Beyond probability-impact matrices in project risk management: A quantitative methodology for risk prioritisation
Fernando Acebes, Jos\'e Manuel Gonz\'alez-Varona, Adolfo, L\'opez-Paredes, Javier Pajares

TL;DR
This paper introduces a novel quantitative methodology using Monte Carlo Simulation to prioritize project risks by assessing their impact on project duration and cost, overcoming limitations of traditional risk matrices.
Contribution
It proposes a Monte Carlo Simulation-based approach for risk prioritization that separately evaluates risks' impacts on project duration and cost, enhancing decision-making.
Findings
Quantitative assessment of risk impacts on project duration and cost.
Differentiation of critical risks based on impact on specific objectives.
Improved risk prioritization method for project management.
Abstract
The project managers who deal with risk management are often faced with the difficult task of determining the relative importance of the various sources of risk that affect the project. This prioritisation is crucial to direct management efforts to ensure higher project profitability. Risk matrices are widely recognised tools by academics and practitioners in various sectors to assess and rank risks according to their likelihood of occurrence and impact on project objectives. However, the existing literature highlights several limitations to use the risk matrix. In response to the weaknesses of its use, this paper proposes a novel approach for prioritising project risks. Monte Carlo Simulation (MCS) is used to perform a quantitative prioritisation of risks with the simulation software MCSimulRisk. Together with the definition of project activities, the simulation includes the identified…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
