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Process Mining for Advanced Service Analytics – From Process Efficiency to Customer Encounter and Experience

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Title:Process Mining for Advanced Service Analytics – From Process Efficiency to Customer Encounter and Experience
Authors:Zilker, Sandra
Marx, Emanuel
Stierle, Matthias
Matzner, Martin
Keywords:Service Analytics
advanced analytics
process mining
service analytics
Date Issued:04 Jan 2022
Abstract:With the ongoing trend of servitization nurtured through digital technologies, the analysis of services as a starting point for improvement is gaining more and more importance. Service analytics has been defined as a concept to analyze the data generated during service execution to create value for providers and customers. To create more useful insights from the data, there is a continuous need for more advanced solutions for service analytics. One promising technology is process mining which has its origins in business process management. Our work provides insights into how process mining is currently used to analyze service processes and how it could be used along the service process. We find that process mining is increasingly applied for the analysis of the providers' internal operations, but more emphasis should be put on analyzing the customer interaction and experience.
Pages/Duration:10 pages
URI:http://hdl.handle.net/10125/79571
ISBN:978-0-9981331-5-7
DOI:10.24251/HICSS.2022.239
Rights:Attribution-NonCommercial-NoDerivatives 4.0 International
https://creativecommons.org/licenses/by-nc-nd/4.0/
Appears in Collections: Service Analytics


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