ensure that the methodology is able to account for the costs
of both creating and holding inventory, and then allocating
those costs to products and customers that are served from
inventory.
Raw material supply costs: Raw material supply costs are
often integrated into standard costs in financial accounting
systems, which can lead to poor decisions in a traditional
cost-to-serve analysis. It’s not a big problem when each raw
material is supplied from a single source to a single location
in the manufacturing footprint; in such cases the practice of
using standard costs works just fine. However, for materials
that are sourced from multiple suppliers and have different
costs based on where they enter the manufacturing supply
chain—because of differences in pricing across suppliers,
freight, duty, or other factors—using average supplier costs
will result in inaccurate TDC calculations. Those companies
that are able to most accurately compute TDC are breaking
out supply costs from the largest-volume raw materials
based on bill-of-material consumption, by supplier and by
the locations where they enter the manufacturing network.
Transportation costs: On many occasions we have seen
businesses understate their total transportation cost by
ignoring the cost of the rolling assets, such as rail cars
or specialized trailers and containers. We have also seen
companies ignore the cost of product inventory that is tied
up in a given move. This is of little consequence when a
shipment moves from warehouse to customer via parcel
express or to a location within a few hours’ drive from the
warehouse. For ocean or rail shipments, however, such an
oversight can represent a significant inaccuracy in the total
cost. As an illustration of the potential magnitude of this
error, we found that one of our clients was including only
the line-haul freight cost for decision making; as a result, it
was understating its total cost by 35 percent.
To avoid these pitfalls, we recommend building “all-in”
transportation costs for each lane that will be considered in
the analysis. These costs should include the line-haul, roll-ing-asset lease cost, inventory cost, and any assessorial costs
that are routinely incurred on a movement. For example, a
rail movement should include the following elements:
• Line-haul freight
• Fuel surcharge, switching, and any other fees paid to the
rail carrier
• The cost of the rail car (car lease per day x the sum of
the loaded transit, the dwell time at destination, the empty
transit, and the dwell time at the loading point before the
next reload of the car)
• The cost of the inventory tied up in the movement
• The cost of cleaning the car
TDC AND DECISIONS ABOUT THE FUTURE
Up to this point, we have defined the elements of total
delivered cost and have suggested an approach for developing estimates of the individual costs that will determine
the projected customer/product-level TDC. Now, we will
explain how optimization technology, combined with computing TDC at the product/customer level, can produce
better supply chain planning decisions.
A leading-edge planning process will investigate and
compare a number of different future options or scenarios
in order to come up with the best future plan. Different scenarios may include an upside or downside demand forecast,
changes in cost or price, plant relocations or shutdowns,
or the launch of a new product. In each of these scenarios,
an optimization model is used to simultaneously make the
interdependent decisions in sourcing, production, warehousing, transportation, and distribution to generate the
best path through the supply chain for raw materials to
be transformed into finished goods and delivered to the
customers.
By definition, optimization is the choice of the best set of
decisions to either maximize or minimize a mathematical
function that defines the objective of the system. In fact, the
“objective function” in traditional network optimization
and in production and distribution planning models minimizes the total cost to deliver the forecasted demand—or,
put slightly differently, to minimize total delivered cost. At
a conceptual level, then, we have been using TDC for years
in the network design process. What’s new is the ability to
generate TDC at the customer/product level of detail. The
ability to view projected TDC at this level of detail opens up
a whole new discussion during the supply chain planning
process, as the following examples demonstrate.
An example using TDC in the strategic network design
process: In a recent engagement, we worked with a client
that wanted to reduce the cost to serve its customers while
strengthening the specialty segment of its business. Because
management had decided not to invest in new manufacturing capacity, any new volume gained on the specialty side
of the business would require a reduction in volume on the
commodity side. However, because the specialty grades of
the product tended to have a higher TDC than the commodity grades, the client needed to ensure that any changes
