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e-Article

Using Process Mining to Formalise Service Level Agreement (SLA) Allocation
Document Type
Conference
Source
2021 IEEE SmartWorld, Ubiquitous Intelligence & Computing, Advanced & Trusted Computing, Scalable Computing & Communications, Internet of People and Smart City Innovation (SmartWorld/SCALCOM/UIC/ATC/IOP/SCI) SMARTWORLD-SCALCOM-UIC-ATC-IOP-SCI SmartWorld, Ubiquitous Intelligence & Computing, Advanced & Trusted Computing, Scalable Computing & Communications, Internet of People and Smart City Innovation (SmartWorld/SCALCOM/UIC/ATC/IOP/SCI), 2021 IEEE. :671-676 Oct, 2021
Subject
Communication, Networking and Broadcast Technologies
Computing and Processing
Robotics and Control Systems
Signal Processing and Analysis
Transportation
Technological innovation
Smart cities
Customer services
Organizations
Internet
Resource management
Service level agreements
Customer classification
Ontology
Process mining
Semantic interoperability
Service Level Agreement
Language
Abstract
Service Level Agreement (SLA) assignment for online services is typically an unstandardized process, and is generally executed in an ad hoc manner to respond to customer service requirements. The steps taken by organizations to assign the SLA to a customer can also be influenced by the technical knowledge of a customer and their ability to explain the service requirement. Also, there is a need to analyze the organization’s SLA assignment for any underlying discrepancies in execution of such complex process. In this paper, we analyze our earlier proposed SLA assignment process using process mining techniques. We validated the suitability of our proposed approach for wider scenarios of customer requirements, including for the customers having no technical knowledge about their required services. We also presented both customer’s and system’s perspective of the SLA assignment process using process discovery techniques. Our proposed SLA assignment process verifies the relevance of the SLA assignment activities such as optimized customer interaction, score assignment, and subsequent customer service allocation.