Characterizing Aerospace Cost Estimate Dynamics: Distributional Metrics for Contextualizing Outcome Variability

Cost estimates are vital to project planning, but traditional metrics often fail to capture the inherent uncertainty and variability of real-world project execution. Recent disruptions, like the COVID-19 pandemic, have highlighted the significant consequences of rare events on supply chains and project costs, especially during the long-term Operations and Sustainment (O\&S) phases in aerospace. This work tackles the challenge of effectively communicating the dynamic nature of cost estimate inputs and the diversity of potential outcomes. By employing distributional metrics, such as the coefficient of variation and measures derived from extreme value theory, a more nuanced understanding of cost variability emerges. These metrics provide context around the spread of outcomes that traditional characterizations overlook, revealing insights into potential outliers and risks. The findings affirm that applying distributional metrics offers a comprehensive characterization of outcome variability, which is essential for effective cost estimation. Ultimately, this approach advocates for a shift towards a more robust framework for cost estimation that incorporates the complexities of rare events and their potential impacts on project viability, enhancing decision-making in project management.