5 Supply Chain Analytics to Give You a Valuable Edge

Analytics is more than a buzzword in a healthcare supply chain setting, it can be a transformative process leading to actionable insights into your supply chain operations. However, you need to understand how analytics can help you before you try to apply it as a problem-solving tool. There are five stages of analytics that you need to know about:

  1. Descriptive Analytics is the rudimentary stage of analytics that creates summaries of historical data that yield information that is useful in understand your supply chain activities. It’s frequently represented by dashboards, alerts and visualization reports.
  2. Diagnostic Analytics is an advanced analytics stage which examines data to answer the question “Why did it happen?”. Like why did your I.V. supplies budget increase unexpectedly by 12% in the first quarter of 2018. This is accomplished with drill downs, data discovery, data mining and correlations.
  3. Predictive Analytics encompasses a variety of statistical techniques (e.g., data mining, predictive modelling and machine learning) that ask the question, “ What could happen?” by employing multiple scenarios to predict the future. As an example, you might want to know the number of pacemakers you will be implanting in the next 12 months based on historical and demographic trends in your region.
  4. Prescriptive Analytics is a stage in business analytics that asked the question, “What should I do?” in a given situation. It uses predictive analytics to find the answer. For instance, what should my hospital’s markup be based on peer hospital trends for a new chargeable product that has been added to my inventory?
  5. Cognitive Analytics harnesses the power of machine learning and artificial intelligence to gain insight into new patterns, data sources, risks and opportunities in your supply chain. Like understanding how your nurses decide when to charge or not to charge for a product.

The healthcare supply chain has now evolved into a highly sophisticated organism, so supply chain leaders need to employ new tools to understand, predict and speed up their supply chain operations. From personal experience, there is no better way to do so  than by employing supply chain analytics to obtain the answers that your management is or will be asking soon. Not to do so, could  be dangerous to your hospital, systems or IDN’s financial health.