A variety of risk and resilience-based design methods have been put forward over the years that seek to provide designers the tools to reduce the effects of potential hazards in the early design phase. However, because of the high level of uncertainty and low-fidelity design representations, one might justifiably wonder if using a resilient design process in the early design phase will reliably produce useful results that would improve the realized design. This paper provides tests that can be performed on a design process to determine whether it gives meaningful results when applied to an uncertain problem. These tests check three metrics: the change in the design when uncertainty is considered, the increase in the expected value of the design, and the cost of choice-related uncertainty: to see if they stay within desirable bounds. This approach is illustrated using two case studies to demonstrate how both discrete and continuous parametric uncertainty can be considered in the testing procedure. These case studies show that early design process validity is sensitive to the level of uncertainty and magnitude of design changes, suggesting that while there is a justifiable decision-theoretic case to consider high-level high-impact design changes during the early design phase, there is less of a case to choose between relatively similar design options because the cost of making the choice under high uncertainty is greater than the expected improvement in value of choosing the better design.