Global supply chains are under increasing pressure. Whether it’s fluctuating demand, unexpected disruptions, or the sheer complexity of coordinating parts, products and people, traditional optimisation tools often struggle to keep up. In today’s volatile landscape, manufacturers and logistics providers need systems that aren’t just efficient, but adaptive.
Quantum computing is emerging as a powerful tool to tackle this complexity head-on. By processing vast combinations of variables in parallel, quantum algorithms can identify optimal or near-optimal solutions far faster than classical methods, even as conditions change in real time.
Case: Supply chain optimisation with quantum computing
Supply chains are intricate systems with countless moving parts, from raw material sourcing to inventory levels, warehouse locations, shipping routes, and demand forecasts. The challenge lies not just in planning, but in adapting to constant change: weather events, geopolitical shifts, transport delays, or supplier shortages.
Quantum algorithms, particularly the Quantum Approximate Optimisation Algorithm (QAOA), can explore huge optimisation spaces in parallel, helping to solve problems that are either too large or too time-sensitive for classical computers.
- Applications include: Vehicle routing: Finding the most efficient paths for fleet operations
- Inventory optimisation: Balancing stock across multiple locations to reduce costs and delays
- Real-time re-optimisation: Dynamically adjusting operations in response to sudden disruptions
- Demand forecasting: Improving the accuracy of predictions by modelling complex correlations
Most current implementations use hybrid quantum-classical approaches, with classical systems handling real-time data inputs and quantum solvers tackling the hardest parts of the problem.
Business value
- Cost reduction: Quantum optimisation reduces fuel costs, warehousing expenses, and inventory losses by fine-tuning logistics flows.
- Increased resilience: Organisations can respond to disruptions faster, re-routing shipments, reallocating resources, and avoiding bottlenecks.
- Improved customer service: More accurate demand forecasting and reliable delivery windows enhance satisfaction and retention.
- Competitive advantage: Quantum-enabled supply chains support more agile, efficient operations, a key differentiator in fast-moving markets.
Technology readiness
Quantum supply chain optimisation is already in the pilot and proof-of-concept stage, with encouraging results from hybrid approaches. While current hardware cannot yet solve the largest commercial problems at scale, key components, like routing and scheduling, are already being tested in live environments.
As quantum hardware improves, full-scale deployments will become more feasible, offering deeper integration with ERP, logistics and procurement systems.
For now, the most forward-thinking organisations are laying the groundwork, investing in partnerships, building internal expertise, and preparing for scalable implementation as the technology matures.
Leading players and experiments
Volkswagen, in collaboration with D-Wave, has run pilots on optimising taxi routing and traffic flows in urban centres using quantum algorithms.
IBM is partnering with logistics and manufacturing clients to explore supply chain use cases through its quantum cloud platform.
DHL and Maersk are working with quantum software startups to model distribution scenarios and improve operational responsiveness.
Multiverse Computing is developing quantum-native applications for logistics, inventory management and financial forecasting, with a focus on industrial supply chains.
Discover more use cases here.
