Training ObjectivesLearn to apply the most rigorous method to support your decision making in the absence of data and under uncertainty. In this course you will be able to gather, assess the performance of and combine expert opinion for your own study. Structured Expert Judgment (SEJ) is a technique that enables you to appropriately account for uncertainty when there is no data or no appropriate data available. An increasing number of organizations are making use of panels of experts in order to provide assessments over key uncertainties. Since the use of multiple experts in decision making results in a significant reduction in risk, SEJ has become a critical part of their decision-making processes for complex issues. But how can data be properly elicited from qualified experts? And how can we guarantee that experts' assessments of uncertainty are evaluated as objectively as possible? In this course you will learn to design a successful expert judgment study using the most rigorous and mathematically sound method known as the Classical Model (CM). This method has been used by institutions and companies such as NASA, RIVM, WHO, Airbus, Shell and KLM, to support their (data-driven) decision-making.
Training ContentsPerform a study within your own context, using CM. Design a complete expert judgment elicitation. Perform an expert judgment elicitation. Analyse expert data gathered during elicitation and develop a report with findings.
Digital Innovation Hubs
- Practical exercices
Technology Absortion Cycle
- Awareness of technology
- More than 20
Date: Future dates to be announced
Durations: +7 days
ProjectDelft University of Technology
Countries where training is providedNetherlands
Cities where training is providedDelft
Languages this training can be provided
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