Studies on the effects of digital transformation on enterprise architectures (EA) indicate that variability in the EA increases on different levels, such as the business and the data architecture. Dealing with variability becomes a common challenge in the daily operations of many enterprises and requires methodical and technological support. Methodical support for controlling variability in EA can help enterprises manage variability more efficiently. In this context, the conjecture motivating this paper is that building blocks integrating business and data architecture or allowing for data-aware business process building blocks can help to ensure a high level of flexibility and, at the same time, control complexity in variability management. The paper aims to contribute to a better understanding of the requirements, necessary activities and frame conditions of method support for variability management of EA. The paper’s main contribution is an initial method for identifying building blocks in enterprise architecture models that integrate several architecture layers and a way to capture such building blocks as ArchiMate models.