Information and reformation in KM systems: big data and strategic decision-making

Intezari, Ali and Gressel, Simone (2017) Information and reformation in KM systems: big data and strategic decision-making. Journal of Knowledge Management, 21 1: 71-91. doi:10.1108/JKM-07-2015-0293


Author Intezari, Ali
Gressel, Simone
Title Information and reformation in KM systems: big data and strategic decision-making
Journal name Journal of Knowledge Management   Check publisher's open access policy
ISSN 1758-7484
1367-3270
Publication date 2017-03-01
Sub-type Article (original research)
DOI 10.1108/JKM-07-2015-0293
Open Access Status Not yet assessed
Volume 21
Issue 1
Start page 71
End page 91
Total pages 21
Place of publication Bingley, United Kingdom
Publisher Emerald Publishing Limited
Language eng
Subject 1408 Strategy and Management
1405 Management of Technology and Innovation
Abstract Purpose: The purpose of this paper is to provide a theoretical framework of how knowledge management (KM) systems can facilitate the incorporation of big data into strategic decisions. Advanced analytics are becoming increasingly critical in making strategic decisions in any organization from the private to public sectors and from for-profit companies to not-for-profit organizations. Despite the growing importance of capturing, sharing and implementing people’s knowledge in organizations, it is still unclear how big data and the need for advanced analytics can inform and, if necessary, reform the design and implementation of KM systems. Design/methodology/approach: To address this gap, a combined approach has been applied. The KM and data analysis systems implemented by companies were analyzed, and the analysis was complemented by a review of the extant literature. Findings: Four types of data-based decisions and a set of ground rules are identified toward enabling KM systems to handle big data and advanced analytics. Practical implications: The paper proposes a practical framework that takes into account the diverse combinations of data-based decisions. Suggestions are provided about how KM systems can be reformed to facilitate the incorporation of big data and advanced analytics into organizations’ strategic decision-making. Originality/value: This is the first typology of data-based decision-making considering advanced analytics.
Formatted abstract
Purpose: The purpose of this paper is to provide a theoretical framework of how knowledge management (KM) systems can facilitate the incorporation of big data into strategic decisions. Advanced analytics are becoming increasingly critical in making strategic decisions in any organization from the private to public sectors and from for-profit companies to not-for-profit organizations. Despite the growing importance of capturing, sharing and implementing people’s knowledge in organizations, it is still unclear how big data and the need for advanced analytics can inform and, if necessary, reform the design and implementation of KM systems.

Design/methodology/approach: To address this gap, a combined approach has been applied. The KM and data analysis systems implemented by companies were analyzed, and the analysis was complemented by a review of the extant literature.

Findings: Four types of data-based decisions and a set of ground rules are identified toward enabling KM systems to handle big data and advanced analytics.

Practical implications: The paper proposes a practical framework that takes into account the diverse combinations of data-based decisions. Suggestions are provided about how KM systems can be reformed to facilitate the incorporation of big data and advanced analytics into organizations’ strategic decision-making.

Originality/value: This is the first typology of data-based decision-making considering advanced analytics.
Keyword Advanced analytics
Big data
Data-based decisions
Knowledge management systems
Strategic decision-making
Q-Index Code C1
Q-Index Status Provisional Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: HERDC Pre-Audit
UQ Business School Publications
 
Versions
Version Filter Type
Citation counts: TR Web of Science Citation Count  Cited 1 times in Thomson Reuters Web of Science Article | Citations
Scopus Citation Count Cited 2 times in Scopus Article | Citations
Google Scholar Search Google Scholar
Created: Tue, 28 Mar 2017, 00:20:19 EST by Web Cron on behalf of Learning and Research Services (UQ Library)