High-Impact Low-Probability Analysis
A SAT that examines events assessed as unlikely but which would have significant consequences if they occurred. Forces analysts to work through scenarios they might otherwise dismiss.
Purpose
Counter the natural tendency to focus analytic attention only on likely events. Some of the most consequential events in history (Pearl Harbor, 9/11, Yom Kippur War) were assessed as low-probability before they occurred.
Biases Primarily Controlled
| Bias | How this technique counters it |
|---|---|
| Availability Heuristic | Specifically designed to force attention onto low-availability events — those that are rare and therefore hard to imagine |
| Overconfidence Bias | Requires working through scenarios the analyst considers unlikely; engages with the distribution tail that overconfidence ignores |
| Status Quo Bias | Requires treating a departure from the current trajectory as a primary object of analysis, not an afterthought |
Applied in Cybersecurity
- Risk Analysts: evaluates unlikely events that could cause catastrophic damage — e.g., a supply chain attack compromising multiple critical vendors (Riley: SATs in Cybersecurity (2024))