Improvement of call center customer service in a thai bank using disco fuzzy mining algorithm

Arpasat, Poohridate; Porouhan, Parham; Premchaiswadi, Wichian

doi:10.1109/ictke.2015.7368477

Cited by 25 publications

(3 citation statements)

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“…Quality is either "internally" or "externally" induced. Internally induced measures commonly include binary categorization of the process outcome (desired or undesired) such as defects, errors, or delays [4]. Externally induced performance refers to the determination of quality from sources external to the process such as customer complaints [43].…”

Section: What Input Data (Rq2)mentioning

confidence: 99%

“…Internal quality regards the conformance of the process outcome to internally defined targets, whereas external quality refers to customers' satisfaction with the process outcome [10]. Internal quality analysis has been conducted by Arpasat et al [4] who analyze the reasons why too many attempts were required to solve a problem in a bank customerservice process. They apply Disco to identify the causes for inappropriate (not successful) interventions.…”

Section: Fig 1: Aspects Of Time Performancementioning

confidence: 99%

“…[41] Logistics [25], [4], [43], [34] Service Processes highlight cases and/or areas in the process where there are opportunities for improvement. For descriptive analysis, the minimum requirement is an input log capturing mandatory data (case id, activity, and timestamp).…”

Section: Frameworkmentioning

confidence: 99%

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A Comparative Evaluation of Log-Based Process Performance Analysis Techniques

Milani

Maggi

2018

Business Information Systems

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Process mining has gained traction over the past decade and an impressive body of research has resulted in the introduction of a variety of process mining approaches measuring process performance. Having this set of techniques available, organizations might find it difficult to identify which approach is best suited considering context, performance indicator, and data availability. In light of this challenge, this paper aims at introducing a framework for categorizing and selecting performance analysis approaches based on existing research. We start from a systematic literature review for identifying the existing works discussing how to measure process performance based on information retrieved from event logs. Then, the proposed framework is built starting from the information retrieved from these studies taking into consideration different aspects of performance analysis. accessibility to open source tools has never been easier, in particular for data driven analysis of business processes. Therefore, in a digital era, businesses cannot hope to survive with manually driven methods. The process analysis must also be digitally transformed by tapping into data-driven analysis methods.One group of techniques for data driven performance analysis uses event logs of processes to assess performance. Indeed, nowadays, business processes are often supported by IT systems that log their execution. For instance, an order-to-invoice process might include activities such as register, validate, approve, fill order and send invoice. Each order has a unique id and every activity is recorded in the event log with information about the time when it was executed (timestamp) and other additional data such as the resource (person or device) that executed the activity. As such, the process is inherently captured in the log. With process mining techniques [2], the performance of such processes can be assessed and analyzed in great detail based on event logs.The body of research and tools within the field of process mining has grown significantly during this decade. However, the availability of tools and approaches developed for specific aspects of process performance does not make it easier for businesses to employ them. In fact, it poses a challenge. There is no way for businesses to easily get an overview of what performance indicators can be measured, what input data is required for such analysis, or what industry specific implementations are available. In light of this context, we propose a framework for the selection of log-based performance analysis techniques. We do so by conducting a systematic literature review to identify the body of existing work. We analyze the results and focus on identifying existing process performance indicators, required input data, and approaches available. Based on the results, we build a framework for the selection of suitable performance analysis approaches.The structure of this paper is as follows. Section 2 summarizes the research protocol for the systematic survey. In Section 3, the research que...

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Section: What Input Data (Rq2)mentioning

confidence: 99%

Section: Fig 1: Aspects Of Time Performancementioning

confidence: 99%

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A Comparative Evaluation of Log-Based Process Performance Analysis Techniques

Milani

Maggi

2018

Business Information Systems

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Process Mining: A Guide for Practitioners

Milani

Lashkevich

Maggi

et al. 2022

Lecture Notes in Business Information Processing

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In the last years, process mining has significantly matured and has increasingly been applied by companies in industrial contexts. However, with the growing number of process mining methods, practitioners might find it difficult to identify which ones to apply in specific contexts and to understand the specific business value of each process mining technique. This paper’s main objective is to develop a business-oriented framework capturing the main process mining use cases and the business-oriented questions they can answer. We conducted a Systematic Literature Review (SLR) and we used the review and the extracted data to develop a framework that (1) classifies existing process mining use cases connecting them to specific methods implementing them, and (2) identifies business-oriented questions that process mining use cases can answer. Practitioners can use the framework to navigate through the available process mining use cases and to identify the process mining methods suitable for their needs.

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