Latest / Deep Dive Ortho — Orthopaedic Surgery, AI & Digital Health Podcast. / The Power Laws of Nature and surgery

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The Power Laws of Nature and surgery · Deep Dive Ortho — Orthopaedic Surgery, AI & Digital Health Podcast.

0:00
Have you ever found yourself wondering about
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the truly invisible forces that shape our world?
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Not just the headlines or the daily challenges
0:07
we face in our professional lives, but those
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deep underlying patterns. The ones that seem
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to govern everything from, say, the smallest
0:16
biological processes right up to the intricate
0:19
dynamics of global economies. It's a compelling
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thought, isn't it? Our instincts often nudge
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us towards believing reality is neat, linear,
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predictable almost, like a sort of grand cosmic
0:30
clockwork. Exactly. But what if the truth is
0:33
far more, well... Nuanced. What if things operate
0:37
on surprising non -linear principles that defy
0:40
our common sense, yet actually hold the key to
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understanding success and failure? Indeed. The
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universe, and by extension, our professional
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landscapes, particularly in complex fields like
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medicine, are far less straightforward than they
0:51
often appear. Right. And that's precisely what
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we're delving into today. Right. Our mission
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with this deep dive is to explore what we call
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power laws. Now, these aren't just abstract scientific
1:00
concepts buried in academic papers. They are
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universal principles, relationships that seem
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to cut across specific disciplines and offer
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truly profound insights into the mechanics of
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business, innovation, and even the daily realities
1:14
you navigate as medical professionals. That's
1:16
right. Think of this as your pathway to gaining,
1:20
well, a quick yet thorough understanding. Hopefully
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leading to those genuine aha moments about how
1:26
the world really functions. Because despite their
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apparent complexity, these power laws offer surprisingly
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simple recurrent explanations for phenomena that,
1:35
on the surface, seem entirely unrelated. Exactly.
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Imagine how a slight tweak in a medical protocol,
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a seemingly small decision in a large hospital
1:44
system, or perhaps a shift in how a new drug
1:46
is introduced, can have these disproportionately
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massive effects. That's the essence of it, isn't
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it? Challenging that conventional sort of clockwork
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universe mindset and embracing a more dynamic
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often counterintuitive Reality, it's about understanding
2:01
the fundamental rules of the game rules that
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well We can't simply change but which once understood
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and recognized can actually be harnessed to multiply
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our effectiveness Right like understanding the
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rules of physics before trying to build a bridge
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precisely Much like a skilled surgeon uses their
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deep knowledge of anatomy and physiology to perform
2:19
complex procedures, you can use these power laws
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to anticipate outcomes, refine strategies, and
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ultimately chart a more successful course for
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your organizations and your careers. Okay, let's
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unpack this then. We're going to start our journey
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by looking at the biological blueprint, how evolution,
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genes, and even our ancient human behaviors play
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out in some surprising ways in modern settings,
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including, of course, the healthcare sector.
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A perfect starting point. When we discuss universal
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drivers in the material world, nothing is more
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fundamental than evolution by natural selection.
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As the philosopher Daniel Dennett put it, if
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you could bestow an award for the best idea ever,
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it would undoubtedly go to Darwin. High praise
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indeed. It is. His theory bridged the seemingly
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disparate worlds of mechanical physical sciences
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and the intricate, meaningful realm of culture,
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art, and biology. Without natural selection,
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our species wouldn't exist. And if its principles
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didn't apply to ideas, technologies, and markets,
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we'd likely still be struggling just to avoid
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famine. It truly drives all material progress,
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even in something as structured as medical innovation.
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It's quite remarkable how Darwin's core insights,
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stemming from observations back in the 1830s,
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boil down to just three plain facts. First, there's
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overproduction. Living organisms consistently
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produce far more offspring than can possibly
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survive. Darwin noted that cod lay millions of
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eggs. If they all survived, the oceans would
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be solid with cod in mere months. An astonishing
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image. Isn't it? Even elephants, among the slowest
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breeders, would number 15 million from a single
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pair within five centuries if unchecked. This
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inherent overproduction everywhere you look in
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nature inevitably leads to a struggle for existence.
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There simply aren't enough resources. Precisely.
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And the second observation is equally simple,
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yet profound. Variation. All creatures are unique.
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We all possess inheritable differences. You see
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everywhere, don't you? For the subtle distinctions
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between siblings to the dramatic variations within
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a species. No two are ever truly identical. Exactly.
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Even identical twins have slight differences.
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And the third, which pulls it all together, is
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inheritance. These variations, these unique traits,
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are passed down from parent to offspring. We
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are quite literally more like our parents than
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other people's parents. It seems obvious when
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stated like that. It does. Putting these three
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facts together, Darwin deduced the rudiments
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of natural selection. Intense competition among
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offspring means only a few can survive and reproduce.
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Those with variations best suited to their environment
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are more likely to survive and pass on those
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advantageous traits. He stressed how difficult
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it is to constantly bear this universal struggle
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for life in mind. Yet it's absolutely crucial
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for understanding nature and indeed many competitive
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fields. And this framework of selection isn't
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just confined to biological species either. You
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mentioned Bruce Henderson earlier, founder of
5:12
the Boston Consulting Group. Yes. He famously
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observed that Darwin is a better guide to competition
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than economists. Selection drives material progress
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and ideas, technologies, markets, companies,
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teams, and even individual products. Absolutely.
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Consider the world of medical research. Countless
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hypotheses generated, numerous clinical trials
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initiated, but only a few truly robust treatments
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or innovative devices ultimately survive the
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rigorous selection process, peer review, regulatory
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approval, clinical efficacy. It's a powerful
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lens for viewing all forms of competition, even
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within healthcare. What's fascinating here is
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how this leads to specialization and differentiation,
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even in medicine. Just as evolution creates distinct
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species economic evolution carves out specific
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niches and specialties Think about how the practice
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of medicine has diversified From general practitioners,
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it forked into countless specialties, cardiology,
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oncology, neurosurgery. And then further subdivisions
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within those. Exactly. Interventional cardiology,
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pediatric, neuro -oncology. It's a constant process
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of differentiation emerging from generality,
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driven by the need to find and exploit unique
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niches of patient need or technological expertise.
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This inherent process of differentiation also
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highlights the critical role of experimentation
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and, crucially, failure. Natural selection is,
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in essence, a grand experiment where luck, or
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rather the random generation of variation, is
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paramount. And the same applies directly to business
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and medical innovation. Directly. The reality
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is most experiments fail. We see huge sums, around
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$160 billion spent annually on R &D in developed
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countries, but only about 5 % of that generates
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a viable product or service. That's a sobering
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statistic. It is. And even those few successful
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products face a high death rate in their early
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months and years, whether that's a new medical
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device or a pharmaceutical. It's a tough environment,
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isn't it? Take Sony, for example, with the Walkman.
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They didn't just launch one model, they understood
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this power of experimentation almost flooding
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the market with hundreds of variants. Letting
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the market select the winners. Precisely. In
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the medical field, this translates to the iterative
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nature of research. Multiple drug candidates,
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various surgical techniques, diverse rehabilitation
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protocols, many are tried. But only a few demonstrate
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superior efficacy or safety. This willingness
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to try and fail rapidly is key. Consider how
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a large hospital system might pilot different
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patient flow models in various departments, quickly
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discarding those that don't work and scaling
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up the ones that do. Procter & Gamble took a
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radical step back in 1930, didn't they? Allowing
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direct competition between their own brands.
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They did. This internal rivalry created challenges
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that forced continuous improvement and prevented
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complacency. It took competitors decades to adopt
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that approach. They also have an incredibly rigorous
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product development process, mandatory test marketing,
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meaning very few concepts actually make it to
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production. But those that do are exceptionally
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well vetted. Exactly. For healthcare, this might
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imply fostering internal competition among research
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teams, perhaps, or even allowing different clinical
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departments to experiment with distinct approaches
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to a common problem, always provided patient
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safety is paramount. So the second lesson here
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is that new product or service variants will
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arrive, whether you introduce them or not. The
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market, or in our case, patient need and scientific
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progress, doesn't really care who owns the innovation.
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It simply wants better solutions. Which means
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you need to proactively scatter new breeds around
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your core offerings, essentially trying to fill
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up potential patient care spaces or research
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avenues yourself. Precisely. If you neglect a
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niche, Think about the rise of telemedicine or
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personalized medicine, maybe five, ten years
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ago, new specialists will inevitably come in
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and fill it, potentially challenging your established
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practices down the line. And the third lesson.
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Product and service improvement can and should
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always be accelerated. Competitive selection
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drives faster evolution. This means tolerating,
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even encouraging what might initially look like
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failure. Because it's part of the process. It's
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an intrinsic part of discovery and refinement.
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P &G's experience with elestra is a classic example.
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Originally conceived as a fat for premature babies,
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it proved unabsorbed a failure for its initial
9:30
purpose. But they didn't just scrap it. They
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redirected the project to develop a fat substitute.
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What looked like a dead end became a massive
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success in a reevaluated direction. So for medical
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research, a drug failing for one indication might
9:44
work for another. A surgical tool not quite right
9:47
for one procedure might be adapted. Exactly.
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The key is recognizing that potential, seeing
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a detour rather than just a dead end. It requires
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flexibility and a willingness to pivot. This
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brings us to a crucial point about time itself.
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Time is a proxy for generations in evolution,
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linking directly to time -based competition.
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Yes, competitive advantage in this view comes
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from minimizing the time it takes to get products
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or services to market or crucially in medicine,
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to adopt a new proven clinical practice. Like
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the HY War, Honda versus Yamaha in the early
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80s. A perfect example. Honda entered with 60
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new motorcycle models in a year, then another
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113 in the next 18 months. They simply out -innovated
10:28
Yamaha. Industries that innovate faster grow
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faster. So in medicine, this means reducing the
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time from research discovery to the patient's
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bedside, from a new diagnostic technique to widespread
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clinical adoption. That's the essence of it.
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The faster you can iterate and implement effectively,
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the more competitive and more importantly, the
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more beneficial to patients you become. This
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concept also forces us to confront Stanislaw
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Ulam's dilemma. He's a brilliant mathematician.
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Indeed. Ulam noted his discipline spawns nearly
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2 ,000 new theorems annually. yet very few survive
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due to limited funding and intellectual space.
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He questioned whether the best products or companies
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always win on objective merits. Or is it more
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just blind competition? His conclusion was somewhat
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stark. There's no assurance of survival of the
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fittest, except in a tautological sense whatever
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survives is by definition the fittest. So for
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healthcare this implies that the most objectively
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perfect treatment protocol might not become standard.
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It might not if another Perhaps less optimal,
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but maybe more accessible, cheaper, or politically
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favored protocol gains traction first. Think
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QWERTY keyboards or Betamax versus VHS. Not necessarily
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the best technology one there. No. Network effects,
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early adoption, marketing, other factors came
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into play. The implication for health care is
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quite direct. The patient is always right. So
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is the market, even when it is unfair or wrong.
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You can't fight the market. even if you're sure
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it's wrong. It's generally futile. If patient
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feedback for a new service is negative or a new
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drug faces unforeseen resistance despite its
12:04
scientific merit, you have to adapt. You can't
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just wish the environment would change to suit
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you. And that leads to the final point on evolution.
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Organizations, practices, hospitals, research
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institutes failing in one environment must either
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find a different market, a different niche, or
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radically change their character. Exactly. Expecting
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the environment to change is usually a losing
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strategy. Darwin's theory states the environment
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selects the species. The species doesn't determine
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the environment, nor can it always adapt perfectly.
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So you have little control over the wider healthcare
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ecosystem. Very little. And if your capabilities
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evolve for a specific patient group or treatment
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model, it's unlikely they'll just happen to fit
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another perfectly without significant change.
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Variations required in what you offer and where
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you offer it. Okay, so if evolution provides
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the grand framework, then understanding the micromechanics
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of inheritance helps us grasp the engine of change
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more granularly. Darwin himself was puzzled by
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this, wasn't he? He was. He admitted, the laws
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governing inheritance are quite unknown. Everyone
13:07
assumed traits blended, which logically would
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water down adaptations over generations. It was
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a real sticking point. Until Gregor Mendel, the
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monk with his peas. Exactly. Reading experiments
13:16
in the mid -19th century showed that inherited
13:19
traits weren't blended but passed on as distinct
13:21
units. Then, Thomas Hunt Morgan's fruit fly experiments,
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observing that white -eyed mutation. Right, early
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20th century. Yes. Between 1907 and 1915, they
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showed these units, which we now call genes,
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were physical entities on chromosomes, passed
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on according to mathematical probabilities. This
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finally solved Darwin's dilemma. Traits were
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passed undiluted. Now, here's where it gets really
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interesting and profoundly applicable, I think.
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Richard Dawkins and his selfish gene concept.
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A powerful idea. He argued that genes, not individuals
13:55
or species, are the fundamental unit of selection.
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Genes build survival machines, organisms, to
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replicate themselves. That metaphor of DNA flowing
14:05
like a river out of Eden through time. It's very
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evocative, isn't it? unaffected by the individual
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bodies it passes through. This perspective offers
14:14
a potent parallel for business and certainly
14:16
for the flow of innovation and knowledge in medicine.
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Business genetics or innovation genetics? Precisely.
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Think of units of economic information ideas,
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knowledge, best practices, unique surgical skills
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that replicate and create value. Just as biological
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genes need vehicles, these conceptual genes need
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their own vehicles. People, clinical teams, research
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labs, specific diagnostic tools, new service
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models. Exactly. These intangible ideas need
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to cloak themselves with physical texture and
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real -world application to become robust and
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replicate effectively. So, the failures of small
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medical startups or research initiatives that
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don't pan out, though painful, become a necessary
14:53
part of creative destruction, as Schumpeter put
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it. Yes. When a less effective treatment or an
15:00
inefficient hospital process is discarded, it
15:02
frees up resources, time, money, attention for
15:06
better use elsewhere. It's not about failure
15:08
being bad. It's about learning and reallocating.
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If a vehicle isn't working, you discard it and
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learn. And this naturally extends to spinoffs
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within the medical field. New clinics, specialized
15:20
units, med tech companies. Absolutely. They often
15:23
inherit good genes from a parent institution,
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valuable knowledge, established practices, key
15:28
talent. But crucially, they add new twists, new
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mutations, if you like. If these innovations
15:33
suit the market, the spin -off prospers. Which
15:35
suggests larger healthcare organizations could
15:37
benefit from actively backing promising spin
15:40
-off ideas from their teams. It does. Rather
15:42
than stifling them or letting that talent walk
15:44
away, leveraging existing genetic material for
15:47
new evolutionary paths seems a much smarter strategy.
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It even applies to individual career evolution
15:52
in medicine, doesn't it? It really does. A successful,
15:56
dynamic career requires continuous variation.
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New roles, new specialties, new responsibilities.
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It demands constant experimentation with fresh
16:05
combinations of skills and ideas. And, importantly,
16:08
accepting failure. a rejected paper, a difficult
16:11
case, a management role that wasn't quite right.
16:14
Accepting it as a constructive mutation. Your
16:17
professional ego shouldn't deny failure. It's
16:20
an opportunity for self -development, a way to
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refine yourself as a better vehicle for effective
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ideas and practices. It's how you evolve professionally.
16:27
Right. Now let's shift gears slightly and explore
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how our ancient, hardwired instincts from the
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Savannah clash with the demands of the modern
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office, or maybe more pointedly, the modern hospital
16:39
environment. This is evolutionary psychology
16:41
territory. Yes, essentially seeing us as Stone
16:44
Age humans in the 21st century. And it offers
16:46
some profound, sometimes unsettling insights.
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It is a bit unsettling how much these ancient
16:51
instincts still influence us. Evolutionary psychology
16:54
contends they often conflict with modern professional
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imperatives. Think about how we react to feedback
16:59
or colleagues. Our natural disposition isn't
17:01
always rational first, is it? No. We react emotionally.
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Those alert instincts were vital on the savanna,
17:09
literally life -saving. So emotions became the
17:11
first reaction, not reasoned thought. And this
17:14
carries right into how we manage teams, respond
17:17
to patient complaints, or even interpret clinical
17:20
data sometimes. Indeed. And it's not just emotions.
17:23
Blind confidence and egotism traits that might
17:25
have been impressive in a tribal leader rallying
17:28
the clan now often just annoy or breed cynicism
17:32
in a modern team. say, in a hospital ward. Our
17:35
environment has changed dramatically, but the
17:37
deep wiring hasn't quite caught up. Not entirely.
17:40
This also helps explain our inherent taste for
17:41
hierarchy. Hunter -gatherer society is often
17:44
in ad hoc hierarchies. Security increased with
17:46
attachment to a strong leader. Which explains
17:48
why attempts to abolish hierarchy often just
17:51
lead to new, informal ones. William White's Organization
17:54
Man, Robert Townsend's critiques. Exactly. Even
17:57
if you flatten the official structure, unofficial
17:59
pecking orders and power structures tend to emerge.
18:02
It seems deeply ingrained. And allied to hierarchy
18:04
is conformism and hurting. We naturally conform
18:08
within our clan, our department, our surgical
18:11
team, our specialty, and are often suspicious
18:14
of outsiders. It played a critical role in tribal
18:17
survival, ensuring group cohesion. But in a complex
18:20
health care organization, it can lead to resistance.
18:23
Resistance to adopting new, evidence -based practices
18:26
that come from outside the immediate group, challenging
18:29
long -held, comfortable routines. It takes real
18:32
courage, or perhaps obstinance, to go against
18:35
the received wisdom of the tribe. It does. We
18:38
also often fall into the trap of thinking of
18:40
business as war, using military analogies. But
18:43
John Kay makes a crucial point. Business competition,
18:46
and arguably competition within healthcare research
18:48
or provision, is fundamentally different. How
18:50
so? In war, the biggest combatant often wins
18:53
by destroying the opposition. In business or
18:56
healthcare, multiple players can flourish. And
18:58
the customer or the patient is the powerful third
19:00
party who ultimately decides the winner. Trying
19:03
to inflict direct damage on competitors is rarely
19:06
effective and often counterproductive. Collaboration
19:09
can yield far greater value. Then there's risk
19:11
aversion. We often see this false market in risk,
19:14
don't we? Individuals and organizations reluctant
19:18
to take real risks, even when evidence suggests
19:21
fortune favors the brave. It probably goes back
19:23
to those hunter -gatherer days. Once you had
19:26
enough food or safety, why risk fighting for
19:28
more? but you'd fiercely defend what you did
19:31
have. Which is why adopting radically new surgical
19:34
techniques or investing in disruptive medical
19:37
technology can be so challenging, even if the
19:40
potential benefits seem clear. It's a significant
19:43
factor. Yeah. And this is strongly linked to
19:45
the endowment effect. Ah, yes, valuing what you
19:48
already own more highly. Precisely. Experiments
19:51
show this clearly. If you're given a ticket,
19:53
you're less likely to sell it than you would
19:54
be to buy it if you didn't already have it. Yeah.
19:57
In business, this translates into a first mover
19:59
advantage, where incumbents have a psychological
20:01
edge simply because they own the current solution.
20:04
So in health care, a hospital might fiercely
20:06
defend an outdated piece of equipment or a legacy
20:09
patient management system. Simply because they've
20:12
already invested in it. They're used to it. Even
20:14
if a newer, more efficient option exists, that's
20:17
the endowment effect in action. It's why incumbents
20:20
often struggle to pivot. They value their existing
20:23
processes far more than a challenger would just
20:25
because they own them. This also comes up in
20:27
the fascinating ultimatum bargaining game. Can
20:29
you remind us how that works? Certainly. Imagine
20:31
Alex is given 500 pounds and told to share it
20:34
with Justin. If Justin refuses Alex's offer,
20:37
neither gets anything. Rationally, Justin should
20:40
accept even five pounds, shouldn't he? It's better
20:42
than nothing. Logically, yes. But people don't,
20:44
do they? Often they don't. They refuse offers
20:47
they perceive as unfair, even if it costs them.
20:50
This raises intriguing questions. Are generosity
20:53
and a strong sense of fairness or perhaps even
20:56
socialistic envy, hardwired into us from shared
20:59
hunting practices. And how might this affect,
21:01
say, negotiations between pharmaceutical companies
21:04
and health care providers over drug pricing,
21:06
where perceptions of fairness might trump purely
21:08
economic logic? That's a very relevant question.
21:11
These deep -seated instincts about fairness can
21:13
absolutely influence high -stakes negotiations.
21:16
But it's not all hardwiring, is it? There are
21:19
counterarguments. Crucially, yes. First, there's
21:22
strong evidence for cultural evolution. Learned
21:25
behavior, or memes, as Dawkins called them, units
21:28
of cultural transmission, like ideas, fashions,
21:30
skills, can operate independently of genes. Cultural
21:34
norms, like adopting new medical ethics or best
21:36
practices, can spread rapidly without genetic
21:38
change. Like a new surgical technique spreading
21:41
through conferences and journals? Exactly. Second,
21:45
neuroplasticity. The idea that the brain isn't
21:48
fixed but can actually be rewired by conscious
21:51
effort, by thought. Dr. Jeffrey Schwartz's work
21:55
on language processing and OCD, for instance,
21:58
shows the brain is far more adaptable than we
22:00
once thought. So what's the takeaway for us as
22:02
medical professionals? Are we puppets of our
22:04
Stone Age genes or not? The conclusion seems
22:06
to be that humans are both hardwired and capable
22:09
of rewiring. And crucially, believing in free
22:12
will and your ability to change and adapt your
22:14
thinking and behavior is actually functional
22:15
for success. So recognize the biases. Yes. Recognize
22:19
ourselves and our colleagues as, perhaps, neolithic
22:22
genes in 21st century imposters. And actively
22:26
work to correct dysfunctional tendencies. Risk
22:29
avoidance when innovation is needed. Resistance
22:31
to new evidence. Rejecting constructive criticism.
22:34
It's about self -awareness and conscious adaptation.
22:37
And structurally within organizations. Favoring
22:40
small, simple, and relatively homogenous units
22:43
can simulate that cohesive Stone Age clan, fostering
22:46
stronger collaboration. Think of successful hospitals
22:49
breaking down large departments into smaller,
22:52
multidisciplinary teams, maybe five, ten people.
22:55
Robin Dunbar's number 150 for cohesive units.
22:58
Exactly. Beyond that, direct social bonds become
23:01
harder to maintain effectively. It's interesting
23:03
that small national size often carries no economic
23:06
disadvantage. Perhaps simplicity and common identity
23:09
are more important than sheer scale. Think of
23:12
Belgium's prosperity. This also means balancing
23:14
heterogeneity and internal cohesion. Diversity
23:16
of thought, background, speciality is immensely
23:19
valuable in medicine. But our ancient genes aren't
23:21
naturally geared for easy cooperation across
23:24
diverse groups. No, so it needs active management.
23:27
A strong organizational culture. Constant reminders
23:30
of the value of variety. Cross -group project
23:33
teams. Job rotation between clinical areas. Hiring
23:36
practices that guard against just hiring clones,
23:39
these are essential. And maybe even collaborating
23:41
with competitors sometimes, avoiding zero -sum
23:44
conflict. Yes, surprisingly often, that can be
23:47
more productive in the long run than trying to
23:49
put them in a corner. Okay, our final stop in
23:51
this biological blueprint. The art of cooperation
23:54
in a competitive world, drawing on game theory
23:57
and alliances. This is where we learn how cooperation
24:01
can actually arise from entirely selfish motivations,
24:04
especially in repeated interactions. The classic
24:07
prisoner's dilemma. The classic example. It shows
24:10
how two individuals acting purely in self -interest
24:13
might not get the best outcome. But if they interact
24:16
repeatedly, if there's a history, a relationship,
24:18
trust, cooperation can emerge as the dominant
24:22
rational strategy. You see that in busy operating
24:24
theaters or between departments collaborating
24:27
on a complex patient case. Trust and repeated
24:30
positive interactions build cooperation. Absolutely.
24:33
It benefits everyone, especially the patient.
24:36
This also links to Dawkins evolutionary arms
24:38
race. Constant escalation with no net advantage.
24:42
Exactly. Predators and prey constantly improve,
24:46
but their relative positions stay the same. In
24:48
business, people work longer hours. Firms innovate
24:51
relentlessly, but often just to stay in place.
24:54
And in medical research, the constant drive for
24:56
more papers, more grants, incrementally better
24:59
treatments. Often it's just about keeping pace
25:01
with a rapidly evolving field, not necessarily
25:04
gaining a massive lead. It's running hard just
25:07
to stand still, in a way. But Matt Ridley's theory
25:10
of social coagulation offers an uplifting counterpoint.
25:13
It does. He argues human society's unique ability
25:16
to cooperate in large groups is the highest form
25:19
of evolution, driven by specialization and trade,
25:22
Adam Smith's division of labor. Trade, Ridley
25:25
says, is a unique competitive advantage for homo
25:28
sapiens between groups. So in health care, specialists
25:30
relying on each other, hospitals referring patients,
25:33
pharma companies collaborating on development.
25:35
All examples of this principle, and it's underpinned
25:38
by memes, those units of cultural transmission
25:41
leaving from brain to brain, enabling knowledge
25:44
to drive progress. Think of a new surgical technique
25:47
spreading rapidly. This encourages social libertarianism,
25:51
exchange between equals. Yes, because paradoxically,
25:54
our minds, built by selfish genes, have evolved
25:57
to be social, trustworthy, and cooperative for
25:59
mutual benefit. So cooperation and competition
26:02
aren't opposites, they're Twin cherries on a
26:05
single stock. A lovely phrase. Cooperation creates
26:08
value. It beaks the pie, improves patient outcomes
26:11
while competition captures it, takes a slice,
26:14
decides who gets credit or funding. Interesting
26:16
to contrast excellent competitors, like maybe
26:18
old ITT, cold and efficient, with excellent cooperators.
26:22
Firms like The Body Shop or Hewlett Packard.
26:25
Inspiring affection. And the data supports cooperation.
26:28
A 30 year study showed socially responsible companies,
26:31
arguably excellent cooperators, significantly
26:33
outperformed the Dow Jones index. Skill and cooperation
26:36
is increasingly vital, especially in knowledge
26:38
fields like medicine. Gaining the cooperation
26:40
of the best researchers, clinicians, nurses.
26:43
It's paramount. Building strong collaborative
26:46
networks internally and externally leads to better
26:49
outcomes and more sustainable success. This leads
26:52
beautifully to Nadelbuff and Brandenberger's
26:56
theory of coopetition. Yes, broadening the view
26:59
beyond just customers, suppliers, and competitors
27:01
to include complimenters. Players who increase
27:05
the value of your product when customers also
27:07
have theirs, like Microsoft and Intel. Exactly.
27:10
Their parts, framework, players, added value,
27:13
rules, tactics, scope helps analyze these interactions.
27:17
The classic example is IBM developing the PC.
27:20
They invited Intel and Microsoft in, creating
27:22
an open architecture. Which led to a huge market.
27:25
But it was Intel and Microsoft, the complimenters,
27:28
who ultimately cashed in more. IBM brought most
27:30
to the party, but took away least because they
27:32
didn't structure the rules to their benefit.
27:34
A harsh lesson. Rules can be rewritten. Always
27:37
by creative players with real value to add. In
27:40
healthcare, think of a new telemedicine platform
27:42
partnering with a diagnostics company. The combined
27:45
value is greater, but who captures it depends
27:47
on how the relationship is structured. And it
27:49
extends to tactics. Sometimes transparency crashes
27:52
prices, so a bit of fog might be usable. Occasionally,
27:56
yes, though generally transparency is favored
27:59
today. And scope, remembering no business game
28:01
is an island. Think of Minnetonka launching soft
28:04
soap. They tied up the pump dispenser production.
28:06
For a year. From the only two manufacturers.
28:09
By the time the majors could enter, soft soap
28:12
was liquid soap in the public mind. It's about
28:14
anticipating bottlenecks. This brings us to the
28:17
cathedral versus bizarre metaphor. Yes, Eric
28:20
Raymond contrasting carefully crafted software
28:22
by isolated wizards, cathedrals, with Linus Torvald's
28:26
open collaborative approach to Linux, the bizarre.
28:30
Given enough eyeballs, all bugs are shallow.
28:32
Debugging is parallelizable. The internet culture
28:35
embodies this. In medicine, think open -source
28:38
medical software or global collaborative research
28:40
projects sharing data freely to accelerate breakthroughs.
28:44
And yet Jared Diamond's principle of intermediate
28:46
fragmentation suggests an optimum between excessive
28:49
unity and fragmentation. Exactly. You want groups
28:52
that compete but also communicate freely. He
28:55
contrasts centralized China, which could dismantle
28:58
its sleep by decree, with fragmented Europe,
29:01
where Columbus could shop his idea around. Silicon
29:04
Valley as an ideal. Fiercely competitive, but
29:07
highly communicative. A good model for medical
29:09
innovation hubs, perhaps. Fostering both rivalry
29:12
and knowledge exchange. It all comes back to
29:15
a beautiful conclusion. Advanced selfishness
29:18
actually requires cooperation, trustworthiness,
29:21
generosity. Taking a long -term view of reciprocity.
29:25
Building networks of cooperators. Short -term
29:27
self -interest can be self -defeating. Cooperation
29:30
truly is the highest form of self -interest for
29:33
individuals and systems. So we've navigated the
29:35
biological landscape. Now let's pivot to the
29:37
grand laws of the physical universe from Newton
29:40
to quantum quarks and see how they echo in business
29:42
and healthcare. Absolutely. Sir Isaac Newton's
29:45
impact was immense. Universal mathematically
29:48
predictable laws governing movement. The clockwork
29:50
universe idea. Building bridges, sending rockets,
29:54
a sense of control. Deeply reassuring. And it's
29:56
not an old hat for business or medicine. Newtonian
29:59
tools are invaluable. Accounting systems, return
30:02
on capital, discounted cash flow, cost benefit
30:05
analyses for new scanners or treatments. You
30:07
couldn't run a hospital or a health service without
30:09
them. Impossible. They provide those simple universal
30:12
numbers that still offer magical insights into
30:15
efficiency and viability. And Newton's third
30:18
law. Action and reaction are equal and opposite.
30:22
A guide to what's around the corner. Almost infallible.
30:25
Any powerful development elicits an opposite
30:28
one. Highly specialized procedures create demand
30:30
for holistic care. Tech advances might spark
30:33
a counter movement emphasizing the human touch.
30:36
It works both ways. Then there's the gravity
30:38
of competition, playing Newton's law of gravitation.
30:41
Metaphorically, yes. Corporate gravity is the
30:43
downward pressure on margins from competitors.
30:46
In healthcare, pressure on pricing for procedures,
30:49
drugs, due to alternatives. And this gravity
30:52
is strong if you're close to a larger competitor,
30:54
where size means resources, skill, not just patient
30:57
numbers. Exactly. And distance is about differentiation,
31:01
unique services, specialization, geography. Crucially,
31:05
this Martian gravity isn't linear. Returns rise
31:07
sharply as you avoid competitors or increase
31:10
relative size. BCG found a 10 % relative market
31:14
share gain led to more than 10 % profit increase.
31:21
systematically increase distance, develop unique
31:24
specialties, patient experiences, concentrate
31:27
resources in competition -free zones, avoid commodity
31:30
black holes. Moving into the 20th century, Einstein
31:33
arrives. Relativity, space, time, mass, energy
31:36
linked. The Verding -Newton, leading to transistors,
31:39
nuclear power, profound changes. And while we
31:41
can't apply the equations directly to medicine,
31:43
The worldview shift matters, the elusive nature
31:45
of time and truth. Precisely. For business, it
31:48
means integrating time into the offering product
31:50
time, service time, delivering faster diagnostic
31:53
results, quicker access to specialists. But here's
31:55
the time heresy. We're often awash with time
31:58
in organizations. Blacksill and Houch research
32:00
suggests most value is added in short bursts,
32:03
oases of productivity, surrounded by deserts
32:06
of low value processes, waiting times. The challenge
32:09
is mental. Think of time as internal to your
32:12
offering. Not external. Measure it. Find savings.
32:16
Map patient journeys. Focus on those who value
32:18
speed. Which, in medicine, is almost everyone.
32:22
Einstein and Goodell's incompleteness theorem
32:24
also imply no absolute truth. Reality is an invention,
32:29
not a given. How does that translate? Key relativities.
32:33
The patient's perspective on care quality is
32:35
always different from the provider's. So continuous
32:37
listening and acting on feedback is crucial.
32:40
Decentralized decisions, moving them closer to
32:42
the patient, even letting patients make some
32:44
choices within safe bounds. Powerful and perceived
32:46
quality is paramount. Absolutely. Quality isn't
32:49
absolute, it's perception. A strong hospital
32:51
brand, good communication, market leadership.
32:54
These can all shape the perception of quality
32:56
in the patient's mind. Marshall McLuhan, the
32:59
medium is the message. Communications tech transforms
33:02
things. Think online patient forums, review sites.
33:06
They've fundamentally shifted how medical services
33:08
are perceived and chosen. The internet is both
33:11
a dominant tech and a communications mechanism.
33:14
Shifting power to individuals, patients seeking
33:16
information and choice, favoring insurgent providers
33:20
like telemedicine startups. Yes, it changes the
33:23
nature of healthcare delivery, making product
33:25
time and service time imperative. Patients expect
33:28
instant access, rapid responses. It pushes the
33:31
whole system. Finally, let's brave the quantum
33:34
realm. Heisenberg, Bohr, a bizarre micro -world.
33:38
Lodley, unpredictably random and interconnected,
33:42
far removed from our everyday experience. Schrödinger's
33:44
cat illustrates the absurdity of applying it
33:46
directly. The cat both alive and dead until observed.
33:49
A bizarre thought experiment, yes, but its core
33:51
message, the opposite of a great truth is also
33:53
true, is highly relevant. How so? For management.
33:57
The key insight is adopting a both -hand approach,
34:00
escaping the tyranny of either. Don't choose
34:02
between Newtonian management, rational, numbers
34:05
-driven hospital administration, or quantum management,
34:07
embracing unpredictability, experimentation,
34:10
paradox. Embrace both. Integrate rigorous, evidence
34:14
-based protocols, and be willing to experiment
34:16
with novel, unconventional approaches when standard
34:19
methods fail, within ethical bounds, of course.
34:22
It suggests the value of thought experiments
34:24
and actual experiments, exploring possibilities
34:26
before committing fully. Okay, now let's transition
34:28
into decoding dynamic systems. chaos, complexity,
34:32
and the powerhouse 80 -20 principle, finding
34:35
patterns and disorder vital for complex systems
34:37
like healthcare. Many important things, whether
34:39
brains, cities, economies, human bodies, are
34:43
nonlinear systems. The whole is greater than
34:45
the sum of its parts. Simple cause and effect
34:47
thinking fails. Traditional linear analysis can't
34:50
cope. No. Chaos theory defines chaos not as randomness,
34:54
but constrained disorder. Patterns are discernible
34:56
within irregularities. Mandelbrot finding similar
34:59
patterns in cotton prices and Nile levels. Unexpected
35:02
order. What are the implications for hospitals
35:04
or health systems? Profound. It's inherently
35:06
uncertain and risky. Past success guarantees
35:09
nothing. Taking intelligent risks is vital because
35:12
outcomes are uncertain anyway. And sensitive
35:14
dependence on initial conditions. Small changes.
35:18
Huge effects. Exactly. A minor change in a clinical
35:21
trial's recruitment. An overlooked detail in
35:23
a drug's formulation. Tiny starting points can
35:27
have massive ripple effects you'd never predict.
35:30
Which also means when things go wrong in complex
35:32
systems, blaming individuals might be pointless.
35:34
Often it is. The system itself can be unpredictable.
35:37
Focus on what to do next, not assigning blame.
35:40
And because of this uncertainty, major decisions
35:43
require more than a single strategy. You need
35:45
options. Building on chaos, complexity theory
35:48
adds feedback systems, emergence. Where groups
35:51
behave differently from individual parts, and
35:54
self -organizing systems. Spontaneous organization
35:56
from simpler parts. Nature is full of them. Lasers,
35:59
hurricanes, cells, termite colonies. But most
36:02
modern corporations, and often hospitals, aren't
36:04
purely self -organizing. Not really. Parkinson's
36:07
law is an example of distorted self -organization
36:10
within bureaucracies. Work expands to fill the
36:13
time available. Officials multiply subordinates
36:15
for empire building, regardless of economic logic.
36:18
You see echoes in healthcare administration sometimes.
36:20
So the lesson is to observe the system, spot
36:23
what's emerging from the front lines, rather
36:25
than dictating from on high. Yes. Recognized
36:29
organizations are more like living organisms
36:31
than machines. They learn. copy, diffuse improvements.
36:35
They have evolving purposes. And the landscapes
36:37
metaphor from complexity science. Lissack and
36:40
Ruse's idea. Competitive terrain shifts dynamically.
36:43
New hills rise, old ones erode. Think of the
36:46
medical device industry. Dominant technology's
36:48
hilltop can be eroded by a disruptive innovation.
36:51
The landscape is never static. Which brings us
36:53
to the nonlinear powerhouse, the 80 -20 principle,
36:56
tipping points, increasing returns, achieving
36:58
more with less. The 80 -20 principle, Pareto's
37:01
observation from 1897, describes that profound
37:04
imbalance. It's everywhere. 700 words make 70
37:07
% of conversation, 1 % of films make 80 % of
37:10
box office, 5 % of websites get 75 % of visits.
37:13
Causes and effects are rarely 50 -50. Always
37:16
sheep and goats, a vital few, a trivial many.
37:18
Joseph Juran, the quality guru, called it the
37:20
rule of the vital few. His insight, always isolate
37:23
the vital few causes of problems, don't get bogged
37:25
down in the trivial many. IBM did this in 1963
37:28
with computer code. Rewriting 20 % of the code
37:31
that used 80 % of the time. Dramatic gains. Microsoft
37:34
did similar things. Exactly. In healthcare, identify
37:37
the 20 % of admin tasks consuming 80 % of staff
37:40
time, or the 20 % of patient complaints representing
37:43
80 % of service issues, addressing the vital
37:46
few yields disproportionate improvement. So strategically,
37:49
Firms, hospitals, they do too much. 20 % of activity
37:53
yields 80 % of benefit. That's the hypothesis.
37:56
It implies doing more of the vital for you and
37:58
less of the trivial many. Challenge the obsession
38:01
with ownership, acquisitions. Consider non -ownership
38:04
options, alliances. Divest non -core services.
38:07
Focus the value chain. Fewer products, customer
38:10
suppliers. Corning's 505 analysis stitching products
38:13
that made up 50 % of the range, but only 2 -5
38:16
% of sales. Simplifying the business boosted
38:19
profitability. In healthcare, streamlined devices
38:21
used focus on core patient segments, optimize
38:24
suppliers. It leads to the simple firm. Maximizing
38:27
return on management employed, Roam. Prioritizing
38:30
that over return on capital employed, ROCE. Because
38:33
management effort, clinical leadership, that's
38:35
often the scarcer, more critical resource in
38:37
complex medical settings today. This also connects
38:39
to the sociological power of weak ties, informal
38:43
networks. Yes, friends of friends, conference
38:45
connections, casual chats between researchers.
38:48
These can be more effective than rigid, formal
38:50
ties. allows influence with less control, tapping
38:54
diverse information, unexpected connections,
38:57
achieving 80 % of the goal with 20 % of the effort.
39:00
Now, back to punctuated equilibrium. Major tech
39:04
changes punctuate equilibria. Railroads, electricity,
39:08
computing, the internet. Penicillin, MRI technology,
39:11
genomics. These enabling technologies drive dramatic
39:14
cost reductions and growth, fundamentally shifting
39:17
the landscape. And this leads to the tipping
39:19
point. Ideas spreading like plagues. Exactly.
39:21
Reaching a critical mass after a gestation period,
39:24
then rapid exponential adoption. Microsoft's
39:27
profits tiny for 10 years, then exploded. Federal
39:30
Express snowballed. In medicine, widespread adoption
39:34
of a preventative measure after it hits critical
39:36
mass, rapid uptake of a new vaccine. Those fit
39:38
the pattern. And Peter Drucker highlighted unexpected
39:41
events, successes or failures as innovation opportunities.
39:44
IBM pivoting to payroll computers. Ford's Edsel
39:47
failure leading to the Mustang. So, in healthcare,
39:50
an unexpected drug side effect might lead to
39:52
a new treatment. A surprising patient outcome
39:55
sparks new research. Absolutely. Be alert to
39:57
the unexpected. We also underestimate exponential
40:00
growth. It's not linear. The Lollipad's doubling.
40:03
Covering half the pond in 16 weeks, the whole
40:06
pond in just one more week. The chess story.
40:09
Seemingly modest grains of rice becoming a colossal
40:12
amount. Exponential growth changes industries
40:14
qualitatively, bringing new leaders. Think genomic
40:17
data growth, computing power for drug discovery.
40:20
It's not just more, it's fundamentally different.
40:23
This challenge is the classical law of diminishing
40:25
returns. Yes. The idea that more effort eventually
40:28
yields less return doesn't reflect many real
40:30
-world markets well, especially tech or network
40:33
industries. Instead, we often see increasing
40:35
returns. More is law computing capacity doubling
40:38
at no extra cost. Brian Arthur's work explains
40:40
it. Products businesses that get ahead get further
40:43
ahead. Due to high upfront costs, low marginal
40:46
costs, like software first sale costs millions,
40:48
second cost pennies, and powerful network effects.
40:52
Value increases with more users, like fax machines,
40:55
email, or electronic medical record EMR systems?
40:59
Exactly. The more doctors and hospitals use a
41:01
particular EMR, the more valuable it becomes.
41:04
Data sharing. Standardization. a self -reinforcing
41:08
loop. Internet economics show winner takes most.
41:11
Low transaction costs, easy customization, separating
41:15
info from physical flows, Amazon. Consumers become
41:18
unpaid producers, reviews. Competitive advantage
41:22
shifts from scale costs to dominant standards,
41:24
capturing high value from a small strategic layer,
41:27
but it demands eternal innovation to defend that
41:29
position. Finally, how do we sustain success?
41:33
Navigate the pitfalls. The paradox of enrichment
41:35
is key. Too much of success can turn virtuous
41:37
cycles vicious. Success breeds arrogance, complacency,
41:41
ignoring new tech. A successful hospital stops
41:43
listening to patients, hires more staff, but
41:45
hinders innovation, diversifies unwisely. Nothing
41:48
fails like unchecked success. Then there's entropy,
41:51
the tendency for things to run down. Competitive
41:53
positions rest on resources needing constant
41:55
tending, renewal. Success is an equilibrium.
41:58
It requires constant innovation. And the law
42:00
of unintended consequences. Critical and complex
42:03
systems like healthcare. Well -intentioned actions
42:06
can have disastrous results due to linear thinking
42:08
in a nonlinear system. Dietrich Dörner's work
42:11
highlights this. The speed bumps causing more
42:14
pollution ultimately urban decline. So in medicine,
42:17
a cost -cutting policy might inadvertently worsen
42:19
outcomes elsewhere? Or increase admin burden?
42:22
It's highly possible. Durner advises clear, multiple
42:26
goals, anticipating side effects, avoiding single
42:28
causes, using simulations. But ultimately, human
42:32
creativity and adaptability are the antidotes.
42:34
Unintended consequences are inevitable. You have
42:37
to notice them, correct them. Knowing those corrections
42:39
will have more unintended consequences. It's
42:41
a continuous cycle. Observation, adaptation,
42:44
learning. So sustainable success for an individual,
42:47
clinician, a team, an institution is a virtuous
42:50
cycle, but constantly threatened. It requires
42:52
creating new value daily, maintaining humility,
42:55
service orientation, focus, leanness, hunger,
42:59
eschewing complexity. rooting out arrogance,
43:02
anticipating and correcting the unexpected through
43:04
systemic thinking. It's been quite a journey
43:06
through these power laws, biology, physics, systems,
43:10
offering a coherent if perhaps wonky view of
43:14
reality. And the point isn't rigid adherence,
43:17
but understanding and harnessing these powerful,
43:20
often hidden forces for advantage, particularly
43:23
in the demanding world of medicine. It's a fascinating
43:26
battle, isn't it? That ongoing struggle between
43:29
our hardwired instincts and the dynamic complex
43:32
world we've created, business and indeed medical
43:35
practice at its core, is this constant process
43:38
of creation and adaptation. Where the greatest
43:41
opportunities lie in identifying and exploiting
43:43
those unexpected patterns and continually reinventing
43:46
value for patients in society. It's a call to
43:49
look beyond the obvious perhaps, to embrace the
43:52
nonlinear. And to understand that progress truly
43:54
depends on the unreasonable medical professional.
43:56
the one who seeks to adapt the world to their
43:58
vision, pioneering new treatments, technologies,
44:01
or models of care rather than just conforming
44:03
to existing demands. If you've enjoyed this deep
44:06
dive into the hidden forces shaping our world,
44:09
please do consider rating and sharing the show.
44:11
It helps us bring more of these surprising insights
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directly to you.