Purpose The purpose of this article is to examine the Brazilian context of real estate feasibility practice, highlight the gap between deterministic and probabilistic approaches – common across emerging markets – and demonstrate how probabilistic modelling can be made accessible even under data-scarce conditions. Design/methodology/approach The article is structured in two interlinked parts. The first reviews previous research, current developer practices, educational content and institutional guidelines to assess the Brazilian context. The second presents a case study that applies Monte Carlo simulation in a spreadsheet environment using expert-judgment elicitation to define input probability distributions. Findings Although local practitioners acknowledge uncertainty qualitatively, feasibility studies in Brazil remain dominated by fixed-point cash-flow simulations. This gap is driven by limited data availability, low technical awareness, restricted access to analytical software and institutional inertia. The adapted model further illustrates that even modest probabilistic integration can enhance transparency and support more informed investment decision-making. Practical implications The framework offers developers and analysts an accessible pathway to incrementally incorporate risk analysis into feasibility studies, helping to align local practice with international standards such as those of the Royal Institution of Chartered Surveyors (RICS). Originality/value This Practice Briefing revisits and extends previous work on Brazilian feasibility practice, offering one of the first contextualised discussions of how probabilistic reasoning can be operationalised in emerging markets, bridging the gap between academic modelling and professional application.
Dennis Alonso Sanchez Clavijo (Thu,) studied this question.