Faculty of Commerce, Law and Management (ETDs)
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Item The Use of Data Analytics in Strategic Decision-Making in a South African Pay-TV Company(University of the Witwatersrand, Johannesburg, 2021) Reddy, Prebashni; Chidzungu, ThandiweThe extent to which data and analytics inform decision-making in the Pay-TV industry in South Africa is not known. Netflix used data to achieve a competitive advantage and became a leading player in the streaming services arena. Blockbusters no longer exist because they did not change with the times and listen to what their customers wanted. Companies must use the data that they collect to make decisions and remain relevant in a continually evolving business environment. This research aims to evaluate the extent to which senior management use data and analytics to make decisions. The study measured the relationship of each of the following 3 constructs: data literacy, data accessibility, and data usage with data-driven decision making. The researcher carried out an exploratory study employing a quantitative and observational design approach. Adopting a cross- sectional methodology and drawing on a purposive nonprobability sample of senior managers from a South African Pay-TV company. An online structured interview survey was used to collect data from a population of 294 senior managers who were assumed to be decision-makers. The findings of the study were that data usage, data literacy, and data accessibility each have a positive relationship with data-driven decision-making. The research identified opportunities for the South African Pay-TV company to improve the use of data in decision-making for better- informed decisions and better business performance through a 3-step programme which was recommended should form part of their data strategy. To improve data literacy amongst senior management and other decision-makers a continuous programme of training in the skills to interpret and understand data and analytics is recommended as the first step and arguably most important step. Crafting and implementing an accessibility strategy is the next step and driving usage of that data and analytics is the last and crucial step in the programme. The findings of this study supported by previous research indicate that this company will improve performance and outperform its competitors with the use of data in decision making.Item Bias in data used to train salesbased decision-making algorithms in a South African retail bank(2021) Wong, AliceBanks are increasingly using algorithms to drive informed and automated decision-making. Due to algorithms being reliant on training data for the model to learn the correct outcome, banks must ensure that the customer data is securely and fairly used when creating product offerings as there is a risk of perpetuating intentional and unintentional bias. This bias can result from unrepresentative and incomplete training data or inherently biased data due to past social inequalities. This study aimed to understand the potential bias found in the training data used to train sales-based decision-making algorithms used by South African retail banks to create customer product offerings. The research adopted a qualitative approach and was conducted through ten virtual one-on-one interviews with semi-structured questions. Purposive sampling was used to select banking professionals from data science teams in a particular South African retail bank across demographics and levels of seniority. The data collected from the participants in the interviews were then thematically analysed to draw a conclusion based on the findings. Key findings included: An inconsistent understanding across data science teams in a South African retail bank around the prohibition of using the gender variable. This could result in certain developers using proxy variables for gender to inform certain product offerings. A potential gap in terms of the potential usage of proxy variables for disability (due to non-collection of this demographic attribute) to inform certain product offerings. Although disability was not identified as a known biased variable, it did, however, raise the question of whether banks should be collecting the customer’s disability data and doing more in terms of social responsibility to address social inequalities and enable disabled individuals to contribute as effectively as abled individuals. As algorithms tend to generalise based on the majority’s requirements, this would result in a higher error rate of underrepresented groups of individuals or minority groups. This could result in financial exclusion or incorrect products being offered to certain groups of customers iii which, if not corrected, would lead to the continued subordination of certain groups of customers based on demographic attributes.Item Opportunities and challenges of open banking in South Africa(University of the Witwatersrand, Johannesburg, 2022) Dreyer, TanyaThere is much hype and speculation around the potential of open banking to increase financial inclusion and competition among incumbent banks in developed and developing economies (Plaitakis & Staschen, 2020 and Zeller & Dahdal, 2021). Mastercard has gone so far as to call it “the most transformational trend in banking since digitization” (Mastercard, 2020). The purpose of this study is therefore to assess the challenges and opportunities of implementing open banking in South Africa as well as potential frameworks for implementation. Further as the existing knowledge base for open banking is globally limited and predominantly focussed on developed economies, it is vital to publish information from the perspective of an emerging economy that is also one of the largest economies in Africa.