Welcome to the Deep Dive. We heard you loud and
clear you wanted a closer look at how innovation
actually, well, happens, how change moves through
the world. Yeah, and specifically how things
like information and communication technology,
ICT, have really shaken up the old rules. Exactly.
We're talking about that classic model, the S
-curve, you know, that blueprint for how technologies
get adopted. That's our focus today. We're breaking
down that S -curve and showing you why, especially
now in the 21st century, it looks Well, fundamentally
different. It's like it's been pull -taught,
straightened out, and made much more volatile.
Right, so for anyone maybe not familiar, the
classic S -curve maps out this typical journey.
Starts slow, only a few innovators jump in. Uh
-huh, the early adopters. Then boom, suddenly
there's the steep climb, mass acceptance, everyone
gets on board. And then finally, it levels off,
it plateaus. Either because, you know, everyone
who wants one has one market saturation, or the
tech itself just hits a limit. It's a really
foundational idea for understanding tech history,
but the sources we looked at, particularly Gary
Ackerman's work, point out something crucial.
The curve for today's ICT, it's not just faster,
it's different in like two big ways structurally.
That's the core insight. It's changed fundamentally.
So let's unpack that. First, this idea that the
curve is straightening out. Yeah, accelerating.
And second, how we get from one curve to the
next, that moment of innovation. It's become
way more disruptive than it used to be. Understanding
those two forces, acceleration and disruption,
is... Oh, it's pretty critical if you're trying
to navigate or plan for pretty much anything
today. Okay, let's tackle that acceleration first,
the straightening S -curve. Right. So what we
mean by straining is really a massive compression
of the whole cycle. The time it takes. Exactly.
The time it takes for a technology to go from
being this obscure thing only a few people know
about to being... everywhere. Yeah. Almost ubiquitous.
That time frame has just collapsed. Yeah. I was
looking at the historical data in the sources.
It really throws the speed difference into sharp
relief, doesn't it? Oh, absolutely. It shows
it's not just a gradual speed up. It's like a
genuine break, a discontinuity. So give us some
examples. OK. Think about reaching, say, 50 million
users. The sources mentioned radio took several
decades to hit that number globally. Decades
Wow all that infrastructure the physical sets
precisely lots of physical stuff needed then
television comes along a bit faster much faster
relatively speaking down to just a few years
Infrastructure was getting better mass production
was kicking in okay still years though still
years, but then yeah, you jump into the digital
age ICT think about platforms like YouTube how
long for them months mere months to hit 50 million
users. Decades to months. That's the straightening
curve in action. It's a list of a gentle S shape
and more like a vertical takeoff followed by
a sudden flat top. That difference is just huge.
But why? Why is ICT so different from radio or
TV? It's not just that we suddenly got better
at adopting things, is it? No, no, absolutely
not. The fundamental difference is economic and
infrastructural. Those classic S -curves. They
were held back by physical stuff. Constraints.
Physical constraints, yeah. Yeah. And marginal
costs. For radio, like you said, you needed transmitters,
licenses, factories making radios, shops selling
them. Every single new listener costs something
significant to add. Right, a physical investment
for each new user. But with digital stuff, software,
apps, online platforms, it's a whole different
ballgame. How so? Well, once you've built the
basic platform, the cost to add one more user,
or 10 million more users. It's tiny. It's virtually
zero. Plus, you have the power of network effects.
Ah, where it gets more valuable the more people
use it. Exactly. That creates this viral loop,
this acceleration that physical goods just couldn't
achieve in the same way. The network's already
there, the internet. Adoption can be almost instant,
global. That's what pulls that curve up, right?
Okay, so that shift from physical friction slowing
things down to this almost frictionless digital
spread, that must completely change how organizations
plan for the future. Oh, totally. It turns planning
on its head. Think back to the 20th century.
Those broad, slow S -curves meant you had time.
You could see a trend coming. Yeah, you could
spot a new technology, watch it for a bit, maybe
form a committee. You had, I don't know, five,
ten years sometimes to adjust your strategy,
retrain people, change how you do things. Slowly.
That sounds nice, actually. A bit leisurely.
It was a luxury, looking back. But the sources
are clear. 21st century planning happens under
these straight S -curves. Things move so fast.
That by the time you're sure it's a real trend.
You're already halfway up the curve. Maybe more.
And the next thing is already starting its climb.
Planning becomes less about catching one wave
and more about Well, continuous reinvention.
Continuous reinvention. That sounds exhausting.
How can any organization, like a school system
or a business, commit resources if they know
the whole setup might be obsolete in, say, 18
months? Does it just lead to paralysis? That's
the million dollar question, isn't it? Yeah.
It's the core challenge. The old way, wait and
see, then make a big, long -term plan that just
doesn't work anymore. So what's the alternative?
Agility. Modularity. You're not planning for
the peach of this curve anymore. You have to
be constantly scanning the horizon, looking for
the start of the next one. It's like juggling.
You might have two or three cycles going at once
in different stages. So less about perfecting
the current system, more about adapting constantly.
Exactly. The mindset shifts from optimization
to adaptation. OK, that constant hunt for the
next curve, that leads us right into the second
big trend you mentioned. Right. Innovation by
replacement. It's not just about speed. It's
about how the new replaces the old. How does
that work? Well, innovation often happens when
one S -curve basically pushes another one out,
replaces it. And that moment of replacement,
that shift, often forces a complete rethink of
whatever the technology was doing. And why does
a curve plateau in the first place? You mentioned
saturation. Saturation is one reason. But often,
as the sources point out, it's because the technology
or the practice hits some kind of wall, a physical
limit maybe, or it just stops being as effective
within its existing setup. So if we still need
the function like calculation or communication,
something new has to come along. Exactly. Something
that does the same job but smashes through that
old limit. And the sources say there are different
ways this replacement happens. Smooth versus
not so smooth. Yeah, basically two flavors. Smooth
and disruptive. Let's look at the smooth kind
first. This often happens with like core hardware
technology. OK. The sources use the evolution
of computers as an example here, right? Case
one, smooth transition. Perfect example. Think
about what powers computers. We went from these
big, hot, clunky vacuum tubes. Right. Room -sized
computers. To much smaller, more efficient transistors.
And then later, another leap to integrated silicon
circuits, microchips. Those sound like massive
changes technologically. Why were they smooth?
Because, from the perspective of the designers
and the users, these changes were largely welcomed.
They were seen as upgrades. Even though the underlying
tech was totally different. Yeah. Because the
function didn't radically change. and the change
was mainly additive. The computer still did computation
right. The new tech just let it do it vastly
faster, smaller, cheaper, using less power. So
the people building and using the computers didn't
have to fundamentally rethink what a computer
was or what it did. Pretty much. They just got
a massively better engine. The limits being hit
were physical heat, size, speed of electrons.
The new tech solved those physical problems.
It increased capacity within the existing idea
of computing. OK, the structure stayed intact,
just the components got better. Makes sense.
It was a capacity -increasing transition welcomed
by the people involved. But, and there's always
a but, the story changes when the innovation
isn't just swapping out hardware bits, when it
hits people systems. Exactly. That takes us to
case two. disruptive transitions. This is where
it gets messy. What makes it disruptive? It's
especially true when the innovation happens in
what we might call social technologies. Things
like education or journalism or governance. The
systems and habits and institutions we build.
There was that mention of the book disrupting
class. Out education. Right. That work highlights
this distinction really well. Why is introducing
say a new type of software for learning often
so much more disruptive than introducing a new
microchip. Because the microchip doesn't have
feelings or a union. Well, kind of. Hardware
doesn't have entrenched cultural norms or established
job roles or decades of bureaucratic procedure
built around it. But social systems do. Absolutely.
Take that education example. If a new model emerges,
maybe highly personalized adaptive learning software,
it isn't just a new tool teachers can choose
to use. It challenges the whole system. Potentially,
yes. It might challenge the teacher's traditional
role, the need for standard classroom hours,
the way schools are administered, even the idea
of a centralized curriculum. So the technology
might promise the same outcome, learning, education,
but getting there requires changing how people
work, their status, the established routines.
The power structures, the budgets, all of it.
And that creates resistance, friction. It's disruptive
because the limit isn't just physical. It's the
existing social structure that's hitting its
limit of effectiveness or adaptability. Got it.
Can you give another example, maybe outside education?
Sure. Think about traditional news media, newspapers,
network television news. That was a huge social
technology, right? Definitely. The newsroom structure,
the printing presses, the delivery trucks. Exactly.
That whole S -curve. relied on things like geographic
monopolies, physical distribution, advertisers
paying for print space. Their limit wasn't running
out of paper. It was the effectiveness of that
entire model once the internet arrived. Precisely.
The newspaper's social structure, the reporter's
role, the editor's power, the ad sales team,
the reliance on a daily print cycle hit its effectiveness
limit when ICT offered zero marginal cost distribution,
instant updates, global reach. And a totally
different advertising model. Right. The new S
-curve, digital news, offered the same basic
function information, but required essentially
dismantling the old organization jobs disappeared
roles changed the relationship with the audience
was redefined that's disruption okay that really
clarifies the two forces we've got these hyper
fast straight adoption curves meaning we have
very little time to react. And the innovations
that replace old ways, especially in human systems,
are often deeply disruptive, forcing fundamental
change. It makes planning incredibly complex.
You're dealing with speed and structural upheaval
simultaneously. That idea of continuous reinvention
seems key then. It's not just about adopting
new tools. No, it's often about reinventing the
whole structure around the tools and doing it
fast. The question shifts from how do we build
this system to last 20 years to how fast can
we build, deploy, and then maybe even dismantle
a system that might only be the best option for
20 months. Wow. So the old S -curve was this
graceful, predictable arc, gave stability. Yeah,
allowed it for maturity. But the modern ICT driven
curve is more like... Sharp, rapid steps up,
where each step requires rebuilding the landing
you just left. That's a good way to put it. And
the pace seems to be accelerating still. Coping
with that speed and that depth of change. That's
really the defining challenge for organizations,
for leaders, for all of us really. A powerful
summary. So for you listening, as you think about
all this... Here's something to chew on after
this deep dive. Yeah, take this back to your
world. Think about the shift from those slow,
broad curves to these fast, straight, often disruptive
ones. Now look at your industry, your field.
What long established social technology, maybe
it's a bureaucratic process, a traditional workflow,
a regulatory system, anything based on human
habits and structures, what system do you see
hitting its limits, its effectiveness cap? And
then ask yourself. What kind of disruptive replacement,
maybe something already quietly gaining traction
on its own fast S -curve, might be poised to
challenge or even shatter it? Something to keep
an eye out for, especially the next time you
run into a process that feels way too rigid for
today's world.