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Take Shelf Life To The Next Level To Unlock Savings

Warehouse Management

By
Steve Kinal
SAP Shelf Life Expiration Date

From Batch Management to Shelf-Life Optimization

Optimizing Shelf Life is essential to improving inventory management, reducing waste, increasing profit margins, and maximizing customer satisfaction. Especially for heavily regulated industries with challenging traceability needs – the agriculture and food industries come instantly to mind– it couldn't be more critical to carefully track materials that expire or, in SAP terms, possess a Shelf Life Expiration Date (SLED).

It would be a mistake, however, to believe that SLED material categories or types are confined exclusively to food and agriculture. Many other materials need to be consumed/used before a specific date when it degrades or expires: adhesives, metals and electrical components, for example. The good news is that Warehouse Management (WM) in SAP can take shelf-life management to the next level with automated data collection tools, real-time tracking capabilities and detailed reports.

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Leveraging SAP to Optimize SLED Control

How do we enable SLED in Warehouse Management to do the heavy lifting in SAP? The first and most obvious requirement is that we must enable batch management. If a material has a shelf-life expiration date and could potentially be sold to a customer, it is vital to have traceability from the start of manufacturing to delivery to the customer.

Once Batch Management is enabled, it’s a new playing field. Now we can enable SAP to manage and assist with SLEDS by configuring standard processes at the storage-type level. Put simply, we can establish specific shelf-life rules for sets of storage types with storage bins that are shelf- life managed as well as others that are not. In addition, SAP features a stock removal strategy/picking strategy based  all around shelf life, which automatically proposes transfer order picks by the latest SLED date.

Warehouse Management offers many standard tools to assist with the management of Shelf Life Expiration Date such as the standard T-Code (Shelf Life Control List). Shelf-Life Control List identifies soon to be expired or past expired materials in the warehouse. It then compares the total remaining shelf-life vs.remaining warehouse-life (factors in lead time to customer) side by side, all the way down to the material level. Additionally, the tool displays these materials in different storage locations if applicable. And finally it presents these materials visually in a traffic light orientation, making it easy for the enduser to quickly identify and make informed decisions about the soon-to-expire materials.

Keep in mind that the Shelf Life Control List is not the only tool to assist with the warehouse management of Shelf Life Expiration Date. SLED is also an optional field in one of the most utilized T-codes from warehouse personal – WM Stock. Here we can also view SLED at a granular level, drilling down to the storage bin, where the system will display what material, which bin, which quantity, and the SLED for that quantity. One important exception: the WM Stock Report will not visually present expired SLED. Rather, it simply lists the date of the SLED in the same line as the other details but can be sorted in ascending or descending order to list the oldest SLED first.

Certainly, shelf-life management is a big leap forward from tracking, siloed data, and relying on isolated inaccurate spreadsheets. Still, some organizations claim that even though SAP has standard processes and tools, the physical limitations do not align to the process. This challenge can be solved when pickers gain the ability to quickly access the oldest material being called upon; otherwise, in the real world, the pickers may simply forego the most soon-to-be-expired material if it is too much effort.

The best example of setting up a physical process to the system is a grocery store in the milk section. Consider: the staff loads the milk from the back of the roller rack by Shelf Life Expiration Date and the milk automatically maintains First-In, First-Out (FIFO) principles, in which the customer picks the oldest SLED from the front.

We can configure SAP to do anything, but if we are not setting up our staff for success or making the process easy, they will too often end up finding work-arounds. The ability to efficiently access data-driven product data, track SLEDs, observe what’s going on in real time, and get shipments out the door in time can lead to higher profitability and less waste.

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