The COVID-19 pandemic put unprecedented pressure on supply chains and emphasized the importance of effective supply chain planning. Before COVID, just-in-time inventory was pushed as the best inventory management method because it allows organizations to reduce expenses by decreasing the inventory on hand. However, as the pandemic demonstrated, while this method may save you money, it leaves you extremely vulnerable when disruptions and emergencies occur. At the same time, you don’t want to have too much inventory on hand, not only because of the maintenance costs but also because it increases waste as many products with an expiration date are disposed of before they can be used. One recent research report found that, on average, 13% of inventory stock for an operating room expires on the shelf.
While effective supply chain planning and inventory management is critical in every industry, it’s particularly crucial in healthcare, where supply chain disruptions can impact patient care, safety, and outcomes. To find the optimal approach and avoid having too much or too little inventory, the manufacturer and healthcare organization need to have visibility both upstream and downstream through the supply chain. Visibility into the entire process gives all parties in the supply chain the agility to leverage different source providers when disruptions occur.
To attain full visibility, healthcare organizations need to blend data from many external and internal sources. Organizations that struggle with data access, transparency, and data accuracy need to solve these challenges to move toward continuous supply chain planning and help ensure continuous operations.
A voluminous amount of supply chain data is available today, and the amount grows exponentially every year. The problem many healthcare organizations face isn’t a lack of data, it’s the inability to understand the data and access the necessary data to develop meaningful insights.
In this use case, we’ll show you how Oracle Data Platform for healthcare can simplify the process of using advanced analytics and machine learning to insulate your supply chain from disruptive events while lowering costs and increasing patient safety.
There are three main options for injecting data into an architecture to build a flexible, open, and performant data platform.
Data persistence and processing is built on three (optionally four) components.
The ability to analyze, learn, and predict is built on four technologies.
Having a full view of the entire supply chain will allow healthcare organizations to answer many questions they’re unable to answer today—but to do so, they must have the right data platform. The platform should be flexible and able to handle all the necessary data types; open and able to easily connect to other clouds, on-premises data centers, or third-party organizations; and secure. With access to all the data, healthcare organizations will be able to accomplish many objectives, which may include
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