Abstract: A method and computer program product for extending a business process model.

Abstract: A method and computer program product for extending a business process model.

Abstract: A method and computer program product for integrating risk management concepts into a standard business process metamodel by defining a set of metamodel extensions to standard process modeling languages that incorporate risk information directly in the process model. The method includes collecting risk-relevant information for addition to a business process model, and enabling visualizing of a risk-extended business process model. using a notation to express notions as failure modes of resources, root cause events, and sources of execution failure and low job output quality directly in the context of process models. Additionally, the method enables the computation of risk-related impacts on the distribution of process performance measures using a Bayesian network model or a discrete-event simulation model.

Abstract: A method and system for quantifying risk by composing a heterogeneous risk model are provided. The method comprises providing risk input data associated with one or more risk nodes to a processor, running one or more risk models to output individual risk quantifications for each risk node, and aggregating the individual risk quantifications into a single output. The system comprises a processor operable to provide risk input data associated with one or more risk nodes to a processor, run one or more risk models to output individual risk quantifications for each risk node and aggregate the individual risk quantifications into a single output.

Abstract: A method and system for collaboratively managing risk is presented. In one embodiment the method comprises analyzing a node in a risk network when an output of said node violates a control limit, identifying a cause of said violation of said control limit, creating a mitigation action in response to said node violating said control limit, performing said mitigation action, said mitigation action having an influence on said output of said node, and measuring said output of said node to determine effectiveness of said mitigation action on said node, wherein a program using a processor unit executes one or more of said analyzing, identifying, creating, performing and measuring steps.

Abstract: A method and system for collaboratively managing risk is presented. In one embodiment the method comprises analyzing a node in a risk network when an output of said node violates a control limit, identifying a cause of said violation of said control limit, creating a mitigation action in response to said node violating said control limit, performing said mitigation action, said mitigation action having an influence on said output of said node, and measuring said output of said node to determine effectiveness of said mitigation action on said node, wherein a program using a processor unit executes one or more of said analyzing, identifying, creating, performing and measuring steps.

Abstract: A method and system for quantifying risk by composing a heterogeneous risk model are provided. The method comprises providing risk input data associated with one or more risk nodes to a processor, running one or more risk models to output individual risk quantifications for each risk node, and aggregating the individual risk quantifications into a single output. The system comprises a processor operable to provide risk input data associated with one or more risk nodes to a processor, run one or more risk models to output individual risk quantifications for each risk node and aggregate the individual risk quantifications into a single output.

Abstract: A method and computer program product for integrating risk management concepts into a standard business process metamodel by defining a set of metamodel extensions to standard process modeling languages that incorporate risk information directly in the process model. The method includes collecting risk-relevant information for addition to a business process model, and enabling visualizing of a risk-extended business process model. using a notation to express notions as failure modes of resources, root cause events, and sources of execution failure and low job output quality directly in the context of process models. Additionally, the method enables the computation of risk-related impacts on the distribution of process performance measures using a Bayesian network model or a discrete-event simulation model.