Intelligent Inventory Optimization

Written By

Pat Schenkel
Pat Schenkel

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Advanced Demand Data Analysis

Collecting the right data is critical to cost transformation, but the power of good data is only realized with the proper insightful analysis. This winning combination of data and analysis for many organizations is mostly underrealized, yet has unimagined potential for medical device manufacturers.

A Common Problem

As economic pressures erode financial margins, controlling costs becomes increasingly key to providing exceptional service levels, and this is remarkably apparent in the healthcare industry. According to a 2017 Cardinal Health survey of healthcare providers, 73% of administrators and 37% of frontline clinicians reported that managing costs are the greatest challenge to their organization’s success.

Similarly, a top priority for many implant medical device manufacturers is reducing inventory costs, while at the same time increasing the support of their healthcare partners. This key objective is accomplished through Data-driven Decision Making. By applying basic statistical analysis to real-time operations data, medical device manufacturers can successfully reduce inventory without compromising the necessary high service levels from their loaner facilities.

Demand Data

Medical device inventory is often (excessively) allocated based on fear and uncertainty, particularly in the loaner environments due to high stakes and complex demand signals. To mitigate this anxiety effectively, it is essential to observe real operations behavior, beyond simply looking at sales in ERP systems. Specifically, demand data–essentially inventory requests–is crucial for inventory analysis of implant medical device loaner locations. Demand is an indicator of the work Field Operations must complete ensuring surgical events occur as expected–including sourcing, delivering, and returning inventory to its home location. Demand observations comprise the sample data used in loaner inventory analysis.

Volatility

Basic descriptive statistics build the foundation for making data-driven decisions. Using demand data, it is possible to mathematically describe the environment at the SKU-location level by applying descriptive statistics–including averages, standard deviations, and coefficients of variation.

For example, average demand is the typical quantity requested for a time period, the standard deviation of the demand is how tightly dispersed the demand values are compared to the average demand, and coefficient of variation normalizes the dispersion allowing better comparison across different SKU-locations that have different scales.

These foundational statistics illustrate the volatility and scale of requests coming to each individual location. With these three measures alone, clients can prioritize asset management to focus on the highest volume and most volatile demand combinations impacting field operations.

Additional operations data further enables data-driven, systematic inventory management.

Inventory Cycle Time

Inventory cycle time is the next most important metric in establishing a demand-based par level. This is the amount of time it takes for an item to be reserved, sent to a case, and made available again. Inventory cycle times–paired with the descriptive demand statistics–facilitate the application of demand distribution models and probability models (i.e. Poisson distributions). Medical device manufacturers are able to set the desired service level and establish data-driven inventory levels.

Using Proper Statistical Analysis The Right Way Transforms Your Business

The right tools can deliver the right data, but understanding, and how to act on that data is where the value is really found. Competent statistics and analysis allow implant medical device manufacturers to use intelligent data instead of subjectivity to allocate inventory. This results in a systematic and often significant reduction of their inventory carrying costs. Further, this type of analysis recognizes two key operational levers that improve inventory costs: volatility, and inventory cycle times. Optimizing these levers, organizations squeeze out more utilization per asset and ultimately reduce their inventory carrying costs. Not only does this fulfill key initiatives for many implant medical device manufacturers, but more importantly, they are able to serve their partners better. Optimization analysis for the win-win!

The implant medical device industry is unique.

Movemedical understands the inventory issues you are trying to solve. In fact, it’s all we do.

Talk to us, learn how we can help:

877.469.3992 or info@movemedical.com

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