expertjudgement

Expert judgement refers to assessments, estimates, or predictions derived from the knowledge and experience of individuals or groups regarded as having specialized expertise. It is commonly used when empirical data are incomplete, uncertain, or unavailable, or when rapid assessment is required.

Methods to obtain expert judgement include structured elicitation protocols that quantify beliefs as probabilities, ranges, and confidence levels. Common approaches are the Delphi method, expert panels, and formal weighting schemes such as Cooke’s method. Elicitation often involves training, calibration questions, anonymized input, and iterative aggregation to reduce bias.

Applications span risk assessment, project planning, technology forecasting, environmental and public health decisions, regulatory analysis, and climate risk modeling. Expert judgement can complement quantitative models by providing qualitative insight and explicit uncertainty bounds.

Advantages include incorporating tacit knowledge, enabling assessments where data are sparse, producing explicit uncertainty estimates, and allowing updates as new information appears.

Limitations include susceptibility to cognitive biases (overconfidence, anchoring), dependence on the chosen experts and sample size, challenges in combining judgments, and potential lack of methodological transparency. Result quality hinges on the elicitation protocol and expert selection.

Evaluation and criticism: well-designed elicitation and aggregation can improve estimates and sometimes outperform single experts, but poorly designed processes can yield biased results. Transparency and careful documentation are essential for credibility.

See also: Delphi method, Bayesian statistics, elicitation, risk assessment.