Florian Gottschalk

Preserving correctness during business process model configuration

A configurable process model captures a family of related process models in a single artifact. Such models are intended to be configured to fit the requirements of specific organizations or projects, leading to individualized process models that are subsequently used for domain analysis or solution design. This article proposes a formal foundation for individualizing configurable process models incrementally, while preserving correctness, both with respect to syntax and behavioral semantics. Specifically, assuming the configurable process model is behaviorally sound, the individualized process models are guaranteed to be sound. The theory is first developed in the context of Petri nets and then extended to a process modeling notation widely used in practice, namely Event-driven Process Chains.

Configurable Process Models: Experiences from a Municipality Case Study

Configurable process models integrate different variants of a business process into a single model. Through configuration users of such models can then combine the variants to derive a process model optimally fitting their individual needs. While techniques for such models were suggested in previous research, this paper presents a case study in which these techniques were extensively tested on a real-world scenario. We gathered information from four Dutch municipalities on registration processes executed on a daily basis. For each process we identified variations among municipalities and integrated them into a single, configurable process model, which can be executed in the YAWL workflow environment. We then evaluated the approach through interviews with organizations that support municipalities in organizing and executing their processes. The paper reports on both the feedback of the interviewed partners and our own observations during the model creation.

Beyond Control-Flow: Extending Business Process Configuration to Roles and Objects

A configurable process model is an integrated representation of multiple variants of a business process. It is designed to be individualized to meet a particular set of requirements. As such, configurable process models promote systematic reuse of proven or common practices. Existing notations for configurable process modeling focus on capturing tasks and control-flow dependencies, neglecting equally important aspects of business processes such as data flow, material flow and resource management. This paper fills this gap by proposing an integrated meta-model for configurable processes with advanced features for capturing resources involved in the performance of tasks (through task-role associations) as well as flow of data and physical artifacts (through task-object associations). Although embodied as an extension of a popular process modeling notation, namely EPC, the meta-model is defined in an abstract and formal manner to make it applicable to other notations.

Merging Event-Driven Process Chains

While business processes are typically handled differently among companies, many of them are variations of a common process like procurement or invoicing. To gain synergy effects from corporate mergers, process analysts align such processes by identifying and seamlessly integrating overlapping process parts. To support this, we present in this paper an approach that merges two business process models which are depicted as Event-driven Process Chains into a single process model which can serve as a starting point for further process optimization. The approach has been implemented in the ProM process mining framework and can thus be used together with a wide range of other process mining and analysis techniques.

Correctness-preserving configuration of business process models

Reference process models capture recurrent business operations in a given domain such as procurement or logistics. These models are intended to be configured to fit the requirements of specific organizations or projects, leading to individualized process models that are subsequently used for domain analysis or solution design. Although the advantages of reusing reference process models compared to designing process models from scratch are widely accepted, the methods employed to configure reference process models are manual and error-prone. In particular, analysts are left with the burden of ensuring the correctness of the individualized process models and to manually fix errors. This paper proposes a foundation for configuring reference process models incrementally and in a way that ensures the correctness of the individualized process models, both with respect to syntax and behavioral semantics. Specifically, assuming the reference process model is behaviorally sound, the individualized process models are guaranteed to be sound.

Configurable process models - a foundational approach

Off-the-shelf packages such as SAP need to be configured to suit the requirements of an organization. Reference models support the configuration of these systems. Existing reference models use rather traditional languages. For example, the SAP reference model uses Event-driven Process Chains (EPCs). Unfortunately, the choice construct within traditional process modeling languages like EPCs do not capture different scopes or impacts of decisions. That means they offer no opportunities to distinguish between decisions made for a single case (i. e. process instance) when executing the process and decisions made in advance for numerous cases impacting bigger parts of the company. This paper discusses the need for configurable process models. An analysis of configuration from a theoretical perspective provides a solid fundament for such models. Within the analysis a link is made to inheritance of dynamic behavior and previously defined inheritance concepts. By applying these concepts to process models the essence of configuration is determined, which enables the development of more mature configurable process modeling languages.

Protos2CPN: using colored Petri nets for configuring and testing business processes

Protos is a popular tool for business process modelling used in more than 1,500 organizations. It has a built-in Petri-net-based simulation engine which shows key performance indicators for the modelled processes. Reference process models offered for Protos reduce modelling efforts by providing generic solutions which only need to be adapted to individual requirements. However, the user can neither inspect or interact with simulations running in Protos, nor does Protos provide any explicit support for the adaptation of reference models. Hence, we aim at a more open and configurable simulation solution. To realize this we provide two transformations from Protos models to colored Petri nets (CPNs), which can be executed by CPN Tools. The first transformation enables the usage of the extensive simulation and measuring features of CPN Tools for the simulation of Protos models. The second transformation creates colored Petri nets with dedicated features for process configuration. Such configurable process models can be restricted directly within the process model without changing the model’s structure and provide therefore dedicated adaptation features for Protos’ reference process models.

Configurable process models as a basis for reference modeling

Off-the-shelf packages such as SAP need to be configured to suit the requirements of an organization. Reference models support the configuration of these systems. Existing reference models use rather traditional languages. For example, the SAP reference model uses Event-driven Process Chains (EPCs). Unfortunately, traditional languages like EPCs do not capture the configuration-aspects well. Consider for example the concept of “choice” in the control-flow perspective. Although any process modeling language, including EPCs, offers a choice construct (e.g., the XOR connector in EPCs), a single construct will not be able to capture the time dimension, scope, and impact of a decision. Some decisions are taken at run-time for a single case while other decisions are taken at build-time impacting a whole organization and all current and future cases. This position paper discusses the need for configurable process models as a basic building block for reference modeling. The focus is on the control-flow perspective.

Linking domain models and process models for reference model configuration

Reference process models capture common practices in a given domain and variations thereof. Such models are intended to be configured in a specific setting, leading to individualized process models. Although the advantages of reference process models are widely accepted, their configuration still requires a high degree of modeling expertise. Thus users not only need to be domain experts, but also need to master the notation in which the reference process model is captured. In this paper we propose a framework for reference process modeling wherein the domain variability is represented separately from the actual process model. Domain variability is captured as a questionnaire that reflects the decisions that need to be made during configuration and their interrelationships. This questionnaire allows subject matter experts to configure the process model without requiring them to understand the process modeling notation. The approach guarantees that the resulting process models are correct according to certain constraints. To demonstrate the applicability of the proposal, we have implemented a questionnaire toolset that guides users through the configuration of reference process models captured in two different notations.

Mining Reference Process Models and Their Configurations

Reference process models are templates for common processes run by many corporations. However, the individual needs among organizations on the execution of these processes usually vary. A process model can address these variations through control-flow choices. Thus, it can integrate the different process variants into one model. Through configuration parameters, a configurable reference models enables corporations to derive their individual process variant from such an integrated model. While this simplifies the adaptation process for the reference model user, the construction of a configurable model integrating several process variants is far more complex than the creation of a traditional reference model depicting a single best-practice variant. In this paper we therefore recommend the use of process mining techniques on log files of existing, well-running IT systems to help the reference model provider in creating such integrated process models. Afterwards, the same log files are used to derive suggestions for common configurations that can serve as starting points for individual configurations.