Expert Judgment in Risk Analysis and Management: Process, Context, and Pitfalls

Otway, H.J.; Winterfeldt, Detlof von

doi:10.1111/j.1539-6924.1992.tb01310.x

Cited by 146 publications

(93 citation statements)

References 11 publications

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“…Despite improvements in understanding of the characteristics that promote good judgments, standardized protocols for the selection, preparation, and elicitation of experts do not exist. Analysts in this field argue that they should not necessarily exist but rather, protocols should be crafted to suit the particular problem under investigation (Morgan and Henrion, 1990;Hora, 1992;Otway and von Winterfeldt, 1992 ).…”

Section: Methodsmentioning

confidence: 99%

“…Many of the early applications were military in nature but formal uses for expert judgment have found application in the aerospace industry, artificial intelligence, engineering, expert systems, medicine, and nuclear energy ( Cooke, 1991 ). Otway and von Winterfeldt ( 1992 ) discuss the use and pitfalls of subjective judgment in risk analysis using examples from nuclear power.…”

Section: Introductionmentioning

confidence: 99%

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Use of expert judgment in exposure assessment. Part I. Characterization of personal exposure to benzene

Walker

Evans

MacIntosh

2001

J Expo Sci Environ Epidemiol

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This paper presents the results of the first phase of a study, conducted as an element of the National Human Exposure Assessment Survey ( NHEXAS ) , to demonstrate the use of expert subjective judgment elicitation techniques to characterize the magnitude of and uncertainty in environmental exposure to benzene. In decisions about the value of exposure research or of regulatory controls, the characterization of uncertainty can play an influential role. Classical methods for characterizing uncertainty may be sufficient when adequate amounts of relevant data are available. Frequently, however, data are neither abundant nor directly relevant, making it necessary to rely to varying degrees on subjective judgment. Since the 1950s, methods to elicit and quantify subjective judgments have been explored but have rarely been applied to the field of environmental exposure assessment. In this phase of the project, seven experts in benzene exposure assessment were selected through a peer nomination process, participated in a 2 -day workshop, and were interviewed individually to elicit their judgments about the distributions of residential ambient, residential indoor, and personal air benzene concentrations ( 6 -day integrated average ) experienced by both the non -smoking, non -occupationally exposed target and study populations of the US EPA Region V pilot study. Specifically, each expert was asked to characterize, in probabilistic form, the arithmetic means and the 90th percentiles of these distributions. This paper presents the experts' judgments about the concentrations of benzene encountered by the target population. The experts' judgments about levels of benzene in personal air were demonstrative of patterns observed in the judgments about the other distributions. They were in closest agreement about their predictions of the mean; with one exception, their best estimates of the mean fell within 7 -11 g / m 3 although they exhibited striking differences in the degree of uncertainty expressed. Their estimates of the 90th percentile were more varied with the best estimates ranging from 12 to 26 g / m 3 for all but one expert. However, their predictions of the 90th percentile were far more uncertain. The paper demonstrates that coherent subjective judgments can be elicited from exposure assessment scientists and critically examines the challenges and potential benefits of a subjective judgment approach. The results of the second phase of the project, in which measurements from the NHEXAS field study in Region V are used to calibrate the experts' judgments about the benzene exposures in the study population, will be presented in a second paper.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Use of expert judgment in exposure assessment. Part I. Characterization of personal exposure to benzene

Walker

Evans

MacIntosh

2001

J Expo Sci Environ Epidemiol

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“…Fortunately, several formal approaches to dealing with diverging expert opinions originally developed in economics [e.g., Otway and von Winterfeldt, 1992] can be adapted in hydrogeology, just as it has been done in seismology [SSHAC, 1997;NRC, 1997]. Their practical implementation is a separate topic that lies outside the scope of the present letter.…”

Section: Definition Of Probabilitiesmentioning

confidence: 99%

Probabilistic risk analysis in subsurface hydrology

Tartakovsky

2007

Geophysical Research Letters

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[1] We present a general framework for probabilistic risk assessment (PRA) of subsurface contamination. PRA provides a natural venue for the rigorous quantification of structural (model) and parametric uncertainties inherent in predictions of subsurface flow and transport. A typical PRA starts by identifying relevant components of a subsurface system (e.g., a buried solid-waste tank, an aquitard, a remediation effort) and proceeds by using uncertainty quantification techniques to estimate the probabilities of their failure. These probabilities are then combined by means of fault-tree analyses to yield probabilistic estimates of the risk of system failure (e.g., aquifer contamination). Since PRA relies on subjective probabilities, it is ideally suited for assimilation of expert judgment and causal relationships.

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“…Expert judgment is a widely used as data input in risk management, e.g. (Cooke and Goossens 2004;Boholm 2010;Celeux et al 2006;Cooke and Goossens 2004;Evans et al 1994;Otway and Winterfeldt 1992). Furthermore, numerical ranges were used if it was difficult for the experts to provide precise numbers, as suggested by (Hubbard 2010).…”

Section: Operationalization Of Model In Case Studies D E Fmentioning

confidence: 99%

A risk based model for quantifying the impact of information quality

Borek

Parlikad

Woodall

et al. 2014

Computers in Industry

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Information quality is one of the key determinants of information system success. When information quality is poor, it can cause a variety of risks in an organization. To manage resources for information quality improvement effectively, it is necessary to understand where, how, and how much information quality impacts an organization's ability to successfully deliver its objectives. So far, existing models have mostly focused on the measurement of information quality but not on the impact that information quality causes. This paper presents a model to quantify the business impact that arises through poor information quality in an organization by using a risk based approach. It hence addresses the inherent uncertainty in the relationship between information quality and organizational impact. The model can help information managers to obtain quantitative figures which can be used to build reliable and convincing business cases for information quality improvement.

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Expert Judgment in Risk Analysis and Management: Process, Context, and Pitfalls

Cited by 146 publications

References 11 publications

Use of expert judgment in exposure assessment. Part I. Characterization of personal exposure to benzene

Use of expert judgment in exposure assessment. Part I. Characterization of personal exposure to benzene

Probabilistic risk analysis in subsurface hydrology

A risk based model for quantifying the impact of information quality

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