Abstract The paper describes a new methodology for analysing quantifiable risks, and it considerably expands present methods while embodying most of the results currently generated. It simplifies the data requirements for analysis, and does not require statistical expertise. It limits analysis to prevent risks/problems, and it calculates their relative ranking. Most importantly, it initially considers a vital question which is usually omitted in, for example, pert , namely the chance of a risk occurring; the nature of the effect is considered. Several dimensions are considered together, e.g. time and cost. Because of its tree-structured nature, in-depth analysis can be performed. The major defects of the frequently used beta distribution are overcome by the Berny distribution. Macrosimulation is shown to simplify and widen the use of risk analysis because it is knowledge-embedded. It allows the consideration of both external and internal project problems/risks. Finally, practical use to date has been most successful, and enables a much wider audience to make use of risk analysis.
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