How much specialist depth the structure makes possible.
Try this first
Suggested exploration: about 4 minutes.
Increase organisation size, then compare specialist functions and hand-offs.
What to look for: Coordination and shared understanding become harder as the organisation grows.
What this simulation shows
Scaling is not simply doing more of the same thing. As a system grows, informal relationships become less sufficient, work becomes more specialised, and information has to cross more boundaries. Those changes can increase capability while also making coordination harder.
This model lets you explore that tension. Change one input at a time, then compare the system’s coherence and lived experience with its local dashboard score.
Interactive simulation
What happens when a system scales?
Increase the size of the organisation, add specialist functions and change the quality of its coordination. The model is deliberately simplified: it is a way of exploring the argument, not pretending an organisation can be reduced to five sliders.
More people create more possible relationships and more information to coordinate.
Specialisation increases capability, but every new function creates another boundary.
How much context survives when work or information crosses a boundary.
Some process stabilises a large system; too much starts to create friction of its own.
Higher pressure encourages functions to optimise their own metric rather than the whole.
Person moving through the system 2 boundaries
How much meaning survives across the full journey.
How well the parts still behave like one organisation.
What the pupil, customer or employee actually encounters.
Average local dashboard 76
Whole-system outcome 78
At this scale, informal coordination still does much of the work.
How the model works
The simulation is intentionally a model, not a claim to organisational physics. Specialist capability rises with functional depth but eventually gives diminishing returns. Coordination load rises with both organisational size and the number of boundaries. Context is lost multiplicatively across hand-offs. Process offsets some coordination load, but excessive process adds friction. Local target pressure can improve local scores while reducing overall coherence. The interesting behaviour is the interaction between those effects.
The mechanism
The simulation treats specialist capability as a benefit of functional depth, while treating coordination load and context loss as costs of scale. Better hand-offs preserve more meaning between functions. Process offsets some coordination load, but excessive process introduces friction. Pressure on local targets can make individual functions look successful while weakening the whole system.
These are deliberately simplified relationships. The purpose is to make the interaction visible: a locally sensible decision can still produce a worse outcome for the system as a whole.
How to use this simulation
Change one input at a time, run the model, and compare the result with the starting state. Then repeat the experiment with a different constraint or strategy so you can see which relationships drive the outcome.
What to look for
Look for trade-offs, thresholds, feedback loops, and points where a locally attractive decision produces a worse system-wide result. The simulation is intended to make the article's idea observable, not to predict a real operation.
Limitations
This is a deliberately simplified model. It omits the data quality, exceptions, human judgement, and operational constraints of a live system, so treat its behaviour as an illustration of a mechanism rather than as a planning recommendation.
Read the related article
Read: From Primary School to Senior School: What Scaling Does to a System →
Explore the complete Systems Thinking for Product Managers series