Overoptimisation is what happens when a system narrows relentlessly to what it can measure and reward, at the expense of the unmeasured things that were actually holding it together.
The process is gradual and each step is locally rational. The organisation removes what it cannot measure because it cannot justify the cost of keeping it. The diverse, the redundant, the slow-yielding — all get cut because they look like inefficiency from inside the frame. But many of these things were providing resilience: the capacity to absorb shocks, respond to novel conditions, and recover when something fails.
In ecology, the equivalent is a monoculture: high yield, maximum fragility. The diversity that looks wasteful is the diversity that survives disease, drought, and disruption. Strip it out and the system performs better right up until the moment it does not.
The organisational version follows the same logic. The NHS reduced its hospital bed numbers by more than half over three decades, driven by genuine efficiency improvements — shorter stays, better day surgery, less duplication. Each decision was defensible. The cumulative result was a system with no slack. When demand surged unexpectedly, there was no buffer to absorb it, and the only available response was to stop doing almost everything else. The efficiency had been real. So was the fragility. They were products of the same dynamic.
This is one of the reasons organisations can be simultaneously excellent at what they measure and failing at what they exist for. The excellence is not a facade — it is genuinely there, and genuinely purchased at the cost of capacity that does not return once it has gone.
The direction out of overoptimisation is not simply doing less. It is rebuilding diversity and adaptive capacity, which requires understanding what was load-bearing in the first place — and that understanding is rarely available from inside the frame that removed it.
Related
- Three mechanisms that keep it in place — overoptimisation is one of three self-reinforcing mechanisms that hold frame failure in place
- Proxy capture — optimising for the measure rather than the goal is how overoptimisation sustains itself
- Productive collapse — the failure mode overoptimisation produces over time
- What gets removed does not come back — why the capacity shed through overoptimisation cannot simply be restored when it is needed
- From optimised to resilient — the direction of travel out
- Resilience as abundance — the positive framing: diversity is not inefficiency, it is productive capacity
- The suppression of finitude — the professional tendency to exclude awareness of genuine time limits; overoptimisation enacts this at the system level by treating finite reserves as permanently available