The Technology Clock: Progress Doesn't Always Look Like Growth (The Four Clocks of Deep Tech — Part II)

The technology clock

Imagine two startups that have each spent the past twelve months building their businesses.

The first has doubled its users, increased recurring revenue, and released several new versions of its product. The second has generated almost no new revenue. Instead, it has taken a technology that worked reliably in a controlled laboratory, redesigned critical components, completed hundreds of hours of testing, improved manufacturing repeatability, and demonstrated that the system can operate safely in the environment where customers will eventually use it.

Which company made more progress?

Conventional startup metrics would probably favor the first. In deep tech, the answer is far less obvious.

This is the challenge of the Technology Clock, the first of the Four Clocks of Deep Tech we introduced in our previous article. Technology, Customer, Capital, and Ecosystem each move according to different timelines, and successful commercialization depends on learning how to synchronize them. But before those clocks can align, founders and investors need to understand something fundamental about the first one: technological progress does not always look like business growth.

Deep Tech Is Not Necessarily Slow

There is a common narrative around deep technology that deserves challenging: deep tech takes a long time, consumes enormous amounts of capital, and eventually, if everything goes well, becomes commercially viable.

There is some truth behind the perception. Deep-tech ventures are characterized by intensive early-stage R&D, elevated technical risk, specialized equipment and facilities, and significant funding requirements before commercialization can begin [1]. Yet recent evidence also complicates the idea that deep tech is simply slow. McKinsey found that European deep-tech startups reached $1 billion valuations in an average of five years and seven months—28 months faster than conventional technology startups [2].

Deep tech, therefore, is not inherently slow. It is nonlinear.

A software company can often demonstrate progress continuously through users, revenue, retention, and product iterations. Deep-tech companies frequently create value differently. Long periods of seemingly limited commercial movement can be followed by major jumps in value when a critical technical risk is removed.

A successful qualification test can matter enormously. So can demonstrating manufacturing repeatability, achieving regulatory approval, proving reliability in the field, or establishing flight heritage. Revenue may barely move while the probability of commercial success changes dramatically.

From “Does It Work?” to “Can We Depend on It?”

Stages of the technology clock

Early in a deep-tech company's life, the technology question can sound deceptively simple: Does it work?

But a successful laboratory demonstration answers only a narrow version of that question. A robot may perform perfectly during a controlled demonstration but struggle with dust, vibration, unpredictable human behavior, or thousands of continuous operating hours. A new material may demonstrate extraordinary properties in a laboratory but prove difficult to manufacture consistently at industrial volumes. An aerospace component may achieve its target performance but still require extensive qualification before anyone is willing to fly it.

As commercialization approaches, the question evolves. Can it work repeatedly? Can it work outside the laboratory? Can someone other than the engineering team operate it? Can we manufacture it consistently? Can we maintain it? Can we certify it? Can a customer depend on it?

That transition—from proving scientific or engineering possibility to proving operational reliability—is where much of the Technology Clock actually runs.

Technology Readiness Levels, or TRLs, provide one useful way of describing technological maturity. NASA uses a nine-level scale running from basic principles at TRL 1 to a system proven through successful operations at TRL 9 [3]. But TRL alone cannot tell founders whether they have a business.

A technology can be technically mature while manufacturing remains immature. It can perform reliably while unit economics remain commercially unattractive. It can pass qualification while integration remains too difficult for customers. Technical readiness is necessary. Commercial readiness is multidimensional.

The Dangerous Pressure to Look Fast

This creates an uncomfortable tension for founders. Startup culture celebrates velocity. Investors understandably want evidence of progress. Boards want milestones. Employees want momentum. Customers want delivery dates. Founders themselves feel pressure to demonstrate that the company is moving quickly.

In software, shipping faster can often create valuable feedback. In deep tech, moving faster is valuable only when it does not create false progress.

Prematurely freezing a design can create expensive redesigns later. Scaling manufacturing before reliability is understood can multiply defects rather than revenue. Announcing aggressive delivery timelines before qualification is complete can turn engineering uncertainty into customer disappointment.

The objective should not be to make the Technology Clock appear to move faster. It should be to make every movement of that clock remove meaningful uncertainty.

This distinction becomes particularly important when capital is limited. Every test, prototype, and engineering iteration should ideally answer a question that materially changes the company's risk profile. If this prototype succeeds, what have we proven? If this qualification test passes, what becomes possible that was impossible yesterday? If we spend the next six months improving reliability, what customer, certification, or manufacturing milestone does that unlock?

Those questions connect engineering progress to company progress.

Runway Should Buy De-Risking, Not Time

This leads to one of the most important financial implications of the Technology Clock. Founders commonly describe runway in months: “We have eighteen months of runway.” For deep tech, that number is incomplete.

A more useful question is: What will those eighteen months buy?

If eighteen months takes a company from an early prototype to a qualified system ready for customer deployment, that runway may create enormous value. If eighteen months produces a more sophisticated prototype but leaves the same fundamental questions about reliability, manufacturability, and customer adoption unanswered, the company may simply arrive at its next fundraising round with less cash and largely the same risk.

This is why deep-tech planning should be built around de-risking milestones rather than elapsed time alone.

Recent cleantech evidence illustrates the nuance. McKinsey's 2026 analysis of more than 11,000 companies found that around 60% of top-tier companies advanced by more than two TRL stages between 2015 and 2025, and around 80% reached TRL 9. Importantly, the strongest performers did not simply move fastest: they advanced deliberately and steadily while de-risking both technology and the business model [4].

The lesson is not that every company should race toward TRL 9. It is that capital should produce measurable reductions in risk.

When the Technology Clock Meets the Other Three

The Technology Clock cannot be optimized in isolation.

Imagine spending three years perfecting a product before allowing a customer to meaningfully interact with it. The engineering may be exceptional, but the company could discover that it solved the wrong operational problem. The opposite is equally dangerous. A customer may love an early prototype and request deployment before the technology is sufficiently reliable. Commercial pressure then begins dictating engineering decisions, potentially creating technical debt in a physical system where mistakes are considerably harder to patch after deployment.

This is why the Four Clocks framework matters. Technology should progress alongside evidence from the Customer Clock. Its development plan must remain achievable within the Capital Clock. And its path toward deployment depends on regulation, infrastructure, supply chains, and standards represented by the Ecosystem Clock.

Recent research on corporate–scale-up partnerships reinforces this interaction. McKinsey found that successful partnerships can provide scale-ups with industrial capabilities, market credibility, customer access, and commercialization pathways that would take years to build independently; unsuccessful pilots often lack a clear path from technical success to commercial rollout [5].

The laboratory cannot answer every question. Eventually, technology has to meet the world.

Progress Should Be Measured by What Becomes Possible Next

Deep-tech founders should absolutely move with urgency. But urgency and speed are not the same thing.

Speed asks how quickly something was completed. Urgency asks whether the organization is relentlessly focused on resolving the uncertainties preventing the technology from becoming commercially viable. That is a much more useful measure of progress.

The Technology Clock does not need to tick at the speed of software. Nor should founders use the complexity of deep tech as an excuse for endless R&D without commercial accountability.

The objective is to understand exactly what the next technical milestone unlocks—and to make sure the Customer, Capital, and Ecosystem clocks are moving with it.

Because the most valuable technical milestone is rarely the one that makes the technology more impressive. It is the one that makes the next stage of commercialization possible.

References

[1] McKinsey & Company, “Europe's deep-tech engine could spur $1 trillion in economic growth,” October 29, 2025. Source

[2] McKinsey & Company, “Deep tech's speed advantage,” January 20, 2026. Source

[3] NASA, “Technology Readiness Levels,” updated June 25, 2026. Source

[4] McKinsey & Company, “Cheaper, faster, better: A formula for cleantech scaling success,” May 11, 2026. Source

[5] McKinsey & Company, “How corporate–scale-up partnering can boost Europe's tech competitiveness,” June 10, 2026. Source