Domain-driven actionable process model discovery

Yahya, Bernardo Nugroho; Song, Minseok; Bae, Hyerim; Sul, Sung-ook; Wu, Jei‐Zheng

doi:10.1016/j.cie.2016.05.010

Cited by 24 publications

(22 citation statements)

References 32 publications

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“…Besides, domain experts who need to work with researchers until the end of the PM projects are always indispensable [20].…”

Section: Domain Of Pmmentioning

confidence: 99%

A Business Process Analysis Methodology Based on Process Mining for Complaint Handling Service Processes

Wang

et al. 2019

Applied Sciences

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To improve the service quality of complaint handling service in a manufacturing company, it is key to analyze the business processes. Process mining is quite a useful approach to diagnose complaint handling service process problems, such as bottlenecks and deviations. However, the current business process analysis methodologies based on process mining mainly focus on operational process analysis and neglect other system level analysis. In this study, we introduce the method of Accimap from the discipline of accident analysis to analyze the diagnosis results of process mining. By creating a complaint handling service process management Accimap model, the process mining results analysis can be carried out across different system levels. A case study in a big manufacturing company in China is implemented to verify our approach. In the case study, 42 complaint handling process management factors are identified and the complaint handling process management Accimap model is created. The testing results by Rasmussen’s seven predictions in his risk management framework show that Accimap method presents a systematic approach to analyze the process diagnosis results based on process mining.

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“…Besides, domain experts who need to work with researchers until the end of the PM projects are always indispensable [20].…”

Section: Domain Of Pmmentioning

confidence: 99%

A Business Process Analysis Methodology Based on Process Mining for Complaint Handling Service Processes

Wang

et al. 2019

Applied Sciences

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“…The research question is based on the general research goal to get an overview of current and missing academic knowledge about cross-organizational process mining. Such an overview is now lacking, whereas researchers in the past have discussed the need for it [12], [16]. Therefore, the research question addressed in this paper is:…”

Section: Research Questionmentioning

confidence: 99%

“…Process discovery is thus proposed to produce more objective, more complete and more up-to-date business process models [11]. It is currently not clear, however, how these techniques can be applied in the context of cross-organizational processes [12].…”

Section: Introductionmentioning

confidence: 99%

Process Mining in Supply Chains: A Systematic Literature Review

Jokonowo¹,

Claes²,

Sarno³

et al. 2018

IJECE

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Performance analysis and continuous process improvement efforts are often supported by the construction of process models representing the interactions of the partners in the supply chain. This study was conducted to determine the state of the art in the process mining field, specifically in the context of cross-organizational process. The Systematic Literature Review (SLR) method is used to review a collection of twenty-one papers that are classified according to the Artifact framework of Hevner, et al. and within the Process Mining framework of Van der Aalst. In the reviewed papers, the authors conducted a variety of techniques to establish the event log, which is then used to perform the process mining analysis. Eight of the reviewed papers focus on the definition of concepts or measures. Five of the papers describe models and other abstractions that are used as a theoretical basis for process mining in the context of supply chains. The majority twenty of papers describe some kind of informal method or formal algorithm to perform process mining analysis. Nine of the papers that propose a formal algorithm also present an accompanying software implementation. Eight papers discuss the data preparation challenges and twelve papers discuss process discovery techniques.

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“…Undoubtedly, Process discovery becomes particularly critical for unstructured processes where model complexity rises. Several contributions recognize significant problem of current process discovery methodologies when handling unstructured processes (e.g., Bose et al, 2013; Song et al, 2013; van der Aalst, 2016; Yahya, Song, Bae, Sul, & Wu, 2016). Specifically, case heterogeneity (high ratio between the number of different process traces and process instances) typically leads to extract extremely complex and often incomprehensible process models (Bose et al, 2013; Diamantini, Genga, & Potena, 2016).…”

Section: Introductionmentioning

confidence: 99%

“…Specifically, case heterogeneity (high ratio between the number of different process traces and process instances) typically leads to extract extremely complex and often incomprehensible process models (Bose et al, 2013; Diamantini, Genga, & Potena, 2016). In process mining literature, the aforementioned models are termed as “spaghetti‐like models” (see for example, Günther & van der Aalst, 2007; van der Aalst, 2016; Yahya et al, 2016). In such cases, the mined models do not provide any meaningful abstraction from the event logs and result in excessively complicated process models that introduce a significant interpretation challenge.…”

Section: Introductionmentioning

confidence: 99%

A process mining methodology for modeling unstructured processes

Stefanini

Aloini

Benevento

et al. 2020

Knowl Process Manag

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The effective representation of business processes is widely recognized as a critical task in Business Process Management (BPM). Unfortunately, the complexity of unstructured processes makes process modeling extremely challenging and limits the suitability of traditional model‐driven approaches, which appear considerably less effective and efficient. Nevertheless, most of the recent and promising data‐driven approaches dealing with unstructured processes are not yet completely developed and typically fail to provide an adequate procedural process model. This study proposes a novel process mining‐based methodology to achieve a significant process model when unstructured processes occur. Specifically, the method assesses and combines the outcomes of different process mining algorithms by evaluating the process model through appropriate quality parameters (i.e., accuracy and comprehensibility). The final output of the method corresponds to a unitary procedural process model that is mathematically computable, evaluable through objective quality metrics, comparable with other process models, convertible to other model languages, and usable for supporting BPM activities. Finally, a real case study of an Italian hospital is presented to verify the applicability of the proposed methodology.

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Domain-driven actionable process model discovery

Cited by 24 publications

References 32 publications

A Business Process Analysis Methodology Based on Process Mining for Complaint Handling Service Processes

A Business Process Analysis Methodology Based on Process Mining for Complaint Handling Service Processes

Process Mining in Supply Chains: A Systematic Literature Review

A process mining methodology for modeling unstructured processes

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