Description
The Monte Carlo simulation is one of the stochastic simulation methods in which random numbers are used within certain ranges for the calculation of the scenarios. To estimate risks or decisions under uncertainty, stochastic and dynamic methods are almost exclusively used today. With the help of Monte Carlo simulation, the impact of different decisions and their probability of occurrence can be estimated using synthetic data. It is a calculation method to simulate extreme cases, but also to secure everyday decisions. This makes it usable for a wide variety of industries.
Effort
Medium
Complexity
Medium
Method Type
Quantitative
ISO 31000
Risk Analysis - Likelihood
Risk Analysis - Severity
Prerequisites
- Monte Carlo simulation program
- Probability function
Basic Approach
- Determine indeterminacy factors (number and ranges)
- Set the number of calculations
- Calculate of the probability function with random values
- Present the result distribution
- recommended software (@risk)
Advantages
• Considered probabilities
• Good graphic representability
• High level of flexibility
Disadvantages
• Dependencies must be recognized by the user and modeled accordingly
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