Cascades, Compounding, and Feedback

Small shocks rarely stay small. In connected supply chains, disruption spreads, combines and loops back in unexpected ways. This post explains the three patterns that drive systemic risk — cascades, compounding and feedback — and how The Signal House framework helps you act earlier.

A late vessel feels routine. A day slips. Teams adjust slots. Customers get an update. Then the knock-ons begin. The DC reschedules labour. A key account misses a shelf date. Finance flags a jump in premium freight. Planning inflates safety stock.

What started as a small delay becomes a week of side effects.

That is the reality of polycrisis. It is not a pile of separate problems. It is interaction. Events push on each other across four channels: physical, informational, financial and reputational. The result is volatility that feels larger than the initial disruption.

Three patterns explain why this happens.

Cascades: one thing leads to another

A cascade is a chain. One trigger sets off a sequence of connected steps. Each step makes sense on its own. The damage comes from the order and speed.

A supplier issues a small label update to meet a new rule. It looks trivial. The line pauses to reprint. The changeover runs long. You miss the contract packer slot. Transport rebooks on a premium service. The DC receives mixed pallets off-plan. A promotion lands without enough stock. Customer service issues credits. Finance reports higher accessorials a week later.

One small disruption set off a chain.

This is the same logic as the bullwhip effect in demand and inventory. The difference is that the whip now cracks across several pathways at once, not just in the forecast.

Cascades thrive in tightly coupled systems. When buffers are thin and calendars full, small slips flow instead of being absorbed.

Compounding: small stresses add up

Compounding happens when two modest pressures interact and push a system past a threshold. Each looks manageable in isolation. Together they create a step change.

Think of lean inventory alongside longer repair cycles. Neither seems critical alone. Combine them and a minor quality hold empties a line. Or pair supplier concentration with a mild credit squeeze. No one defaults, but allocation quietly shifts away for a quarter.

The effect is not linear. It feels sudden because the threshold is invisible until it breaks.

Compounding sits in the background. It hides in “known issues” until a trigger exposes it.

Feedback: today’s fix shapes tomorrow’s problem

Feedback loops occur when a system reacts to its own output. The response becomes a new input. Sometimes that stabilises the situation. Sometimes it amplifies it.

After a shortage, teams add safety stock to prevent repeats. It makes sense. But if planning cannot see the change in time, order noise grows. Forecast error increases. The next cycle adds even more stock. A few months later inventory looks high in the wrong places. You cut too hard, service drops, and the loop continues.

It appears as a run of sensible decisions that never quite land, and they quietly add to disruption.

Feedback lives in both process and perception. Internal dashboards nudge behaviour. External signals do too. A headline about port delays can pull forward demand and change the very pattern you are trying to correct.

Why these patterns change how we view risk

Most risk tools start with lists. They put hazards in rows and assign scores. That gives coverage, not mechanism. Lists hide the links. Managers fix what sits in their row and push cost to the next one.

The Signal House framework starts with how trouble moves. It classifies stresses, triggers and crises.

• Stresses are the background conditions that make systems fragile.
• Triggers are thresholds that flip the state.
• Crises are the operational outcomes leaders feel: missed OTIF, margin pressure, cash strain or reputation damage.

Then we trace propagation pathways — physical, informational, financial and reputational.

• Cascades appear as chains of arrows.
• Compounding shows up where two stresses meet.
• Feedback is the short loop that closes the circuit.

This approach changes the question. Instead of “How likely is this event?” you ask “Where will it travel and where can we interrupt it?”

That shift delivers three results:

1. Earlier intervention. You act on the first controllable link.
2. Cleaner trade-offs. You weigh cost and service on one map.
3. Lower decision latency. You reduce time from signal to decision to action.

What this looks like in practice

A small cyber alert forces manual workarounds for a day. The cascade shows up a week later in forecast error. The fix is not only technical. It is procedural: a standard message to planning when telemetry drops. That breaks the loop.

Or take a regional power outage. The physical pathway halts operations. The informational one creates planning noise. The financial one strains cash buffers. The reputational one triggers customer escalation. A risk map shows all four at once and highlights the earliest switches to break the chain.

The takeaway

Cascades, compounding and feedback turn ordinary incidents into costly weeks. They are not exotic theories. They are the everyday physics of connected systems.

When you make them visible, you regain control. You act sooner. You spend where it matters. You avoid paying twice.

If you want to see how this applies to your network, book a 30-minute discovery call with The Signal House. We will outline a pilot tailored to your governance and partners.