Supply Chain Requisition System with Predictive Analysis and Supply Utilization Forecasting using Multiple Linear Regression Algorithm



In the year 2022, Quezon Medical Center (QMC) had a total of 1,485 personnel and seven main divisions that deliver health care services to the patients of Quezon Province. As additional personnel are hired, there is a corresponding increase in the utilization rate of the various supplies in the daily operations of the institution. As such, Supply Chain Division faces some challenges in requisition and inventory procedures such as still carrying out paper-based materials, reports manually encoded using the Microsoft Excel application, printer for processing and storage of data, and in difficulty in managing inventory due to a lack of control of the supplies resulting in a significant loss of revenue occurs overstocking leads to wastage of both the procured products and funds and understocking leads to the failure of meeting the demand and poor customer satisfaction. Furthermore, it was proposed for the fast retrieval of data, create a new requisition feature that reduces the amount of paper used, the system distribution of the requisition for review and approval or rejection, and generate an accurate weekly, and monthly, or yearly report for an inventory of the requested item, and forecasts or predict supply chain utilization report. In addition, the method used is Multiple Linear Regression for predicting how many supplies are utilized. This capstone project is developed to help the hospital department do the task efficiently and prioritize the service request and forecast report based on their importance and urgency to the overall supply chain division process. Future research will include an assessment of the system with the personnel and user to assess the effectiveness of this system and gather some information on improvements


multiple linear regression
predictive analytics
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