The process for designing and testing solutions employes computational models, data mining/integration, experiments, etc. within a common quantitative analysis environment. Designing and testing solutions are problem dependent, focused on answering questions relevant to any aspiration:
- How might the aspiration be implemented and are there feasible choices within the multi-objective space?
- How robust are these choices to uncertainties in assumptions?
- What are the critical enablers that increase system resilience?
Included in this process is the delineation of unintended consequences and their amelioration/mitigation.
Uncertainty Quantification and Verification/Validation efforts are integrated throughout the design process.
If analysts are satisfied that the design solutions, modeling output and solution robustness under uncertainty match the needs of the problem holder, move on to Phase 3: Actualizing. Otherwise, iterate within this phase or phase 1 to refine components.