STRATEGIC IMPLEMENTATION OF BIG DATA AUTOMATION FOR WASTAGE MANAGEMENT REPORTING USING ANALYTICAL HIERARCHY PROCESS IN THE TOBACCO INDUSTRY

• Main Author: Guspuji Maulana, Ilham
• Format: Theses
• Language: Indonesia
• Online Access: https://digilib.itb.ac.id/gdl/view/83938
• Institution: Institut Teknologi Bandung

In today's data-driven era, big data automation is crucial, often referred to as "the new oil." Industries, particularly the fast-moving consumer goods (FMCG) sector like the tobacco industry, must undergo digital transformation to stay competitive. The integration of big data automation with reporting processes is significantly correlated, as it can automate repetitive reporting tasks, enhancing efficiency. This automation enables decision-makers to make faster and more accurate decisions. This research focuses on assessing the capacity and factors involved in the collaboration between the operations department and the digital team to automate repetitive reporting processes by integrating big data from various sources such as SAP and Microsoft Forms. The study employs a combination of qualitative and quantitative methods, along with the Analytic Hierarchy Process (AHP), to identify optimal business solutions. Insights from this research prioritize big data automation and reporting projects to meet business needs. Results indicate among four alternative project groups, the Central Data Wastage project is the top priority with a score of 51.7%, followed by SMD Wastage at 25.2%, PMD Wastage at 14.7%, and FMD Wastage at 8.4%. Five stakeholders participated in this research, including a product manager, business user, business analyst, and two developers. These participants contributed to assessing criteria, sub-criteria, and alternative project groups. This research not only helps prioritize projects but also facilitates seamless digitalization within the operations team, fostering synergy with the digital team