Sensitivity analysis is the quantitative risk assessment of how changes in a specific model variable impacts the output of the model. It is also a key result of Monte Carlo simulations of project schedules.
After performing the qualitative risk analysis, every risk entry in the risk register is assigned with a probability factor and the impact factor. Ideally one must make either the probability to zero or the impact to zero to make PxI zero. Practically this can be very expensive or next to impossible. That forces the project teams to identify the ideal values probability and impact for risks, which is accomplished through sensitivity analysis based tools like Monte Carlo analysis.
In a project schedule, all the tasks will not be affected by a risk. In other words, every risk has an impact on a set of activities within the schedule. By changing the values of probability and impact of risks, the duration of the activities which are associated with the risks changes between their optimistic, pessimistic and most likely values.
Automated software for Montecarlo analysis performs this simulation by varying the probability of the risk items, and provides the most optimal values for probabilities and the corresponding schedule duration.