Fuzziness and randomness ‘a hybrid approach’ to risk management

Uncertainty is a prominent feature of any major project. Yet, addressing this uncertainty and dealing with its impact is arguably one of the most remarkable topics of this period. Nevertheless, with the increased level of complexity and the emphasis on avoiding project cost overruns, there is an even higher emphasis on researchers to deliver an improved methodology for dealing with risk and uncertainty. Until recently, probability theory using Monte Carlo simulation seemed to be the most dominant approach to modelling random risks and probable events. However, in the past decade possibility theory based fuzzy sets theory has been recognised as a new methodology that can simplify the fuzziness behind uncertain events and vague impacts. This paper argues for the necessity of using both theories in quantifying risks and uncertainties. It is proposed that using a hybrid approach for the analysis of uncertainties, estimating cost and project planning, is a significantly more effective approach than those used previously. This new approach offers a tangible approach for costing of risks and uncertainties; furthermore it is proposed that classifying uncertainty sources under randomness and fuzziness to minimise the error in prediction and estimation. The case study considered in this paper will demonstrate the feasibility of the application of this approach to major projects, namely to UK construction projects.