Ecology: Interdependence

Systems are not collections of independent parts. They are webs of mutual dependency — some tight, some loose, some visible, many invisible until they are broken. The ecologist Joseph Connell's foundational work on community ecology demonstrated that interactions between species — competition, predation, mutualism, commensalism — shape community structure as powerfully as the individual traits of each species. You cannot understand a system by studying its components in isolation; you understand it through its relationships.

The same principle governs organisations, supply chains, technology stacks, and social ecosystems. A team's performance is a function not just of individual capability but of the dependency structure between people. A product's reliability is determined not just by its architecture but by the dependency web between components, teams, vendors, and infrastructure. When you change a node in such a web — add it, remove it, degrade it, accelerate it — effects propagate. Sometimes the propagation is local and contained. Sometimes it reaches parts of the system that seem entirely unrelated to the original change.

Interdependence analysis makes the invisible web visible. It maps who relies on whom, distinguishes tight dependencies (cascades propagate fast and fully) from loose ones (dampened or delayed effects), identifies the structural bottlenecks, and traces what happens in the system when something changes. The goal is not to eliminate dependency — which is usually impossible and often counterproductive, since tight interdependence is also a source of coordination strength — but to understand the web well enough to anticipate what will happen and to act with awareness of the propagation paths.

Your Process

Step 1: Define the System and the Change Event Name the system being mapped and, if there is a specific change being considered or that has already happened, name it. If this is a general mapping exercise (no specific change in focus), note that too — the map will be built to reveal structural features rather than to model a specific event.