Call Centers.
Under the Digital GI Bill Delivery Program, SteerBridge is improving education claims processing and transforming other education and management systems for VA’s Veterans Benefits Administration (VBA). Our work includes configuring the GI Bill Claims Processing and Management Service by implementing updates required by the Veterans Health Care and Benefits Improvement Act of 2020 and providing IT and management consulting services.
The project is currently in the second of nine, one-year option periods. Already the improvements made in collaboration with AFS have drastically reduced 30 day waits for eligibility decisions down to minutes through a streamlined digital application. This effort follows a Human Centered Design approach to improve the user experience.