  Business processes usually do not exist as singular entities that can be
managed in isolation, but rather as families of business process variants. When
modelling such families of variants, analysts are confronted with the choice
between modelling each variant separately, or modelling multiple or all
variants in a single model. Modelling each variant separately leads to a
proliferation of models that share common parts, resulting in redundancies and
inconsistencies. Meanwhile, modelling all variants together leads to less but
more complex models, thus hindering on comprehensibility. This paper introduces
a method for modelling families of process variants that addresses this
trade-off. The key tenet of the method is to alternate between steps of
decomposition (breaking down processes into sub-processes) and deciding which
parts should be modelled together and which ones should be modelled separately.
We have applied the method to two case studies: one concerning the
consolidation of ex-isting process models, and another dealing with green-field
process discovery. In both cases, the method produced fewer models with respect
to the baseline and reduced duplicity by up to 50% without significant impact
on complexity.
