Demand Sensing, Replenishment and Order Management Optimization

In healthcare we usually see amazing advancements when it comes to clinical improvements but when it comes to processes, the opportunities are immense. In this article, I will focus on supply chain processes in the medical devices industry and, more specifically, order and inventory management. In Latin American countries, and Mexico is no exception, these processes involve heavy manual labor, are greatly people dependent, result in many inefficiencies for both customer (hospital) and provider (medical devices company) and, in many cases, affect patients.

In the following lines, I will try to explain the general process that takes place between many hospitals and their device providers in Latin America for consigned products. I will assume here that the process starts when the physician requests the devices. Next, the assistant retrieves the necessary products from the stockroom and brings them to the operating room. After the surgery is over, all product that is not used is returned to the stockroom. For used products, stickers are cut from the box and pasted into a notebook. At the end of the shift, the stockroom assistant manually feeds product usage into the hospital’s system to update  medical records and the cost sheets related to  patients. The stockroom assistant also types consumed products, batches and quantities into an Excel spreadsheet and sends an email to the purchasing analyst so that the product can be replaced. Usually there is no inventory validation in any system as most hospitals do not keep records of consigned inventory. A replenishment order is then sent via email to the device’s provider. The whole replenishment process can take more than five days, especially when the order management process at the provider of the devices requires manual processing as well, as is the case for this article.

This lack of technology and lack of real-time information results in inefficient processes, excessive use of working capital, delays in the order-to-cash cycle of both hospital and provider, the potential for unnecessary human errors and excessive overhead that often  adds up to poor patient care.

By using and integrating existing and new technologies, such as scanning devices, RFID, APIs and blockchain, and applying collaborative planning and demand-driven methodologies, this process can be optimized, eliminating friction from the order management process of both parties. The new process triggers the replenishment and order management processes, by using either a scanning device or RFID technologies at the point of usage, sending the demand signal throughout the hospital and provider supply chains. By integrating the different platforms involved, this can be a seamless process and can reduce 90 percent of the replenishment time. It will also provide near real-time demand sensing, a better understanding of the behavior of the consumption of products and open the door to fewer transactional conversations between customer and provider. Inventories are optimized, presenting reductions of up to 40 percent and transactional workload is eliminated as the process becomes touchless. The new demand sensing process will better position both provider and customer (the hospital) to predict and more accurately forecast product needs and ensure product availability. Having real-time point of use (POU) demand will provide the necessary inventory in the right customer locations without having to deliver excess amounts of inventory that will then be at risk of obsolescence.  

In addition, POU data can be used to automatically bill and replenish customers, while providing complete transparency to utilization. Customers can rely on and trust their vendors will deliver inventory when it is needed and offload a significant amount of work related to requisitioning, purchase order (PO) creation and submission. Backorder information can be predicted in advance and customers can be notified to improve patient care by alerting them and offering alternative products when a specific product is not available.

Following are some technical definitions taken from the APICS dictionary that are key to the collaborative planning process:

ATP: Available to Promise inventory. As per the definition in the APICS dictionary, in operations, it is the uncommitted portion of a company’s inventory and planned production maintained in the master schedule to support customer-order promising. The ATP quantity is the uncommitted inventory balance in the first period and is normally calculated for each period in which a Master Production Schedule (MPS) receipt is scheduled. 

ATP for period 1 = Available inventory - customer orders (due and overdue)

ATP for Period 2 = ATP Period 1 + MPS - customer orders (due and overdue)

In logistics, ATP, is the quantity of inventory of a finished product that is or will be available to a customer order(s) based on the required shipped date. It considers incoming transit inventory.

ROP: Reorder Point. The APICS dictionary, 15th edition, defines Order Point as the inventory level where, if the total stock on hand plus on order falls to or below that point, action is taken to replenish the stock. The order point is normally calculated as forecasted usage during the replenishment lead time plus safety stock

ROP=SS+Average Demand During Lead Time (LT)

SS=Z(service Level)* LT*Demand Standard Deviation

Demand During LT=Average Demand*LT

Lead Time (LT): The APICS dictionary, 15th edition, defines Lead Time in the logistics context as the time between recognition of the need for an order and the receipt of goods. Individual components of LT can include order preparation time, planning time (time between revisions), processing time, move or transportation time, and receiving and inspection time.

Z (Service level): This is defined as the probability of not having stock-outs. It is used in the safety stock equation in terms of its Z score. In statistical terms, the Z score refers to the number of standard deviations above that mean that a parameter can fluctuate. Here, with respect to safety stock, Z(service level) is the number of standard deviations above mean demand needed to protect you from having stock-outs. If the Z-score equals 1.04, the safety stock will protect against one standard deviation; there will be enough inventory 85 percent of the time. But the desired service level is 98 percent  so you need to hold two times the safety stock in the case of 85 percent Service Level.

And finally, this is how  a multi-echelon fully integrated supply chain will look like: