In systems thinking, mental models represent the assumptions and beliefs that influence a system's behavior.
They are the most influential yet least visible component of a system.
A revenue plan is an example of a mental model, containing beliefs about the market, buyers, reasons for purchasing, and what drives results.
These beliefs were valid when created, and they serve as operational instructions for downstream decisions.
In complex systems, mental models are risky because they do not update automatically as reality changes: they tend to stick, causing behavior to follow outdated models while the actual
system has evolved.
This is a sign of a structural trait of mental models: they don't self-correct and need external signals for revision.
Often, when a mental model fails, the first indicator is a missed target.
By then, the model has been inaccurate for months, leading to decisions based on incorrect assumptions.
Organizations that safeguard revenue aren't necessarily those with better mental models, but those with systems to recognize when their mental models no longer match reality before negative outcomes occur.
