This is the Final Thesis wrote by Pol Aguirre Antonell within Infineon Technologies during the spring semester of 2023. The title of the Thesis is the Design of a tool to drive improved Supply Chain Planning decisions within the semiconductor Industry. We start of explaining the context to understand the necessity of agile planning tools and data analysis within the team. How the Supply Chain and the production of semiconductor products is key for a prosperous European semiconductor segment. To have a good understanding of the needs of the team and company, we study and present the Supply Chain Planning process of Infineon. Having this knowledge, we can start the process of creating the right and best tool to solve the knowledge gap between planning allocation and revenue impacts. To do so we benchmark the existing Data tools and solutions within Infineon Technologies, and we choose to create a Tableau Dashboard. This Dashboard will be connected to an automated data-source. Managed by a Tableau prep flow connected to the Data-lake through Cloudera Hadoop. Coding the Dashboard, it has also been an important practical part of this Thesis and it is presented in Chapter 6. Effective coding, seems simple, light, and easier to explain. Maybe you can explain that most complexity comes from the Waterfall chart whereas the rest requires less workarounds. Overall, we present the use of Tableau workarounds towards a lean dashboarding, and a one-stop dashboard. Lean Dashboarding is as important as having accurate data , and in Chapter 7 there is explanations on how and why the dashboard meets the design and interactivity requirements set by the different stakeholders and key users. To finalize, we study some business analysis that derives uniquely thanks to the report. In this las part we address how the team can integrate the findings from this analysis into their process. Overall, the thesis includes all steps of creating a Data Analysis tool and Dashboard. From idea to result
