Supply chains are the lifeblood of the global economy, yet their complexity makes them challenging to manage. With over 50% of supply chain leaders planning to implement digital twin technology by 2023, virtual modeling is becoming a gamechanger for boosting supply chain performance.
What are Digital Twins?
Before diving into the applications, let‘s briefly examine what digital twins are and how they work.
A digital twin is a virtual representation of a physical object or process that uses real-time and historical data to enable learning, reasoning, and dynamic recalibration. Digital twins for supply chains combine vast amounts of data from across the ecosystem into living virtual models.
Supply chain digital twins integrate data from sources such as:
- IoT sensors
- Transportation databases
- Enterprise systems
- Supplier records
- Consumer feedback
Advanced analytics, artificial intelligence, and machine learning analyze this data to understand bottlenecks, predict disruptions, and test optimization strategies.
Now let‘s explore the top 5 applications of digital twins for supply chain excellence:
1. Test Supply Chain Design Changes
Digital twins allow companies to simulate changes to supply chain processes and infrastructure before disrupting live operations.
For example, a consumer packaged goods manufacturer could use a digital twin to model the effects of adding a new production line. The virtual simulation predicts how the change would impact output capacity, quality, labor requirements, and profitability.
Simulation via digital twins enables supply chain leaders to:
- Calculate costs and ROI of transformations before deployment
- Reduce risks by seeing impacts in advance
- Optimize designs through virtual testing
According to Gartner, half of all large industrial companies will use digital twins by 2026, enabling savings of up to 25% in conceptual design costs.
2. Map Your Supply Chain DNA
Digital twins give supply chain professionals an end-to-end view of their network by integrating data across suppliers, manufacturing, inventory, transport, and customers.
Mapping out the supply chain DNA enables businesses to:
- Spot inefficiencies anywhere along the chain
- Identify root causes of issues
- Continuously optimize based on insights
For example, a delivery provider could link data from truck sensors, traffic feeds, weather forecasts, and parcel tracking systems into a digital twin model of its logistics operations. This supply chain digital twin helps pinpoint causes of bottlenecks like driver shortages, distribution center congestion, or inclement weather.
With deep visibility, companies using supply chain digital twins increase on-time deliveries by 8-12%.
3. Inventory Optimization
For supply chain organizations, suboptimal inventory planning causes major headaches including shortages, excess stock, and costs.
Digital twins optimize inventory by combining demand forecasts, supply constraints, logistics barriers, and other variables into a virtual inventory model. This enables smarter strategies for:
- Safety stock levels across goods
- Order quantities and frequencies
- Buffer sizes by location
Cosmetics brand L‘Oreal implemented an inventory digital twin that increased product availability by 10% and lowered working capital by 20% over 3 years.
4. Intelligent Transportation Planning
Transportation is the driving force behind modern supply chains. Digital twins help optimize logistics by assimilating data from vehicles, traffic patterns, weather, and shipments.
For instance, a large grocery distributor could feed delivery route data from its truck fleet into a transportation digital twin. AI algorithms analyze the data streams to adapt routes based on changing conditions, avoiding delays.
Key use cases include:
- Dynamic routing based on congestion
- Fleet optimization for fuel efficiency
- Shipment tracking for supply chain visibility
Per DHL, real-time transportation digital twins can reduce delivery times by 10-40%.
5. Next-Gen Packaging Design
For packaging engineers, digital twins enable low-cost virtual testing of designs.
Packaging digital twins simulate the performance of different materials and structures under various conditions including:
- Vibration
- Compression
- Impact
- Extreme weather
This virtual testing identifies weaknesses earlier and optimizes protective packaging. Companies using the technology report up to 20% faster packaging design times.
Overcoming Digital Twin Challenges
While digital twins unlock immense potential, effectively leveraging them poses some key challenges:
Ensuring Clean, Connected Data
Digital twins are only as strong as their data foundation. Low-quality data leads to inaccurate models and simulations.
To fuel digital twins, supply chains need practices like:
- Data cleaning to fix errors and fill gaps
- Data integration across disparate systems
- Data governance for accuracy and accessibility
Emerging technologies like AI and ML can help curate reliable, comprehensive data sets from across the ecosystem.
Driving Adoption Across the Ecosystem
Since digital twins synthesize data from numerous players, adoption challenges arise when trading partners have fragmented technology maturity.
As supply chain leaders roll out digital twins within their organizations, they need to promote digitalization across the broader value chain. Change management and clear ROI cases are key.
Digital Twins – A Core Capability for the Future
Digital twins are unlocking transformative efficiencies, insights, and capabilities for global supply chains. By 2025, IDC predicts worldwide spending on digital twins to reach $48 billion.
For supply chain leaders, embracing digital twin technology today creates a resilient, predictive, and self-optimizing supply chain for tomorrow. With the power to synthesize exponentially growing data into dynamic planning capabilities, digital twins represent a core building block of the cognitive supply chain.
To continue your education on digital transformation, explore these additional resources:
Using Process Mining to Power-Up Supply Chain Digital Twins
Top Digital Twin Applications in Manufacturing
Digital Twins for Predictive Maintenance
For help identifying the right digital twin platform for your supply chain needs, see our detailed guide comparing providers.