Whilst it is a City in Monaco, it is actually (from a statistical standpoint) a collection of analysis methods that rely on random sampling to determine the end results of scenarios where uncertainty exists.

Recently we were asked to host several risk workshops to identify the requirements for a simulation:

1. Risk ID, Title and Description
2. Probability (assumption by team) of occurance
3. Basis of Probability – why did you choose that value?
4. Low, Medium and High Costs (if the risk occurs)
5. Basis of Estimate

Whilst there are many more components to risk management, the above 4 are the most simplistic requirements needed for a proper analysis. The reason is because:

Point (2) Above:
You need to, as a project team, understand what the probability is of the risk occuring. The monte carlo simulation will derive thousands of random percentage probabilities based on a probability distribution model so whatever value entered here is merely subjective.

Some simluations can use the subjective value to weight the random number, which tends to skew the distribution towards the subjectivity of your input, however most tools simply discard the risk if it’s probability is less than the random number found.

Point (3) Above:
You need to enter in the cost of the risk if it did occur. This does not mean setting a value to zero if you think the risk will not occur as this is not the point of it! You need to ask yourself:

“If this risk does occur, what will it cost us as a minimum, maximum and most likely?”

Essentially you need to ask yourself what the expect dollar impact will be if your risk does occur.

Once you have run your simulation you have the chance to select a Probability factor (P50, P80) that will be used overall to determine your final contingency. For example, P80 assumes that you need to reserve 80% of your simulated risk, which therefore assumes you have a higher level of uncertainty!