Business Process Mining Application: A Literature Review

Dakić, Dušanka; Stefanović, Darko; Ćosić, Ilija; Lolić, Teodora; Medojevic, Milovan

doi:10.2507/29th.daaam.proceedings.125

Cited by 36 publications

(25 citation statements)

References 37 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…For example, several studies investigate the application of different process mining algorithms in specific domains, such as healthcare (Farid et al 2019), education (Ghazal et al 2017), and supply chains (Jokonowo et al 2018). In addition, extant literature addresses the application of process mining across industries to compare prevailing source systems and techniques (Dakic et al 2018;Thiede et al 2018).…”

Section: Process Miningmentioning

confidence: 99%

No Longer Out of Sight, No Longer Out of Mind? How Organizations Engage with Process Mining-Induced Transparency to Achieve Increased Process Awareness

et al. 2021

View full text Add to dashboard Cite

In recent years, process mining has emerged as the leading big data technology for business process analysis. By extracting knowledge from event logs in information systems, process mining provides unprecedented transparency of business processes while being independent of the source system. However, despite its practical relevance, there is still a limited understanding of how organizations act upon the pervasive transparency created by process mining and how they leverage it to benefit from increased process awareness. Addressing this gap, this study conducts a multiple case study to explore how four organizations achieved increased process awareness by using process mining. Drawing on data from 24 semi-structured interviews and archival sources, this study reveals seven sociotechnical mechanisms based on process mining that enable organizations to create either standardized or shared awareness of sub-processes, end-to-end processes, and the firm’s process landscape. Thereby, this study contributes to research on business process management by revealing how process mining facilitates mechanisms that serve as a new, data-driven way of creating process awareness. In addition, the findings indicate that these mechanisms are influenced by the governance approach chosen to conduct process mining, i.e., a top-down or bottom-up driven implementation approach. Last, this study also points to the importance of balancing the social complications of increased process transparency and awareness. These results serve as a valuable starting point for practitioners to reflect on measures to increase organizational process awareness through process mining.

show abstract

Section: Process Miningmentioning

confidence: 99%

No Longer Out of Sight, No Longer Out of Mind? How Organizations Engage with Process Mining-Induced Transparency to Achieve Increased Process Awareness

et al. 2021

View full text Add to dashboard Cite

show abstract

“…Depending on the scenario, different are the points of view that could be used to discover a process, such as the activities executed, persons involved, the resources used, the location where the actions occur, etc. The versatility of process mining techniques has brought about its application to several scenarios (Dakic et al 2018), healthcare (Mans et al 2009;Rozinat et al 2009;Perimal-Lewis et al 2016) and IT (Sahlabadi et al 2014;Mȃruşter and van Beest 2009;Pérez-´A lvarez et al 2018;Fernández-Cerero et al 2019) being the most active areas.…”

Section: Application Of Process Mining In Different Contextsmentioning

confidence: 99%

Discovering configuration workflows from existing logs using process mining

et al. 2021

View full text Add to dashboard Cite

Variability models are used to build configurators, for guiding users through the configuration process to reach the desired setting that fulfils user requirements. The same variability model can be used to design different configurators employing different techniques. One of the design options that can change in a configurator is the configuration workflow, i.e., the order and sequence in which the different configuration elements are presented to the configuration stakeholders. When developing a configurator, a challenge is to decide the configuration workflow that better suits stakeholders according to previous configurations. For example, when configuring a Linux distribution the configuration process starts by choosing the network or the graphic card and then, other packages concerning a given sequence. In this paper, we present COnfiguration workfLOw proceSS mIning (COLOSSI), a framework that can automatically assist determining the configuration workflow that better fits the configuration logs generated by user activities given a set of logs of previous configurations and a variability model. COLOSSI is based on process discovery, commonly used in the process mining area, with an adaptation to configuration contexts. Derived from the possible complexity of both logs and the discovered processes, often, it is necessary to divide the traces into small ones. This provides an easier configuration workflow to be understood and followed by the user during the configuration process. In this paper, we apply and compare four different techniques for the traces clustering: greedy, backtracking, genetic and hierarchical algorithms. Our proposal is validated in three different scenarios, to show its feasibility, an ERP configuration, a Smart Farming, and a Computer Configuration. Furthermore, we open the door to new applications of process mining techniques in different areas of software product line engineering along with the necessity to apply clustering techniques for the trace preparation in the context of configuration workflows.

show abstract

“…However, these models are often completely disconnected from the actual operation of the process [70]. A new approach to traditional BPM initiatives which is much capable in improving and optimizing business processes is enabled by process mining [71]. Specifically, process mining techniques facilitate a dynamic system that reflects the changes in the process in real time.…”

Section: Process Mining and Its Impact On Bpmmentioning

confidence: 99%

Untitled

2021

IJMVSC

View full text Add to dashboard Cite

Business Process Management (BPM) is considered as a management approach that primarily focuses on analyzing and continuously improving business processes. It has been a key strategy adapted by organizations to manage their businesses successfully along with information technology. In the past few decades BPM has been one of the promising research areas. This paper adds knowledge to the existing research by answering following questions: (1) what is the status of BPM research domain? And (2) what are the possible future research directions on BPM? A thematic review was conducted focusing a series of literature on BPM which have been published between 2001 and 2020. The findings highlight that the integration of BPM into new digital innovations, such as process mining, is essential for an effective and efficient organization. More research on BPM and IT management needs to be conducted to support this integration between BPM and digital innovations.

show abstract

Business Process Mining Application: A Literature Review

Cited by 36 publications

References 37 publications

No Longer Out of Sight, No Longer Out of Mind? How Organizations Engage with Process Mining-Induced Transparency to Achieve Increased Process Awareness

No Longer Out of Sight, No Longer Out of Mind? How Organizations Engage with Process Mining-Induced Transparency to Achieve Increased Process Awareness

Discovering configuration workflows from existing logs using process mining

Untitled

Contact Info

Product

Resources

About