Explainer video #01.04.01

Collection #01

Unstable Systems

The collection “Unstable Systems” is essentially about one core question:

How do systems become unstable while still appearing functional?

Unstable systems are organizational environments that remain seemingly functional while gradually losing their ability to absorb pressure, adapt coherently, or maintain long-term structural integrity.

As instability deepens, systems often adapt locally in ways that preserve short-term functioning while increasing long-term fragility. This creates the illusion of stability precisely when systems are becoming more vulnerable.

Many strategic challenges are not isolated problems but symptoms of systems operating near the limits of their adaptive capacity.

In this collection:

Research objects exploring system drift, false stability, adaptive fragility, delayed consequences, and the hidden tensions preceding systemic change.

Examples #01.02.1-4

Manifestations

Common ways instability shows up across systems, sectors, and scales.

Resource Strain

Demand outpaces regenerative capacity, increasing structural pressure over time.

Examples:

✔️ groundwater depletion
✔️ housing shortages
✔️ power grid strain

The entire UK power grid gets rewired. Instead of power being generated by coal and gas plants close to big cities, it is increasingly coming from renewable sources such as offshore wind. This leaves the massive task of getting the power from where it is generated to where it is used.

Congestion

Flows exceed system capacity, creating backlogs, delays, and brittleness.

Examples:

✔️ traffic delays and maintenance backlogs
✔️ health care backlogs and demographics
✔️ power grid congestion and subsidies

Structural Gaps

Missing buffers and capabilities leave systems exposed to disruption.

Examples:

✔️ ICU capacity before and after the pandemic
✔️ Critical skills in emerging technologies
✔️ Weak data infrastructure and hacks

In June 2024, a section of Switzerland's A13 motorway, an important route linking north and south, has collapsed after violent storms and floods caused landslides. The road has been closed up til September 2024.

Rising Volatility

Small fluctuations grow in magnitude and frequency, reducing the reliability of the system

Examples:

✔️ Climate change & flooding
✔️ Energy price volatility
✔️ Information bubbles and polarization

Flashcards #01.03

Weak Signal Types to Look For

Swipe to see some early indicators that instability is accumulating in the system.

Deeper insight into weak signals

Concept Cards #01.01.01-04

Core Dynamics

Recurring dynamics shape how systems absorb instability until something gives. Here are four of them.

The ripple effect of our decisions is like water ripples when we throw in stones: we only see the interference after a while

Delay

Consequences emerge long after the decisions that produced them were made. Makes the system difficult to interpret.

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Drift

The system slowly and imperceptibly changes direction, despite nobody intends to change it.

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A rotting wooden bridge is repaired by adding new planks on top. This keeps the bridge in operation while increasing instability

False Stability

The system still “works,” but that's an illusion. So many decisions aren't effective anymore.

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Although the system adapts en continues to exist, its direction and form will change uncontrollably

Adaptive Fragility

Actors increasingly compensate in the now, but that increases the problems over time.

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Exercise #01.06.01

Field Observation

Use this week to observe these core dynamics in your organization's environment (its system).

Explainer video #01.04.02

Fieldnote (to consider) #01.05.10

Strategic failure often begins with solving problems in isolation rather than taming the big picture

Exercise #01.06.02

Scenario Thinking

Think about your organization's context and market (its system). Imagine the year is 2032.

For years, the system worked exactly as expected.
Then several small disruptions started interacting with each other (see example block).

Nothing collapses overnight, but the system becomes harder to predict.

--> What changes would most people notice too late?

Example Block

Combine at least two disruptions:

Energy prices remain structurally volatile
AI automates part of the workforce faster than expected
Extreme weather disrupts logistics several times per year
Younger workers avoid certain sectors
Infrastructure investments lag behind demand

Applying These Ideas

The concepts in this collection have been used in executive education, technology foresight projects, innovation ecosystem studies, and strategic decision-making exercises.

Learn more about:

Back to the collections

Collections on unstable systems and strategic information

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On with the dynamics

Concept cards on delay, drift, false stability, and adaptive fragility

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