| dc.description.abstract | This dissertation delves into the intricate process of shifting from conventional
inventory management practices to digital methodologies, addressing the challenges faced
by businesses in effectively harnessing and processing raw data. The study articulates the
real-world problem, employing Power BI Dashboards as a powerful tool to
comprehensively scrutinize various dimensions of the identified issue.
Through a meticulous exploration, the dissertation discerns a pivotal challenge
arising from the absence of a well-defined purchasing roadmap. Leveraging raw data and
harnessing the capabilities of Power BI Dashboards, the author develops a sophisticated
computational model designed to optimize purchasing costs. This model operates within
the constraints imposed by budgetary limitations, specifically focusing on ordering costs
and the imperative reduction of inventory value.
Beyond the confines of mathematical formulations, this dissertation places
significant emphasis on the visualization of results through dynamic dashboards. Such
visual representations facilitate businesses in effortlessly tracking and utilizing pertinent
information, while also vividly illustrating the transformative changes witnessed before
and after the implementation of the novel method. Consequently, the study not only
proposes theoretical enhancements but also provides actionable insights to improve
inventory management efficiency and strategically optimize purchasing costs, thus offering
invaluable support for the nuanced decision-making processes within the business
landscape. | en_US |
