Interactive data visualization of the CSPC supply and property inventory management system using business intelligence / Ma. Gabrielle S. Gonzales, Eric F. Pino, and Jehan R. Talagtag

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Dissertation note: Undergraduate Thesis (BSIS) - Information System. Camarines Sur Polytechnic Colleges, 2024. Abstract: The increasing reliance on technology has transformed inventory management through business intelligence (BI) tools. This study integrates Power BI into the Supply and Property Inventory Management System (SPIMS) of Camarines Sur Polytechnic Colleges (CSPC) to optimize inventory tracking, demand forecasting, and cost efficiency. The study employs descriptive analysis and statistical models to analyze inventory levels, stock fluctuations, and procurement patterns. Findings indicate inefficiencies in inventory control, with overstocking of disinfectant bleach (430 excess units per month) and stockout risks for high-demand items like accountable forms. Demand forecasting analysis showed stable demand projections, but poor inventory monitoring led to excessive holding costs, particularly for the T8 LED Tube, which incurred a holding cost of P17,068. Safety stock analysis identified critical items requiring buffer stock management, such as batteries and bleach, which faced demand fluctuations. The cost analysis revealed that office supplies contributed to P69,578 in total inventory expenses, highlighting procurement inefficiencies. To enhance inventory operations, the study recommends expanding data collection to include supplier performance metrics, implementing predictive analytics for real-time inventory monitoring, and conducting regular staff training on Bl tools. Additionally, optimizing stock levels through improved procurement strategies can reduce unnecessary expenses. The study concludes that Power BI significantly enhances CSPC's inventory management, but further refinement in data accuracy, system integration, and strategic stock planning is necessary for long-term efficiency. Future research should explore the integration of machine learning for more accurate forecasting and automation of procurement workflows.
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Undergraduate Thesis (BSIS) - Information System. Camarines Sur Polytechnic Colleges, 2024.

Includes bibliographical references.

The increasing reliance on technology has transformed inventory management through business intelligence (BI) tools. This study integrates Power BI into the Supply and Property Inventory Management System (SPIMS) of Camarines Sur Polytechnic Colleges (CSPC) to optimize inventory tracking, demand forecasting, and cost efficiency. The study employs descriptive analysis and statistical models to analyze inventory levels, stock fluctuations, and procurement patterns. Findings indicate inefficiencies in inventory control, with overstocking of disinfectant bleach (430 excess units per month) and stockout risks for high-demand items like accountable forms. Demand forecasting analysis showed stable demand projections, but poor inventory monitoring led to excessive holding costs, particularly for the T8 LED Tube, which incurred a holding cost of P17,068. Safety stock analysis identified critical items requiring buffer stock management, such as batteries and bleach, which faced demand fluctuations. The cost analysis revealed that office supplies contributed to P69,578 in total inventory expenses, highlighting procurement inefficiencies. To enhance inventory operations, the study recommends expanding data collection to include supplier performance metrics, implementing predictive analytics for real-time inventory monitoring, and conducting regular staff training on Bl tools. Additionally, optimizing stock levels through improved procurement strategies can reduce unnecessary expenses. The study concludes that Power BI significantly enhances CSPC's inventory management, but further refinement in data accuracy, system integration, and strategic stock planning is necessary for long-term efficiency. Future research should explore the integration of machine learning for more accurate forecasting and automation of procurement workflows.

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