Dennis M. M. Schunselaar

Creating sound and reversible configurable process models using CoSeNets

All Dutch municipalities offer the same range of services, and the processes delivering these services are quite similar. Therefore, these municipalities can benefit from configurable process models. This requires the merging of existing process variants into configurable models. Unfortunately, existing merging techniques (1) allow for configurable process models which can be instantiated to unsound process models, and (2) are not always reversible, which means that not all original models can be obtained by instantiation of the configurable process model. In this paper, we propose to capture the control-flow of a process by a CoSeNet: a configurable, tree-like representation of the process model, which is sound by construction, and we describe how to merge two CoSeNets into another CoSeNet such that the merge is reversible. Initial experiments show that this approach does not influence complexity significantly, i.e. it results in similar complexities for the configurable process model compared to existing techniques, while it guarantees soundness and reversibility.

Patterns for a log-based strengthening of declarative compliance models

LTL-based declarative process models are very effective when modelling loosely structured processes or working in environments with a lot of variability. A process model is represented by a set of constraints that must be satisfied during the process execution. An important application of such models is compliance checking: a process model defines then the boundaries in which a system/organisation may work, and the actual behaviour of the system, recorded in an event log, can be checked on its compliance to the given model. A compliance model is often a general one, e.g., applicable for a whole branch of industry, and some constraints used there may be irrelevant for a company in question: for example, a constraint related to property assessment regulations will be irrelevant for a rental agency that does not execute property assessment at all. In this paper, we take the compliance model and the information about past executions of the process instances registered in an event log and, by using a set of patterns, we check which constraints of the compliance model are irrelevant (vacuously satisfied) with respect to the event log. Our compliance patterns are inspired by vacuity detection techniques working on a single trace. However, here we take all the knowledge available in the log into consideration.

Configurable Declare: Designing Customisable Flexible Process Models

Declarative languages are becoming more popular for modelling business processes with a high degree of variability. Unlike procedural languages, where the models define what is to be done, a declarative model specifies what behaviour is not allowed, using constraints on process events. In this paper, we study how to support configurability in such a declarative setting. We take Declare as an example of a declarative process modelling language and introduce Configurable Declare. Configurability is achieved by using configuration options for event hiding and constraint omission. We illustrate our approach using a case study, based on process models of ten Dutch municipalities. A Configurable Declare model is constructed supporting the variations within these municipalities.

YAWL in the Cloud: Supporting Process Sharing and Variability

The cloud is at the centre of attention in various fields, including that of BPM. However, all BPM systems in the cloud seem to be nothing more than an installation in the cloud with a web-interface for a single organisation, while cloud technology offers an excellent platform for cooperation on an intra- and inter-organisational level. In this paper, we show how cloud technology can be used for supporting different variants of the same process (due to “couleur locale”), and how these organisations can aid each other in achieving the completion of a running case. In this paper we describe how we have brought a BPM system (YAWL) into the cloud that supports variants.

A Systematic Evaluation of Enterprise Modelling Approaches on Their Applicability to Automatically Generate ERP Software

Customising Enterprise Resource Planning (ERP) software to the enterprises needs is still a technical endeavour often involving enabling/disabling modules, modifying configuration files, etc. This is quite surprising given the large body of work on Enterprise Modelling and Model-Driven Software Engineering. Ideally, one models ones enterprise and, with a press on a button, the ERP software supporting the enterprise is generated. In this paper, we present a systematic evaluation of Enterprise Modelling approaches for their applicability to automatically generate ERP software supporting an enterprise. Inspired by the work of an ERP vendor, which, next to generating ERP software to support an enterprise, also wants to incorporate the common-sense of an enterprise in the ERP software, we also evaluate Enterprise Ontologies since current Enterprise Modelling languages lack semantics on the instance level. None of the existing approaches are tailored towards automated (ERP) software generation without the need for programming. However, the approaches possess valuable aspects which can aid in the ERP software generation process. Therefore, next to the evaluation, we present take-home points from the approaches, e.,g., reasoning capabilities to make common-sense suggestions when something is not possible.

A Cross-Organizational Process Mining Framework for Obtaining Insights from Software Products: Accurate Comparison Challenges

Software vendors offer various software products to large numbers of enterprises to support their organization, in particular Enterprise Resource Planning (ERP) software. Each of these enterprises use the same product for similar goals, albeit with different processes and configurations. Therefore, software vendors want to obtain insights into how the enterprises use the software product, what the differences are in usage between enterprises, and the reasons behind these differences. Cross-organizational process mining is a possible solution to address these needs, as it aims at comparing enterprises based on their usage. In this paper, we present a novel Cross-Organizational Process Mining Framework which takes as input, besides event log, semantics (meaning of terms in an enterprise) and organizational context (characteristics of an enterprise). The framework provides reasoning capabilities to determine what to compare and how. Besides, the framework enables one to create a catalog of metrics by deducing diagnostics from the usage. By using this catalog, the framework can monitor the (positive) effects of changes on processes. An enterprise operating in a similar context might also benefit from the same changes. To accommodate these improvement suggestions, the framework creates an improvement catalog of observed changes. Later, we provide a set of challenges which have to be met in order to obtain the inputs from current products to show the feasibility of the framework. Next to this, we provide preliminary results showing they can be met and illustrate an example application of the framework in cooperation with an ERP software vendor.

Configuring configurable process models made easier : an automated approach

Configurable process models have shown their usefulness for capturing the commonalities and variability within business processes. However, an end user will require an abstraction from the configurable process model, which is a highly technical artifact, to select a suitable configuration. Currently, the creation of such an abstraction requires considerable steps and technical knowledge. We provide an approach to construct such an abstraction automatically on the basis of an understanding of common concepts underlying process models on the one hand and automated analysis techniques on the other. Our approach also guarantees the consistency between the configuration choices of the end user. A positive yet preliminary evaluation with business users has been carried out to test the usability of our approach.

Mining hybrid business process models : A quest for better precision

In this paper, we present a technique for the discovery of hybrid process models that combine imperative and declarative constructs. In particular, we first employ the popular Inductive Miner to generate a fully imperative model from a log. Like most imperative miners, the Inductive Miner tends to return so-called flower models for the less structured parts of the process. These parts are often imprecise. To counter these imprecise parts, we replace them with declarative models to increase the precision since declarative models are good at specifying which behavior is disallowed. The approach has been implemented in ProM and tested on several synthetic and real-life event logs. Our experiments show that hybrid models can be found to be more precise without overfitting the data.

NEXT: Generating Tailored ERP Applications from Ontological Enterprise Models

Tailoring Enterprise Resource Planning (ERP) software to the needs of the enterprise still is a technical endeavor, often requiring the (de)activation of modules, modification of configuration files or even execution of database queries. Considering the large body of work on Enterprise Modeling and Model-Driven Software Engineering, this is remarkable: Ideally, one models one’s own enterprise and, at the press of a button, ERP software tailored to the needs of the modeled enterprise is generated. In this paper, we introduce NEXT, a novel model-driven software generation approach being developed with precisely this goal in mind. It uses the expressive power of ontological enterprise models (OEMs) to generate ERP cloud applications. An OEM only describes the real-world phenomena essential to the enterprise, using terms and customizations specific to the enterprise. We present our considerations during development of the OEM modeling language, which is designed to capture the specifics of enterprise phenomena in a way that technical details can be derived from it. We expect NEXT to drastically shorten the time-to-market of ERP software, from months–years to hours–days.

Selecting a process variant modeling approach: guidelines and application

Various modeling approaches have been introduced to manage process diversity in a business context. For practitioners, it is difficult to select an approach suitable for the needs and limitations of their organization due to the limited number of examples and guidelines. In this paper, we report on an action research study to perform a comparative process variant modeling application in a process management consultancy company. This company experienced difficulties in maintaining and reusing process definitions of their customers. We describe how the requirements were determined and led to the selection of two specific approaches, the Decomposition Driven Method and the Provop approach. We comparatively evaluated the suitability of these approaches to develop variant models for six software project management processes of five customers. This study contributes to the field by presenting an industrial case for process variant modeling, reporting in-depth, real-life applications of two approaches, applying the approaches for hierarchical processes, and presenting guidelines for choosing an approach under comparable conditions.