Big Data refers to large unstructured datasets from multiple dissimilar sources. Using Big Data Analytics (BDA), insights can be gained that cannot be obtained by other means, allowing better decision-making. Big Data is disruptive, and because it is vast and complex, it is difficult to manage from technological, regulatory, and social perspectives. Big Data can provide decision-makers (knowledge workers) with bottom-up access to information for decision-making, thus providing potential benefits due to the democratisation of decision-makers in data-driven decision-making (DDD). The workforce is enabled to make better decisions, thereby improving participation and productivity. Enterprises that enable DDD are more successful than firms that are solely dependent on management's perception and intuition. Understanding the links between key concepts (Big Data, democratisation, and DDD) and decision-makers are important, because the use of Big Data is growing, the workforce is continually evolving, and effective decision-making based on Big Data insights is critical to a firm's competitiveness. This research investigates the influence of Big Data on the democratisation of decision-makers in data-driven decision-making. A Grounded Theory Method (GTM) was adopted due to the scarcity of literature around the interrelationships between the key concepts. An empirical study was undertaken, based on a case study of a large and leading financial services organisation in South Africa. The case study participants were diverse and represented three different departments. GTM facilitates emergence of novel theory that is grounded in empirical data. Theoretical elaboration of new concepts with existing literature permits the comparison of the emergent or substantive theory for similarities, differences, and uniqueness. By applying the GTM principles of constant comparison, theoretical sampling and emergence, decision-makers (people, knowledge workers) became the focal point of study rather than organisational decision-making processes or decision support systems. The concentrate of the thesis is therefore on the democratisation of decision-makers in a Big Data environment. The findings suggest that the influence of Big Data on the democratisation of the decisionmaker in relation to DDD is dependent on the completeness and quality of the Information Systems (IS) artefact. The IS artefact results from, and is comprised of, information that is extracted from Big Data through Big Data Analytics (BDA) and decision-making indicators (DMI). DMI are contributions of valuable decision-making parameters by actors that include Big Data, People, The Organisation, and Organisational Structures. DMI is an aspect of knowledge management as it contains both the story behind the decision and the knowledge that was used to decide. The IS artefact is intended to provide a better and more complete picture of the decision-making landscape, which adds to the confidence of decision-makers and promotes participation in DDD which, in turn, exemplifies democratisation of the decisionmaker. Therefore, the main theoretical contribution is that the democratisation of the decisionmaker in DDD is based on the completeness of the IS artefact, which is assessed within the democratisation inflection point (DIP). The DIP is the point at which the decision-maker evaluates the IS artefact. When the IS artefact is complete, meaning that all the parameters that are pertinent to a decision for specific information is available, then democratisation of the decision-maker is realised. When the IS artefact is incomplete, meaning that all the parameters that are pertinent to a decision for specific information is unavailable, then democratisation of the decision-maker breaks down. The research contributes new knowledge in the form of a substantive theory, grounded in empirical findings, to the academic field of IS. The IS artefact constitutes a contribution to practice: it highlights the importance of interrelationships and contributions of DMI by actors within an organisation, based on information extracted through BDA, that promote decisionmaker confidence and participation in DDD. DMI, within the IS artefact, are critical to decision-making, the lack of which has implications for the democratisation of the decisionmaker in DDD. The study has uncovered the need to further investigate the extent of each actor's contribution (agency) to DMI, the implications of generational characteristics on adoption and use of Big Data and an in-depth understanding of the relationships between individual differences, Big Data and decision-making. Research is also recommended to better explain democratisation as it relates to data-driven decision-making processes.
| Identifer | oai:union.ndltd.org:netd.ac.za/oai:union.ndltd.org:uct/oai:localhost:11427/32509 |
| Date | January 2020 |
| Creators | Hassa, Ishmael |
| Contributors | Tanner, Maureen, Brown, Irwin |
| Publisher | University of Cape Town, Faculty of Commerce, Department of Information Systems |
| Source Sets | South African National ETD Portal |
| Language | English |
| Detected Language | English |
| Type | Doctoral Thesis, Doctoral, PhD |
| Format | application/pdf |
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