A key assumptions check (KAC) is a structured analytic technique that requires analysts to explicitly identify the unstated assumptions on which their assessment depends, evaluate the evidence supporting each assumption, and consider what would change if the assumption proved false. The technique addresses a vulnerability that Robert Jervis’s work on perception and misperception identified: analysts embed assumptions in their assessments without examining them, and once embedded, assumptions become invisible — they function as background conditions rather than contestable claims.
Method
The procedure is straightforward: (1) articulate the assessment’s conclusion; (2) list every assumption the conclusion depends on, including assumptions about adversary rationality, institutional behavior, technical capability, and the reliability of the evidence base; (3) for each assumption, ask what evidence supports it and whether the evidence is independent of the assumption itself; (4) for each assumption, ask what the assessment would look like if the assumption were false.
The value of the technique lies not in the answers but in the surfacing. Assumptions that seemed natural — “Iran’s leadership would not provoke a war it cannot win,” “the diplomatic track was genuine on both sides,” “the adversary’s retaliatory capability was degraded by the first strike wave” — become visible as contingent claims that could be wrong. Once visible, they can be monitored: the indications and warning system can be tasked to watch for signs that key assumptions are failing.
Limitations
The KAC’s limitation is the same as its purpose: it can only surface assumptions the analyst is capable of articulating. The deepest assumptions — the ones that structure the analyst’s entire framework rather than appearing within it — may be invisible to the technique. The assumption that the adversary is a unitary rational actor, for instance, is so foundational to most intelligence analysis that it may not appear on the assumptions list. This is why the KAC is most effective when conducted by a team that includes analysts with different frameworks, and why red teaming — which adopts the adversary’s framework rather than examining one’s own — provides a complementary check that the KAC alone cannot.
Related terms
- Analysis of competing hypotheses — complementary technique that tests hypotheses against evidence
- Red teaming — complementary technique that adopts the adversary’s perspective
- Mirror-imaging — the cognitive bias that assumptions checks are designed to surface
- Estimative language — the probabilistic vocabulary that assumptions checks help calibrate