The alignment of formal, structured and unstructured process descriptions

Nowadays organizations are experimenting a drift on the way processes are managed. On the one hand, formal notations like Petri nets or Business Process Model and Notation (BPMN) enable the unambiguous reasoning and automation of designed processes. This way of eliciting processes by manual design, which stemmed decades ago, will still be an important actor in the future. On the other hand, regulations require organizations to store their process executions in structured representations, so that they are known and can be analyzed. Finally, due to the different nature of stakeholders within an organization (ranging from the most technical members, e.g., developers, to less technical), textual descriptions of processes are also maintained to enable that everyone in the organization understands their processes. In this paper I will describe techniques for facilitating the interconnection between these three process representations. This requires interdisciplinary research to connect several fields: business process management, formal methods, natural language processing and process mining.Peer ReviewedPostprint (author's final draft

Business Process Management: 13th International Conference, BPM 2015, Innsbruck, Austria, August 31 -- September 3, 2015, Proceedings

BPM 2015 was the 13th International Conference on Business Process Management. It provided a global forum for researchers to meet and exchange views over research\ud topics and outcomes in business process management. BPM 2015 was hosted by the University of Innsbruck and took place August 31 to September 3

Automated Process Discovery: A Literature Review and a Comparative Evaluation with Domain Experts

Äriprotsesside kaeve meetodi võimaldavad analüütikul kasutada logisid saamaks teadmisi protsessi tegeliku toimise kohta. Neist meetodist üks enim uuritud on automaatne äriprotsesside avastamine. Sündmuste logi võetakse kui sisend automaatse äriprotsesside avastamise meetodi poolt ning väljundina toodetakse äriprotsessi mudel, mis kujutab logis talletatud sündmuste kontrollvoogu. Viimase kahe kümnendi jooksul on väljapakutud mitmeidki automaatseid äriprotsessi avastamise meetodeid balansseerides erinevalt toodetavate mudelite skaleeruvuse, täpsuse ning keerukuse vahel. Siiani on automaatsed äriprotsesside avastamise meetodid testitud ad-hoc kombel, kus erinevad autorid kasutavad erinevaid andmestike, seadistusi, hindamismeetrikuid ning alustõdesid, mis viib tihti võrdlematute tulemusteni ning mõnikord ka mittetaastoodetavate tulemusteni suletud andmestike kasutamise tõttu. Eelpool toodu mõistes sooritatakse antud magistritöö raames süstemaatiline kirjanduse ülevaade automaatsete äriprotsesside avastamise meetoditest ja ka süstemaatiline hindav võrdlus üle nelja kvaliteedimeetriku olemasolevate automaatsete äriprotsesside avastamise meetodite kohta koostöös domeeniekspertidega ning kasutades reaalset logi rahvusvahelisest tarkvara firmast. Kirjanduse ülevaate ning hindamise tulemused tõstavad esile puudujääke ning seni uurimata kompromisse mudelite loomiseks nelja kvaliteedimeetriku kontekstis. Antud magistritöö tulemused võimaldavad teaduritel parandada puudujäägid meetodites. Samuti vastatakse küsimusele automaatsete äriprotsesside avastamise meetodite kasutamise kohta väljaspool akadeemilist maailma.Process mining methods allow analysts to use logs of historical executions of business processes in order to gain knowledge about the actual performance of these processes.One of the most widely studied process mining operations is automated process discovery.An event log is taken as input by an automated process discovery method and produces a business process model as output that captures the control-flow relations between tasks that are described by the event log.Several automated process discovery methods have been proposed in the past two decades, striking different tradeoffs between scalability, accuracy and complexity of the resulting models.So far, automated process discovery methods have been evaluated in an ad hoc manner, with different authors employing different datasets, experimental setups, evaluation measures and baselines, often leading to incomparable conclusions and sometimes unreproducible results due to the use of non-publicly available datasets.In this setting, this thesis provides a systematic review of automated process discovery methods and a systematic comparative evaluation of existing implementations of these methods with domain experts by using a real-life event log extracted from a international software engineering company and four quality metrics.The review and evaluation results highlight gaps and unexplored tradeoffs in the field in the context of four business process model quality metrics.The results of this master thesis allows researchers to improve the lacks in the automated process discovery methods and also answers question about the usability of process discovery techniques in industry

Presenting Business Process Improvement Changes – A Systematic Literature Review

Äriprotsessi täiustamine aitab parandada lõppkasutaja kogemust, vähendada kulutusi ja kiirendada tööd. Eksisteerib mitmeid äriprotsessi täiustamise tehnikaid. Olemasolevate protsesside juures ei ole aga demonstreeritud muutuste mõju. Et täita see lünk, pakub antud lõputöö ülevaadet viisidest, kuidas demonstreerida äriprotsesside muutuste mõju päris elu näidete põhjal. Sel eesmärgil on tehtud süstemaatiline kirjanduse ülevaade artiklitest, mis kasutavad äriprotsesside täiustamist päris elu näidetes, et näha, kuidas need muutuseid on esitletud. Leitud artikleid analüüsiti ning leiti vastused uurimuse küsimustele. Analüüsi tulemusena leiti, et nagu igas teises teadusvaldkonnas, mis käsitleb muutusi, saab neid esitleda visuaalselt, numbriliselt või mitte- struktureeritud viisil, kasutates erinevaid esitlemise strateegiaid. Teadmine, kuidas antakse edasi asjade muutumist, aitab inimestel paremini aru saada nende sisust. Võimalik on paremini aru saada äriprotsesside muutustest.Business Process Improvement (BPI) has a big potential by helping to improve end-user satisfaction, to reduce costs and throughput times. A lot of business process improvement techniques exist, but they lack the information about the presentation of the effects of business process change. In order to fill this gap, this thesis provides an overview of the ways that are used to present the effects of business process change in real-life business process scenarios. For that purpose, a systematic literature review is performed to identify papers that apply BPI on real-life cases from industry to see what means are used to capture and present those changes. The identified final papers are analysed in order to answer to Research Questions (RQ). The analysis reveals that as in any other scientific field where change is occurring the change could be presented either visually, or in a numerical way, or in a not structured (narrative) way using some presentation strategies. This knowledge that gives some hints on how changes are conveyed can be used to support people to better understand the changes which occur in a process after a BPI

Advancements and Challenges in Object-Centric Process Mining: A Systematic Literature Review

Recent years have seen the emergence of object-centric process mining techniques. Born as a response to the limitations of traditional process mining in analyzing event data from prevalent information systems like CRM and ERP, these techniques aim to tackle the deficiency, convergence, and divergence issues seen in traditional event logs. Despite the promise, the adoption in real-world process mining analyses remains limited. This paper embarks on a comprehensive literature review of object-centric process mining, providing insights into the current status of the discipline and its historical trajectory

Encoding process discovery problems in SMT

Information systems, which are responsible for driving many processes in our lives (health care, the web, municipalities, commerce and business, among others), store information in the form of logs which is often left unused. Process mining, a discipline in between data mining and software engineering, proposes tailored algorithms to exploit the information stored in a log, in order to reason about the processes underlying an information system. A key challenge in process mining is discovery: Given a log, derive a formal process model that can be used afterward for a formal analysis. In this paper, we provide a general approach based on satisfiability modulo theories (SMT) as a solution for this challenging problem. By encoding the problem into the logical/arithmetic domains and using modern SMT engines, it is shown how two separate families of process models can be discovered. The theory of this paper is accompanied with a tool, and experimental results witness the significance of this novel view of the process discovery problem.Peer ReviewedPostprint (author's final draft