Data-Driven Risk Management: A Practical Approach to Minimize Subjectivity
ICH Q9(R1) introduced the need to manage and minimize subjectivity in risk management in order to enhance scientific sound risk based decision making. In this presentation, a practical approach to respond to this need is outlined in the context of a production process risk management. A set of digital state-of-the-art integrated tools is used to manage risk assessment activities. Once a risk baseline is defined, based on a existing set of tacit and explicit knowledge (if available), an iterative process of risk refinement is defined in which risks are re-calculated as new data and knowledge is available. Besides RPN revision, the integration with data allows the identification of new risks for a continuously improved control strategy.
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