Freight Spend Visualization and Analytics with BI Tools
Tran, Kim (2021)
Tran, Kim
2021
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Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:amk-2021060414307
https://urn.fi/URN:NBN:fi:amk-2021060414307
Tiivistelmä
Transportation or freight cost is considered to be a big part of supply chain cost to keep a manufacturing firm operated. Hence, how to optimize freight cost is a frequent question asked by many logistics specialists. In this thesis, freight data is the focus to be examined for improvement since it reflects what is happening in the operations.
This study is conducted by using qualitative research methods. Data is gathered through interviews and discussions with the key stakeholders from the case company. The selected research approach is action research because improvements were suggested based on shreds of evidence gathered from the deep involvement with the case company. After the problems were identified through the CSA process, existing knowledge about data visualization and related concepts were explored, which then, together with the suggestion from stakeholders, were used to form the proposal.
The outcome of this study is the improvement plan for freight data visualization to enhance the problem-solving process and reporting practices at the case company. Freight data is exploited by using and implementing a BI tool for reporting and analytics. The benefits for the company are significant because the key stakeholder can, later on, create and customized reports with freight data stored on the cloud. The proposal is approved by the case company and will start immediately to test its practicalities.
This study is conducted by using qualitative research methods. Data is gathered through interviews and discussions with the key stakeholders from the case company. The selected research approach is action research because improvements were suggested based on shreds of evidence gathered from the deep involvement with the case company. After the problems were identified through the CSA process, existing knowledge about data visualization and related concepts were explored, which then, together with the suggestion from stakeholders, were used to form the proposal.
The outcome of this study is the improvement plan for freight data visualization to enhance the problem-solving process and reporting practices at the case company. Freight data is exploited by using and implementing a BI tool for reporting and analytics. The benefits for the company are significant because the key stakeholder can, later on, create and customized reports with freight data stored on the cloud. The proposal is approved by the case company and will start immediately to test its practicalities.