S4E12: Technology Adoption as Key Metric for Science Policy

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We've discussed science and tech policy in this podcast before, most recently in the episode The Future of Transatlantic Relations in Deep Tech with Milja Kalliosaari, Government Relations Manager at Finland's IQM Quantum Computers. Then with Christina Willis. Director of Government [00:01:00] Affairs with Colorado's quantum company Inflexion in her interview When Scientists and Policymakers Speak the Same Language.

And earlier in 2024 with Dr. Bob Souter on Why the Quantum Industry Needs an Apollo Program. Today, in January 2025, as the United States is entering a second term with President Trump, I wanted to continue on this extremely important topic, important both for Europe and for the U. S. I was fascinated to read this article that's called Technology Adoption Should Be a Key Metric for U.

S. Science and Engineering Policy by Tanya Ramond. Tanya Ramond is the founder and CEO of Sapien Consulting, a firm dedicated to helping companies With commercialization strategy in deep tech areas such as airspace, quantum, photonics, [00:02:00] cleantech and more. You may remember her from our interview two years ago in season two, episode four, turning deep tech into sellable products.

It's so good to have you back at DeepPockets, Tanya. Thank you, Petra. It's great to be back. So, excuse me, could you reintroduce yourself to those listeners who are not familiar? With your work already, you are the founder and CEO of your company, but how did you get there? Um, what is your career journey?

Yeah, thank you, Petra. I would call my career journey double layered. I started out extremely technical, completing a PhD and postdoc in quantum physics, then 10 years at what was at the time Ball Aerospace in product development and technical management of internal R& D, research and development programs, and new business development.

Towards the end of my time there, I decided against Staying at a big company my [00:03:00] entire career, I wanted to try new things and transitioned on to a series of small and startup companies working with aerospace and quantum technologies. However, at the time of this career inflection, my interests started to change.

The story I'd like to tell is this one. At the end of my tenure at Ball, I was called in to lead a team of engineers in an internal R& D project. The objective was essentially to Let's say build me a widget. And in this case, the widget was a LiDAR. I said, okay, great. I know the team. We've worked together before to do something similar.

I'm sure we can get it done. We went off and talked about what exactly to build, but came up with many questions like, who wants this? Why do they want it from us? Why do they not want it from someone else? How will they use it? How much will they pay for it? How much will they not pay for it? And all these questions were top of mind because, from the engineer's standpoint, these answers drove major design decisions.

[00:04:00] So, for example, do we shell out for the top of the line laser? Because that's the only way we get the required data product. Or, does a middle of the line laser work just fine? This all drives cost, schedule risk, and complexity. But the interesting thing is that when I posed these questions, I got no responses, no guidance.

Uh, the guidance was just not there. And I couldn't articulate it at the time, but that did not sit well with me. It seemed like an extraordinary inefficient use of, um, time and money and engineering talent to build something without having done the homework needed to build a business case. There had to be a better way and this search for answers became my career fuel from then on.

I went on to earn an MBA. I dove into the entrepreneurial ecosystem, taught myself product management, and my company roles morphed into strategy and product roles. Today, I am an independent consultant at Sapien Consulting, and I specialize in [00:05:00] commercialization strategy for deep tech companies. I love that journey.

So let's dive directly into the topic of the day. This article, technology adoption should be a key metric for U. S. science and engineering policy. Um, so we've, we had some background discussions and in our conversations when we were preparing for this. Uh, you told me that you were reading the U. S.

National Science Board's. Policy briefed called a changed science and engineering landscape. And, uh, as you were reading this, you mentioned the word anger. Tell us about that. Right. Well, the anger did not come from what they said, but rather what they did not say, the three key points of the publication were this, the U S government.

Forms, uh, applies in a very important foundation for R& D funding, but in terms of strictly dollars, business and private sector funds the majority of U. S. R& D. Second, [00:06:00] China is our biggest, biggest competitor, as discussed, based on metrics like dollars spent in R& D, a number of patents, and the number of doctoral awards.

And we need to beef up our STEM education efforts, uh, specifically K through 12. You know, I don't argue with any of these points. They're all correct and valid. However, the brief just stops there. The implication is that if we increase R& D funding, our number of patents or PhDs, and invigorate STEM education, then that is tantamount to technological leadership.

This narrative ignores an elephant in the room, which is that it is not just the creation of technology, but the adoption of technology that wields potency. Hmm. And that really speaks to your story, uh, on your career path as well. I love it. Uh, so indeed an important topic. Um, let's digest the arguments here first.

Why do you think that technology adoption must be the metric for success as opposed to, let's say the [00:07:00] patents you mentioned or the amount of VC funding going into startups? Sure. Well, if you think about it from a pipeline perspective, we are ignoring the integrity of the pipeline. Some pretty big leaks.

So increasing STEM education, R& D funding, the number of doctorates, the number of patents. Yes, they all contribute to bigger volume flowing through that pipeline without a doubt. But if that pipeline is leaky, you aren't going to get the desired effect at the end. Sticking with this metaphor, these leaks arise due to factors impeding technology adoption.

And so what do I mean by that? I think the best description of technology adoption is given by Geoffrey Moore, as described in his seminal book called Crossing the Chasm. He discusses the palpable difference in mindset, which could be considered a valley of death. between those that would try out a new technology as an early adopter and more mainstream users who would buy a technology to solve a problem.

If a technology stays with [00:08:00] early adopters and cannot make the jump to mainstream buyers, generally speaking, adoption is hindered as the technology stays within the hands of a relatively small group of early adopters. Okay. Yeah, that makes sense. So in this article, your second excuse me, argument is that we need more graduate level STEM workforce development.

Tell us more about that. Yes, uh, well, the stark reality is that only PhDs ends up as a professor, and the PhD glut is not something new, it's existed for decades. Furthermore, as a general rule, even though 9 out of 10 will not become a professor, PhDs are offered no No support during their programs to explore nonacademic jobs, and if they do, they're often haunted by feelings of, say, quitting science or selling out to work in industry.

Ph. D. career coaching is a necessity. Furthermore, many Ph. D. s decide to pursue an [00:09:00] entrepreneurial career path after their graduation, and universities Tend to offer entrepreneurial education, but it's usually offered, you know, on the side and typically, typically only if they know they want this path.

However, if entrepreneurial success is part of technology adoption, entrepreneurial education needs to be better integrated into educational curriculum, starting earlier in the educational path. Terrific. Yeah. Good stuff. Stuff. Um, let's move on to the startups. You, you say that star in your article, that startup success rates are unacceptably low.

Yet, uh, if you look at the amount of private investments that go into the U S startups in these emerging technology sectors versus how much money startups in other parts of the world receive, the U S is the envy of the world. And I can attest, I'm currently sitting in France, in Europe, and we're all, uh, envying the American startup VC funds.

So if you're saying that even with the most money in the world. American startups need to [00:10:00] step up in delivering great products, delivering success. Yeah, well, the real reality is that the vast majority of startups fail, no matter what country you're in. The often cited statistics are as high as 90%. The reasons for failure are many, but research shows that the majority of the time the failure is traced to a lack of market need.

Another way to say this is that it is not the difficulty of the technology or something fundamental to the science or technology that causes the failure. Again, it has to do with doing your homework. In other words, business strategy and business approaches. This is really good news because that is more controllable than, say, the laws of physics.

We have many new entrepreneurial tools now, not just for startups, but also for those who are innovating in a corporate environment. I mean, decreasing the startup failure rate anywhere south of 90 percent seems like a blue ocean opportunity to increase technical. Technological adoption. I'll go [00:11:00] back to that pipeline metaphor.

You know, if a large chunk of technological startups fail because of insufficient business due diligence, that is a leak in the pipeline we can patch. So in this story, you're almost describing a need for a product management type of role, aren't you? Yeah, that's exactly it. Um, that was the app. What I was experiencing was the absence of the function of product management.

So as I, as I went on in my career from there, as I said, I needed to find a better way. And in fact, there is a better way. It's not new. I did not invent it. This is a role that's very, very seasoned. Um, and that's of the product manager. And. It's not the same thing as product development. A product manager is that link between the customer, understanding the customer, understanding their pain points, [00:12:00] doing the research to, to really characterize them, and then bringing that.

Understanding back to back internally drive the engineering requirements that you need to build something. And, you know, these are, these are the foot soldiers that you, that you need to rely on to make that link and make sure that you're building something that, that solves an actual problem. I think there's a big role.

For technical product management, we could really beef that up and that would be a great way to increase the technology adoption for the, uh, uh, to, to shore up the, the pipeline for tech technology adoption. To continue on that thought, uh, you mentioned, uh, build it and they will come mindset. What does that mean?

Yeah. So this is the corollary of say, bringing a product to market without market need. It's exemplified [00:13:00] in the story I told earlier when my team was instructed to build the widget without any context for who wants it and why. That would drive the requirements for the design because we build it.

Obviously, someone's going to buy it, right? We know that's not true. Customers are very happy to ignore a product that does not solve a problem for them, but especially for technical minded folks. They're so ingrained in the technology. It's beauties. It's challenges that it becomes all about. Encompassing they are technology.

First problem. Second, that mindset does not change organically. You have to have a deliberate effort to rewire that mindset in order to move to a customer curious mindset that puts the problem that they're experiencing first and the solution. Second, Einstein families famously said that if he had to solve a hard problem, he would spend 99 percent of the time thinking about the problem and 1 percent thinking about the solution.

Mm hmm. Mm hmm. Nice. Uh, my last question, politics and [00:14:00] policy aside, leave us with something uplifting either from your personal life or from your work in the intersection of science, policy and business. Yeah, no, I think this is. Really uplifting. I look at it as, uh, as, uh, again, a blue ocean. Um, you know, once we, we all start to see these pipeline leaks because they are so big, even making modest improvements can yield big improvements overall in, uh, in technology adoption and technology, um, Strength.

Furthermore, these pipeline leaks are not unique to the US. China, I am sure, experiences the same. So if we can shore up the pipeline to technology adoption and impact, we have a leg up on the competition. Mhm. Shore up the pipeline. There you had it. This has been Tanja Ramond, the founder and CEO of Sapient Consulting, discussing her recent article, Technology Adoption Should Be a Key Metric for U.

S. Science and Engineering [00:15:00] Policy, which was published by Dynamic Tech Media. And I'll add the link in the show notes so you can go and read it yourself. Thank you so much for coming back to Deep Pockets. Oh, thank you, Petra. Thank you for having me back.

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