How quantum computing can improve supply chains

Quantum on the horizon

Most organizations, however, can't yet use the power of quantum computing to solve supply chain management and logistics challenges -- or for any other purpose, for that matter.

Quantum computing is still in its early stages, according to Scott Likens, U.S. and global chief AI engineering officer at professional services firm PwC. Only a handful of large technology vendors have built quantum computers, and the capacity of those computers is not at a scale to handle widespread commercial demand.

However, Likens said organizations can access quantum computing technologies through cloud quantum-as-a-service platforms, and they can run quantum algorithms through simulators as a way to develop and test them before running them on real quantum processors.

Likens and others said organizations should consider now how they will put the technology to use as it matures.

"Quantum computing isn't ready for production use in most supply chains today, but it's advancing quickly," Mukesh Ranjan, vice president at research and consulting firm Everest Group, said in an email response to questions. "Leading organizations are experimenting through pilots and proofs of concept, often via quantum-as-a-service platforms from cloud providers."

Quantum computing use cases in supply chain and logistics

Ranjan explained that quantum computing's promise to transform areas such as route optimization, inventory placement, demand forecasting and disruption modeling lies in its ability to process vast numbers of variables and constraints in parallel, which enables it to find better solutions faster than classical algorithms in highly complex scenarios.

In fact, quantum computing is already having a powerful impact.

According to a 2023 report in the Virginia Economic Review, the Port of Los Angeles -- the largest facility handling shipborne cargo in the United States -- used quantum computing to streamline operations at its second-largest shipping container terminal, "with cranes increasing their number of deliveries by more than 60%, and the trucks arriving there each spending nearly 10 minutes less to receive their payloads," the report said.

That could be just the start of the breakthroughs, as organizations begin to experiment with quantum computing and quantum algorithms to optimize routes, plan for weather events and maximize fleet utilization.

Here are the key use cases for quantum computing in supply chain management and logistics:

1. Route optimization

As Ranjan highlighted, the algorithms used in quantum computing are capable of simultaneously considering myriad variables, such as possible routes and traffic scenarios, in parallel rather than linearly, as in classical computing. That enables quantum computers to be better at identifying the most efficient routes with quicker delivery times and lower fuel consumption, Rege said. Moreover, quantum computers can produce results in a fraction of the time it would take today's computers to do comparable analyses.

2. Improved warehouse operations

Rege described a related use case, in which companies can use quantum computing to determine the optimal routes and sequencing of activities in warehouses, such as locating and retrieving products to fulfill orders -- a process known as picking. Like other quantum computing applications, this use of the technology would save time and money while reducing waste.

3. Improved inventory management

Similarly, quantum computing analyzes the many complex data sets organizations use to understand their inventory needs. It enables organizations to do a better job identifying optimal inventory levels, thereby cutting the cost and waste of excess inventory while ensuring enough inventory is in stock to meet demand. The analysis typically involves demand forecasts as well as vendor, market and contract data. Quantum computers can perform this type of complex computation better than classical computers because they use quantum bits, or qubits, which can have a value of 1 or 0 or both at the same time, meaning they have the ability to exist in multiple states. That, in turn, enables more accurate calculations on data.

4. Cargo loading

This is an area where quantum computing is already delivering benefits, said Jeff Zych, a partner at Guidehouse, a global advisory, technology and managed services firm. Organizations use it to determine where packages should be placed on a ship, plane or truck to ensure maximum efficiency based on calculations across multiple dimensions, he said. According to a report from D-Wave Quantum Systems, a provider of quantum computing hardware, software and services, quantum-based cargo loading improves weight distribution and balance, enhances loading speed and efficiency, and better handles complex loading constraints simultaneously.

5. Fleet utilization optimization

Logistics providers are likewise looking to use quantum computing to improve fleet management, Rege said. He explained that quantum computing -- and even quantum algorithms running on simulators or hybrid quantum computing, where classical and quantum computers work together to solve problems -- can analyze the multitude of data sets used in fleet management and consider them within various parameters. They can then devise the most effective and efficient use of vehicles in the organization's fleet, no matter how large or dispersed.

6. Weather forecasting

Quantum computing's ability to process large amounts of data in parallel is expected to benefit weather forecasting, Likens said, noting the infinite number of permutations of weather. Improved weather data can be used to generate more insights in other areas of supply chain and logistics operations. That, in turn, could lead to better results for organizations seeking to optimize routes as they work through IROPs, or irregular operations, where the ability to analyze complex data in near real time helps in making quick decisions.

How supply chains can begin integrating quantum computing technology

Quantum computing at scale is still a ways off, and predictions about when the technology will be ready for broad commercial adoption vary from a few years to more than a decade.

Exact predictions aside, Likens said the technology is advancing faster than most people predicted. He and others advised supply chain and logistics leaders to prepare now for quantum computing's arrival.

They advised executives to do the following:

1. Get educated about quantum computing

"Organizations that begin exploring quantum early will be better positioned to capitalize when the technology matures. Even short-term engagement can surface new insights into supply chain inefficiencies and prepare teams for a quantum-augmented future," Ranjan said.

2. Pick the right use cases to pilot

Access to quantum computing resources is limited and expensive, and it will likely remain costly to use for the foreseeable future. Rege said organizations should consider where they'll get the most value from using the technology and start by trying to address those challenges. A large retailer's first application of the technology might be to improve its inventory management, for example, while a transportation company might use it to optimize routes, he said.

3. Estimate the ROI of each proposed use case

Rege also advised organizations to consider the returns they'll get for each quantum computing use case to ensure the costs don't exceed the anticipated ROI. Additionally, he and others stressed that quantum computing is not the right technology for all analytics work, explaining that classical computing remains the better choice for some types of data analysis.

4. Build skills

Organizations should start building quantum computing skills now, so they'll be ready to take advantage of the technology as it matures and becomes mainstream, Rege said. That means hiring or training workers on quantum algorithms. It also means modernizing IT infrastructure and adopting quantum-safe encryption, which is also known as post-quantum cryptography. "We want to make sure we have the skill sets to make use of this technology, and the right security protocols to protect data," Rege added.

5. Be realistic about accessing quantum computing resources and what they can deliver at this early stage

"Quantum computers are extremely sensitive, expensive and still in development. Current limitations in hardware scalability, error correction and algorithm maturity make them impractical for broad operational deployment right now," Ranjan said. "Challenges include limited access to stable quantum hardware, a shortage of quantum-literate talent, and the need to re-architect existing models to take advantage of quantum capabilities. There's also a long learning curve for organizations new to quantum thinking."

Mary K. Pratt is an award-winning freelance journalist with a focus on covering enterprise IT and cybersecurity management.