As part of his mission to gain a better understanding of out-of-stocks (OOS), Dan Gilmore, president and editor-in-chief of Supply Chain Digest, has held a recent discussion on how extra inventory can be driven by lead time variability. For those who do not protect themselves from lead time variability, there is the prospect of more out-of-stock (OOS) occurrences. In each occurrence of variability in the supply chain, it is important to protect it with increasing inventory, capacity, or time, by making customers wait or an increase in OOS.
Gilmore also released an online inventory calculator to make the concepts more clear and demonstrates the impact of a reduced lead time. The math of the calculation is difficult, but the underlying intuition is less so—a late shipment means that you must have the inventory in reserve in order to meet demand in the meantime. Therefore, reducing lead-time variability has a significant impact on OOS or inventory.
He also states that in spite of the evidence pointing to how important lead time variability is, only a very small amount of companies track it.
Problems arise from the fact that it’s not always easy to get insight into lead time and variability. Existing systems are not yet equipped to track it. Here are three areas defined as those to measure in order to be able to measure lead time and variability. Each should be measured separately, as they display different characteristics:
The first is transit time. Transit time is measured from when a product departs the suppliers’ dock and arrives at your companies dock. This is the most straight-forward area as the data is accessible. A calculation can be made between all of the transit times by calculating an average and standard amount of deviation. It’s made slightly more difficult by shipping via a variety of platforms and these should be taken into account, e.g. the difference between ocean shipping and air freight must be taken into account, and a decision whether to calculate the dominant method or a blend must be taken.
Order to Ship Time
The second is the order to ship time—the time between when the order is placed and when it is shipped. For suppliers, this is comparatively easy, by measuring when the order was placed, having visibility of the shipment data and knowing when the item shipped. It gets more complex if the order changes frequently or the PO is open. In this case it could be tough to decipher when the order was placed. It’s even harder if you are dealing with your own plant, in this case it is the time from when you made another batch until the item ships.
The third is replenishment frequency—the extra time occurring from periodical production. If you place an order once a week, that’s an extra week of lead-time. Even daily orders are subject to how often they are shipped. Unless the production schedule is fixed this can lead to difficulty, variations in production must be factored into lead-time calculations.
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