Simulación Monte Carlo como herramienta para priorizar los riesgos de los proyectos

• Fernando Acebes Senovilla ^[1] ; José Manuel González Varona ^[2] ; Adolfo López Paredes ^[2] ; Javier Pajares Gutiérrez Pajares Gutiérrez ^[1]
  1. [1] Universidad de Valladolid
  2. [2] Universidad de Málaga
• Localización: Dirección y organización: Revista de dirección, organización y administración de empresas, ISSN 1132-175X, Nº 85, 2025, págs. 43-56
• Idioma: español
• DOI: 10.37610/85.689
• Títulos paralelos:
  • Monte Carlo simulation for project risk prioritisation
• Enlaces
  • Texto completo
• Resumen
  • español

    En este artículo proponemos un método cuantitativo para priorizar los riesgos identificados en un proyecto. Basado en simu-lación de Montecarlo, la propuesta que presentamos evita la utilización de la matriz probabilidad – impacto por los proble-mas que plantea. Para conseguir ordenar por importancia los riesgos identificados en el proyecto, modelamos cada uno de los riesgos según funciones de probabilidad y, aplicando técnicas cuantitativas y simulación de Montecarlo, conseguimos medir el impacto real de cada una de las incertidumbres sobre los objetivos de coste y de duración del proyecto. Demostramos la validez de la metodología utilizando como ejemplo un caso de estudio

  • English

    The risk matrix is a commonly used tool to assess, visualise and analyse risks. It consists of a two-dimensional graphical representation of the probability (“likelihood” or “frequency”) of an outcome occurring and the impact (“severity” or “con-sequences”) that the outcome would have if it were to occur. Each of the two dimensions of the matrix is further divided into various levels of probability, usually located on the ordinate axis of the matrix, and diverse levels of impact, located on the abscissa axis. The result of each cell, formed by interconnecting a given probability level with the corresponding impact level, is associated with a risk level (urgency, priority, or management action).The risk matrix (or probability-impact matrix) has been widely implemented as a decision-support tool in both the public and private sectors in areas such as well-integrity risk, drilling hazard management, climatic change responses, or health and safety. Using these matrices to set priorities and guide resource allocation has been established as a recommendation within various international standards and industry guidelines. It is easy to construct and simple to apply compared to other risk assessment methodologies. Also, they provide a clear framework for the systematic review of risks, practically justify risk ranking and prioritisation, and keep stakeholders informed visually and attractively, among other reasons.Despite this, recent studies have shown that the risk matrix has shortcomings and limitations, making authors question its functionality and accuracy. Taking these limitations into account, in this article, we propose a quantitative method based on Monte Carlo simulation for prioritising the risks of a project, avoiding the use of the probability-impact matrix. To conduct the simulation, we will have the probability and impact data of the risks identified in the project and use ‘MCSimulRisk’ as a simulation tool. We will be able to quantitatively determine the impact of each risk on the cost objective and total duration of the project. The magnitude of the resulting impact will allow us to determine a quantitative prioritisation of the risks identified in the project.On the other hand, after estimating the probability and impact of the project’s risks, we have connected the qualitative risk analysis with the quantitative analysis by quantitatively prioritising the identified risks. In addition, we have managed to quantify the impact of each risk on the cost and duration objectives. We observed existing risks that significantly impact the project’s cost, even though they were initially identified for their impact on the project duration.As a result of applying the proposed method, we obtain a list of prioritised risks according to their impact on the duration objective and another list, different from the previous one, with the prioritised risks on the impact on the project’s cost. The order is different; thus, we can discriminate on which risk to act according to which is the most crucial objective in our proj-ect and the impact each risk has on the project

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