Supply chain problems can be among the first to benefit from quantum computers. As quantum hardware matures, the earliest production solutions of any kind that can run on quantum machines are supply chain optimization problems.

Quantum computing uses the physics of quantum mechanics as ‘bits’ in a computer. Bits in a classical computer can be ‘0’ or ‘1’ and by switching those ‘0’s and ‘1’s, a computer calculates a solution. In the classical world, a standard PC has millions of bits in its memory (RAM). In quantum computing, these ‘bits’ are called ‘qubits’. By taking advantage of aspects of quantum mechanics, a small collection of qubits can be equal to many times a group of classical bits. In other words, far fewer qubits are necessary to calculate a solution that has a similar number of variables. And, often, quantum computers can solve these problems much faster.

The number of qubits is one of the most popular ways to measure a quantum computer’s capability. It is far from the only metric and doesn’t necessarily describe how one kind of quantum computer is better than another. But main stream media and others used qubit counts as a simple benchmark. Depending on how one counts qubits(this is an ongoing debate), there are machines available via the cloud with somewhere between 30-100 qubits.

Putting this into context for a supply chain professional, lets consider a simple case of a truck routing. In our simplest example, we have one truck that needs to make a delivery stop at 4 different locations (stores, warehouses, homes, etc). What is the best(optimal path) for our truck? One route would be to go to store 1, then store 2, store 3, and finish at store 4. Another possibility is to start at Store 2, then 3, 4 and finally 1. There are 24 different combinations to choose. This seems like a trivial problem, and it is. A human can choose the optimal path with just a little bit of thinking.

However, now increase the number of stops to 25. The number of possible routes is enormous, 1.5 x1025 or 15,511,210,043,330,985,984,000,000 different routes! Classical computers can’t solve this problem in our lifetime. In real life we narrow the options by noting the different delivery windows of each store, or delivering one after another to stores very close together and so on. Our classical approach relies on constraints and assumptions to find a good solution. This works really well, until we add more variables or re-imagine these problems with different constraints.

But, a quantum computer can solve this. And, the best news? You need approximately 83 logical qubits to solve our 25-store delivery problem. This means current quantum hardware is very close to being able to solve our supply chain problem.

There is specific type of quantum computer, built using an approach called ‘quantum annealing’ and qubits ar counted a differently than other hardware designs. Quantum annealing is ideal for optimization problems like our truck routing example. DWave, a company that makes quantum annealing hardware has already demonstrated the ability to handle larger logistics problems, including having early success running actual production problems.

Supply chain professionals are in an enviable position. We are most likely to be the first to use real quantum computers to solve real world problems. Most non-supply chain problems will require more qubits before they can solve real world problems, including cryptography. The only other industry that can use early production equipment are chemists using quantum computers to search for small molecules to create new materials or pharmaceuticals.

The purpose here is to show that the quantum hardware is close to being ready for production. Its not too early to begin building capabilities in your organization to take advantage of this opportunity as soon as possible and create a lasting benefit for your company.