Latest / The Demographics Podcast with Fexingo: Aging Populations, Birth Rates, and Economic Impact / How Aging Workforces Are Reshaping Corporate Innovation
Transcript
- Lucas: So there's this narrative that older workforces are less innovative. That young companies disrupt, old companies stagnate, and the only way to stay dynamic is to keep hiring twenty-somethings. Luna: Right, the classic Silicon Valley playbook — ping-pong tables, beanbags, average age of twenty-eight. Lucas: Exactly. But that narrative is increasingly at odds with the actual demographics of developed economies. The median age in Germany is now forty-seven. In Japan it's forty-eight. These are not countries full of twenty-eight-year-olds. Luna: So what happens to innovation when the median employee in a company is forty-five or older? Lucas: Let's look at a specific case: Siemens. The company has around three hundred thousand employees globally, but its core engineering workforce in Germany has a median age of forty-four. That number has been creeping up for a decade. And it forced the company to rethink what innovation actually means. Luna: Did they just accept that they'd produce fewer patents, or did they change the way they innovate? Lucas: They changed the type of innovation they pursue. A 2023 study from the German Economic Institute looked at patent data from Siemens and similar industrial firms. It found that companies with a median employee age over forty-five produce about fifteen percent fewer patents per capita than those with a median age under thirty-five. But here's the twist: their process-innovation efficiency — the ability to improve existing products and manufacturing lines — actually went up by about twenty percent. Luna: So they're trading radical breakthroughs for incremental refinements. Is that a bad thing? Lucas: It depends on your industry. For a pharmaceutical company, you need those blockbuster drug discoveries — radical breakthroughs are the business model. But for an industrial conglomerate like Siemens, which makes turbines, trains, and factory automation gear, incremental improvements in efficiency and reliability can be enormously valuable. Their gas turbines, for example, have seen efficiency gains of about one point five percent every five years from incremental tweaks by veteran engineers. That adds up to billions in fuel savings for customers. Luna: And that kind of knowledge is hard to replicate. It's tacit — you can't just hire a twenty-five-year-old and expect them to intuit thirty years of turbine metallurgy. Lucas: Right. So Siemens invested heavily in what they call 'knowledge-retention programs'. They pair senior engineers approaching retirement with mid-career engineers in structured mentorship tandems that last twelve to eighteen months. The goal isn't just to transfer explicit knowledge — the manuals already exist. It's to transfer judgment. When do you push a design further versus when do you stick with a proven configuration? That's the kind of thing that only comes from seeing hundreds of projects succeed or fail. Luna: And they've measured the ROI of that? I recall a study from the Fraunhofer Institute that found mentorship tandems in German manufacturing boosted project success rates by about twelve percent. Lucas: That's the one. And Siemens has been running formalized mentorship programs since 2016. They now have over fifteen hundred active tandems globally. The company's internal data shows that teams with at least one veteran mentor are thirty percent more likely to meet their project deadlines and cost targets. Luna: So the playbook isn't 'don't hire older workers'. It's 'design your innovation process around the strengths of an older workforce'. That seems like an obvious insight, but most companies don't do it. Lucas: Most companies are still operating on the assumption that innovation equals youth. And that assumption is baked into everything from recruiting to office design to performance metrics. But the data from Japan, which has the oldest workforce in the world, is really instructive. Japan's patent output per capita has been declining since the early 2000s, but its share of high-quality patents — patents that are cited frequently and generate licensing revenue — has remained stable. Older Japanese engineers are producing fewer patents, but the ones they produce are more commercially valuable. Luna: Because they're more focused on practical applications rather than blue-sky research? Lucas: Exactly. There's a wonderful paper by economists at Hitotsubashi University that looked at Japanese manufacturing firms from 2000 to 2020. They found that the optimal age for patent quality — measured by forward citations — is actually around fifty-two. That's the peak. The optimal age for patent quantity is thirty-eight. So there's a real trade-off. An older workforce produces fewer ideas, but the ideas they produce are more refined and more likely to succeed in the market. Luna: So companies that manage this transition well — like Siemens and some Japanese firms — might actually outperform younger-focused competitors on profitability, even if they lag on raw patent counts. Lucas: That's the hypothesis. And some preliminary data supports it. A 2024 McKinsey report on demographic resilience looked at the return on invested capital for companies in eleven developed economies. They found that firms with a median employee age over forty-five and a formal knowledge-retention program had an ROIC about two percentage points higher than similar-aged firms without such programs. It's not a huge gap, but in capital-intensive industries, two percentage points is significant. Luna: And this ties back to something we've talked about before — the idea that aging populations aren't necessarily an economic drag. They change the structure of production, but they can be navigated. Lucas: I think that's the right framing. The challenge is that most corporate incentive systems are still built for a younger demographic. Quarterly earnings pressure discourages long-term investments in mentorship and knowledge retention. It's much easier to cut costs and hire cheap junior talent than to maintain a seasoned workforce. Luna: Speaking of sustaining things that require long-term investment — you know what else relies on that kind of consistent support? This podcast. Lucas: Yeah, and we're really careful not to make this a regular thing, but we do want to mention that if walking through the economy with us has made something click — maybe you see your own company's demographic patterns differently now — then a couple of dollars a month genuinely helps keep the show ad-free and independent. Luna: It's a small thing that makes a real difference. And we're grateful to everyone who's already chipped in. Lucas: So if you've gotten something out of these episodes, you can find us at buy me a coffee dot com slash fexingo. No pressure, just a way to keep this going. Luna: And speaking of navigating demographic shifts — I want to come back to that McKinsey report. They also found something interesting about company culture. Lucas: Right. The report highlighted that firms with older workforces and high employee engagement scores — like above the 75th percentile on engagement surveys — actually had higher innovation output than younger firms with low engagement. So culture is a powerful moderator. If you have a motivated older workforce, they can outperform a disengaged younger one. Luna: That's a hopeful finding, because engagement is something managers can influence. You can't change your workforce's age distribution overnight, but you can change how you manage them. Lucas: And that's where we're likely to see more corporate experimentation in the next decade. As the baby boomer generation fully retires, the cohort of experienced workers in their fifties and sixties will shrink. Companies that built their innovation strategy around an older workforce will need to adapt again. But the ones that have the systems in place — the mentorship programs, the knowledge-retention tools, the engagement metrics — will have a much easier time transitioning to whatever demographic comes next. Luna: So the lesson from Siemens and from Japan is: don't fight the demographics, design around them. Lucas: Exactly. And that's probably the most pragmatic takeaway for anyone listening who works in a large organization. Look at the age distribution of your own team or department. If the median is over forty, start thinking about how you capture the tacit knowledge. And if the median is under thirty, start thinking about how you build the mentorship that will create that depth of experience down the line. Luna: Great advice. Alright, that's all for this episode of The Demographics Podcast. We'll be back next time with another angle on how population trends shape the economy.