Digital twins enhance supply chain efficiency with predictive AI: report

Digital twins also improve network design, optimising distribution centre placement.

Digital twins, which are virtual replicas of objects or systems, enable organizations to simulate real-world scenarios using real data and predictive AI, QuantumBlack said.

In its report, QuantumBlack noted the technology empowers businesses to model end-to-end supply chain processes, from production to distribution, offering unprecedented insights for decision-making.

Digital twins address some of the most pressing challenges in supply chains today, including labor shortages, inventory management inefficiencies, and fulfillment delays.

They enhance demand planning through dynamic SKU-level forecasting and optimise sourcing and production by balancing costs, logistics, and customer satisfaction.

Digital twins also improve network design, optimising distribution centre placement, and inventory management. In fulfillment and logistics, they help reduce last-mile delivery costs and ensure on-time deliveries.

QuantumBlack emphasises the significant benefits of adopting digital twins. Organizations can achieve up to a 20% improvement in delivery performance, reduce labor and logistics costs, and improve inventory positioning.

While the potential of digital twins is immense, QuantumBlack acknowledges the challenges of implementation. Building these systems requires significant investment, robust data integration, and specialized expertise in data science and AI.