The Application of Data Management Technology in Implementing Inventory Model - Semiconductor Industry : Business Case Study
Do, Thi (2023)
2023
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Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:amk-2023120433949
https://urn.fi/URN:NBN:fi:amk-2023120433949
Tiivistelmä
This thesis studies the inventory planning model designed for Silicon Laboratories Finland Oy. The study took place when the case company adjusted its inventory strategy after the supply shortage caused by the COVID-19 pandemic. In response to the circumstance, the paper aimed to explore the advantages of the new inventory model for the company and proposed an initial implementation plan leveraging the advanced data management platform.
The essential theories such as the utilization of forecast data to optimize inventory planning and the achievement of a competitive edge through logistics planning were underscored. The new inventory model can assist in the enhancement of coordination among diverse departments and bridge the information gaps within the supply chain effectively by using an advanced data management platform. Due to the practical aspect of this study, a mixed method approach between the quantitative research method and project-based method was employed. Data was gathered through meetings and emails to harness actual information. Thus, all collected data was used to support the author and the team in analyzing results and planning subsequent steps. Ultimately, the thesis aims to offer tactical recommendations for future implementation and unveil potential areas for further research.
The essential theories such as the utilization of forecast data to optimize inventory planning and the achievement of a competitive edge through logistics planning were underscored. The new inventory model can assist in the enhancement of coordination among diverse departments and bridge the information gaps within the supply chain effectively by using an advanced data management platform. Due to the practical aspect of this study, a mixed method approach between the quantitative research method and project-based method was employed. Data was gathered through meetings and emails to harness actual information. Thus, all collected data was used to support the author and the team in analyzing results and planning subsequent steps. Ultimately, the thesis aims to offer tactical recommendations for future implementation and unveil potential areas for further research.