Erhebung der Potentiale und Hürden für den Einsatz von Data Mining in der Absatzplanung der oberösterreichischen Prozessindustrie

Abstract

In today's business world, characterized by rapid changes and increasing complexity, the strategic importance of sales planning in the process industry of Upper Austria is becoming increasingly apparent. Against this backdrop, this bachelor thesis examines the role of data mining technologies as tools for optimizing sales planning and coping with market-related uncertainties. These technologies, gaining importance in both business-tocustomer and business-to-business areas, offer the potential to make more accurate predictions through the analysis of large data sets, thereby improving decision-making. The thesis is structured into five chapters, initially dealing with the theoretical foundations. Special attention is given to the significance of digital transformation, digitization, business intelligence, advanced analytics, big data, and data mining. Subsequently, an empiricalqualitative research design is presented, based on expert interviews and qualitative content analysis. This method was chosen to gain a deep understanding of the challenges, success factors, hurdles, potentials, and future application areas of data mining in practice. The findings of the study show that the introduction and use of data mining in sales planning bring not only technical and economic challenges but also require profound organizational adjustments. These challenges include integrating data mining technologies into existing IT systems, ensuring data quality, and overcoming resistance within the organization. Despite these obstacles, the results suggest that data mining can significantly enhance efficiency and competitiveness, particularly by improving responsiveness to market changes and optimizing costs. Furthermore, the study identifies key success factors that support the successful implementation of data mining. These include positive experiences with data mining from past projects or external examples, support from top management, provision of necessary resources, and a clear strategic orientation. The study highlights potentials for future implementations, which, according to experts, mainly lie in improving operational efficiency and decision-making. Finally, the thesis provides an outlook emphasizing the growing importance of data mining due to ongoing digitalization, the increasing flood of data, and the advancement of technologies such as artificial intelligence. It underscores the necessity for companies to invest in these technologies to strengthen their competitive position.

Date of Award	2024
Original language	German (Austria)
Supervisor	Harald Dobernig (Supervisor)