-
Notifications
You must be signed in to change notification settings - Fork 5
General Characteristics of fCM
In general, fCM should be used when the process is semi-structured. That means, the process should consist of multiple structured parts, i.e., sequences of activities and events that are always executed together, that can be combined in different ways to create a multitude of possible execution paths to achieve the process goal.
References: [Hewelt and Weske, 2016], [Di Ciccio et al, 2015]
Decisions and process progression are highly dependent on data/knowledge obtained during execution. Based on this information, the decision space is defined at each point in time, reducing the number of different options available regarding the continuation of the process. Knowledge in general evolves during process execution, i.e., enriching data objects with discovered knowledge.
References: [Haarmann, 2020], [Hewelt and Weske, 2016]
The process execution is highly dependent on the (tacit) knowledge of a domain expert. This expert drives the process execution and decides, based on the data available combined with his/her domain expertise, on the next activities when different options are available. This is different from other approaches where a system decides on the execution path.
References: [Hewelt and Weske, 2016]
The execution of an fCM process means, above all, that the case object is continuously updated and resolved until a (pre-defined) process goal is reached, i.e., the situation of the case is resolved. Thus, it is not about working through a predefined list of activities, but rather about selecting specific activities/fragments to resolve the case object based on the evolution of the data during the process. Therefore, the designer should be able to capture the process goal with a set of data objects in certain states (cf. goal state).
References: [Haarmann, 2020], [Haarmann, 2021]
[Di Ciccio et al, 2015] Di Ciccio, C., Marrella, A., & Russo, A. (2015). Knowledge-intensive processes: characteristics, requirements and analysis of contemporary approaches. Journal on Data Semantics, 4(1), 29-57.
[Hewelt and Weske, 2016] Hewelt, M., & Weske, M. (2016, September). A hybrid approach for flexible case modeling and execution. In International Conference on Business Process Management (pp. 38-54). Springer, Cham.
[Haarmann, 2020] Haarmann, S. (2020). Fragment-Based Case Management Models: Metamodel, Consistency, and Correctness. Central-European Workshop on Services and their Composition (ZEUS 2020), 1, 1.
[Haarmann, 2021] Haarmann, S. (2021). WICKR A Joint Semantics for Flexible Business Processes and Data.