Subscribe
Share
Share
Embed
Understand Systems. Drive Change. Create Coherence. The Adaptive Thinker applies systems thinking to what matters most: our relationships, our money, our work, the environment, politics, healthcare, etc. The Adaptive Thinker approach is simple. Every week, one pattern applied to something real and current and impactful in your life. Hosted by Will North, founder of Coherence Systems, creator of the Systems Analyzer, and the Architect of Adaptive Intelligence The list goes on. Our goal is simple — make visible the systems shaping your life. The ones driving results you wanted, and the ones driving outcomes you didn't. Drive positive change. Create coherence.
There are seven principles governing every
complex system you've ever worked inside.
They were running while you
were trying to fix things.
They were running when things worked, too.
Nobody named them.
Nobody put them on the wall.
And because they were invisible, you
kept doing what all of us do: treating
the symptoms, adding new programs, and
watching the same problems come back.
Today, you get them,
all seven, one at a time
Systems thinking goes back to the 1950s.
Jay Forrester at MIT,
Donella Meadows, Peter Senge.
The core discovery, complex systems don't
behave the way linear thinking predicts.
They have their own logic,
circular, delayed, structural.
These seven principles are that logic.
And here's what I didn't fully absorb
until years into this work, and still
today working to try and figure it out.
They're just not for organizations.
The same structural dynamics
run at the personal level, the
interpersonal, the community level.
We'll get into that.
First, the seven
Feedback loops
Systems circle back on themselves.
There are two types: reinforcing
loops, which amplify, and
balancing loops, which resist.
Most systems have both running at once.
That's why they're hard to predict.
You're not dealing with a line,
you're dealing with circles inside
of circles inside of circles.
Feedback loops are pretty straightforward.
Uh, reinforcing is like compound
interest in a savings account.
It adds on to the balance, and
then you earn more interest on the
balance, which adds to the balance,
and it continues to reinforce.
Balancing loops resist.
It's like turning down the
temperature, uh, on your thermostat
in the summertime when it's hot.
So the heat still rises outside,
but the temperature continues to
balance down to the level you want.
Delays.
Cause and effect in complex systems
are rarely connected in time.
That gap is what makes
systems so hard to manage.
When we don't see the results, we tend
to change something, add more force, add
more resources, and it's often exactly
what the original intervention is still
working to do but hasn't accomplished yet.
I've watched this type of intervention
strategy end really good policy work.
The intervention was right to begin
with, it just needed a little more time.
The timeline was longer than the
impatient political process would allow
Stocks and flows.
Stocks are what accumulate.
Trust accumulates over time.
Debt accumulates.
Mine tends to accumulate
faster than I want it to.
Trained staff accumulate and become
competent and capable over time.
Public confidence grows and
accumulates with results.
Flows are the rates that change them.
Most policy debate
focuses only on the flows.
The stocks are where the real action
is, where we actually create the
conditions that we care about.
And stocks take time to move.
Briefly, trust is a stock, and it builds
slowly, but it's lost in an instant.
You've probably heard
that, and it's so true.
But in a system, the issue then becomes
that the loss in trust continues
to reinforce itself and reinforce
itself and reinforce its- itself.
That occurs in politics today.
Leverage points.
Not everywhere in a system
responds equally to effort.
The leverage points produce
large effects from small inputs.
They're almost never where
the pain is most visible.
They're upstream, structural,
and counterintuitive.
Finding them is the work that
actually produces the change.
Leverage points are found
in really good models.
And when you find that leverage point,
it's like finding gold in a gold mine
Mental models.
Every decision maker has a
model of how the system works.
Most of it is implicit, built
over years from experience, from
training, from what worked in a
crisis, uh, from what was molded by
a previous leader or mentor or coach.
That model determines what you see,
what you notice, what you focus
on, what you measure, and as a
result, what you think and what you
try to do when it comes to either
reinforcing or balancing that system.
When I moved into healthcare leadership,
I arrived with what I thought was
a solid mental model: business
school, total quality management,
a decade of management experience.
I was wrong in ways I couldn't even
begin to see because the model in
my mind, the mental formulation, was
shaping what I was able to see, and I
couldn't see what was really going on.
I kept looking for management failures
when the problem was structural.
I kept adding programs and changing
things when the problem was a
feedback loop that wasn't visible.
Confident, competent, and focused
on the wrong level of the system.
That was me.
It was truly humbling.
When I updated the model in my
mind, things changed, not because
I worked harder, because I started
looking at the right level.
I had the correct mental model
for the problem in front of me.
Now, that's a beginning, and it
was for me, because a wrong model
confidently applied produces
confidently wrong answers.
In a quality improvement
process, it shows up this way.
Improving a variance in a
metric is easier than it looks.
Improving the right variance is
altogether a different story.
I've often said, "Quality improvement
will tell you what to improve, but
it won't tell you what to improve."
So if you wanna improve a metric,
you can, but you may be suboptimizing
the rest of the system as a result.
Non-linearity.
Systems don't respond
proportionally to different inputs.
Small changes at the right
point create large effects.
Large changes at the wrong level
create almost nothing and, in fact,
waste tremendous amounts of resources.
This is why the more resources, throw
more money at it type of solution
often fails on structural problems
Emergence.
System behavior comes from the
interactions between parts.
You can study every element perfectly
and still not understand the system.
The behavior lives in the relationships.
The scientific method has its limits.
It's a reductionist approach, trying
to find the single cause for a problem.
But it doesn't always work that way.
Sometimes it's a combination, and that's
where the limits of a simple scientific
method approach doesn't always work.
Here's what I want to
name before we go further.
These seven principles were first mapped
in organizational and industrial systems.
That's where most of the literature lives.
But they operate identically
at the personal, interpersonal,
and community levels.
A feedback loop compounding trust
in a relationship is no different
than a feedback loop compounding,
uh, more water in a bathtub.
A delay explaining why the results
of improved sleep habits don't
show up with improved sleep
for three weeks or two months.
A mental model running your
self-perception with the same
persistence it has since you were
young is no different than an
institutional culture that resists
change by outside intervention.
My work over many years has traced these
dynamics across a continuum from the
classic problem-oriented level through
a recurring problem of diagnosis and
recurring failure through the personal,
interpersonal, and community levels, where
the same structural principles produce
human scale problems, habits, different
activities that don't change over time.
Each level has its own archetypes,
its own disciplines, its own
leverage points, but the underlying
operating logic is the same seven.
The full map of that continuum is
the work of the book I'm writing, but
the foundation is what you have now.
These principles are running right
now in the policy debates happening in
Washington, DC, in the AI systems being
deployed by high tech at extraordinary
speed on top of unexamined structural
assumptions and mental models.
The mental model driving most modern
governance and most large corporations
that complex systems respond predictably
to targeted interventions is itself
a mental model that is correct in
some instances but wrong in others.
And it produces a specific
recognizable pattern of failure.
Confident, well-resourced,
repeatedly wrong.
We're governing AI, climate policy,
and democratic institutions with
that old mental model still in place.
These seven principles are where you can
begin to start replacing it with clearer
models, better models to explain behavior
You have the operating
rules now, seven of them.
The vocabulary for what you've
been living inside without
having the words to explain it.
And we're just beginning.
As this unfolds over the next several
weeks, we'll apply these same principles
to your relationships, to the organization
you work at, to your community, and
also to the larger political world
that we're finding ourselves in today.
Next week, the 12 archetypes.
These are the recurring configurations of
these seven principles, the patterns that
show up across industries, geographies,
and contexts with enough consistency
that researchers have named them.
Once you know the names, you'll see
the patterns everywhere, and once
you see them, you can't unsee them.
They were always there.
Now you'll be equipped to
find them in everyday life.
If you want to be among the first
to know when I have new products or
services available or get an early
reader discount on some of my products,
find the link in the show notes.
For now, I'm Will North, and
this is The Adaptive Thinker