Morphological analysis can help with discussing permutations and interactions of drivers of change in scenario building, as well as deepen and broaden scenario narratives. Related to field anomaly relaxation.

Essentially, GMA is a method for identifying and investigating the total set of possible relationships or “configurations” contained in a given problem complex. This is accomplished by going through a number of iterative phases which represent cycles of analysis and synthesis—the basic method for developing (scientific) models

From http://www.swemorph.com/pdf/wfr-ritchey.pdf

GMA in detail: http://www.swemorph.com/ma.html

Consider a complex, real-world problem, like those of marketing or making policies for a nation, where there are many governing factors, and most of them cannot be expressed as numerical time series data, as one would like to have for building mathematical models.

The conventional approach here would be to break the system down into parts, isolate the vital parts (dropping the 'trivial' components) for their contributions to the output and solve the simplified system for creating desired models or scenarios. The disadvantage of this method is that real-world scenarios do not behave rationally: more often than not, a simplified model will break down when the contribution of the 'trivial' components becomes significant. Also, importantly, the behaviour of many components will be governed by the states of, and their relations with, other components – ones that may be seen to be minor before the analysis.

Morphological Analysis, on the other hand, does not drop any of the components from the system itself, but works backwards from the output towards the system internals.

From https://en.wikipedia.org/wiki/Morphological_analysis_%28problem-solving%29