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

Enterprise, Business-Process and Information Systems Modeling : 15th International Conference, BPMDS 2014, 19th International Conference, EMMSAD 2014, Held at CAiSE 2014, Thessaloniki, Greece, June 16-17, 2014, Proceedings

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Extensibility of Enterprise Modelling Languages

Die Arbeit adressiert insgesamt drei Forschungsschwerpunkte. Der erste Schwerpunkt setzt sich mit zu entwickelnden BPMN-Erweiterungen auseinander und stellt deren methodische Implikationen im Rahmen der bestehenden Sprachstandards dar. Dies umfasst zum einen ganz konkrete Spracherweiterungen wie z. B. BPMN4CP, eine BPMN-Erweiterung zur multi-perspektivischen Modellierung von klinischen Behandlungspfaden. Zum anderen betrifft dieser Teil auch modellierungsmethodische Konsequenzen, um parallel sowohl die zugrunde liegende Sprache (d. h. das BPMN-Metamodell) als auch die Methode zur Erweiterungsentwicklung zu verbessern und somit den festgestellten Unzulänglichkeiten zu begegnen. Der zweite Schwerpunkt adressiert die Untersuchung von sprachunabhängigen Fragen der Erweiterbarkeit, welche sich entweder während der Bearbeitung des ersten Teils ergeben haben oder aus dessen Ergebnissen induktiv geschlossen wurden. Der Forschungsschwerpunkt fokussiert dabei insbesondere eine Konsolidierung bestehender Terminologien, die Beschreibung generisch anwendbarer Erweiterungsmechanismen sowie die nutzerorientierte Analyse eines potentiellen Erweiterungsbedarfs. Dieser Teil bereitet somit die Entwicklung einer generischen Erweiterungsmethode grundlegend vor. Hierzu zählt auch die fundamentale Auseinandersetzung mit Unternehmensmodellierungssprachen generell, da nur eine ganzheitliche, widerspruchsfreie und integrierte Sprachdefinition Erweiterungen überhaupt ermöglichen und gelingen lassen kann. Dies betrifft beispielsweise die Spezifikation der intendierten Semantik einer Sprache

Linguistic Refactoring of Business Process Models

In the past decades, organizations had to face numerous challenges due to intensifying globalization and internationalization, shorter innovation cycles and growing IT support for business. Business process management is seen as a comprehensive approach to align business strategy, organization, controlling, and business activities to react flexibly to market changes. For this purpose, business process models are increasingly utilized to document and redesign relevant parts of the organization's business operations. Since companies tend to have a growing number of business process models stored in a process model repository, analysis techniques are required that assess the quality of these process models in an automatic fashion. While available techniques can easily check the formal content of a process model, there are only a few techniques available that analyze the natural language content of a process model. Therefore, techniques are required that address linguistic issues caused by the actual use of natural language. In order to close this gap, this doctoral thesis explicitly targets inconsistencies caused by natural language and investigates the potential of automatically detecting and resolving them under a linguistic perspective. In particular, this doctoral thesis provides the following contributions. First, it defines a classification framework that structures existing work on process model analysis and refactoring. Second, it introduces the notion of atomicity, which implements a strict consistency condition between the formal content and the textual content of a process model. Based on an explorative investigation, we reveal several reoccurring violation patterns are not compliant with the notion of atomicity. Third, this thesis proposes an automatic refactoring technique that formalizes the identified patterns to transform a non-atomic process models into an atomic one. Fourth, this thesis defines an automatic technique for detecting and refactoring synonyms and homonyms in process models, which is eventually useful to unify the terminology used in an organization. Fifth and finally, this thesis proposes a recommendation-based refactoring approach that addresses process models suffering from incompleteness and leading to several possible interpretations. The efficiency and usefulness of the proposed techniques is further evaluated by real-world process model repositories from various industries. (author's abstract