How the G-D Logic in BI’s worldview contributes to the prevalence of BI challenges

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Business Intelligence (BI) is highly promoted and praised in the media, specifically in terms of the benefits that the organisation is described to gain after implementing a BI solution. However, by examining BI literature and practice, it is established that benefits are not consistently or fully achieved and not all organisations realise the benefits that are promised. Instead, numerous reports of BI failures and challenges prevail. Conversely, even organisations that state that they benefit from BI are on the lookout for opportunities to improve. This highlights the need for research within the discipline of BI to assist BI practice to overcome its challenges on the one hand and, on the other, the need to identify and act on opportunities to improve. This thesis examines BI’s challenges, identifying the persistent challenges that emerge within BI theory and practice. It identifies and compares current measures proposed to address BI’s challenges. In doing this, it establishes that existing attempts to resolve BI’s persistent challenges are largely ineffective and that a paradigm shift is needed. Rather than attempt to address BI’s challenges in the same manner as previous attempts do, this thesis applies a new approach.
This thesis analyses BI at a conceptual level to identify the worldview that currently dominates BI, with a view to determine what contributes towards the occurrence of BI’s challenges. It then examines the dominant worldview of BI that emerges in the literature and case study through philosophical lenses. In doing so, this thesis determines that there is an inherent underlying logic influencing BI theory and practice that can be associated with BI’s persistent challenges. Based on this, this thesis proposes that a shift in this underlying logic in BI’s worldview has the potential to introduce new ways to address many of BI’s prevailing challenges, thus allowing for increased BI successes and achievement of anticipated benefits.

Literature’s view: a BI market for technology

Literature on the BI landscape is dominated by market reports written predominantly by BI vendors and research houses with a narrow focus on BI vendors and their technical BI products. Market reports focus on, for example: vendor size, mergers, capabilities, performance, new or emerging vendors as well as on BI technology trends, licencing, integration and evaluations of BI technologies. This highlights the narrow perception where the BI landscape consists of BI vendors and BI customers operating in a BI market selling BI technology and related products. In terms of this, BI customers are perceived on the demand side, demanding BI technology solutions that they anticipate will enable decision-making (Shetty, 2011) and BI providers are seen on the supply side, providing for this demand.
BI providers are categorised according to whether they are “IT titans” selling a full range of their IT products to their installed user base or specialised (“pure play”) vendors that specialise in a specific BI offering (Sallam et al., 2011:1). Unfortunately, this presents a short-sighted view of the BI landscape as it omits many of the role players. For example: role players who facilitate the integration of legacy applications and data into BI solutions, or those who sell entire databases of data (e.g. the Companies and Intellectual Property Commission (CIPC)) or even governing and authority role players (e.g. regulatory and legislative bodies such as the Competition Commission). In addition, available literature reflects inconsistency and confusion on the scope, categorisation and segmentation of the BI landscape (e.g. Shetty, 2010 vs. Daems, 2008). Many vendors contribute to this confusion by marketing themselves as BI vendors, with the view of increasing market visibility and thereby sales, without actually providing a true BI solution (Glancy and Yadav, 2011:49; Haasbroek 2012; Joubert, 2012). As a result, there is a need to describe the current BI landscape in broader terms for the context of this thesis – as per Section 2.2.2 below.

The South Africa BI landscape and banking industry

The case study was conducted within the South African banking industry. Despite this it is believed that, as the research findings are at a conceptual and not detailed banking- or countryspecific level, use of the research findings is not restricted to a South African or banking industry audience. Simultaneously, it is necessary to provide context on the case study environment, given that the case study context will naturally have bearing on the researcher, the research process and the research findings. In addition, it is necessary to provide perspective for the reader so that they can have a sense of “being there” (Stake, 1995:63).
Relevant context is now provided. Available literature does not distinguish between the South African and the international BI market or landscape. In fact, both in South Africa and internationally, this market is said to be dominated by a handful of IT titans such as SAP (including Business objects), IBM, Inform (former Comshare and MIS), Oracle (including Hyperion), Microsoft and SAS (Kanaracus, 2011; Pendse, 2009). Many of these IT titans operate in South Africa and internationally, which is possibly a reason why many of the same trends are noticed in South African and international BI literature on BI vendors, e.g. the mergers and acquisitions (Sallam et al., 2011:1); awareness of the need for integration between BI vendors, the organisation and vendors of other hard and software in the organisation (Daems, 2008; McKnight, 2009). In addition, the congruence between the South African and international BI landscape or market was noticeable during the case study, as firstly, the bank’s senior managers selected vendors to approach locally, based on an international and not a local vendor guide and, secondly, the majority of vendors that participated in the case study are international vendors.

The concept of a BI worldview

In terms of the conceptual understanding of BI, this thesis identifies that many of the actors involved in BI exchange have perceptions and engage in actions that shape their interactions and relationships and shape the various BI exchange processes they are involved in. By analysing these perceptions and actions, this thesis identifies typical characteristics and common assumptions that are shared amongst many of BI’s actors. These are seen to guide the understanding of the nature of BI, establish the underlying paradigm of BI, organise what is known about BI and make sense of new information that emerges on BI – thereby forming a common BI worldview (Leo Apostel Center, 2012).
While some of the concepts and shifts discussed and proposed in this thesis (which fall within and beyond BI or even IS) may not be novel, it is the integration of these and other concepts (e.g. S-D Logic concepts) within the context of a worldview that provides a new approach (Akaka, 2007:17). Existing concepts and shifts that may be related to or which may have preceded this approach are discussed further in section 2.5.2, specifically in the context of existing paradigm shifts within BI and, more broadly, within IS. A worldview is, simply put: a view of reality that affects behaviour (Heylighen, 2000). It can be held by an individual or collectively by a group. It is not believed that there is only one BI worldview or one set of characteristics and common assumptions shared amongst BI actors (also referred to as role players or entities). However, analysis performed in this thesis identifies distinct, recurring characteristics and assumptions shared amongst BI actors – both in practice and theory – that point towards a dominating BI worldview that distinctly drives and influences BI.

Key contributions made by this thesis to existing research

The research presented in this thesis offers four key contributions to research areas wherein research gaps are currently identified. Firstly, this research contributes towards understanding BI at a broader and more conceptual level by analysing perceptions, beliefs, behaviour and actions that currently shape and inform the BI discipline as a whole. In doing this, it contributes towards the understanding of a socio-technical view of BI. There are few authors who make quality academic contributions towards understanding BI at a conceptual level, none of which share this thesis’ approach. For example, contributions include: Ackerman’s (2005) research on a definition and process for BI; Glancy and Yadav’s (2011) discourse on a true BI system; Middelton’s (2006) conceptual framework for IM; Pirttimäki’s (2007) conceptual analysis of BI and related terms; Vanmare’s (2006) research of BI benefits and; Venter and Tustin’s (2009) study of BI and CI availability in South African organisations.
Analysis of BI at a conceptual level leads to the identification of a dominating BI worldview, which is then examined in this thesis. To the researcher’s knowledge, this is a unique approach to examine BI and provides novel insight to the discipline of BI. It thereby forms a second contribution. By examining the BI worldview through G-D and S-D Logic lenses, a third contribution is made. Although G-D and S-D Logic are not new topics, research that spans BI and G-D or S-D Logic remains largely unexplored at present – there are only a few quality academic contributions (e.g. Goul et al., 2012; Lin et al., 2012). Although the shift from G-D to S-D Logic is discussed at a conceptual level on topics such as value co-creation for Enterprise Architecture (EA) (e.g. Chuang et al. (2010)), similar discourse at this level appears to be largely absent from a BI (or related) viewpoint. This limitation is specifically evident for less technical and more conceptual and managerial aspects of BI. Hsu (2008:425) and Zhao (2008:416) stress the need to bridge the gap between computing and management, highlighting MIS’ need for a service orientation. While this is not a direct plea for research on BI and S-D Logic, it is logical that research on BI and S-D Logic can contribute towards closing the gap Hsu and Zhao identify.

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This research represents an enquiry within the interpretive paradigm, based on a qualitative approach. A literature and a case study have been used to collect and analyse data. Both aimed to gain an understanding of the perception of BI, its challenges and attempts to address the challenges as experienced by participants in the case study and reported in the literature. This understanding is aimed at BI at a conceptual level, but also involves examples to support this from pragmatic levels of BI. Existing research on S-D Logic has informed the conceptualisation of the research that was undertaken and existing research on worldviews provided the basis of the framework that was used to analyse, structure and represent data. This approach resulted in an explicitly socio-technical perspective on BI. The case study is based at one of the “big four” banks in South Africa, located in Johannesburg. It is referred to as “Fortune Bank” (a pseudonym ascribed by the researcher) in this thesis due to the bank’s request to remain anonymous. The case study was conducted from January 2008 until the end of March 2010 (two years and three months), with an informal follow-up observation between January and April 2012. Three research techniques were used: participatory observation, semi-structured interviews and questionnaires (largely open-ended and qualitative). Questionnaires were conducted as part of a Request for Proposal (RFP) process that Fortune Bank was engaging in at the time of the case study.


  • Abstract
  • Declaration
  • Acknowledgement
  • Table of contents
  • List of abbreviations and acronyms
  • List of figures
  • List of tables
  • Chapter 1: Introduction and background
    • 1. Introduction
    • 2. Background and context
    • 2.1 The conceptual understanding of BI as a series of exchange processes
    • 2.2 BI exchange within the BI landscape
    • 2.3 The South Africa BI landscape and banking industry
    • 2.4 The concept of a BI worldview
    • 2.5 New lenses to examine BI’s dominant worldview
    • 3. Definition of key terms
    • 4. Purpose
    • 5. Problem statement
    • 6. Research questions
    • 7. Key contributions made by this thesis to existing research
    • 8. Methodology
    • 9. Scope of thesis
    • 9.1 Clarification on aspects that are in the scope of this thesis
    • 9.2 Aspects that are out of scope for this thesis
    • 10. Potential limitations
    • 11. Target audience
    • 12. Thesis outline
    • 13. Conclusion
  • Chapter 2: Research methodology
    • 1. Introduction
    • 2. High level view of research methodology
    • 3. Research process
    • 4. Research paradigm
    • 4.1 Interpretivist paradigm
    • 4.2 Rationale for choice of the interpretivist research paradigm
    • 5. Research philosophy
    • 6. Research approach
    • 7. Research techniques
    • 7.1 Literature study
    • 7.2 Case study
    • 8. Case study research techniques
    • 8.1 Participatory observation
    • 8.2 Interviews
    • 8.3 Questionnaires
    • 9. Conclusion
  • Chapter 3 Part 1: The promise and challenge of BI
    • 1. Introduction
    • 2. The promise of BI
    • 2.1 Promise, promotion and praise
    • 2.2 Benefits of BI
    • 2.3 Heavy investment in BI
    • 2.4 BI’s purpose: solve the historic management issue
    • 2.5 BI’s failure to consistently serve its purpose
    • 3. The challenge of BI
    • 3.1 Numerous reports of BI failure
    • 3.2 Numerous challenges reported for BI
    • 3.3 The generic nature of “BI” challenges
    • 3.4 BI challenges per category
    • Using BI optimally
    • Managing “big data”
    • Integrating BI across many complex technology, data and business layers
    • Aligning and balancing the needs of the various role players in BI
    • Recruiting, retaining and using BI personnel and their skills effectively
    • Absence of the right type of sponsor
    • 3.5 Summary of BI’s challenges
    • 4. Attempts to solve BI’s challenges
    • 4.1 Critical Success Factors (CSFs)
    • 4.2 Actor-Network Theory (ANT)
    • 4.3 Multi-faceted solutions using CSFs
    • 4.4 Critical Contextual Success Factors (CCSFs)
    • 4.5 BI Maturity Models (BI MMs)
    • 4.6 BI frameworks
    • 4.7 Business Intelligence Competence Centres (BICCs)
    • 5. Conclusion
  • Chapter 3 Part 2: Understanding BI’s worldview
    • 1. Introduction
    • 2. “Worldview” in context
    • 3. Method to determine BI’s worldview
    • 4. Elements of BI’s worldview
    • 4.1 BI’s model of reality as a whole (Ontology)
    • 4.2 BI’s model of the past (Explanation)
    • 4.3 BI’s model of the future (Prediction)
    • 4.4 BI’s values (Axiology)
    • 4.5 BI’s guiding principles (Praxeology)
    • 4.6 Source of knowledge on BI (Epistemology)
    • 5. Contextualising BI’s perceptions
    • 5.1 Related analysis available in the literature used as a foundation
    • 5.2 Method to perform analysis
    • 5.3 Perceptions identified through BI definitions
    • 6. Consolidating a worldview of BI
    • 7. Understanding BI’s worldview to identify novel perspectives to address BI challenges
    • 8. Conclusion
  • Chapter 3 Part 3: Goods- and Service Dominant Logic
    • 1. Introduction
    • 2. The notion of exchange
    • 3. A worldview based on G-D Logic
    • 3.1 G-D Logic informed worldview: A model of what is (ontology)
    • 3.2 G-D Logic informed worldview: A model of the past (explanation)
    • 3.3 G-D Logic informed worldview: Source of knowledge (epistemology)
    • 3.4 G-D Logic informed worldview: Values (axiology)
    • 3.5 G-D Logic informed worldview: Guiding principles and actions (praxeology)
    • 3.6 G-D Logic informed worldview: A model of the future (prediction)
    • 4. A worldview based on S-D Logic
    • 4.1 S-D Logic informed worldview: A model of what is (ontology)
    • 4.2 S-D Logic informed worldview: A model of the past (explanation)
    • 4.3 S-D Logic informed worldview: Source of knowledge (epistemology)
    • 4.4 S-D Logic informed worldview: Values (axiology)
    • 4.5 S-D Logic informed worldview: Guiding principles and actions (praxeology)
    • 4.6 S-D Logic informed worldview: A model of the future (prediction)
    • 5. The need for a shift from G-D to S-D Logic
    • 6. The G-D and S-D Logic debate
    • 6.1 Faction 1: Supportive of S-D Logic
    • 6.2 Faction 2: Resistant to S-D Logic
    • 6.3 Faction 3: Hesitant but critical and/or hopeful
    • 7. Positioning S-D Logic as a viable approach for BI
    • 7.1 Insights emphasising the viability of using S-D Logic
    • 7.2 Addressing insights about S-D Logic to warrant the use thereof
    • 8. Conclusion
  • Chapter 4 Part 1: Case study background and context
    • 1. Introduction
    • 2. Case study structure, input and notation
    • 3. BI customers and BI providers in the case study context
    • 4. Fortune Bank overview
    • 4.1 Location and size
    • 4.2 Structure and nature of business
    • 4.3 BI and BI projects at Fortune Bank
    • 4.4 Behaviour and culture
    • 4.5 History and background
    • 4.6 Method of operation
    • 5. BI vendors
    • 6. Conclusion
  • Chapter 4 Part 2: Case study insights on BI challenges
    • 1. Introduction
    • 2. Research data used to inform this part of the case study
    • 3. The promise of BI
    • 3.1 High expectations for BI
    • 3.2 Purpose of BI
    • 3.3 Heavy investment in BI
    • 3.4 BI vendors’ contribution to high expectations and heavy investment
    • 4. The challenge of BI: perceptions that BI does not consistently serve its purpose
    • 4.1 BI customers’ perceptions
    • 4.2 BI providers’ perceptions
    • 4.3 Insights and observations
    • 5. The challenge of BI: BI’s challenges and measures to address BI’s challenges
    • 5.1 Challenges identified through observation at Fortune Bank
    • 5.2 Challenges raised by case study participants
    • 5.3 Analysis and discussion of case study challenges
    • 5.4 Attempts to solve BI’s challenges
    • 5.5 Consolidation of literature and case study findings on BI’s challenges
    • 6. Conclusion
  • Chapter 4 Part 3: Case study insights on a dominating worldview for BI
    • 1. Introduction
    • 2. Research data used to inform this part of the case study
    • 3. Elements of BI’s worldview
    • 4. Contextualising BI’s perceptions
    • 5. Consolidating a worldview of BI from literature and practice
    • 6. BI’s challenges: in the context of the dominant worldview that emerges for BI
    • 7. Conclusion
  • Chapter 5: A conceptual shift from G-D to S-D Logic for BI
    • 1. Introduction
    • 2. BI’s dominant worldview grounded in G-D Logic
    • 3. How the G-D Logic in BI’s worldview contributes to the prevalence of BI challenges
    • 4. A conceptual shift from G-D to S-D Logic in terms of BI’s dominant worldview
    • 4.1 A shift from value-in-exchange to value-in-use (A)
    • 4.2 A shift from the view that competitive advantage is gained through value embedded in
    • goods and their features to competitive advantage gained through operant resources
    • embedded in value networks (B)
    • 4.3 A shift from separation of customer and provider to a customer-oriented and relationship
    • focus (C)
    • 4.4 A shift of focus from the means, production and producer to focus on both production
    • and use activities and role players (D)
    • 4.5 A shift from “services” to “service” and BI as a service flow informed by S-D Logic (E)
    • 5. Conceptual approaches to apply S-D Logic to BI with the aim of contributing towards
    • overcoming BI’s prevailing challenges
    • 5.1 The “BI value coin”
    • 5.2 The ten FPs of S-D Logic adapted for BI
    • 5.3 Guiding principles to apply S-D Logic to BI
    • 6. Opportunities to overcome BI’s challenges
    • 7. Implications of and potential arguments against a shift from G-D to S-D Logic for BI
    • 7.1 The argument that S-D Logic is not a new perspective
    • 7.2 Arguments highlighting complications arising from the emerging nature of S-D Logic
    • 7.3 The implication of significant paradigm shifts for participants in the BI service flow
    • 7.4 The implication of the potential co-destruction of value
    • 8. Conclusion
  • Chapter 6: Conclusion
    • 1. Introduction
    • 2. Key findings
    • 2.1 Core challenges experienced in BI
    • 2.2 Attempts made to address core challenges
    • 2.3 Characteristics of BI’s worldview
    • 2.4 Differences in worldview characteristics between BI customer and BI provider
    • 2.5 A typical or dominant worldview for BI
    • 2.6 BI’s dominant worldview grounded in G-D Logic
    • 2.7 The relationship between BI’s dominant worldview, its challenges and G-D Logic
    • 2.8 New avenues to overcome BI’s prevailing challenges
    • 3. Contribution
    • 3.1 Contributions identified in Chapter
    • 3.2 Additional contributions and key insights
    • 3.3 Key academic contributions
    • 4. Future research
    • 5. Overall conclusion
    • Bibliography


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