Split Decision: How Back to Basics Supply Chain Management

Can Save a Lot of Dough

Often, simple improvements in the process can be lever$-$

aged for large cost savings and significantly better customer

service. Consider the following real$-$life example in which a

large baked goods company did exactly that to get control of

its supply chain costs. This company produced baked prod$-$

ucts in Alberta that had a $10-$day "shelf life" after production.

When the product arrived at their store, customers expected at

least another $7$ days of shelf life, meaning that the product had

to arrive within $3$ days $(72$ hours$)$ of production. Two cities

the company shipped product to were Vancouver and Victoria,

and $60$ and $68$ hours lead$-$time respectively were needed to

ensure the product arrived at the distribution depots in time to

be taken to grocery stores. Shipments occurred five days each

week. For four of these days, two "double trailer" loads $($two

trucks hauling two trailers each$)$ were sent to each city. Once a

week, though, since demand dropped, the company sent only

one double trailer to service both locations. The driver would

then drop the rear trailer at a Vancouver depot and catch the

ferry to Victoria.

This split trailer strategy worked well for a long period,

because demand was consistent and the "split load" consistently

took place on a given day. However, when market demands

started to change, the system began to break down. As demand

from the two cities began to fluctuate, split$-$loads would be

assigned sporadically, as needed, with little or no warning.

Sometimes, drivers accustomed to going to the Island would

mistakenly take loads that were scheduled to split in Vancouver

straight on to Victoria instead. Other times, drivers would

divide loads that were not intended to be split in Vancouver

and continue to Victoria, with only half the required stock.

Sometimes, drivers would even drop both trailers in Vancouver

and return to Alberta, without splitting the load. All three

mistakes resulted in excess stock in one location that would

have to be discarded since it was past the due date, and produced

dissatisfied customers who did not receive their product at the

other location.

The resulting chaos cost the company hundreds of thou$-$

sands of dollars annually due to lost product, extra shipping

charges, and extra production to make up for shortfalls. As

well, customers would fine the company when it didn't meet

its contractual obligations. Worse yet, clients would sometimes

switch to other suppliers. For years, the company had struggled to

avoid these costs by hiring extra staff, opening a $24-$hour hotline

for customers, increasing safety stock in the depot to accommo$-$

date losses, and even hiring jet aircraft to "hotshot" the product

when mistakes were made. The cumulative result was not only an

exponential increase in shipping costs of around $$400000$ annu$-$

ally, but also dissatisfied customers, strained production lines,

and stressed$-$out managers, thus contributing other "soft costs" to

the company $($estimated at between $$200000$ and $$800000$ per

year$)$ as well as lost revenue. Many in the company were simply

resigned to the fact that these additional costs were just part of

doing business between Alberta and the West Coast.

The company hired a consultant to look at all areas to find

the right solution. They suspected he might have to rework

the shipping and distribution schedules, retrain the staff and

drivers, and consider a different ordering system.

Questions:

What might be the root causes of this distribution prob$-$

lem?

What solution$($s$)$ would you suggest for this issue? $($Be as

creative as you like$).$ How much might it$/$they cost$?$

Source: This case was written by Tim Sweet from Revolve Consulting in Calgary and Janice Eliasson of the Haskayne School of

Business. It is based on a real situation.