Faculty of Commerce, Law and Management (ETDs)
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Item The Impact of Big Data Analytics in the South African Retail Industry(2023) Sethathi, Mohlahlami DavidThe utilisation of big data analytics has emerged as a promising way for companies to improve their performance, and more retailers are adopting this technology to enhance their customer service and competitive abilities. Despite the extensive exploration of the impact of big data analytics within the global retail context, a noticeable research gap exists with regard to its specific utilization by South African retailers to improve their competitiveness. The purpose of this study was to assess the impact of big data analytics in the South African industry. The research design employed in this study is qualitative; the data collection was done through semi-structured interviews with two South African retail organisations. The data was analysed using the thematic-analysis process to formulate codes and themes emerging from the study. The study's findings revealed that the adoption of big data analytics in the South African retail industry is limited. However, those retailers leveraging this technology are gaining notable benefits, such as a better understanding of customers, effective inventory management, strategic pricing, and accurate forecasting. Conversely, challenges encountered by South African retailers in implementing big data analytics include insufficient skills, poor infrastructure, cost, and lack of support from top management. The study's implications underscore the critical role of skill development, data utilization, infrastructure, and leadership support in successful big data analytics implementation within the South African retail sector. These findings provide a comprehensive framework for navigating the complexities of data-driven decision-making, offering valuable guidance for strategic investments and sustained competitiveness in an evolving technological landscape.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 The perceived value of data analytics in the South African banking sector(University of the Witwatersrand, Johannesburg, 2023) Khedama, Thembela; Munkuli, BonganiBig data analytics is a technological process that covers the processing, arranging, categorization, and analysing of large voluminous data for purposeful usage by organizations. Big data analytics has in recent times become a buzz word as it proliferates exponentially within the banking sector in South Africa due to the maturity of storage, information technology and human skills within the domain of data. Despite this, there is little literature on big data analytics within the South African banking industry. It is evident that there is utilization of big data analytics tools and processes in the banking sector, but one question remains, is there value in South African banks derive from integrating big data analytics. The objective of this study is to understand the perception on the value of big data analytics held by South African banking senior management and executives. The researcher aims to understand if big data analytics is a mere tool to perform basic analysis with little to no power to add value in business outcomes. The perception of seeing BDA as an analysis tool has led to the undervaluing of big data analytics within the South African banking industry as there are no group executive seats with data or analytics titles. To achieve the intended research outcome of this study this research adopts the qualitative approach method. The data is collected through unstructured interviews across four major banks in South Africa. A purposive sampling strategy was employed in selecting the respondents. Data analysis is conducted through thematic analysis. This study found three global themes banking executives perceived to be valuable from adopting big data analytics. These were: (1) The state of big data analytics in banking, (2) Data Skills, (3) Driver of insights. The sub themes from the state of big data analytics in banking were: (1) Processing of the right data, (2) High volumes of data in the repository, (3) advanced analytics and the right tools to analyse data. The sub themes from data skills were: (1) resources, (2) technical skills. Lastly, the sub themes from the driver of insights were: (1) organization’s performance, (2) competitiveness in banking, (3) fighting fraud and financial crime.