The year 2017 has been a big one in terms of venture capital investments in quantum computing startups. Several significant deals have taken place this year with the expectation from the VCs that they will get a good return on their investment someday. Large companies funding internal developments are also looking to make their efforts eventually profitable. Although everyone agrees that successfully building a quantum computer is a very challenging task, one should also realize that getting an end user to successfully program and find value in the computer will be just as challenging, if not more.
With that in mind, I will try to outline four basic business models that I have seen that can be used to turn a quantum computing project into a profitable enterprise. Many companies are using a mixture of several of these models. So to help stimulate some thinking for those working to create their next business plan I am listing these models below to help provide a good framework for thought.
A platform supplier will try to provide all the tools and resources to an end user to utilize the technology to solve their particular problem. However, the supplier will not be an expert in the customerâ€™s use case like Salesforce with their articles on cloud-based ERP solutions and wonâ€™t even try to be. In the quantum computing world, this will entail providing the quantum computer, access to the quantum computer over the cloud, programming software, documentation and other tools. The supplier may also eventually provide training classes and a partner program to enable third parties to support end users to provide additional end user support. Clearly, IBM and D-Wave are currently using this business model with Google, Microsoft, Rigetti, IonQ, and others talking about using this model in the future.
Vertical Market Specialist
Programming a quantum computer is quite complex and entails large differences with the methodologies and algorithms that one might use in programming a classical computer. On the other hand, many of the potential end users will be experts in their respective areas such as chemistry, logistics, or artificial intelligence but have little understanding of the programming techniques used in quantum computing. They will require a lot of training and support to find a way to apply quantum computing to their problems. This chasm in skills between fully understanding the use case and the quantum programming will provide an opportunity for those companies that can help to bridge this gap. Although training individuals to be expert in both an end use area and quantum computing can be a long task, there can be efficiencies gained by a vertical market specialist if their expertise can be applied to help solve multiple problems for multiple clients in similar fields. The best example of this today may be QXBranch which is realizing the majority of its revenue from the finance and insurance markets.
They say that the people who made the most money during the California Gold Rush of 1849 were the folks who sold picks and shovels to the gold miners. Perhaps a similar phenomenon will happen with quantum computing. There is already an infrastructure of companies that are taking this component approach. This includes dilution refrigerator suppliers like Bluefors and Oxford Instruments, suppliers of certain specialized waveform generators, photonics, and measurement devices like Zurich Instruments, Tektronix, and Toptica Photonics, and software providers like QCWare, Cambridge Quantum Computing and others. Some developers of quantum computing processing chips may also want to take this approach rather than building the full machine. Supplying a components rather than a full quantum computer is certainly less resource intensive and offers lower risk for someone wishing to participate in the market. Silicon Quantum Computing in Australia will likely take this approach with their silicon based qubit chip.
Quantum Under the Hood
Another business model is to use a quantum computer as a means to offer a service for an end application. The end user may not even know or care whether the calculations were performed by a classical or a quantum computer. For example, a company may offer a cloud-based machine learning or computational chemistry, drug discovery, or logistics optimization service. They just know it is fast and provides valuable results. Google may be an example of someone who may use this as one of their business models since they have a strong interest and investment in various artificial intelligence applications and could leverage their quantum computing expertise to power these applications.
As the industry moves from being research oriented towards a more commercial orientation, achieving a monetary return on investment will continue to become more important and having a solid business model and marketing strategy may make the difference between getting funding or not.