Towards an effective design of the business intelligence & analytics function within an organisation
Publication Type
PhD Dissertation
Version
publishedVersion
Publication Date
10-2017
Abstract
This dissertation is about the organisational considerations in setting up a successful business intelligence and analytics (BI&A) function. It addresses a gap in academic literature by presenting a theoretical framework on organisational attributes that impacts the BI&A function’s ability to improve the completeness and relevance of their data-driven solutions.
BI&A is a subset of information processing, and as such, subject to the phenomenon of uncertainty and equivocality. Most BI&A functions do not explicitly address this phenomenon in their organisation design, leading to suboptimal BI&A outcomes as widely publicised in both academic and practice literature.
This dissertation contributes to theory by identifying the organisation design variables that moderate the effects of a BI&A function’s ability to deal with uncertainty and equivocality in problem-solving. The research led to a proposed ‘transmutation’ framework where BI&A practitioners translate a business problem into a business solution that is key to understanding the role these moderating variables play.
This proposed transmutation framework has practical implications to the emerging discipline of BI&A. It provides insights into the interface model between the BI&A function and its business stakeholders, the specialisation of roles and responsibilities within the BI&A function, and the benefits and dis-benefits of pursuing a distributed organisational model such as offshoring.
Insights for this dissertation were drawn from 25 in-depth interviews with BI&A leaders and practitioners, and their senior business stakeholders.
Keywords
Business Intelligence function, Organising analytics, Business analytics function, Equivocality and uncertainty
Degree Awarded
PhD in Business (General Management)
Discipline
Business Analytics | Business Intelligence | Strategic Management Policy
Supervisor(s)
Rajendra K. Srivastava
First Page
1
Last Page
486
Publisher
Singapore Management University
City or Country
Singapore
Citation
SANDOSHAM, Eric.
Towards an effective design of the business intelligence & analytics function within an organisation. (2017). 1-486.
Available at: https://ink.library.smu.edu.sg/etd_coll_all/47
Copyright Owner and License
Author
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Included in
Business Analytics Commons, Business Intelligence Commons, Strategic Management Policy Commons