We looked at the options, and choose Analytica largely because of a paucity of other good options, and my familiarity with it. Having spoken with them in the past, and then specifically for this project, I also think that the fact that the company which makes it is happy to be supportive of our work is a big potential advantage. Why Not Large BNs? 1. BNs are expensive to elicit. (You need output∗∏inputi values elicited per node, where inputi and output are the number of discrete levels of each.) They also have relatively little flexibility due to needing those discrete buckets. There are clever ways around this, but they are complicated, and outside the specific expertise of our group.  2. BNs assume that every node is a single value, which may or may not make sense. Most software for BNs don't have great ways to do visual communication of clusters, and AFAIK, none have a way to leave parts undefined until later. You also need to strongly assert conditional independence, and if that assumption is broken, you need to redo large parts of the network. 3. The way we actually did this shares most of the advantages in terms of decomposition and splitting subproblems, though removing duplication /overlap is still tricky.