Description
Objective: The Defense Logistics Agency (DLA) seeks to develop and implement a dynamic workforce digital twin to enhance organizational effectiveness, support mission-critical decisions, and accelerate the adoption of advanced technologies. As Artificial Intelligence (AI) fundamentally changes the workforce of the future, the Department must achieve a 10x productivity increase to maintain strategic overmatch and compete effectively with near-peer adversaries and the workforce plays a critical role in achieving this scale. The primary objective is to create a Digital Twin (DT) of the organization capable of generating synthetic data and enabling leaders to react quickly to dynamic changes. This tool will inform key workforce-related decisions, improve how work gets done, and allow for robust scenario-planning for core mission activities under unpredictable global conditions. Description: A digital twin of the organization is a critical enabler for the DLA, empowering leaders to model and test workforce scenarios, optimize processes, and achieve the exponential efficiency gains required for modern great power competition. Current static models are insufficient for the agility needed today. The proposed solution will move beyond legacy systems by integrating real-time data to provide dynamic insights into workforce capabilities, productivity limitations, and the potential impacts of organizational restructuring. Crucially, this organizational DT must possess the capability to generate synthetic data to simulate complex, unforeseen scenarios, allowing the enterprise to react rapidly to supply chain disruptions, geopolitical shifts, or internal surges. By modeling the workforce of the future—one that is heavily augmented by AI—this effort will explore innovative data sources and functionalities to address critical questions: Strategic Competition & Productivity: How can we leverage the DT to identify structural and process pathways to a 10x productivity increase, countering the scale of adversaries like China? Surge Deployment & Rapid Reaction: How ready is the workforce for a sudden surge scenario? Utilizing synthetic data generation, how can we proactively test personnel moves to backfill deployed staff without mission degradation? AI Integration & Organizational Structure: What are the root causes of manual work, and what activities must be stopped or automated by AI? How does the organizational structure need to shift to maximize human-machine teaming and efficiently integrate new mission sets? Research and Development (R&D) efforts for this topic should demonstrate a technical feasibility that has not been fully established and must be judged to be at a Technology and/or Manufacturing Readiness Level (TRL/MRL) between 3 and 6 to be considered for funding. Keywords: Digital Twin, Workforce, Organization, Artificial Intelligence, Synthetic Data, Scenario Planning, Great Power Competition, Productivity, Logistics, Mission Readiness CMMC Level: Level 2 (Self)