Using knowledge management to give context to analytics and big data and reduce strategic risk

John S. Edwards*, Eduardo Rodriguez Taborda

*Corresponding author for this work

Research output: Contribution to journalArticle

Abstract

At the moment, the phrases “big data” and “analytics” are often being used as if they were magic incantations that will solve all an organization’s problems at a stroke. The reality is that data on its own, even with the application of analytics, will not solve any problems. The resources that analytics and big data can consume represent a significant strategic risk if applied ineffectively. Any analysis of data needs to be guided, and to lead to action. So while analytics may lead to knowledge and intelligence (in the military sense of that term), it also needs the input of knowledge and intelligence (in the human sense of that term). And somebody then has to do something new or different as a result of the new insights, or it won’t have been done to any purpose.
Using an analytics example concerning accounts payable in the public sector in Canada, this paper reviews thinking from the domains of analytics, risk management and knowledge management, to show some of the pitfalls, and to present a holistic picture of how knowledge management might help tackle the challenges of big data and analytics.

Original languageEnglish
Pages (from-to)36-49
Number of pages14
JournalProcedia Computer Science
Volume99
Early online date27 Sep 2016
DOIs
Publication statusE-pub ahead of print - 27 Sep 2016
EventInternational Conference on Knowledge Management - Vienna, Austria
Duration: 10 Oct 201611 Oct 2016

Bibliographical note

© 2016 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/license/by-nc-nd/4.0)

Keywords

  • knowledge management
  • Canada
  • strategic risk
  • analytics
  • big data
  • Data Envelopment Analysis (DEA)
  • processes

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  • Research Output

    Knowledge management education: five Ws and one H

    Handzic, M., Edwards, J., Moffett, S., Garcia-Perez, A., Kianto, A. & Bolisani, E., 27 Sep 2016, In : Procedia Computer Science. 99, p. 213-214 2 p.

    Research output: Contribution to journalArticle

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