Digital Twins for Supply Chain

Trend Definition 

What is the essence of this trend? What is its impact? 

• Essence: Digital supply chain twins and the enterprise metaverse are digital representatives of their real-life counterparts that allow scenario analysis, predictive maintenance, and stress testing
• Impact: Digital twins enable companies to optimise their supply chain activities by identifying bottlenecks, enhancing efficiency and predictability, stress-testing, and creating transparency regarding the impact of changes and events along the supply chain

Trend Drivers 

Why is this trend emerging now? What’s changing? 

• Improved Data Foundation: Rapid growth in IoT, AI, and cloud computing enables more sophisticated digital replication of physical supply chains and the thorough simulation of various events to make early adjustments due to improved data collection and availability
• Need for Resilience: Increasing global supply chain disruptions necessitate more robust predictive and responsive solutions
• Demand for Efficiency: Pressure to reduce costs and downtime while improving productivity as well as an increasing awareness for sustainability drive the adoption of advanced digital solutions

Use Cases 

How to apply this trend? 

• Stress Testing in Logistics: Supply chain twins are used for dynamic simulation and stress testing, enabling proactive management of potential disruptions
  Example: DHL’s usage of digital twins helps in the management of container fleets, monitoring shipments, and logistics systems
• Alternative Materials: Simulation of CO2 emissions caused by different materials
  Example: Microsoft used digital twins to simulate how replacing wood with alternative materials in the sourcing of their pallets can reduce carbon emissions

Procurement Relevance & Response Strategies 

How should Procurement adapt its Processes, Organisation, and Strategy?

• Laying the Foundation: Start collecting data, introduce simulation software, and conduct simulations, for instance using JAGGAER or ivoflow, to enable a profound preparation for extreme events through the identification of bottlenecks
• Predicting Disruptions: Using the results of digital twin analysis can help mitigate the risks of supply outages