Lead Times: How to Model, Evaluate, Reduce, and Stabilize
This article discusses how inventory planners can cope with variable lead times. I will first illustrate the fundamental problem using dice. We will then highlight practices to evaluate, reduce, and stabilize lead times.
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The current shortage of shipping containers is putting supply chains around the globe under pressure as lead times increase and become less reliable. Dealing with long chaotic lead times is a nightmare for inventory planners. And a showstopper for service levels.
Inventory Targets and Demand: Roll a Die
Imagine you are responsible for baking cakes in a bakery. Every morning you must decide how many delicious cakes you will bake.
On an average day, the demand for cakes is between 1 and 6 pieces — let’s assume it is equally likely that your clients will want 1, 2, 3, 4, 5, or 6 cakes. In this simple case, the daily demand for cakes behaves like rolling a dice.
We can easily set inventory targets for such a predictable* demand pattern. For example, if you bake five cakes, you have an 83% chance to fulfill all demand (5/6 = 83 % as you satisfy all demand five days out of six).
*I am calling this predictable as we know the demand distribution probability. Demand could be highly variable — but still predictable.
Inventory Targets, Demand, and Lead Times: Roll a Die, and Then Some More
Let’s complexify our first example. You are now in charge of a supermarket with a similar daily demand for cakes (1 to 6 pieces per day). However, your supermarket doesn’t bake cakes. Instead, you order them from the close-by bakery. The baker will deliver you cakes, but she can’t promise a fixed lead time…
