Abstract
The calculation and analysis of process performance indicators (PPIs) and, in particular, the customized performance measures defined to measure a specific process domain, provide insight into whether a business process’s results align with the strategic objectives within an organization. These measures and PPIs can be calculated using process execution data. This data is traditionally structured in such a way that for each process instance (case), there is a case notion (object), for example, the order in a purchasing process. Recently, the object-centric approach introduced the multiple case notion, i.e., the idea that several objects can be associated in the execution of tasks of one or several process instances, which better reflects what happens in reality. However, this approach generates more complex event logs that include data involving interacting instances and complex data dependencies. These changes impact the types of PPIs that can be defined and should therefore be analyzed in detail from a different perspective than the traditional one. In this paper, we focus on the PPI modeling area. In particular, we aim at extending the classical definition of PPIs for an object-centric context. For this purpose, we analyze how different customized performance measures are defined in the traditional context and identify a set of requirements to define those measures in an object-centric context. In addition, we propose to extend the established PPINOT metamodel, focused on the definition of PPIs, to integrate the identified requirements, thus laying the groundwork for the automatic calculation of such PPIs.
This work has been funded by grants RTI2018-101204-B-C22 funded by MCIN/ AEI/ 10.13039/501100011033/ and ERDF A way of making Europe; grant P18-FR-2895 funded by Junta de Andalucía/FEDER, UE; and grant US-1381595 (US/JUNTA/FEDER, UE).
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Estrada-Torres, B., del-Río-Ortega, A., Resinas, M. (2023). Defining Process Performance Measures in an Object-Centric Context. In: Cabanillas, C., Garmann-Johnsen, N.F., Koschmider, A. (eds) Business Process Management Workshops. BPM 2022. Lecture Notes in Business Information Processing, vol 460. Springer, Cham. https://doi.org/10.1007/978-3-031-25383-6_16
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