Direct Store Deliveries and Lowest Total Supply Chain Costs

From a supply chain perspective, it often makes sense to have the warehouse work harder, so that downstream recipients of shipments don’t have to work as hard. If certain tasks can be done more cost efficiently in the warehouse, then those tasks should be performed there. 

However, there are instances where the warehouse can actually work less hard and still provide lower total supply chain costs. A recent article by Derek Curtis in “Raising the Bar,” HighJump Software’s blog, provides a concrete example of this, as well as the tradeoff logic that is employed. 

Side-load trucks are commonly used by manufacturers that do direct store deliveries (DSD). A delivery truck will visit several stores, and at each stop, the driver will stock the shelves with whatever product that store ordered. The traditional picking practice is to build a pallet based on a store’s order. So, if a particular store orders ten cases of one stock keeping unit (SKU), thirteen cased of another SKU, and seven cases of a third product, then the pallet is built with those different SKUs.

In DSD, it might make sense to do “aggregate” picking. So, if a truck will be delivering goods to seven stores, and Store 1 has ordered nine cases of a particular SKU, Store 3 has ordered five cases of the same SKU, and Store 6 has ordered twelve cases, then a warehouse worker will pick twenty-six cases of that SKU at the same time despite the fact that the SKU is being used to fulfill different orders. Obviously, a picker will be more productive in aggregate picking because travel time is reduced. 

But from a total supply chain cost perspective, does this really make sense? The labor costs for delivery drivers are higher than for warehouse pickers. If orders are palletized by store, it makes sense that the driver would be able to complete store deliveries more quickly because he wouldn’t have to pick the store orders out of the truck.

But the math is not necessarily so straight forward. As Derek wrote in his piece:

If your driver takes an 8 hour shift to deliver while handling aggregate loads, do they really cut their time down to 7 hours (or less) if you provide them with palletized loads? Compare this with your warehouse staff where you have active management in house and stop the shift at the end of the work (or redeploy to other tasks). This type of control over a delivery workforce is difficult to achieve.

Further, when loads are palletized by store order, they are shrink-wrapped to avoid damage. 

Now you have to account for an additional time and materials component when comparing the costs between aggregate and palletized.

Finally, there is the issue of vehicle cube utilization:

This is probably one of the most basic arguments against palletizing. Utilization of vehicle cube is obviously much higher while building aggregate… by improving cube utilization you may be able to remove vehicle(s) from the road. 

In summary, while the principle is clear—you should seek to hit delivery targets at the lowest total supply chain cost—implementing the principle is not always straightforward. Making the right choice can involve a creative approach to processes, time and motion studies, and trial and error.

(Note: HighJump is an ARC client).

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