AI and other discontinuities raise the speed and ambiguity of change. Institutions are slower systems. Most organizations now have more intelligence, data and analysis than they can use. The constraint is their ability to absorb it and act.
In practice: recognizing which changes matter, separating signal from noise, translating an external development into implications, deciding before the evidence is complete, coordinating across departments, experimenting before certainty, learning from the experiment, moving resources, and making a successful adaptation normal practice. Institutions fail at different points on that list. Where they fail determines the intervention.
Adaptive capacity has seven dimensions. Each is a question about what an institution did in the past twelve months. Questions about attitude are excluded because the desirable answer is obvious.
Can the organization notice relevant change early?
Can it understand what that change means?
Can it make consequential decisions under uncertainty?
Can different actors align around a response?
Can it test responses cheaply and quickly?
Does evidence change beliefs and behavior?
Can successful responses become normal institutional practice?
These are working categories. Benchmark data will confirm or revise them.
Understand the environment. Signals and the open research map what is changing outside the institution: thousands of technologies, checked against sources.
Understand the institution. Two benchmarks measure adaptive capacity: the National Capability Benchmark for countries, 53 of them published at ncb.envisioning.com, and the Organizational Capability Benchmark for companies, agencies, universities and NGOs.
Strengthen adaptive capacity. Each service works on named dimensions:
Data from Signals, the benchmarks and the interventions feeds back into the model. A Build Session also tests whether rapid experimentation moves one dimension. A benchmark also tests whether the seven dimensions are the right ones.
The model makes three claims that data can contradict.
The national benchmark runs the first test on every release: each dimension score is compared with the score its income level predicts, and correlation and redundancy between dimensions are reported. The organizational benchmark will run the same tests once the sample supports them.