Chang, C; (2016) Harnessing BIM data in the management of project risks: the Bayesian risk-bearing capacity approach. In: Transforming the Future of Infrastructure through Smarter Information: Proceedings of the International Conference on Smart Infrastructure and Construction, 27–29 June 2016. (pp. pp. 537-542). ICE Publishing: Cambridge, UK.

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Abstract

With the increasing proliferation of Building Information Modelling (BIM) worldwide, an emerging issue is how to better leverage the BIM data in decision making. This research demonstrates formally that the cost information attached to BIM can be utilised to inform risk management decisions by incorporating the newly developed risk-bearing capacity (RBC) approach into the Bayesian statistics framework. Under BIM, the deviations of outturn costs from planned costs can be systematically recorded and used to update the old ‘beliefs’ that are normally formed by resorting to subjective probabilities. With the potential to integrate the data held by insurers, cost estimators and credit raters, this framework can greatly facilitate the effective use of enormous new data in improving risk management practices.

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