Process improvement is the most value-adding activity in the business process management (BPM) lifecycle. Despite mature knowledge, many approaches have been criticized to lack guidance on how to put process improvement into practice. Given the variety of emerging digital technologies, organizations not only face a process improvement black box, but also high uncertainty regarding digital technologies. This paper thus proposes a method that supports organizations in exploiting the digitalization potential of their business processes. To achieve this, action design research and situational method engineering were adopted. Two design cycles involving practitioners (i.e., managers and BPM experts) and end-users (i.e., process owners and participants) were conducted. In the first cycle, the method’s alpha version was evaluated by interviewing practitioners from five organizations. In the second cycle, the beta version was evaluated via real-world case studies. In this paper, detailed results of one case study, which was conducted at a semiconductor manufacturer, are included.

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How to Exploit the Digitalization Potential of Business Processes

The design and development of process-aware information systems is often supported by specifying requirements as business process models. Although this approach is generally accepted as an effective strategy, it remains a fundamental challenge to adequately validate these models given the diverging skill set of domain experts and system analysts. As domain experts often do not feel confident in judging the correctness and completeness of process models that system analysts create, the validation often has to regress to a discourse using natural language. In order to support such a discourse appropriately, so-called verbalization techniques have been defined for different types of conceptual models. However, there is currently no sophisticated technique available that is capable of generating natural-looking text from process models. In this paper, we address this research gap and propose a technique for generating natural language texts from business process models. A comparison with manually created process descriptions demonstrates that the generated texts are superior in terms of completeness, structure, and linguistic complexity. An evaluation with users further demonstrates that the texts are very understandable and effectively allow the reader to infer the process model semantics. Hence, the generated texts represent a useful input for process model validation.

Supporting Process Model Validation through Natural Language Generation.

Process discovery is one of the main branches of process mining that allows the user to build a process model representing the process behavior as recorded in the logs. Standard process discovery techniques produce as output a procedural process model (e.g., a Petri net). Recently, several approaches have been developed to derive declarative process models from logs and have been proven to be more suitable to analyze processes working in environments that are less stable and predictable. However, a large part of these techniques are focused on the analysis of the control flow perspective of a business process. Therefore, one of the challenges still open in this field is the development of techniques for the analysis of business processes also from other perspectives, like data, time, and resources. In this paper, we present a full-fledged approach for the discovery of multi-perspective declarative process models from event logs that allows the user to discover declarative models taking into consideration all the information an event log can provide. The approach has been implemented and experimented in real-life case studies.

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Discovery of Multi-perspective Declarative Process Models

Process mining aims at discovering processes by extracting knowledge from event logs. Such knowledge may refer to different business process perspectives. The organisational perspective deals, among other things, with the assignment of human resources to process activities. Information about the resources that are involved in process activities can be mined from event logs in order to discover resource assignment conditions, which is valuable for process analysis and redesign. Prior process mining approaches in this context present one of the following issues: (i) they are limited to discovering a restricted set of resource assignment conditions; (ii) they do not aim at providing efficient solutions; or (iii) the discovered process models are difficult to read due to the number of assignment conditions included.In this paper we address these problems and develop an efficient and effective process mining framework that provides extensive support for the discovery of patterns related to resource assignment. The framework is validated in terms of performance and applicability. A process mining approach for the organisational perspective is proposed.It supports the discovery of resource assignment patterns and how involvement of resources influences the control-flow.The framework consists of an event log pre-processing phase to increase efficiency.A model post-processing phase improves effectiveness by removing redundant rules.

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A framework for efficiently mining the organisational perspective of business processes

Flexible business processes can often be modelled more easily using a declarative rather than a procedural modelling approach. Process mining aims at automating the discovery of business process models. Existing declarative process mining approaches either suffer from performance issues with real-life event logs or limit their expressiveness to a specific set of constaint types. Lately, RelationalXES, a relational database architecture for storing event log data, has been introduced. In this paper, we introduce a mining approach that directly works on relational event data by querying the log with conventional SQL. By leveraging database performance technology, the mining procedure is fast without limiting itself to detecting certain control-flow constraints. Queries can be customised and cover process perspectives beyond control flow, e.g., organisational aspects. We evaluated the performance and the capabilities of our approach with regard to several real-life event logs.

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Efficient and Customisable Declarative Process Mining with SQL

The spectrum of an organization's business processes ranges from routine processes with a well-defined flow to agile processes with a degree of uncertainty. The Process Navigation platform aims at supporting both types of processes as well as combinations of them. It offers execution support for traditional flow-oriented notations like BPMN as they are well-suited for the routine type of processes. Rule-based notations for agile processes like CMMN are on the way of getting established but still have a number of weaknesses. As a consequence, the platform's agile part does not target one single notation but relies on a rule-based cross-perspective and modal intermediate language. CMMN models are then translated to the intermediate language for execution. The contribution of this paper is built up in three parts: first of all, the overall architecture of the execution platform is explained. In a second step, the intermediate language is evaluated on the basis of a comprehensive and acknowledged framework of business process requirements. And finally, the translation of CMMN to the intermediate language is described by means of an example.

Common Platform for the Support of Routine and Agile Business Processes

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Towards a common platform for the support of routine and agile business processes

Recent work shows an increasing interest of the Business Process Management (BPM) community in unstructured, so-called "human-centric" processes. Case Management (CM) is a new trend that focuses on the support of collaborative human-centric processes. Although CM provides concepts that support human-centric work, processes have to be modelled beforehand in order to be supported by IT systems. Hence, a problem that arises when applying CM is that when organisations begin to formalize CM practice, it is often difficult to express rules controlling the applicability of tasks. Furthermore, fundamental complexity challenges arise when applying CM in practice. In this contribution, we provide a solution to these two issues. We propose that managing human-centric processes should start with model skeletons that serve as a lattice where initial process execution can lean against. Additionally, by tracking different process cases, substantial process knowledge is recorded. Exploring process history might reveal certain recurring patterns that serve as dynamic guidance enhancement for CM systems. In this way, process models might evolve over time, become more and more complete and better reflect operational reality.

Supporting collaborative work by learning process models and patterns from cases

The Declarative Process Intermediate Language (DPIL) is a declarative process modelling language that allows for specifying multiperspective and multi-modal agile, i.e., flexible, processes. The expressiveness of DPIL and its suitability for business process modelling have been evaluated with respect to the well-known Workflow Patterns. The DPIL Framework provides a tool set for supporting agile and resourceaware business processes based on the language DPIL. While the DPIL Modeller component is used to create and verify models, the DPIL Navigator depicts a rule-based execution engine for enacting models. It comprises a web-based worklist which allows process participants to choose and perform tasks. In addition to this, the DPIL Miner component allows for the discovery of DPIL models from event logs. 1 Background and Significance to BPM Two different representational paradigms for business processes can be distinguished: procedural models describe which activities can be executed next and declarative, i.e., rule-based models define execution constraints that the process has to satisfy [1]. In flexible processes the exact flow of activities cannot be fully determined at design time. These processes heavily depend on human participants, their decisions and expert knowledge. These information cannot be identified and formalized in a whole. As a result, these processes require highly flexible IT support. Flexible processes are common in healthcare where, e.g., patient diagnosis and treatment processes require flexibility to cope with unanticipated circumstances. In brief, a more flexible business process and IT support means a greater number of alternative paths. Within a rule-based model initially all paths are considered viable. The more constraints are added to the model the less paths remain. As result, to make a rule-based model more flexible constraints have to be removed or weakened. Moreover, a rule-based model focuses on crosscutting relations instead of the flow of activities. Hence, a rule-based approach is well-suited for modelling flexible processes [1, 2]. As mentioned above, declarative modelling provides means for increasing the number of alternative ? Copyright c ©2015 for this paper by its authors. Copying permitted for private and academic purposes.

The DPIL Framework: Tool Support for Agile and Resource-Aware Business Processes.

Drawing tools are typically used in an early phase of software development when outlining and communicating ideas is more important than representing problems and solutions formally. But in contrast to that during later development phases formal models are needed for different purposes like simulation or code generation. Within this contribution, we present our modeling environment OMME that is based on methods and paradigms known from meta modeling. With OMME models of different stages of the development process may be linked to each other and constraints are used to ensure the integrity of these links.

Michael Zeising

Papers

Common Platform for the Support of Routine and Agile Business Processes

Towards a common platform for the support of routine and agile business processes

Supporting collaborative work by learning process models and patterns from cases

The DPIL Framework: Tool Support for Agile and Resource-Aware Business Processes.

The Open Meta Modeling Environment