The Product Management Opportunity in Quantum Computing
Ian Hellström | 6 December 2022 | 4 min read
Recent surveys by Omdia and Q-CTRL point to an urgent need for product management in quantum computing: vendors and early adopters disagree on the top priorities for near-term use cases.
Hardware researchers are already satisfied with 5 qubits, whereas 50 qubits is where industry experts see obvious benefits. This is hardly surprising, as the amount of genuine problems that can be solved with a handful of noisy qubits is approximately zero. Things get more interesting with over 50 high-quality qubits, as that is roughly where quantum advantage lies.
Vendors see optimization as the key use case for quantum computing, whereas industry practitioners are more interested in quantum machine learning. Vendors and customers, therefore, disagree on the value and relative importance of near-term use cases.
Just making a quantum computer available is not enough. Vendors must ensure product/market fit and that involves the entire stack: hardware, software, and services. This is especially challenging when the hardware exists in the lab.
A fair question to ask is whether it is too early for quantum computers in industry? The answer from product management is clear: it is never too early to discover what problems customers are trying to solve and find potential solutions for that. And that is an ongoing effort, not a one-off ‘requirements gathering’ exercise. What is more, companies from various industries have already built successful though mostly trivial first applications on top of quantum computers, so there definitely is near-term value to be had by customers and vendors.
A quarter of Fortune Global 500 companies are exploring quantum technologies. These early adopters are willing to put up with the rough edges of quantum technology as long as they see a strategic advantage. Most companies will not invest indefinitely with little to show for it though, particularly in an economic downturn.
It is on the vendors to show the value of quantum computing, even though most of that value lies in the distant future. That is the essence of product management: ensure that the business offers a product that is valuable, available, and familiar to the market, profitable to the business, and matches the overall company vision.
Products vs Projects
Product management goes beyond project management in that it seeks to deliver value early and often rather than deliver an initiative (as specified) on time and within budget, given certain resource constraints. The success of products depends on minimizing four product risks:
- Value — Is the product something customers will pay for?
- Usability — Can customers figure out how to use the product?
- Feasibility — Can scientists and engineers build the product with the expertise and resources available?
- Viability — Does the product work for our business overall?
While feasibility is the biggest obstacle on the road towards universal fault-tolerant quantum computers, the value risk is present even in the NISQ era. The same goes for usability of the entire stack. Viability applies to larger companies who do not solely focus on quantum and for whom quantum computing may pose a threat to their existing business models and processes.
What does this mean for quantum computing?
Project management is common in (academic) research, especially with larger scientific endeavours. Product management is not. Since many quantum startups have spun off academia, modern product management is unfamiliar territory.
Vendors must gain deep knowledge of and empathy for the problems customers and prospects face if they are to eliminate or at least reduce the four product risks. A laundry list of requirements is not sufficient: what customers need and what they claim they need are often very different, which is why understanding the customer problem and its impact is essential.
Without modern product management, vendors are liable to fall into the build trap, in which companies measure value by the number of things they produce (output) rather than the value they create for businesses and customers (outcome). Product discovery is about spending a little effort to uncover the right product to satisfy the market and business needs before investing a lot of resources in building a product. Without it, delivery often turns companies into feature factories that fail to capture a significant share of the market before they fizz out.
Rapid iteration and fast customer feedback are a lot easier with software than with hardware. A full-stack approach therefore offers obvious benefits: quantum vendors can try out different solutions with customers on simulators to see if they can capture significant value by solving relevant customer problems. The vendors themselves can use these simulators to understand the behaviour of their hardware and tweak algorithms. All four product risks can be reduced with such an approach.
The build trap leads to a poor product/market fit, which explains the survey results mentioned in the introduction. Vendors do well to learn the lessons from the past and adopt modern product management practices before their competitors do.