Data Driven Predictive Risk Modelling, M Beard (Paper)

By July 25, 2022Documents, Hong Kong 2017
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This paper presents the work that Arthur D. Little completed to develop a new safety risk model for a major utilities sector client. The risks in question are low probability, high consequence risks, arising from safety critical lone workers leaving unsafe conditions in their work. This new model depends on using multiple disparate data sources effectively to provide indicators of employees potentially at risk of leaving these unsafe conditions. The model takes diverse performance measures to contribute to a reliable risk metric that informs management decision making in both the operational and safety assurance functions.

Year of Publication: 2017

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