Avoid being the Turkey: How big data analytics changes the game of strategy in times of ambiguity and uncertainty

van Rijmenam, M; Erekhinskaya, T; Schweitzer, J; Williams, MA

Avoid being the Turkey: How big data analytics changes the game of strategy in times of ambiguity and uncertainty

van Rijmenam, M

Erekhinskaya, T Schweitzer, J

Williams, MA

Permalink

Publication Type:: Journal Article
Citation:: Long Range Planning, 2019, 52 (5)
Issue Date:: 2019-10-01

Open Access

Copyright Clearance Process

Recently Added
In Progress
Open Access

This item is open access.

The embargo period expires on 2 Jan 2022

Adobe PDF

Download Accepted Manuscript VersionAdobe PDF (1.48 MB)

View on publisher's site

View statistics

Full metadata record

Field	Value	Language
dc.contributor.author	van Rijmenam, M https://orcid.org/0000-0002-5382-4164	en_US
dc.contributor.author	Erekhinskaya, T	en_US
dc.contributor.author	Schweitzer, J https://orcid.org/0000-0002-3145-721X	en_US
dc.contributor.author	Williams, MA https://orcid.org/0000-0002-1047-0503	en_US
dc.date.available	2018-05-17	en_US
dc.date.issued	2019-10-01	en_US
dc.identifier.citation	Long Range Planning, 2019, 52 (5)	en_US
dc.identifier.issn	0024-6301	en_US
dc.identifier.uri	http://hdl.handle.net/10453/124328
dc.description.abstract	© 2018 Elsevier Ltd In order for organisations to remain competitive in times of ambiguity and uncertainty, there is a need to detect and anticipate unknown unknowns, also called ‘black swans’. When these are ignored they may lead to competitive struggles. In this paper, we build on this view and suggest that big data analytics can provide necessary insights to help change strategy making. Research suggests that ambidextrous organisations should focus on developing and maintaining their dynamic capabilities. Following on from this, we take a dynamic capabilities perspective and propose a theoretical framework to explain the intricacies of big data analytics. This framework explains the ability of organisations to detect, anticipate and respond strategically in ambiguous and uncertain business environments. For a meta-synthesis of 101 cases of big data analytics, we employ a multi-method approach that incorporates Natural Language Processing, semantic analysis and case analysis, allowing extraction and analysis of structured information from unstructured data. Overall, we find evidence of big data analytics helping to detect, anticipate and respond to industry disruption. We offer six propositions about the relationships between the levels of data analytics capabilities and strategic dynamic capabilities. We find that descriptive data analytics improves the capability of an organisation to understand the business context (sensing) and that predictive data analytics aids in the realisation of business opportunities (seizing). This study contributes to an understanding of big data analytics as a dynamic organisational capability that supports strategic decision-making in times of ambiguity and uncertainty. We conclude by suggesting areas for further investigation, particularly in regard to the strategic application of prescriptive data analytics.	en_US
dc.relation	http://purl.org/au-research/grants/arc/DP160102693
dc.relation.ispartof	Long Range Planning	en_US
dc.relation.isbasedon	10.1016/j.lrp.2018.05.007	en_US
dc.rights	info:eu-repo/semantics/embargoedAccess
dc.subject.classification	Business & Management	en_US
dc.title	Avoid being the Turkey: How big data analytics changes the game of strategy in times of ambiguity and uncertainty	en_US
dc.type	Journal Article
utslib.citation.volume	5	en_US
utslib.citation.volume	52	en_US
utslib.for	1503 Business and Management	en_US
utslib.for	1505 Marketing	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Business
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Computer Science
pubs.organisational-group	/University of Technology Sydney/Strength - CAI - Centre for Artificial Intelligence
pubs.organisational-group	/University of Technology Sydney/Students
utslib.copyright.status	open_access	*
utslib.copyright.embargo	2022-01-02T00:00:00+1100
pubs.issue	5	en_US
pubs.publication-status	Published	en_US
pubs.volume	52	en_US

Abstract:

© 2018 Elsevier Ltd In order for organisations to remain competitive in times of ambiguity and uncertainty, there is a need to detect and anticipate unknown unknowns, also called ‘black swans’. When these are ignored they may lead to competitive struggles. In this paper, we build on this view and suggest that big data analytics can provide necessary insights to help change strategy making. Research suggests that ambidextrous organisations should focus on developing and maintaining their dynamic capabilities. Following on from this, we take a dynamic capabilities perspective and propose a theoretical framework to explain the intricacies of big data analytics. This framework explains the ability of organisations to detect, anticipate and respond strategically in ambiguous and uncertain business environments. For a meta-synthesis of 101 cases of big data analytics, we employ a multi-method approach that incorporates Natural Language Processing, semantic analysis and case analysis, allowing extraction and analysis of structured information from unstructured data. Overall, we find evidence of big data analytics helping to detect, anticipate and respond to industry disruption. We offer six propositions about the relationships between the levels of data analytics capabilities and strategic dynamic capabilities. We find that descriptive data analytics improves the capability of an organisation to understand the business context (sensing) and that predictive data analytics aids in the realisation of business opportunities (seizing). This study contributes to an understanding of big data analytics as a dynamic organisational capability that supports strategic decision-making in times of ambiguity and uncertainty. We conclude by suggesting areas for further investigation, particularly in regard to the strategic application of prescriptive data analytics.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/124328