Petra : Process model based extensible toolset for redesign and analysis

In different settings, it is of great value to be able to compare the performance of processes that aim to fulfill the same purpose but do so in different ways. Petra is a toolset for the analysis of so-called process families, which support the use of a multitude of analysis tools, including simulation. Through the use of Petra, organisations can make an educated decision about the exact configuration of their processes as to satisfy their exact requirements and performance objectives. The CoSeLoG project, in which we work together with 10 municipalities, provides exactly the setting for this type of functionality to come into play

VIVACE: A framework for the systematic evaluation of variability support in process-aware information systems

Context: The increasing adoption of process-aware information systems (PAISs) such as workflow management systems, enterprise resource planning systems, or case management systems, together with the high variability in business processes (e.g., sales processes may vary depending on the respective products and countries), has resulted in large industrial process model repositories. To cope with this business process variability, the proper management of process variants along the entire process lifecycle becomes crucial. Objective: The goal of this paper is to develop a fundamental understanding of business process variability. In particular, the paper will provide a framework for assessing and comparing process variability approaches and the support they provide for the different phases of the business process lifecycle (i.e., process analysis and design, configuration, enactment, diagnosis, and evolution). Method: We conducted a systematic literature review (SLR) in order to discover how process variability is supported by existing approaches. Results: The SLR resulted in 63 primary studies which were deeply analyzed. Based on this analysis, we derived the VIVACE framework. VIVACE allows assessing the expressiveness of a process modeling language regarding the explicit specification of process variability. Furthermore, the support provided by a process-aware information system to properly deal with process model variants can be assessed with VIVACE as well. Conclusions: VIVACE provides an empirically-grounded framework for process engineers that enables them to evaluate existing process variability approaches as well as to select that variability approach meeting their requirements best. Finally, it helps process engineers in implementing PAISs supporting process variability along the entire process lifecycle. (C) 2014 Elsevier B.V. All rights reserved.This work has been developed with the support of MICINN under the project EVERYWARE TIN2010-18011.Ayora Esteras, C.; Torres Bosch, MV.; Weber, B.; Reichert, M.; Pelechano Ferragud, V. (2015). VIVACE: A framework for the systematic evaluation of variability support in process-aware information systems. Information and Software Technology. 57:248-276. https://doi.org/10.1016/j.infsof.2014.05.009S2482765

VIVACE: A framework for the systematic evaluation of variability support in process-aware information systems

Context: The increasing adoption of process-aware information systems (PAISs) such as workflow management systems, enterprise resource planning systems, or case management systems, together with the high variability in business processes (e.g., sales processes may vary depending on the respective products and countries), has resulted in large industrial process model repositories. To cope with this business process variability, the proper management of process variants along the entire process lifecycle becomes crucial. Objective: The goal of this paper is to develop a fundamental understand-ing of business process variability. In particular, the paper will provide a framework for assessing and comparing process variability approaches and the support they provide for the different phases of the business process life

Alamprotsessidest, protsesside variatsioonidest ja nendevahelisest koosmõjust: Integreeritud “jaga ja valitse” meetod äriprotsesside ja nende variatsioonide modelleerimiseks

Igat organisatsiooni võib vaadelda kui süsteemi, mis rakendab äriprotsesse väärtuste loomiseks. Suurtes organisatsioonides on tavapärane esitada äriprotsesse kasutades protsessimudeleid, mida kasutatakse erinevatel eesmärkidel nagu näiteks sisekommunikatsiooniks, koolitusteks, protsesside parendamiseks ja infosüsteemide arendamiseks. Arvestades protsessimudelite multifunktsionaalset olemust tuleb protsessimudeleid koostada selliselt, et see võimaldab nendest arusaamist ning haldamist erinevate osapoolte poolt. Käesolev doktoritöö pakkudes välja integreeritud dekompositsioonist ajendatud meetodi äriprotsesside modelleerimiseks koos nende variatsioonidega. Meetodi kandvaks ideeks on järkjärguline äriprotsessi ja selle variatsioonide dekomponeerimine alamprotsessideks. Igal dekompositsiooni tasemel ning iga alamprotsessi jaoks määratletakse esmalt kas vastavat alamprotsessi tuleks modelleerida konsolideeritud moel (üks alamprotsessi mudel kõikide või osade variatsioonide jaoks) või fragmenteeritud moel (üks alamprotsess ühe variatsiooni jaoks). Sel moel kasutades ülalt-alla lähenemist viilutatakse ja tükeldatakse äriprotsess väiksemateks osadeks. Äriprotsess viilutatakse esmalt tema variatsioonideks ning seejärel tükeldatakse dekompositsioonideks kasutades kaht peamist parameetrit. Esimeseks on äri ajendid variatsioonide jaoks – igal äriprotsessi variatsioonil on oma juurpõhjus, mis pärineb ärist endast ja põhjustab protsesside käivitamisel erisusi. Need juurpõhjused jagatakse viide kategooriasse – ajendid kliendist, tootest, operatiivsetest põhjustest, turust ja ajast. Teine parameeter on erinevuste hulk viisides (tegevuste järjekord, tulemuste väärtused jms) kuidas variatsioonid oma väljundit toodavad. Käesolevas töös esitatud meetod on valideeritud kahes praktilises juhtumiuuringus. Kui esimeses juhtumiuuringus on põhirõhk olemasolevate protsessimudelite konsolideerimisel, siis teises protsessimudelite avastamisel. Sel moel rakendatakse meetodit kahes eri kontekstis kahele üksteisest eristatud juhtumile. Mõlemas juhtumiuuringus tootis meetod protsessimudelite hulgad, milles oli liiasust kuni 50% vähem võrreldes tavapäraste meetoditega jättes samas mudelite keerukuse nendega võrreldes enamvähem samale tasemele.Every organization can be conceived as a system where value is created by means of business processes. In large organizations, it is common for business processes to be represented by means of process models, which are used for a range of purposes such as internal communication, training, process improvement and information systems development. Given their multifunctional character, process models need to be captured in a way that facilitates understanding and maintenance by a variety of stakeholders. This thesis proposes an integrated decomposition-driven method for modeling business processes with variants. The core idea of the method is to incrementally construct a decomposition of a business process and its variants into subprocesses. At each level of the decomposition and for each subprocess, we determine if this subprocess should be modeled in a consolidated manner (one subprocess model for all variants or for multiple variants) or in a fragmented manner (one subprocess model per variant). In this manner, a top-down approach of slicing and dicing a business process is taken. The process model is sliced in accordance with its variants, and then diced (decomposed). This decision is taken based on two parameters. The first is the business drivers for the existence of the variants. All variants of a business process has a root cause i.e. a reason stemming from the business that causes the processes to have differences in how they are executed. The second parameter considered when deciding how to model the variants is the degree of difference in the way the variants produce their outcomes. As such, the modeling of business process variations is dependent on their degree of similarity in regards to how they produce value (such as values, execution order and so on). The method presented in this thesis is validated by two real-life case studies. The first case study concerns a case of consolidation existing process models. The other deals with green-field process discovery. As such, the method is applied in two different contexts (consolidation and discovery) on two different cases that differ from each other. In both cases, the method produced sets of process models that had reduced the duplicity rate by up to 50 % while keeping the degree of complexity of the models relatively stable

Automatiser le support de la variabilité dans les modèles de processus configurables

Today's fast changing environment imposes new challenges for effective management of business processes. In such a highly dynamic environment, the business process design becomes time-consuming, error-prone, and costly. Therefore, seeking reuse and adaptability is a pressing need for a successful business process design. Configurable reference models recently introduced were a step toward enabling a process design by reuse while providing flexibility. A configurable process model is a generic model that integrates multiple process variants of a same business process in a given domain through variation points. These variation points are referred to as configurable elements and allow for multiple design options in the process model. A configurable process model needs to be configured according to a specific requirement by selecting one design option for each configurable element.Recent research activities on configurable process models have led to the specification of configurable process modeling notations as for example configurable Event-Driven Process Chain (C-EPC) that extends the EPC notation with configurable elements. Since then, the issue of building and configuring configurable process models has been investigated. On the one hand, as configurable process models tend to be very complex with a large number of configurable elements, many automated approaches have been proposed to assist their design. However, existing approaches propose to recommend entire configurable process models which are difficult to reuse, cost much computation time and may confuse the process designer. On the other hand, the research results on configurable process model design highlight the need for means of support to configure the process. Therefore, many approaches proposed to build a configuration support system for assisting end users selecting desirable configuration choices according to their requirements. However, these systems are currently manually created by domain experts which is undoubtedly a time-consuming and error-prone task.In this thesis, we aim at automating the support of the variability in configurable process models. Our objective is twofold: (i) assisting the configurable process design in a fin-grained way using configurable process fragments that are close to the designers interest and (ii) automating the creation of configuration support systems in order to release the process analysts from the burden of manually building them. In order to achieve the first objective, we propose to learn from the experience gained through past process modeling in order to assist the process designers with configurable process fragments. The proposed fragments inspire the process designer to complete the design of the ongoing process. To achieve the second objective, we realize that previously designed and configured process models contain implicit and useful knowledge for process configuration. Therefore, we propose to benefit from the experience gained through past process modeling and configuration in order to assist process analysts building their configuration support systems. Such systems assist end users interactively configuring the process by recommending suitable configuration decisions.L'évolution rapide dans les environnements métier d'aujourd'hui impose de nouveaux défis pour la gestion efficace et rentable des processus métiers. Dans un tel environnement très dynamique, la conception des processus métiers devient une tâche fastidieuse, source d'erreurs et coûteuse. Par conséquent, l'adoption d'une approche permettant la réutilisation et l'adaptabilité devient un besoin urgent pour une conception de processus prospère. Les modèles de processus configurables récemment introduits représentent l'une des solutions recherchées permettant une conception de processus par la réutilisation, tout en offrant la flexibilité. Un modèle de processus configurable est un modèle générique qui intègre de multiples variantes de procédés d'un même processus métier à travers des points de variation. Ces points de variation sont appelés éléments configurables et permettent de multiples options de conception dans le modèle de processus. Un modèle de processus configurable doit être configuré selon une exigence spécifique en sélectionnant une option de conception pour chaque élément configurable.Les activités de recherche récentes sur les modèles de processus configurables ont conduit à la spécification des langages de modélisation de processus configurables comme par exemple configurable Event-Driven Process Chain (C-EPC) qui étend la notation de l'EPC avec des éléments configurables. Depuis lors, la question de la conception et de la configuration des modèles de processus configurables a été étudiée. D'une part, puisque les modèles de processus configurables ont tendance à être très complexe avec un grand nombre d'éléments configurables, de nombreuses approches automatisées ont été proposées afin d'assister leur conception. Cependant, les approches existantes proposent de recommander des modèles de processus configurables entiers qui sont difficiles à réutiliser, nécessitent un temps complexe de calcul et peuvent confondre le concepteur du processus. D'autre part, les résultats de la recherche sur la conception des modèles de processus configurables ont mis en évidence la nécessité des moyens de soutien pour configurer le processus. Par conséquent, de nombreuses approches ont proposé de construire un système de support de configuration pour aider les utilisateurs finaux à sélectionner les choix de configuration souhaitables en fonction de leurs exigences. Cependant, ces systèmes sont actuellement créés manuellement par des experts du domaine qui est sans aucun doute une tâche fastidieuse et source d'erreurs .Dans cette thèse, nous visons à automatiser le soutien de la variabilité dans les modèles de processus configurables. Notre objectif est double: (i) assister la conception des processus configurables d'une manière à ne pas confondre les concepteurs par des recommandations complexes et (i) assister la création des systèmes de soutien de configuration afin de libérer les analystes de processus de la charge de les construire manuellement. Pour atteindre le premier objectif, nous proposons d'apprendre de l'expérience acquise grâce à la modélisation des processus passés afin d'aider les concepteurs de processus avec des fragments de processus configurables. Les fragments proposés inspirent le concepteur du processus pour compléter la conception du processus en cours. Pour atteindre le deuxième objectif, nous nous rendons compte que les modèles de processus préalablement conçus et configurés contiennent des connaissances implicites et utiles pour la configuration de processus. Par conséquent, nous proposons de bénéficier de l'expérience acquise grâce à la modélisation et à la configuration passées des processus afin d'aider les analystes de processus dans la construction de leurs systèmes de support de configuration