Generating performance improvement suggestions by using cross organizational process mining

Date

2015-12-10

Author

Yılmaz, Onur
Karagöz, Pınar

Metadata

Show full item record

Item Usage Stats

124
views

0
downloads

Process mining is a relatively young and developing research area with the main idea of discovering, monitoring and improving processes by extracting information from event logs. With the increase of cloud computing and shared infrastructures, event logs of multiple organizations are available for analysis where cross-organizational process mining stands with the opportunity for organizations learning from each other. The approach proposed in this study mines process models of organizations and calculates performance indicators; followed by clustering of organizations based on performance indicators and finally spots mismatches between the process models to generate recommendations. This approach is implemented as an extensible and configurable plug-in set in ProM framework and tested by synthetic and real life logs where successful and suitable results are achieved with defined evaluation metrics. Generated recommendation results indicate that the use of this approach can help users to focus on the parts of process models with potential performance improvement, which are difficult to spot manually and visually.

Subject Keywords

Process mining,, Cross-organizational process mining,, Performance indicators,, Clustering,, Process performance improvement

URI

https://hdl.handle.net/11511/88117

Conference Name

5th International Symposium on Data-driven Process Discovery and Analysis (SIMPDA 2015), (8 - 10 Aralık 2015),

Collections

Department of Computer Engineering, Conference / Seminar

Suggestions

OpenMETU
Core

Recommendation generation for performance improvement by using cross-organizational process mining Yılmaz, Onur; Yarman Vural, Fatoş Tunay; Department of Computer Engineering (2015) Process mining is a relatively young and developing research area with the main idea of discovering, monitoring and improving processes by extracting information from the event logs. With the increase of cloud computing and shared infrastructures, event logs of multiple organizations are available for analysis where cross-organizational process mining stands with the opportunity for organizations learning from each other. The approach proposed in this study mines process models of organizations and calculat...
Extracting process hierarchies by multi-sequence alignment adaptations Esgin, Eren; Karagöz, Pınar (2021-01-01) Process mining is an active research area that provides a wide range of automated process discovery, conformance checking and process enhancement solutions by extracting process information from event logs. With the emerge of new shared economy models and system architectures, monolithic perspective of process mining, i.e. a single process within a single organisation, is evolved towards cross-organisational business processes. The results can be used to form new collaboration among the organisations and sh...
A Hybrid Approach to Process Mining: Finding Immediate Successors of a Process by Using From-To Chart Esgin, Eren; Karagöz, Pınar (2009-12-15) Process mining is a branch of data mining that aims to discover process model from the event logs. In this study, we propose a hybrid approach to process mining in such a way that, "from-to chart" is used as the front-end to monitor the transitions among activities of a realistic event log. Another novelty of this study is developed evaluation metrics, which are used for finding immediate successors in order to convert these raw relations into dependency/frequency graph.
Process Profiling based Synthetic Event Log Generation ESGIN, EREN; Karagöz, Pınar (2019-09-19) The goal of process mining is to discover the process behavior from the runtime information of process executions. Having labeled process logs is crucial for process mining research. However, real life event logs at process-aware information systems are mostly partially assigned to case identifiers, known as unlabeled event log problem. As a remedy to labeled data need in process mining research, we propose an approach to generate synthetic event logs according to the provided process profile, which outline...
Learning from risks: A tool for post-project risk assessment Dikmen Toker, İrem; Birgönül, Mustafa Talat; Aouad, G. (2008-12-01) Risk management (RM) comprises of risk identification, risk analysis, response planning, monitoring and action planning tasks that are carried out throughout the life cycle of a project in order to ensure that project objectives are met. Although the methodological aspects of RM are well-defined, the philosophical background is rather vague. In this paper, a learning-based approach is proposed. In order to implement this approach in practice, a tool has been developed to facilitate construction of a lessons...

Citation Formats

O. Yılmaz and P. Karagöz, “Generating performance improvement suggestions by using cross organizational process mining,” 2015, p. 3, Accessed: 00, 2021. [Online]. Available: https://hdl.handle.net/11511/88117.