Quantitative risk models based on statistics of past failures have the limitation that future failures are not reflected by historical averages and cannot be predicted.

Additionally, statistically repeatable studies cannot be performed on low probability-high consequence events, and are difficult to perform in complex systems when the failure frequencies are low and the interactions within the system are poorly understood.

Failures often appear perfectly predictable in hindsight. For that reason, DNV GL has developed a smart risk assessment methodology, Multi-Analytic Risk Visualization (MARV), to improve decision-making related to risk assessment of pipelines.