It seems totally reasonable to start with a simple model and add complexity necessary to explain the phenomenon.

Careful. It is reasonable to add complexity if the complexity is justified by increased explanatory power on a sufficiently large quantity of data. If you attempt to use a complex model to explain a small amount of data, you will end up overfitting the data. Note that this leaves us in a somewhat unpleasant situation: if there is a complex phenomenon regarding which we can obtain only small amounts of data, we may be forced to accept that the phenomenon simply cannot be understood.