### Monte Carlo Schedule Risk Analysis with Actuals

Posted:

**Sat Aug 29, 2015 9:10 am**The Monte Carlo analysis is always performed with taking in to account actuals. Here is how it works:

* If task is fully completed, risks and uncertainties are not applied to the tasks

* If task is partially completed, the risks are applied only to remaining duration. For example, if 50% of task is completed and original risk probability is 60%, effective risk probability will be 30%.

* If task has a statistical distribution for duration, it will be applied automatically to the remaining duration. For example, if task originally supposes to be completed in 10 days, but after 2 days only 10% is done, new total task duration will be 20 days. Remaining duration will be 18 days. If you defined low and high duration as 90% and 120% of original duration, the same coefficients will be applied to the remaining duration. So low remaining duration will be 18 days * 0.9 = 16.2 days and high duration will be 18 days * 1.2 = 21.6 days.

You may always define statistical distribution for remaining duration manually, as it is shown below.

* If task is fully completed, risks and uncertainties are not applied to the tasks

* If task is partially completed, the risks are applied only to remaining duration. For example, if 50% of task is completed and original risk probability is 60%, effective risk probability will be 30%.

* If task has a statistical distribution for duration, it will be applied automatically to the remaining duration. For example, if task originally supposes to be completed in 10 days, but after 2 days only 10% is done, new total task duration will be 20 days. Remaining duration will be 18 days. If you defined low and high duration as 90% and 120% of original duration, the same coefficients will be applied to the remaining duration. So low remaining duration will be 18 days * 0.9 = 16.2 days and high duration will be 18 days * 1.2 = 21.6 days.

You may always define statistical distribution for remaining duration manually, as it is shown below.