Modelo de evaluación de proyecto de inversión basado en analítica de datos para determinar la viabilidad del montaje de una sucursal Starbucks en el municipio de Apartadó (Antioquia)

Abstract

This This work develops an investment-project appraisal model that integrates data-analytics tools with classical financial methods such as Net Present Value (NPV), Internal Rate of Return (IRR), payback period, and benefit-cost ratio, in order to assess the feasibility of opening a Starbucks branch in the municipality of Apartadó (Antioquia, Colombia), under the licensing scheme operated by Alsea in Colombia. The methodology combines a market study conducted with the local population, a technical-operational analysis of location and capacity, as well as a legal, tax, and five-year financial analysis. In addition, data-analytics techniques such as a 10,000-iteration Monte Carlo simulation, scenario analysis, and the construction of the Markowitz efficient frontier are incorporated to evaluate risk and profitability behavior. The results show a 58.5 % purchase-intention rate, mainly concentrated in socio-economic strata 3 and 4, together with projected demand growth from 80,482 to 142,952 annual transactions. Financially, the project presents an NPV of COP 702.6 million and an IRR of 61.31 %, based on an initial investment of COP 530 million recoverable in approximately two years. Furthermore, the stochastic simulation indicates a near-zero probability of loss and a Sharpe ratio of 1.86. In conclusion, the project is considered viable and demonstrates that integrating data analytics strengthens decision-making during the pre-investment phase.