Updated: Mar 31, 2021
Its most important feature is its ability to calculate likelihood (conditional probability) of the two or more actions (e.g. what will be the likelihood of event C when event B and A has already occurred, and what will be the likelihood if only event A occurs but B fails). The technique is particularly useful on complex systems which has many causes and effects (causal relationships).
Some of the key benefits are; it’s easy to visualize the relationships, different relationships can be chained / combined to allow for more complex situations, which gives room for scaling, and more likelihoods (conditional probabilities) can be calculated.