Effects of Data Science, Predictive Analytics & Big Data (DPB) on the Supply Chain (eBook, PDF)
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Bachelor Thesis from the year 2017 in the subject Business economics - Review of Business Studies, grade: 1,0, Northumbria University (Newcastle Business School), language: English, abstract: A Study on the Opportunities and Threats of Data Science, Predictive Analytics & Big Data (DPB) on the Services Supply Chain on the example of a key player in the german leasing/financial services market. Working for a financial service provider raises the awareness for certain issues within this sector and how those could be solved by means of new trends such as big data. This undergraduate thesis presen...
Bachelor Thesis from the year 2017 in the subject Business economics - Review of Business Studies, grade: 1,0, Northumbria University (Newcastle Business School), language: English, abstract: A Study on the Opportunities and Threats of Data Science, Predictive Analytics & Big Data (DPB) on the Services Supply Chain on the example of a key player in the german leasing/financial services market. Working for a financial service provider raises the awareness for certain issues within this sector and how those could be solved by means of new trends such as big data. This undergraduate thesis presents an exploration of the effects of big data on the supply chain and on decision making. A topic of significant relevance, especially since the literature review discovered that there had been insufficient research conducted on the supply chains of service providers. Furthermore, this investigation of existing literature created a frame for the content of the dissertation by displaying the roots and development of big data and its farreaching impact in and beyond the business context. The research method that was used for this dissertation consists of qualitative data collection by interviewing employees of a key player in the German leasing and asset finance market, providing insight to the business from the industry leaders viewpoint. After conducting and analysing the input, the key findings on one hand corresponded with parts of the reviewed literature in terms of the application of big data and on the other hand filled the identified gap regarding services supply chains. More specifically, as a tangible outcome an exemplary supply chain framework was created, based on the identified opportunities and threats regarding an implementation of big data as well as their critical evaluation. The results ranged from chances for increased efficiency of background processes and improved effectivity of sales processes, leading to a greater profitability on one side, to being confronted with issues of privacy, economic viability and the adaptions caused by the better decision making stemming from enhanced insights through data science, predictive analytics and big data, on the other side. In order to fully exploit these identified opportunities, further research within this field is recommenced, especially in regard to the increasing relevance of the sector and the megatrend itself as well as the actual technical implementation.
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