Strengthening Supply Chain Resilience Through Automated Data Labeling and Predictive Analytics

The Army and broader Department of Defense (DoD) is re-aligning to strategically prepare for a confrontation with China. This will involve planning and deploying forces across the vast Pacific Ocean; at times, with distances as far as 7,000 miles. This creates a ōtyranny of distanceö scenario where the sheer size of the area of operations (AOR) limits the ArmyÆs combat readiness and force projection capabilities. The Army lacks dynamic logistics and supply chain planning capabilities that ensure rapid resupply of material and aid across the Pacific AOR. ĀCurrently the Army utilizes static planning tools that cannot account for the shocks or disruptions that a conflict with China would entail.Ā The Army therefore requires an advanced logistics planning capability that harvests the enormous amount of logistical and supply chain data on-hand and enables it to better plan and model supply chain contingencies and shocks that a war with China will bring. r4 Technologies proposes to develop a modified/adapted prototype of its ĀXEM Logistics Planning Platform to enhance current Army supply chain and logistics planning. Ār4 XEM is a best-in-class Artificial Intelligence and Machine Learning (AI/ML) Software as a Service (SaaS) platform that accelerates and enhances end-usersÆ ability to proactively identify, predict, protect, detect, respond to, and plan and recover from logistics and supply chain fluctuations. The r4 XEM platform is a highly automated, rapidly deployable AI/ML software platform that utilizes a proprietary ōDigital Twinö capability to make predictions, recommendations, or optimizations for supply chain and logistics planning. The r4 XEM platform easily connects to both legacy systems and systems of record such as Vantage, Advana, or G-Army and enables advanced AI/ML algorithms to drive significant improvements in logistics scenarios planning. The r4 XEM platform synchronizes demand and supply inputs across three (3) domains: 1. Demand-side AI Domain Models to understand and predict readiness and consumption patterns. 2. Supply-side AI Domain Models to provide a holistic view of each supply ecosystem. 3. Predictive Logistics optimizations to augment decisions and take prescriptive actions. The r4 XEM AI/ML platform provides an end-to-end holistic predictive capability from data ingestion, data preparation, analytics, modeling, and through to output/export to reports or visualizations. Ār4 XEM routinely provides outputs to existing User Interfaces removing the need for end-users to be trained on yet another data system. ĀWe envision the XEM platform feeding either the ArmyÆs PEO C3T Command Post Computing Environment (CPCE) or Army Future CommandÆs Pangea visualization tool hosted within the Lower Echelon Analytics Platform Tactical (LTAC). Results from any established use cases on other software platforms can also feed the XEM platform as an input, or outputs from XEM can feed any of the established use cases to improve their outcomes. Ā