How Much do Customer Ordering Practices Drive Medical Supplies Distribution (In)Efficiency for Primary Care Markets?
Jeff Shockley, Virginia Commonwealth University
Jason R. W. Merrick, Virginia Commonwealth University
Xiaojin Liu, Virginia Commonwealth University
Jeffery S. Smith, Virginia Commonwealth University
In examining the intricate relationship between customer ordering and supply chain distribution performance, this study concentrates on the U.S. medical supplies industry, where wholesalers apply substantial data visibility. By scrutinizing the ordering practices of wholesale medical supplies buyers over a two-year period, researchers employ the concept of data clumpiness to unravel how these practices impact the inefficiency of distribution within the industry.
Let’s dive deeper with a brief Q&A session with a member of the research team, Associate Professor of Supply Chain Management and Analytics, Jeff Shockley, Ph.D.:
How can businesses in other industries use your study’s insights to improve distribution efficiency linked to customer ordering?
It is essential to understand that we are dealing with an industry supply chain with a strong business-to-business (B2B) focus made up of very few wholesalers.
Specifically, we looked at the clumpiness (non-conformance to equal spacing) of all customer order patterns related to the order-sizing decisions (how much the primary care customer decided to order over a given time) coupled with the frequency of the order patterns (where they replenish stock based on need or ordering in fixed intervals) using data from a medical supplies industry wholesale distributor.
While our focus in analyzing these data patterns was within the medical supplies industry, the methodology we used in the study could be widely applied to other industries where a large wholesale distributor may serve a larger number of B2B customers. Until now, segmenting customers based on their actual behaviors revealed in data was mostly confined to the e-commerce space studying customer website visitation. However, this approach to segmenting customers based on their patterns of ordering can also help with supply chain management, particularly for a large industry wholesaler with good downstream customer data visibility. It shows the value of using patterns revealed in customer data to improve supply chain operating efficiency.
What practical changes would you recommend for wholesale distributors, especially when dealing with buyers ordering across multiple categories or in industries with centralized purchasing practices?
Specifically, the analysis revealed specific customer groups that might be underperforming from a supply chain cost of delivery standpoint.
For instance, we found that community health centers served by the wholesale distributor often engaged in suboptimal ordering behaviors that could undermine the cost efficiency of distributing products to this growing sector, and that there were opportunities to create “win-win” coordination scenarios through technology-sharing and order flow coordination to benefit both parties in the relationship. Our analysis further revealed specific medical supply categories that were “loss leaders” when fulfilled in isolation by specific customer groups. This knowledge might be used in future business proposals (contracts) with those customers, or to target those categories for specific process improvement efforts.
Finally, we see that customer’s use of centralized (or group) purchasing (something that is increasingly prevalent across healthcare) doesn’t have to undermine cost performance for wholesalers. We find evidence that centralized (group) purchasing costs to the wholesaler could be fully mitigated when combined with specific purchasing and order fulfillment coordination practices.
Read the full research paper: https://onlinelibrary.wiley.com/doi/full/10.1111/poms.14068