Expiry planning adds a whole new dimension to the supply chain planning and simulation process, but in those industries where expiry (or best before) is part of their manufacturing and distribution process (pharma, food, med devices among others), the ability to generate production plans that take into account expiry is absolutely vital to creating a realistic plan.
Most ERP systems support expiry on some level, usually from a transactional point of view (what I will call simple expiry). Simple expiry allows the users to set expiry limits on a part by part basis, and the system will then calculate when a particular supply will expire. This is mainly used for 3 things in an ERP system:
- determining when a particular supply expires so it can be scrapped and/or replaced,
- allowing planning to determine in what order to use a supply in order to avoid scrap, and
- to enable inventory control and shipping to determine what supply can or cannot be used in production or order fulfillment.
The problem with this expiry model is that it does not realistically model actual expiry conditions in the supply chain, as actual expiry times can be consumed by production and quality inspection lead times, perhaps through several levels in the supply chain. What this means is that supply that was projected to be available until a certain period in time will actually expire earlier, leaving an unanticipated gap in supply. This could lead to real shortages and dire consequences for customers if not recognized in time.
What simple expiry does not do is allow expiry to be driven by dependent components in the BoM, which I will call complex expiry. In this model, component parts (perhaps several levels down in the BoM), drive the expiry date of the parent part. A true expiry planning system must be able to account for the lost expiry time as the driving expiry component is processed and tested up through multiple levels in the BoM. As well, when supplies are allocated to demands, the originating demand’s expiry requirements (minimum shelf life, or how long the product must last before expiring once it has been shipped) must be known when planning supply, otherwise a mismatch between the demands requirements and the supply’s ability to meet them can occur. Another issue to consider is safety stock being held at multiple levels in the supply chain, as by its very definition, safety stock can exist in inventory for extended periods of time, further consuming expiry time.
In order to get a true supply/demand picture when planning or simulating in the supply chain, actual or planned supplies must be matched to their allocated demands. This can only truly be done in a CTP (Capable to Promise), bottom up analysis of the true available dates of the components, and how they affect the parent’s availability. In other words, you cannot properly fulfill demand for expiring product unless you have a true picture of when your supply will be available, and when it actually expires.
A simple expiry model can be made to accommodate certain aspects of this planning model (by manually or programmatically accounting for lead times etc. in each level of the BoM in the expiry data), but without the ability to account for actual variations in the supply plan through a CTP analysis, the picture will always be incomplete.
In summary, in order to get a realistic view of your supply chain under expiry, a complex expiry model is required (and a planning tool which supports this). In order to get a true picture of scrap, gaps in coverage, safety stock requirements, batch production timing, and the financial implications associated with each, the ability to support the complex expiry model is a requirement in any planning tool.
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“A true expiry planning system must be able to account for the lost expiry time as the driving expiry component is processed and tested up through multiple levels in the BoM.”
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The question has been asked, what is meant by complex expiry and how it must be account for lost expiry time. To further explain this concept, the following simple BoM will be examined :
FG : 2 weeks safety stock, 6 months shelf life required at shipment time
——– Component A : Manufacture Lead Time : 1 month, One Month Safety Stock
———- Component B : Manufacture Lead Time : 1 month, One Month Safety Stock
————–Component C : Manufacture Lead Time : 1 month, One Month Safety Stock
FG is composed of Component A, Component A is composed of Component B, and Component B is composed of Component C, the raw material. Each part can be inventoried and stored for several months at each level if required.
If Component C determines expiry all the way up to the FG level, when Component C is processed, the expiry for Component A, B, and FG will be set at that time. This means that all the time consumed at each stage to manufacture, test, and store the components and FG consumes expiry time. Looking at the model above, it can be seen that Component C must have at least 12.5 months of expiry life when it is manufactured, if it is to make it to the end customer with 6 months left on its expiry.
As the product is processed thru each stage, the expiry clock is ticking continuously as each stage requires 1 month to produce and test, and another month as it sits in inventory as safety stock buffer. If the expiry calculation at each level does not account for the lost expiry experienced at the previous stage or stages (which would happen in the simple expiry model), then planning will indicate sufficient supply will exist at the FG level, when in fact it will not. If Component C only has 12 months of expiry life, by the time it is processed to FG, it must either be shipped immediately (which would leave no safety stock at this level), or scrapped, as it now cannot meet the shelf life requirement. This means either an out of stock situation, or an expensive scrap transaction that must be processed.
This illustrates why the ability to handle complex expiry is a necessity in any planning tool if the accurate supply picture of complex pharmaceuticals and other chemicals is to be modelled.