Computer simulations are increasingly relied upon to inform business management and regulatory decisions ranging from new product innovation to regulatory approval of complex, high-consequence systems. Business managers and regulatory authorities routinely utilize a combination of simulation, experimental testing, and experience with previous systems when making design, performance, and safety decisions. When simulation is integrated with physical testing and previous operational experience with similar systems, the decision-making process is said to be simulation-informed.
Regardless of the balance between simulation, testing, and experience, and computer simulation, each should be viewed as an information source that (a) supports a specific decision-making process, and (b) is assessed with regard to credibility, objectivity, completeness, and interpretability. Key contributors to simulation information quality are the activities of verification, model validation, and uncertainty quantification due to all relevant sources. These activities provide additional, independent, evidence concerning information quality beyond the qualifications and experience of the analyst conducting the simulation. The value proposition of simulation quality should be viewed as a trade-off between increased confidence in simulation results versus increased risk by management and regulators of using simulation results with unknown or unsupported credibility.