Towards an effective design of the business intelligence & analytics function within an organisation

• Main Author: SANDOSHAM, Eric
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2017
• Subjects: Business Intelligence function; Organising analytics; Business analytics function; Equivocality and uncertainty; Business Analytics; Business Intelligence; Strategic Management Policy
• Online Access: https://ink.library.smu.edu.sg/etd_coll_all/47; https://ink.library.smu.edu.sg/cgi/viewcontent.cgi?article=1046&context=etd_coll_all
• Institution: Singapore Management University

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.