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Augmenting Advanced Analytics into Enterprise Systems: A Focus on Post-Implementation Activities
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Digital Services and Systems.ORCID iD: 0000-0003-4250-4752
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Digital Services and Systems.ORCID iD: 0000-0002-1095-8437
2019 (English)In: Systems, E-ISSN 2079-8954, Vol. 7, no 2, article id 31Article in journal (Refereed) Published
Abstract [en]

An analytics-empowered enterprise system looks to many organizations to be a far-fetched target, owing to the vast amounts of factors that need to be controlled across the implementation lifecycle activities, especially during usage and maintenance phases. On the other hand, advanced analytics techniques such as machine learning and data mining have been strongly present in academic as well as industrial arenas through robust classification and prediction. Correspondingly, this paper is set out to address a methodological approach that works on tackling post-live implementation activities, focusing on employing advanced analytics techniques to detect (business process) problems, find and recommend a solution to them, and confirm the solution. The objective is to make enterprise systems self-moderated by reducing the reliance on vendor support. The paper will profile an advanced analytics engine architecture fitted on top of an enterprise system to demonstrate the approach. Employing an advanced analytics engine has the potential to support post-implementation activities. Our research is innovative in two ways: (1) it enables enterprise systems to become self-moderated and increase their availability; and (2) the IT artifact i.e., the analytics engine, has the potential to solve other problems and be used by other systems, e.g., HRIS. This paper is beneficial to businesses implementing enterprise systems. It highlights how enterprise systems could be safeguarded from retirement caused by post-implementation problems.

Place, publisher, year, edition, pages
MDPI, 2019. Vol. 7, no 2, article id 31
Keywords [en]
enterprise system, advanced analytics, post-live activities, post-implementation
National Category
Information Systems, Social aspects
Research subject
Information systems
Identifiers
URN: urn:nbn:se:ltu:diva-74850DOI: 10.3390/systems7020031ISI: 000474932700013OAI: oai:DiVA.org:ltu-74850DiVA, id: diva2:1328555
Note

Validerad;2019;Nivå 2;2019-06-24 (johcin)

Available from: 2019-06-21 Created: 2019-06-21 Last updated: 2019-08-16Bibliographically approved

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Elragal, AhmedHassanien, Hossam El-Din
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