How Do You Use Big Data to Drive Supply Chain Decision-Making?

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Tue Mar 29 13:00:29 CDT 2016

Big Data is the big buzzword that's supposed to transform business. Marketers need it to reach people, sports GMs need it to evaluate players – and hospital supply chains need it to sustain under the accountable care model.

 

The problem is, most technology vendors in healthcare haven't caught up to the fact that data housed in a hospital needs to be more universal in order to be useful; in order to be "Big Data." Its current disconnected state is preventing (and frustrating) hospital supply chains from leveraging real-time, accurate and complete information to make smart purchasing and other operational decisions to meet new measurement standards.

 

One key opportunity with Big Data is linking products to outcomes. In other words, data that provides metrics on key issues such as clinical outcomes and total costs, based on supply chain decisions.

 

Orlando Health is one example of a health organization that is working to link products to outcomes, as highlighted in this recent Healthcare Financial Management Association report. The organization uses a tool that allows product information to be shared between revenue and materials management, which means users can compare charge and cost data, helping them with a range of decisions, from accurately changing health delivery prices to ensuring charges are in line with what patients were provided.

 

Big Data will be instrumental in healthcare supply chains moving forward, as systems are asked to improve efficiency and margins year after year. While hospitals often look to their supply chain for quick cost savings, Big Data can offer a more lasting strategy toward improvement requirements which deeply affect supply chain decisions.

 

Of course, the million-dollar question is, when will we get there? Or better yet, how will we get there? This blueprint from McKinsey & Company and the Health Industry Distributors Association is a start. We're also curious to know your thoughts on when and how we'll arrive at true data-driven decision-making.