15 research outputs found
Towards the Detection of Promising Processes by Analysing the Relational Data
Business process discovery provides mechanisms to extract
the general process behaviour from event observations. However, not
always the logs are available and must be extracted from repositories,
such as relational databases. Derived from the references that exist
between the relational tables, several are the possible combinations of
traces of events that can be extracted from a relational database. Dif ferent traces can be extracted depending on which attribute represents
the caseâid, what are the attributes that represent the execution of an
activity, or how to obtain the timestamp to define the order of the events.
This paper proposes a method to analyse a wide range of possible traces
that could be extracted from a relational database, based on measuring
the level of interest of extracting a trace log, later used for a discov ery process. The analysis is done by means of a set of proposed metrics
before the traces are generated and the process is discovered. This anal ysis helps to reduce the computational cost of process discovery. For a
possible caseâid every possible traces are analysed and measured. To
validate our proposal, we have used a real relational database, where the
detection of processes (most and least promising) are compared to rely
on our proposal.Ministerio de Ciencia y TecnologĂa RTI2018-094283-B-C3
Requirements Catalog for Business Process Modeling Recommender Systems
The manual construction of business process models is a time-consuming and error-prone task. To improve the quality of business process models, several modeling support techniques have been suggested spanning from strict auto-completion of a business process model with pre-defined model elements to suggesting closely matching recommendations. While recommendation systems are widely used and auto-completion functions are a standard feature of programming tools, such techniques have not been exploited for business process modeling although implementation strategies have already been suggested. Therefore, this paper collects requirements from different perspectives (literature and empirical studies) of how to effectively and efficiently assist process modelers in their modeling task. The condensation of requirements represents a comprehensive catalog, which constitutes a solid foundation to implement effective and efficient Process Modeling Recommender Systems (PMRSs). We expect that our contribution will fertilize the field of modeling support techniques to make them a common feature of BPM tools
IngĂ©nierie et Architecture dâEntreprise et des SystĂšmes dâInformation - Concepts, Fondements et MĂ©thodes
L'ingĂ©nierie des systĂšmes d'information s'est longtemps cantonnĂ©e Ă la modĂ©lisation du produit (objet) qu'est le systĂšme dâinformation sans se prĂ©occuper des processus d'usage de ce systĂšme. Dans un environnement de plus en plus Ă©volutif, la modĂ©lisation du fonctionnement du systĂšme dâinformation au sein de l'entreprise me semble primordiale. Pendant les deux derniĂšres dĂ©cennies, les pratiques de management, dâingĂ©nierie et dâopĂ©ration ont subi des mutations profondes et multiformes. Nous devons tenir compte de ces mutations dans les recherches en ingĂ©nierie des systĂšmes dâinformation afin de produire des formalismes et des dĂ©marches mĂ©thodologiques qui sauront anticiper et satisfaire les nouveaux besoins, regroupĂ©s dans ce document sous quatre thĂšmes:1) Le systĂšme dâinformation est le lieu mĂȘme oĂč sâĂ©labore la coordination des actes et des informations sans laquelle une entreprise (et toute organisation), dans la diversitĂ© des mĂ©tiers et des compĂ©tences quâelle met en Ćuvre, ne peut exister que dans la mĂ©diocritĂ©. La comprĂ©hension des exigences de coopĂ©ration dans toutes ses dimensions (communication, coordination, collaboration) et le support que lâinformatique peut et doit y apporter deviennent donc un sujet digne dâintĂ©rĂȘt pour les recherches en systĂšme dâinformation.2) Le paradigme de management des processus dâentreprise (BPM) est en forte opposition avec le dĂ©veloppement traditionnel des systĂšmes dâinformation qui, pendant plusieurs dĂ©cennies, a cristallisĂ© la division verticale des activitĂ©s des organisations et favorisĂ© ainsi la construction dâĂźlots dâinformation et dâapplications. Cependant, les approches traditionnelles de modĂ©lisation de processus ne sont pas Ă la hauteur des besoins dâingĂ©nierie des processus dans ce contexte en constant changement, que ce dernier soit de nature contextuelle ou permanente. Nous avons donc besoin de formalismes (i) qui permettent non seulement de reprĂ©senter les processus dâentreprise et leurs liens avec les composants logiciels du systĂšme existant ou Ă venir mais (ii) qui ont aussi lâaptitude Ă reprĂ©senter la nature variable et/ou Ă©volutive (donc parfois Ă©minemment dĂ©cisionnelle) de ces processus.3) Les systĂšmes dâinformation continuent aujourdâhui de supporter les besoins classiques tels que lâautomatisation et la coordination de la chaĂźne de production, lâamĂ©lioration de la qualitĂ© des produits et/ou services offerts. Cependant un nouveau rĂŽle leur est attribuĂ©. Il sâagit du potentiel offert par les systĂšmes dâinformation pour adopter un rĂŽle de support au service de la stratĂ©gie de lâentreprise. Les technologies de lâinformation, de la communication et de la connaissance se sont ainsi positionnĂ©es comme une ressource stratĂ©gique, support de la transformation organisationnelle voire comme levier du changement. Les modĂšles dâentreprise peuvent reprĂ©senter lâĂ©tat actuel de lâorganisation afin de comprendre, de disposer dâune reprĂ©sentation partagĂ©e, de mesurer les performances, et Ă©ventuellement dâidentifier les dysfonctionnements. Ils permettent aussi de reprĂ©senter un Ă©tat futur souhaitĂ© afin de dĂ©finir une cible vers laquelle avancer par la mise en Ćuvre des projets. Lâentreprise Ă©tant en mouvement perpĂ©tuel, son Ă©volution fait partie de ses multiples dimensions. Nous avons donc besoin de reprĂ©senter, a minima, un Ă©tat futur et le chemin de transformation Ă construire pour avancer vers cette cible. Cependant planifier/imaginer/se projeter vers une cible unique et, en supposant que lâon y arrive, croire quâil puisse exister un seul chemin pour lâatteindre semble irrĂ©aliste. Nous devons donc proposer des formalismes qui permettront de spĂ©cifier des scenarii Ă la fois pour des cibles Ă atteindre et pour des chemins Ă parcourir. Nous devons aussi dĂ©velopper des dĂ©marches mĂ©thodologiques pour guider de maniĂšre systĂ©matique la construction de ces modĂšles dâentreprise et la rationalitĂ© sous-jacente.4) En moins de cinquante ans, le propos du systĂšme dâinformation a Ă©voluĂ© et sâest complexifiĂ©. Aujourdâhui, le systĂšme dâinformation doit supporter non seulement les fonctions de support de maniĂšre isolĂ©e et en silos (1970-1990), et les activitĂ©s appartenant Ă la chaĂźne de valeur [Porter, 1985] de lâentreprise (1980-2000) mais aussi les activitĂ©s de contrĂŽle, de pilotage, de planification stratĂ©gique ainsi que la cohĂ©rence et lâharmonie de lâensemble des processus liĂ©s aux activitĂ©s mĂ©tier (2000-201x), en un mot les activitĂ©s de management stratĂ©gique et de gouvernance dâentreprise. La gouvernance d'entreprise est l'ensemble des processus, rĂ©glementations, lois et institutions influant la maniĂšre dont l'entreprise est dirigĂ©e, administrĂ©e et contrĂŽlĂ©e. Ces processus qui produisent des âdĂ©cisionsâ en guise de âproduitâ ont autant besoin dâĂȘtre instrumentalisĂ©s par les systĂšmes dâinformation que les processus de nature plus opĂ©rationnels de lâentreprise. De mĂȘme, ces processus stratĂ©giques (dits aussi âde dĂ©veloppementâ) nĂ©cessitent dâavoir recours Ă des formalismes de reprĂ©sentation qui sont trĂšs loin, en pouvoir dâexpression, des notations largement adoptĂ©es ces derniĂšres annĂ©es pour la reprĂ©sentation des processus dâentreprise.Ainsi, il semble peu judicieux de vouloir (ou penser pouvoir) isoler, pendant sa construction, lâobjet âsystĂšme dâinformationâ de son environnement dâexĂ©cution. Si le sens donnĂ© Ă lâinformation dĂ©pend de la personne qui la reçoit, ce sens ne peut ĂȘtre entiĂšrement capturĂ© dans le systĂšme technique. Il sera plutĂŽt apprĂ©hendĂ© comme une composante essentielle dâun systĂšme socio-technique incluant les usagers du systĂšme dâinformation technologisĂ©, autrement dit, les acteurs agissant de lâentreprise. De mon point de vue, ce systĂšme socio-technique qui mĂ©rite lâintĂ©rĂȘt scientifique de notre discipline est lâentreprise. Les recherches que jâai rĂ©alisĂ©es, animĂ©es ou supervisĂ©es , et qui sont structurĂ©es en quatre thĂšmes dans ce document, visent Ă rĂ©soudre les problĂšmes liĂ©s aux contextes de l'usage (l'entreprise et son environnement) des systĂšmes dâinformation. Le point discriminant de ma recherche est l'intĂ©rĂȘt que je porte Ă la capacitĂ© de reprĂ©sentation :(i) de l'Ă©volutivitĂ© et de la flexibilitĂ© des processus d'entreprise en particulier de ceux supportĂ©s par un systĂšme logiciel, dâun point de vue microscopique (modĂšle dâun processus) et macroscopique (reprĂ©sentation et configuration dâun rĂ©seau de processus) : thĂšme 2(ii) du systĂšme dâentreprise dans toutes ses dimensions (stratĂ©gie, organisation des processus, systĂšme dâinformation et changement) : thĂšme 3Pour composer avec ces motivations, il fallait :(iii) sâintĂ©resser Ă la nature mĂȘme du travail coopĂ©ratif et Ă lâintentionnalitĂ© des acteurs agissant afin dâidentifier et/ou proposer des formalismes appropriĂ©s pour les dĂ©crire et les comprendre : thĂšme 1(iv) se questionner aussi sur les processus de management dont le rĂŽle est de surveiller, mesurer, piloter lâentreprise afin de leur apporter le soutien quâils mĂ©ritent du systĂšme dâinformation : thĂšme
ON THE THEORETICAL FOUNDATIONS OF RESEARCH INTO THE UNDERSTANDABILITY OF BUSINESS PROCESS MODELS
Against the background of the growing significance of Business Process Management (BPM) for Information Systems (IS) research and practice, especially the field of Business Process Modeling gains more and more importance. Business process models support communication about as well as the coordination of processes and have become a widely adopted tool in practice. As the understandability of business process models plays a crucial role in communication processes, more and more studies on process model understandability have been conducted in IS research. This article aims at investigating underlying theories of research into business process model understandability by means of an in-depth analysis of 126 systematically retrieved research articles on the topic. It shows in how far process model understandability research is multi-theoretically founded. Identified theories differ regarding addressed subject matters, their coverage, their focus as well as the underlying notion of model understanding, which is exemplarily demonstrated and discussed in this article. Moreover, implications of the findings are discussed and an outlook on future business process model understandability research and on the integration potential of theories in this field is given
Verifying goal-oriented specifications used in model-driven development processes
[EN] Goal-oriented requirements engineering promotes the use of goals to elicit, elaborate, structure, specify, analyze, negotiate, document, and modify requirements. Thus, goal-oriented specifications are essential for capturing the objectives that the system to be developed should achieve. However, the application of goal oriented specifications into model-driven development (MDD) processes is still handcrafted, not aligned in the automated flow from models to code. In other words, the experience of analysts and designers is necessary to manually transform the input goal-oriented models into system models for code generation (models compilation). Some authors have proposed guidelines to facilitate and partially automate this translation, but there is a lack of techniques to assess the adequacy of goal-oriented models as starting point of MDD processes. In this paper, we present and evaluate a verification approach that guarantees the automatic, correct, and complete transformation of goal-oriented models into design models used by specific MDD solutions. In particular, this approach has been put into practice by adopting a well-known goal-oriented modeling approach, the i* framework, and an industrial MDD solution called Integranova.This work has been developed with the support of FONDECYT under the projects AMoDDI 11130583 and TESTMODE 11121395.This work is also supported by EOSSAC project, funded by the Ministry of Economy and Competitiveness of the Spanish government (TIN2013-44641-P).Giachetti Herrera, GA.; MarĂn, B.; LĂłpez, L.; Franch, X.; Pastor LĂłpez, O. (2017). Verifying goal-oriented specifications used in model-driven development processes. Information Systems. 64:41-62. https://doi.org/10.1016/j.is.2016.06.011S41626
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
Investigating the process of process modeling and its relation to modeling quality : the role of structured serialization
Lately, the focus of organizations is changing fundamentally. Where they used to spend almost exclusively attention to results, in terms of goods, services, revenue and costs, they are now concerned about the efficiency of their business processes. Each step of the business processes needs to be known, controlled and optimized. This explains the huge effort that many organizations currently put into the mapping of their processes in so-called (business) process models.
Unfortunately, sometimes these models do not (completely) reflect the business reality or the reader of the model does not interpret the represented information as intended. Hence, whereas on the one hand we observe how organizations are attaching increasing importance to these models, on the other hand we notice how the quality of process models in companies often proves to be insufficient.
The doctoral research makes a significant contribution in this context. This work investigates in detail how people create process models and why and when this goes wrong. A better understanding of current process modeling practice will form the basis for the development of concrete guidelines that result in the construction of better process models in the future.
The first study investigated how we can represent the approach of different modelers in a cognitive effective way, in order to facilitate knowledge building. For this purpose the PPMChart was developed. It represents the different operations of a modeler in a modeling tool in such a way that patterns in their way of working can be detected easily. Through the collection of 704 unique modeling executions (a joint contribution of several authors in the research domain), and through the development of a concrete implementation of the visualization, it became possible to gather a great amount of insights about how different people work in different situations while modeling a concrete process.
The second study explored, based on the discovered modeling patterns of the first study, the potential relations between how process models were being constructed and which quality was delivered. To be precise, three modeling patterns from the previous study were investigated further in their relation with the understandability of the produced process model. By comparing the PPMCharts that show these patterns with corresponding process models, a connection was found in each case. It was noticed that when a process model was constructed in consecutive blocks (i.e., in a structured way), a better understandable process model was produced. A second relation stated that modelers who (frequently) moved (many) model elements during modeling usually created a less understandable model. The third connection was found between the amount of time spent at constructing the model and a declining understandability of the resulting model. These relations were established graphically on paper, but were also confirmed by a simple statistical analysis.
The third study selected one of the relations from the previous study, i.e., the relation between structured modeling and model quality, and investigated this relation in more detail. Again, the PPMChart was used, which has lead to the identification of different ways of structured process modeling. When a task is difficult, people will spontaneously split up this task in sub-tasks that are executed consecutively (instead of simultaneously). Structuring is the way in which the splitting of tasks is handled. It was found that when this happens consistently and according to certain logic, modeling became more effective and more efficient. Effective because a process model was created with less syntactic and semantic errors and efficient because it took less time and modeling operations. Still, we noticed that splitting up the modeling in sub-tasks in a structured way, did not always lead to a positive result. This can be explained by some people structuring the modeling in the wrong way. Our brain has cognitive preferences that cause certain ways of working not to fit. The study identified three important cognitive preferences: does one have a sequential or a global learning style, how context-dependent one is and how big oneâs desire and need for structure is. The Structured Process Modeling Theory was developed, which captures these relations and which can form the basis for the development of an optimal individual approach to process modeling. In our opinion the theory has the potential to also be applicable in a broader context and to help solving various types of problems effectively and efficiently
Implementierung einer flexiblen Prozess-Engine auf Basis aktueller Webtechnologien
In der heutigen Zeit arbeiten immer mehr Unternehmen prozessorientiert. ArbeitsablĂ€ufe werden in grafischen Notationen erstellt, dokumentiert und anschlieĂend nach diesem Schema ausgefĂŒhrt. Um jedoch besser und schneller auf KundenwĂŒnsche reagieren zu können, mĂŒssen Unternehmen flexibler werden. HierfĂŒr werden zunehmend mehr anpassungsfĂ€hige, mobile AusfĂŒhrungsplattformen fĂŒr GeschĂ€ftsprozesse benötigt. Dazu ist eine AusfĂŒhrung der GeschĂ€ftsprozesse direkt auf dem GerĂ€t wĂŒnschenswert. Dadurch wird die AusfĂŒhrung der GeschĂ€ftsprozesse unabhĂ€ngig von einer Internetverbindung. Diese mobilen AusfĂŒhrungsplattformen, auf denen die GeschĂ€ftsprozesse ausgefĂŒhrt werden sollen, besitzen ein groĂes Problem: Werden sie plattformspezifisch entwickelt, können diese nur auf dem mobilen Betriebssystem ausgefĂŒhrt werden, fĂŒr das sie entwickelt wurden. Eine AusfĂŒhrung auf einer anderen Plattform ist aufgrund der verwendeten Technologien nicht möglich. Eine Lösung fĂŒr dieses Problem wĂ€re eine plattformunabhĂ€ngige Implementierung.
Im Zuge dieser Arbeit wird eine flexible, mobile AusfĂŒhrungsplattform entwickelt. Dabei liegt der Fokus auf der ProzessausfĂŒhrung und der leichten Portierbarkeit auf andere Betriebssysteme. Zudem soll die Prozess-Engine leicht erweiterbar sein, sodass sich neue Funktionen ohne groĂe Ănderungen hinzufĂŒgen lassen. Die Prozess-Engine soll in der Lage sein konditionale Verzweigungen und parallele AusfĂŒhrungen behandeln zu können. Durch diese Prozess-Engine lassen sich GeschĂ€ftsprozesse mobil auf unterschiedlichen Plattformen ausfĂŒhren. Dies trĂ€gt dazu bei, dass prozessorientierte Unternehmen eine weitere Möglichkeit geboten bekommen, ihre FlexibilitĂ€t zu erhöhen. Somit können sie in Zukunft schneller und besser auf KundenwĂŒnsche reagieren
Improving data preparation for the application of process mining
Immersed in what is already known as the fourth industrial revolution, automation and data exchange are taking on a particularly relevant role in complex environments, such as industrial manufacturing environments or logistics. This digitisation and transition to the Industry 4.0 paradigm is causing experts to start analysing business processes from other perspectives. Consequently, where management and business intelligence used to dominate, process mining appears as a link, trying to build a bridge between both disciplines to unite and improve them. This new perspective on process analysis helps to improve strategic decision making and competitive capabilities. Process mining brings together data and process perspectives in a single discipline that covers the entire spectrum of process management. Through process mining, and based on observations of their actual operations, organisations can understand the state of their operations, detect deviations, and improve their performance based on what they observe. In this way, process mining is an ally, occupying a large part of current academic and industrial research.
However, although this discipline is receiving more and more attention, it presents severe application problems when it is implemented in real environments. The variety of input data in terms of form, content, semantics, and levels of abstraction makes the execution of process mining tasks in industry an iterative, tedious, and manual process, requiring multidisciplinary experts with extensive knowledge of the domain, process management, and data processing. Currently, although there are numerous academic proposals, there are no industrial solutions capable of automating these tasks. For this reason, in this thesis by compendium we address the problem of improving business processes in complex environments thanks to the study of the state-of-the-art and a set of proposals that improve relevant aspects in the life cycle of processes, from the creation of logs, log preparation, process quality assessment, and improvement of business processes.
Firstly, for this thesis, a systematic study of the literature was carried out in order to gain an in-depth knowledge of the state-of-the-art in this field, as well as the different challenges faced by this discipline. This in-depth analysis has allowed us to detect a number of challenges that have not been addressed or received insufficient attention, of which three have been selected and presented as the objectives of this thesis. The first challenge is related to the assessment of the quality of input data, known as event logs, since the requeriment of the application of techniques for improving the event log must be based on the level of quality of the initial data, which is why this thesis presents a methodology and a set of metrics that support the expert in selecting which technique to apply to the data according to the quality estimation at each moment, another challenge obtained as a result of our analysis of the literature. Likewise, the use of a set of metrics to evaluate the quality of the resulting process models is also proposed, with the aim of assessing whether improvement in the quality of the input data has a direct impact on the final results.
The second challenge identified is the need to improve the input data used in the analysis of business processes. As in any data-driven discipline, the quality of the results strongly depends on the quality of the input data, so the second challenge to be addressed is the improvement of the preparation of event logs. The contribution in this area is the application of natural language processing techniques to relabel activities from textual descriptions of process activities, as well as the application of clustering techniques to help simplify the results, generating more understandable models from a human point of view.
Finally, the third challenge detected is related to the process optimisation, so we contribute with an approach for the optimisation of resources associated with business processes, which, through the inclusion of decision-making in the creation of flexible processes, enables significant cost reductions. Furthermore, all the proposals made in this thesis are validated and designed in collaboration with experts from different fields of industry and have been evaluated through real case studies in public and private projects in collaboration with the aeronautical industry and the logistics sector