When dealing with workflows, either at design-time or run-time, it is very likely to have to take resources into account at some points. Many kinds of requirements on workflows can involve resources : they can constraints the execution of specific tasks, require global optimization, allow some flexibility or not, etc. However, resource is seldom expressed as "first class citizen" in many workflow definition languages. Hence it is difficult to design rich reasoning abilities on top of them and consequently this does not ease the development of powerful resource-aware decision support.
In this paper, we propose an enhanced workflow metamodel capturing the resource dimension within both design-time and run-time dimensions. Based on this metamodel, we illustrate some interesting usage scenarios coping with design-time aspects (e.g. potential bottlenecks) and, most importantly, run-time aspects (e.g. strategies from intelligent recovery, degraded mode). The model was elicited and validated from an industrial case study which is illustrated in a simplified way.