Improving Force Readiness by Reducing Risk in the Supply Chain

The warfighter’s ability to be force ready and resilient, across multiple risk and time horizons, requires a support network that is responsive, agility and reliable.  Measuring a supplier’s responsiveness, agility and reliability as part of a blended forecast methodology for future risk and supplier delivery enables planning, buying and logistics desks to prioritize their daily work across all suppliers and risk factors.  With better prioritization of work queues, resources are better able to review and respond to risk factors, resulting in improved asset availability, less stand-by time caused by parts unavailability, improved inventory positions and fewer stockouts,  The ForeOptics DAM suite delivers a risk classification score (Delivery Assurance Metirc) that, in conjunction with internal and >5M data points, forecasts future risk and a corresponding supplier delivery. This project will focus on an objective feasibility study to identify the strengths and weaknesses of the state-of-the-art (SOTA) stochastic methods as well as AI/generative AI methods for supply chain risk management as well as mitigation approaches to reducing biases and other risks that stem from biased data and AI algorithms that will use DAF data to feed the ForeOptics DAM suite.