  Business Process Model and Notation (BPMN) provides a standard for the design
of business processes. It focuses on bridging the gap between the analysis and
the technical perspectives, and aims to deliver process automation. The aim of
this technical report is to complement this effort by transferring knowledge
from the related field of data-centric workflows aiming to provide automated
performance optimization of the business process execution. Automated
optimization lifts a burden from BPMN designers and increases workflow
flexibility and resilience. As a key step towards this goal, the contribution
of this work is to provide a methodology to map BPMNv2.0 models to annotated
directed acyclic graphs, which emphasize the volume of the tokens exchanged and
are amenable to existing automated optimization algorithms. In addition,
concrete examples of mappings are given, while the optimization opportunities
that are opened are explained, thus providing insights into the potential
performance benefits and we discuss technical research issues.
