Form Follows Forecast: Monte Carlo Based Feasibility Analysis of Architectural Partis

Abstract

Contemporary American multifamily development is typically evaluated through financial models that reduce architecture to scalar inputs: gross floor area, story count, cost per square foot, rent, and exit value, among others. These variables are necessary, but they are largely blind to geometry. This thesis proposes an abstracted proxy framework for making the architectural parti more financially legible by translating early massing decisions into two composite indices: Architectural Complexity C and Asset Quality Q. These indices connect measurable design conditions to cost- and value-facing consequences, then enter a Monte Carlo pro forma that samples market and delivery uncertainty. The framework is tested on a hypothetical market-rate multifamily tower in Seattle’s Eastlake neighborhood through a sequence of authored massing iterations. The results show that spatial ambition and financial robustness do not automatically align: balconies, rounded forms, amenity moves, and added height can improve architectural value while weakening underwriting performance. Rather than a finished predictive model, this thesis is a focused exploration of how architectural form might be quantified earlier, while the parti is still flexible enough to be tested, revised, and improved.