Multi-criteria treatment choice
Options for treating a risk are scored against objectives such as safety, cost, service continuity and equity, with weights elicited from decision makers and the sensitivity of the ranking to those weights reported.
GCRI · Systemic Risk Management
Decision analysis for risk management
Decision analysis structures choices under uncertainty: it makes the options, objectives, uncertainties and trade-offs explicit so that a decision can be examined and defended. In systemic risk management it supports appetite setting, the choice of treatments and the selection of investments in resilience where consequences are uncertain and values conflict.
01Register
Decision analysis for risk management on the record.
Method recordSTEM method
- MethodDecision analysis under uncertainty
- StewardSystemic Risk Management
- Applied inSystemic Risk Management
- Data4 inputs
- Checks3 validation steps
- Canonical pageSTEM Commons
02Application
What decision analysis under uncertainty does here.
Decision analysis under uncertainty provides structured methods for choosing among options when outcomes are uncertain and objectives conflict. It makes trade-offs and value judgements explicit. In risk management and systemic risk and methods and modelling, decision analysis helps choose actions that perform acceptably across interconnected risks and uncertain futures. It clarifies when to act now and when to keep options open. The canonical description is on the STEM Commons.
Decision trees for contingent plans
Sequential choices, such as whether to invest now or wait for information, are laid out with their probabilities and consequences, and the value of further information is estimated before commissioning it.
Robust choices across scenarios
Strategies are tested across many plausible futures to find those that perform acceptably in most of them, and the conditions under which each strategy fails are identified.
03Monitor
Uncertainty analysis.
The screen a team would use to follow this method: its measures, states and decisions. Names are examples and values are illustrative.
Uncertainty analysis
Systemic risk · Decision analysis for risk · Run R-0911
Sensitivity rankedGCRI · Systemic Risk Management
Total-order sensitivity
Output distribution
Inputs
| Risks above appetite | Normal | risks, stated | expert elicitation |
| Key risk indicators in breach | Normal | KRIs, stated | expert elicitation |
| Controls tested effective | Lognormal | of controls, stated | expert elicitation |
| Interdependency links mapped | Normal | links, stated | expert elicitation |
04Data
What the method consumes.
Datasets and records used by decision analysis under uncertainty on this platform, with the role each plays and the label its values carry. Sources are listed in the source register.
| Data | Role | Label |
|---|---|---|
| Elicited objectives and weights from decision makers | Value model inputs | DECLARED |
| Risk register assessments | Likelihood and consequence inputs | ESTIMATED |
| Scenario libraries | Futures for robustness testing | MODELLED |
| Cost and performance records of past treatments | Option evaluation | OBSERVED |
05Methods and evidence
How decision analysis for risk management is modelled, measured and tested.
The model, its assumptions, its data and its uncertainty, in the form a scientist or engineer would check. Structures follow published methods. The values drawn are illustrative, not findings.
Model, equations and assumptions
The model structure used for decision analysis for risk management, the assumptions it makes and how each is tested.
Risk of element i
Ri = f(Hi, Ei, Vi, Ci)hazard, exposure, vulnerability and coping capacityExpected annual loss
EAL = ∑k pk · Lkover events k with annual probability pkCoupled systems
xt+1 = A xt + B ut + εtA carries the couplings, u the shock, ε the error| Assumption | Why it is made | How it is tested |
|---|---|---|
| Hazard and exposure are independent within an event | Keeps the loss integral tractable | Compare with a copula fit on joint records |
| Couplings are linear near the operating point | Lets shocks propagate through A | Perturb beyond the linear range and compare |
| Vulnerability curves transfer between places | Local curves are rarely available | Validate against observed losses where they exist |
- Inputs
- versioned datasets with provenance
- Outputs
- distributions, never single numbers
- Code
- released with the model card and tests
- Reproduction
- same data, code, environment and seed
FAIR guiding principles · GO FAIR and FORCE11W3C PROV · World Wide Web ConsortiumGuidance on consistent treatment of uncertainties · IPCCCEOS Analysis Ready Data · Committee on Earth Observation Satellites
06Validation
How results are checked.
Analyses are checked through sensitivity analysis, peer review and stakeholder scrutiny. Retrospective review compares decisions with outcomes.
| Check | How it is done |
|---|---|
| Sensitivity to weights | Rankings are recomputed across plausible weight ranges and changes in the preferred option are reported |
| Value of information | The expected value of reducing an uncertainty is estimated before commissioning further study |
| Requisite model review | Decision makers confirm that the model captures the objectives and options they consider relevant |
Results depend on elicited probabilities and preferences that may be biased. Deep uncertainty can make expected value comparisons misleading.
07Process
How the process runs.
Process
Decision analysis for risk management: Hazard, exposure, vulnerability
In IPCC AR6 Working Group II, climate risk results from interactions between hazards and a system’s exposure and vulnerability, and responses can add risk.
01 Drivers
- 01HazardDataset · Board risk committeeThe potential occurrence of a natural or human-induced physical event or trend that may harm people, property, services or ecosystems.
- 02ExposureDataset · Board risk committeeThe presence of people, livelihoods, species, ecosystems, infrastructure or assets in places and settings that could be adversely affected.
- 03SensitivityDataset · Board risk committeeThe degree to which a system or species is affected, either adversely or beneficially, by climate variability or change.
- 04Capacity to cope and adaptDataset · Board risk committeeThe ability of systems, institutions, humans and other organisms to adjust to damage, take opportunities or respond to consequences.
02 Assessment
- 05Risk from responsesComponent · Board risk committeeRisks from climate responses arise when responses miss their objectives, or from trade-offs or negative side effects.
- 06VulnerabilityComponent · Board risk committeeThe propensity or predisposition to be adversely affected. It includes sensitivity to harm and lack of capacity to cope and adapt.
- 07RiskModel · Systemic Risk ManagementRisk results from dynamic interactions between hazards and the system’s exposure and vulnerability. Each may be uncertain and change.
03 Response
- 08Risk management and responseStep · Board risk committeeRisk management is plans, actions, strategies or policies that reduce the likelihood or size of adverse consequences.
- 09Residual riskRecord · Board risk committeeThe climate impact risk that remains after adaptation and mitigation efforts. Adaptation can redistribute risk between areas and groups.
04 Decision
- 10Decision by the responsible partyDecision · Board risk committeeThe framing names no single decision maker. Decisions on responses rest with the responsible party under its own rules.
Outline of an external standard or method, from its public sources. It describes what the framework says, not a record of any run. It does not show that Nexus or any partner performs, certifies or approves a step. A gate is a step of the method, never a Nexus approval.
08Connections
Topics that rely on this method.
09Stewardship
Who maintains the method.
Systemic Risk Management stewards decision analysis under uncertainty for the Consortium and reviews how it is applied across platforms.
10Questions
Questions and answers.
What are the limits of decision analysis under uncertainty in this field?
Results depend on elicited probabilities and preferences that may be biased. Deep uncertainty can make expected value comparisons misleading.
How are results checked?
Analyses are checked through sensitivity analysis, peer review and stakeholder scrutiny. Retrospective review compares decisions with outcomes.
Are the values on this page real?
The data names, roles and checks are real descriptions of practice. The canvas shows a design of the method’s use, not a run; no result is reported here.
Where else is this method applied?
The canonical method page lists every platform that applies it.
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