Risk & Decision-Making
Risk & Decision-Making
- Decision clarity: What decision is being made, by whom, by when, under what constraints.
- Objective function: What is being optimized (survival, return, stability, ethics) and what is non-negotiable.
- Uncertainty type separation: Risk (known probabilities) vs uncertainty (unknown) vs ignorance (unknown unknowns).
- Outcome space completeness: Range of plausible outcomes, including adverse and tail events.
- Probability discipline: Where probabilities come from; calibration; base rates; priors.
- Tail-risk handling: Fat tails, black swans, ruin risk, cascading failures.
- Dependency and correlation: Interdependence, contagion, hidden coupling.
- Time and path dependence: Sequencing, compounding, irreversibility, lock-in.
- Model limitations: Assumption sensitivity; error bounds; model risk.
- Incentives and governance: Who bears downside vs upside; moral hazard; accountability.
- Option value and flexibility: Reversibility, real options, staged commitments.
- Robustness vs optimality: Resilient strategies that survive variance vs fragile optimal bets.
- Information value: What to learn next; when to wait; when to act.
- Stress testing & scenarios: Adversarial scenarios, worst-case, base-case, best-case.
- Human cognitive biases: Overconfidence, loss aversion, availability, narrative fallacy.
- Early-warning signals: Indicators, triggers, escalation thresholds.
- Ethical boundaries: Risk shifting to others, externalities, fairness.