Human–AI Collective Intelligence in Demand Planning

Problem Statement Despite the recognized potential of AI/ML in demand planning, many organizations struggle with its effective adoption, often due to a lack of clarity regarding the optimal balance between automation and human intervention. This uncertainty is...

The Human-Robot Duet: AI-Driven Warehouses

Problem Statement Despite the significant and growing capital investment in robotics for logistics—with 80% of warehouses expected to deploy some form of automation by 2028—Human-Robot Collaboration (HRC) remains sub-optimized and is currently failing to realize its...

Advanced AIML Demand Forecasting

Problem Statement FMCG demand forecasting efficacy is fundamentally constrained by current AI/ML models that are insufficiently dynamic and fail to integrate the influence of crucial exogenous variables (such as macroeconomic fluctuations, population shifts, and...

Supply Chain Risk Mapping for Quantum Computing

Problem Statement Recognizing its strategic significance, the importance of quantum computing has been underscored in maintaining technological leadership. On the global stage, the race for quantum supremacy intensifies. Given the high stakes, it is essential to...

Autonomous Negotiation

Problem Statement The AI advancements are driven by the need for greater speed, scalability, and strategic agility due to increasingly complex supply chains and disruptions caused by external factors. However, adopting AI isn’t straightforward. Data quality,...

Dell’s Digital Supply Chain Transformation

Problem Statement This research is the exploration of how leading organizations are transforming their supply chains through digital innovation and AI. Drawing on research conducted with more than 40 global companies, including Dell and Coca-Cola FEMSA, this project...