Staying up on emerging technologies, changing public perceptions, and breaking government action makes us better at our jobs.
December 4, 2024
The US government has long viewed technological development as a national priority and key competitive advantage. However, current policy geared toward technology commercialization is misaligned in how it measures success.
As an example, in July 2024 the US National Science Board (NSB) released a policy brief called A Changed Science and Engineering Landscape that yielded the following conclusions:
“Federal investment is the foundation of R&D funding, but business funds most US R&D.”
“China is our biggest competitor and collaborator.”
There is “a need to re-build STEM education and build a robust STEM workforce.”
These are all vital findings. But by stopping there, the NSB only tells part of the story. .
STEM education, STEM training, and fundamental STEM research are without a doubt the pedestal of the US’s efforts to stay at the forefront of technological power. The report implies that if we pour more and more money into these areas, we will cement our status as the world’s technological leader.
Of course, it is not wrong to say that putting more money into something will likely yield greater returns. It is certainly true that we need fundamental scientific expertise and comprehension before we can extract applications from it
However, we should work smarter, not harder.
The NSB report concludes with the push for a national-level STEM education workforce policy. The metrics they cite are number of patents produced, number of doctorate-level workers, and student average mathematics scores. This fails to address an enormous leak in the pipeline to technological leadership.
If we want to “ensure US leadership in critical and emerging technologies,” as the report demands, we cannot continue to ignore the last segment of the pipeline, which is technology adoption.
Geoffrey Moore describes the technology adoption life cycle curve in his book Crossing the Chasm. The key feature of the life cycle is the “valley of death” that lies between first adopters who will buy a new technology just because it is cool and mainstream customers who care little about the technology and instead are seeking a solution to a problem. The US needs to bridge this chasm to launch new technologies into the mainstream.
This goes beyond the number of patents created or the number of PhDs awarded. It goes beyond the number of startups created. It even goes beyond the amount of venture capital invested in said startups.
We need to examine how to make current technological product pipelines more efficient. We have major leaks that must be addressed in several key areas of PhD workforce development, startup success rates, and the process of building products that people can use.
Today, there are only enough professor jobs available for fewer than 1 out of 10 PhDs, and this PhD glut has existed for decades. Despite this, PhDs receive little to no support in exploring nonacademic jobs.
This is improving, but only slowly—and certainly not at the scale required to address the US’s increased emphasis on technological leadership. PhD-granting institutions must overcome certain obstacles in terms of career coaching, but we also need to change mindsets around “quitting science” and “selling out.”
Furthermore, we need to level up our integration of entrepreneurial education into K-12, undergraduate, and graduate education. Amazing STEM technology is emerging from US universities, and yet very few programs are teaching students how to use these new tools to solve real-world problems.
Many universities are now providing entrepreneurial education, although too often it is taught “on the side” instead of integrated into a traditional degree program. The National Science Foundation (NSF) iCorps program, as an example, offers immersive entrepreneurial training within the university setting. If entrepreneurial education exists, it exists for those who, practically speaking, already know they want it.
If we agree, however, that graduate-level education is a key part of boosting US competitiveness in cutting-edge technology, we need to take a new approach that is gradual and continuous.
We need to do a better job of equipping entrepreneurs with the training they need to succeed. It is well known that the majority of startups fail. The statistics vary based on the type of startup or its age, but the often-cited number is a 90% failure rate. It is less well known that one of the top reasons for failure is lack of market need (which is discussed in more detail below).
To put it another way, a startup rarely fails because of scientific or technological risk itself. It may be difficult to lower the technical risk of developing a product, but market risk can be minimized with the right combination of customer discovery and business strategies. We have many new entrepreneurial tools specifically targeted to deep tech startups and corporate innovators.
If we could reduce the startup failure rate and bring innovative technologies to the market at greater rates, think of how much further STEM education budgets could go.
What is prevalent, especially for scientifically inclined mindsets, is the “build it and they will come” mentality.
This problem is not unique to startups; it is also rampant in corporate and government spheres. The default direction of scientific thinking is: “This technology is profound. What product can we make from it?” instead of: ”This problem is profound. What technology can address it?”
We need much more of the latter here, but it feels like an uphill battle to reverse this ingrained approach. However, it must be reversed. Building technology for a customer who won’t buy it or does not need it is a recipe for failure. What if we could orchestrate a paradigm shift away from “build it and they will come” as the default and instead embrace “build something that someone will use to solve a problem”?
If we want technology products that make an impact, we need to leave “build it and they will come” behind.
We already have powerful tools that are being used to address this problem. Within the context of startup companies, the art of customer discovery is standard curriculum for entrepreneurial education, startup accelerators, and the iCorps program. However, as mentioned above, entrepreneurial education and mindsets are typically not integrated into science education. Better and earlier integration into the educational pipeline will help avoid “build it and they will come” as the default mindset.
In addition, for many companies, customer discovery gets operationalized in the form of product managers. A product manager’s express purpose is to be the liaison between researching customer pain points and translating them into requirements for product development.
Product managers are the foot soldiers tasked with ensuring the company is building the right thing so the engineers can build the thing right. Product management is not a new job concept, and yet product managers themselves are still underutilized across companies that typically don’t fully understand their role.
This is especially true for technical product managers, perhaps because of the prevalence of “build it and they will come.” However, in an era where the US must find ways to generate cutting-edge products that are quickly adopted and solve urgent problems, it is critical that we double down on training technical product managers.
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We are living in an incredible age of scientific discovery but also one of grave concerns for humankind—concerns like climate change, pandemics, and international political tension. The US has a chance to cement its role as the world’s science and engineering leader, but to do so will require viewing our efforts within the context of both technology AND adoption.
Issues like a lack of career development for advanced degree holders, startup failure rates, and “build it and they will come” do sizable damage to our technological potency. Now is the time to use this momentum and concern to change our viewpoint and expectations.
Tanya Ramond is the founder and CEO of Sapienne Consulting, a firm dedicated to helping companies with commercialization strategy in deep tech areas such as aerospace, quantum, photonics, cleantech, and more.
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