Anyone can buy a truck or warehouse. The successful organization is the one that uses these resources most efficiently.
Before computers, inventory was managed by classes, such as “A-B-C”. This made it possible to achieve big, obvious efficiencies. But with computers, we can now manage inventory at the level of the individual stock-keeping unit (SKU), even for hundreds of thousands of SKUs.
Imagine each SKU as a commuter traveling to a destination. Each commuter makes choices of timing and travel — car, taxi, bus, bicycle, foot — based on budget and urgency. In a similar way, we can help each SKU plan its travel to the consumer. Along the way it will make a series of decisions based on economic models.
We call this “nano-economics”.
By optimizing decisions at the level of individual SKUs, it is possible to save a few seconds here and a few centimeters there, which, when accumulated over hundreds of thousands or more transactions, can amount to significant savings.
To achieve this it is necessary to understand the role of the two limited resources in a warehouse: Time and space. In this context time is measured in person-hours and space is measured in cubic meters. Each has a cost particular to its time and place. For example person-hours are relatively inexpensive in most of SE Asia but relatively expensive in Western Europe. Refrigerated space is more expensive than space at ambient temperatures.
In general we hope to minimize use of both time and space, but sometimes we trade one off for the other. For example, shelving wastes some space but it makes product more easily accessible and therefore reduces time to retrieve product. This is a good trade-off where time is relatively expensive compared to space.
Much of this book addresses the challenges of how to make such trade-offs in the best way.
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