Print ISSN: 2616-5163
Online ISSN: 2616-4655
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Volume 4 | Issue 1 | 2021
Title: Performance Predictive Analytics for Operations Management of Shared Services
Author(S): Hai Wang
Corresponding Author Affiliation*: Saint Mary’s University, Canada
Conference Information: Applied Research International Conferences (Oxford, Cambridge, London & Boston)
Conference URL: https://arintconferences.com/
Abstract:
Shared services have been widely used in many organizations as an alternative to outsourcing. For shared services, common services are standardized and consolidated across multiple organizations to reduce the operational cost and to increase information and knowledge sharing. Two major advantages of shared services over outsourcing are long-term stable cost-saving and knowledge sharing. One important aspect of successful operations management of shared services is to ensure the quality of services delivered by a shared service provider to each individual partner organization. This paper proposes a performance predictive analytics framework for operations management of shared services. The paper presents a case study to demonstrate the usefulness and effectiveness of this framework.
Keywords: Shared Services; Business Analytics; Performance Prediction; Key Performance Indicators; Queuing Network Model
DOI: https://doi.org/10.37227/JIBM-2020-03-18