Developing a Power BI Dashboard for Operational Efficiency : a case study of Divithura Tea Factory
Guruge, Thelikada Palliyage Nilushika Tharangani (2025)
2025
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Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:amk-2025111928725
https://urn.fi/URN:NBN:fi:amk-2025111928725
Tiivistelmä
This thesis aims to develop a Power BI dashboard to improve operational efficiency at Divithura Tea Factory in Sri Lanka while providing real-time insights into tea production metrics and enabling data-driven decision-making. The study can also be considered as a modest but meaningful attempt to apply dashboard technology and data-driven decision-making practices in the Sri Lankan tea industry.
The applied action research strategy was adopted to develop the primary solution of this study. This approach aligns well with the thesis objective while providing a practical and data-driven solution that is tailored to the specific needs of the case company. The process began with a current state analysis (CSA), then a review of existing knowledge, and finally the iterative development of the dashboard. In this thesis, the methodology involves combining qualitative and quantitative data. Data collection primarily includes interviews and discussions held with the stakeholders and observations derived through a data audit. The data was collected in three data collection rounds and followed by data analysis using thematic methods to inform the development of the dashboard. Finally, the prototype undergoes validation with key stakeholders to ensure both usability and accuracy.
The research integrated both theoretical and practical elements. The theoretical framework focused on some essential elements: KPI selection, data accessibility, and dashboard development, while the practical component translated these concepts into a dashboard, including five different interfaces covering strategic, tactical, and operational views classified based on stakeholder requirements.
The outcome, the dashboard prototype, gave a centralized visualization of factory operations, performance, collection line efficiency, and supplier metrics. It aims to reduce reporting delays, enhance data quality, and support more efficient decision-making. Overall, this project marks an important initial step toward data-drivenness in the case company, demonstrating how business analytics tools can strengthen operational control and productivity.
The applied action research strategy was adopted to develop the primary solution of this study. This approach aligns well with the thesis objective while providing a practical and data-driven solution that is tailored to the specific needs of the case company. The process began with a current state analysis (CSA), then a review of existing knowledge, and finally the iterative development of the dashboard. In this thesis, the methodology involves combining qualitative and quantitative data. Data collection primarily includes interviews and discussions held with the stakeholders and observations derived through a data audit. The data was collected in three data collection rounds and followed by data analysis using thematic methods to inform the development of the dashboard. Finally, the prototype undergoes validation with key stakeholders to ensure both usability and accuracy.
The research integrated both theoretical and practical elements. The theoretical framework focused on some essential elements: KPI selection, data accessibility, and dashboard development, while the practical component translated these concepts into a dashboard, including five different interfaces covering strategic, tactical, and operational views classified based on stakeholder requirements.
The outcome, the dashboard prototype, gave a centralized visualization of factory operations, performance, collection line efficiency, and supplier metrics. It aims to reduce reporting delays, enhance data quality, and support more efficient decision-making. Overall, this project marks an important initial step toward data-drivenness in the case company, demonstrating how business analytics tools can strengthen operational control and productivity.