Scott Buchholz is the CTO of Deloitte Consulting LLP‘s Government and Public Services practice.
There have been significant research advancements in quantum computing in recent years, and a bridge exists between those developments and how the technology can benefit organizations today.
Business leaders need to be aware that the bridge exists to start preparing for the quantum future (whichever form or forms it takes), but should not plan to sprint across that bridge. In a recent report my team and I published, we discussed how leaders can balance quantum computing investment timing to avoid spending too early without ROI or delaying it so long that they fall behind.
Leaders should balance business outcomes and accountability with novel intellectual property development in their organizations’ quantum computing journeys.
Why Leaders Should Consider Using Quantum-Inspired Techniques
I previously wrote about three quantum-inspired techniques that can run on current classical hardware: quantum-inspired feature engineering for machine learning, quantum-inspired simulated annealing and quantum-inspired Monte Carlo alternatives.
These quantum-inspired techniques give leaders an opportunity to improve outcomes without the risks of waiting for quantum computing to mature commercially or making investments in technology that may not yield short-term results.
For instance, teams can use quantum-inspired feature engineering to improve existing machine learning pipelines for anomaly and fraud detection. They can leverage quantum-inspired simulated annealing to tackle complex optimization problems, such as inventory management and supply chain logistics. As for quantum-inspired Monte Carlo alternatives, leaders can use them to make more accurate valuations and risk assessments, such as derivative pricing and estimates of catastrophic but rare events.
Which techniques an organization should explore depends on its industry and the use cases it wants to solve. A bank may benefit from quantum-inspired feature engineering for fraud detection, whereas a manufacturer would see more value in quantum-inspired simulated annealing for supply chain logistics.
A Four-Part Framework For Quantum Investment And Capability Building
Regardless of which technique(s) leaders pursue, they should do so in a structured, measured way. I’ve observed several organizations with quantum computing initiatives that operate under innovation departments with little accountability for generating ROI. In some cases, that’s appropriate. A biotech startup at the cutting edge of genomics research might prioritize scientific exploration over near-term ROI in its quantum efforts, with good reason.
But leaders should treat such cases as exceptions. Scientific novelty at the expense of business relevance and impact can cost organizations valuable time and money—with little to no ROI. In our report, my team and I developed a four-part framework for quantum investment and capability building.
First, leaders should design their quantum efforts around testability. They should frame every hypothesis around a business problem, not interesting science. It would be useful for a bank to explore, say, quantum applications beyond its core needs in fraud detection and risk management, but it would not necessarily be impactful to its bottom line.
As leaders start leveraging quantum-inspired methods, they should evaluate whether these methods generate more value than current methods. For example, if a team pilots a quantum-inspired simulated annealing solution to improve supply chain logistics, are delivery times and costs improving significantly? If leaders notice that the results aren’t up to par, they should stop and move on to the next-best quantum-inspired alternative that can deliver results. While some ideas and initiatives may prove merely intellectually interesting, some may have real business payoff. Pursuing a strategic path to quantum computing hinges on leaders’ ability to quickly tell the difference.
Once leaders can distinguish investable opportunities from merely interesting ones, they should put small teams and modest budgets behind the techniques that are showing promise. For example, they may consider dedicating a couple of data scientists or engineers already on staff and adding a Ph.D.-level specialist or a part-time external advisor to support method selection and validation. Budgets should also cover training, sandboxes and a few priority use cases that can be tested and refined quickly.
If leaders determine that their initiatives are delivering results, they can gradually expand their use of quantum-inspired techniques before committing to full production. What works in one pilot or a few pilots may not yield great ROI when scaled across the organization.
Regardless Of What The Future Holds, Leaders Can Still Benefit From Getting Started Today
The reality is that we don’t know how exactly quantum computing technology will materialize in the business world in the future. It may never fully materialize. But leaders shouldn’t regret preparing for an eventual quantum future. Even if it never occurs, they can still gain material advantages in the interim.
Delaying action puts leaders at risk of falling behind and having regrets later. Getting started now, regardless of what the future holds, can help leaders in the here and now.
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