Logistics Network Modeling
Project Assures Higher Return On Assets
Typical Logistics Cost Reductions Average 11% For Fortune 500
Your mission is secured by the answers to these logistics
Why? A typical Fortune 500 Company Reduces Annual Logistics
Costs By $23m
What? Given demand for all products, what logistics
infrastructure maximizes profit and capital turnover while meeting customer
How? Through top management’s commitment to sponsor the
logistics modeling project, formulate global corporate policies, and supply all
The corporate benefits of a logistics network modeling
project are increasing Return On Assets (ROA), decreasing logistics costs, and
higher after-tax profit margins.
To attain definitive and optimal answers requires several
key ingredients, such as:
A logistics network modeling project that handles global
Answers to specific questions about the existing logistics
Corporate policies and in-country provisions of production and
A working group charged with determining the optimal, global
“Make or buy” evaluations covering products, distribution
centers, and staffing
If you do not have the modeling tools or expertise in-house,
selecting an outside, focused team of modeling experts will speed your project.
A large oil company wanted to determine the best way to
introduce its products into an Asian country. Prior experience taught that a
marketing partnership be formed with a local distributor. However, the tax
structure in the Asian country was not favorable for such arrangements.
Significant tax reductions were available if a certain level of capital
investment was made in the host country. This is a classic trade-off,
increasing profit margin versus decreasing capital turnover. The critical
determination was the product volume, or throughput, in the host country that
raises profit margin sufficiently to outweigh the reduction in capital
turnover. The result was that a reasonable investment yielded tax benefits,
which raised profitability.
This example helps explain the benefits of a global
logistics strategy, which typically increases your company’s return on assets.
Given that, let’s start with an example, which clearly shows the benefits
through a simple exercise in the finance of logistics. Assume the following
aggregate numbers for a global manufacturing company:
Annual sales $1B
Total assets $667M
Profit last year $100M
Logistics cost last year $100M
The above first three values from the financial statement
and balance sheet enable us to compute the return on the assets (ROA) employed
in the business:
ROA = Profit Margin x
ROA = 10% x 1.5
ROA = 15%
Our board of directors now resolves that an analysis be done
of what the company’s global distribution strategy should be. The board
believes the business should be returning at least 20% on assets, and one of
the outside directors recently heard a presentation at a CLM conference about
the potential returns from optimizing a company’s logistics strategy. This
director heard that savings in logistics operating costs of 10-15% are typical,
and further, that substantial reductions in assets might be achieved by
outsourcing logistics functions, rationalizing logistics infrastructure, and
eliminating non-productive inventory.
In accordance with the board’s direction, a logistics
network modeling project is undertaken. After four months of careful data
collection, the optimization model of the company’s business has been validated
and the modeling scenarios begin. Within a couple of weeks some thirty
scenarios have been run through the optimization model and evaluated. After
some further off-line analysis to make sure the modeling results can be
implemented, the recommendations are presented to the board. At the highest
level those recommendations reflect the following:
Assuming no increase in sales (a
very conservative assumption as service is expected to improve):
Plugging these new values into our
ROA calculations gives the following:
margin = 12%
turns = 2.0
ROA = 24%
By rationalizing the company’s logistics infrastructure and
practices, the target of 20% or higher ROA has been met. In fact, ROA has gone
from 15% to 24%, or an increase of 47%!
How was such an ROA increase achieved, and are such results
typical? Taking the last question first, the answer is such results most
definitely are typical. INSIGHT’s client community was surveyed a couple of
years ago to see what kinds of savings their companies had achieved using
INSIGHT’s SAILS network optimization package. The average documented savings
of this large group of FORTUNE 500 companies was 11% of logistics costs
representing $23M annually.
Answering the first question, how to raise ROA, will be the
subject of the rest of this article. I hope the above highly typical example,
although somewhat artificial, provides the motivation or the “WHY” of using a
rigorous, disciplined approach to formulating a global logistics strategy. It
remains to describe the WHAT and HOW of doing it.
At its simplest level the WHAT comes down to answering the
question: Given demand for all products we make or sell at any level, what
logistics infrastructure will maximize profit and capital turnover while
meeting customer service objectives? That general question, which represents
the goal of a strategic logistics analysis and plan, can be broken down into a
series of specific issues or questions we want answered.
Should we make or buy certain products or components?
How many manufacturing locations should we have
What products should be made at each manufacturing location?
Which sources of raw materials and components should we use?
What modes of transportation should be used for various product
Should we have a private fleet of vehicles?
What sorts of distribution facilities should we have; how
many should there be and where should they be located? These questions include
such issues as:
What should be the mission of each distribution center (DC)?
What size DC and what kind of materials handling equipment should
Should we own these DC facilities or use third-party providers?
How should inventory be deployed in our logistics network?
Should we have full line or partial line distribution centers?
Will we use cross-dock operations to reduce inventory while
saving on freight cost?
What effect are eco-political factors, such as taxes, duties,
drawback, local content requirements, in-country investment requirements, and
Moving from the WHAT stated in terms of the above general
questions and issues, HOW does a given company get started in deriving answers
to those questions relevant to its business situation?
The first and most critical ingredient to success is support
and commitment from top management. A steering committee of senior executives
should be set up and charged with setting the policy parameters and decision
issues for the analysis. This steering group should represent all the key
functional areas of the company and should be responsible for assuring data and
resources from their respective functions are made available as required. The
steering committee should establish a working group to actually conduct the
data collection and modeling analysis.
The final step in the preliminary planning phase will be to
determine if outside help is required to carryout the project. If the company
already owns a license for logistics network optimization software such as
INSIGHT’s SAILS (Strategic Analysis for Integrated Logistic Systems) model, no
outside help may be required. However, even if such a license is held, it may
be decided that outside expertise to assist in doing the modeling work is
desired. This is often seen as a prudent way to speed up the project and
assure that focused modeling expertise is available to the working group. If
the company has no in-house capability or a license to the necessary software,
clearly outside help will be required to get the project done. A decision may
be made to license the software as part of doing the project so that the
expertise and modeling capability developed during the project can be used on a
continuing basis inside the company.
The steering committee will have some initial decisions to
make which will guide the scope and nature of subsequent analytical work. Such
policy issues as the following will have to be resolved and passed to the
Will we buy (OEM), contract out, or manufacture our products?
Do we want run our distribution centers (DC’s) or evaluate using
Third Party Logistics (3PL) providers?
Do we want to own our DC’s or lease them?
How do we want to handle overseas operations—joint ventures,
marketing agreement, infrastructure expansion?
Will we consider getting rid of our truck fleet?
Obviously the direction the steering committee gives to the
working group will have major impact on the scope, nature, and outcome of the
project. Looking at it just in terms of the impact on materials handling
equipment, if the steering committee directs that all manufacturing and
distribution be to be done in-house, there will be significant materials
handling requirements for operating the optimal network once determined. On
the other hand, if the direction is to outsource everything, the materials
handling requirements become some third party’s responsibility.
The working group must take the steering committee’s
guidance and then answer a series of questions themselves that will ultimately
translate into materials handling requirements. These issues include:
What kinds of customers do we have, and how do they receive our
products? Are we shipping in full pallet loads to customer distribution
centers or are we shipping individual small pieces direct to customers?
Is our business “make to order” or “make to stock?” Do we or could we
do final assembly, labeling, kitting, etc. at DC’s close to our customers?
Is a high percentage of our demand accounted for by a small percentage
of fast-moving items? What are the value and security characteristics of our
products? For example, do they need to be guarded or refrigerated? Do we have
significant seasonality like anti-freeze before winter or fertilizer before
spring planting? The answers lead to such modeling the desirability of having
one or two large DC’s which carry all products and several smaller DC’s that
are highly automated and carry just the fast-movers.
Must we decide the counties, outside our national boarders, within which
to locate facilities, source components, or conduct assembly operations? If
so, acquiring data about taxes and duties in all these countries is critical to
the evaluation. What level of investment in a country is required for local
operations or tax consessions or incentives? If we have operations in a
country, should we consider distributing from that country to outside or limit
distribution internally to that country. That answer influences where, within
a given country, we will want to locate because of infrastructure such as
parts, roads, rail, labor, and materials.
The above list is representative, not exhaustive. But it
illustrates the complexity of arriving at a global logistics strategy and the
Example: Pharmaceutical Firm Benefits from European Union
A large pharmaceutical company faced the classical issue of
doing business in the countries of the European Union (EU). Historically,
there was a manufacturing operation or DC in almost every country of Europe.
This was largely for tax and duty reasons, but also because of national
perceptions and cultural differences. Formation of the EU and its
eco-political implications justified a review of the logistics strategy for Europe.
Should there be one large, centrally located plant or DC which supplies all
countries? This would require significant investment but save considerable
operating costs. Labeling, and perhaps packaging, would have to be customized
for each country because of language, local customers, etc. The firm
discovered that greatly reduced handling and inventory costs could well make
having a larger, more complex facility a big contributor to profit margin in Europe.
In sum, a sound, well-developed logistics strategy is
virtually guaranteed to enhance a company’s ROA. Developing such a strategy
without using advanced optimization modeling tools is next to impossible
because of the complexity, amount of data, and the time, which would be
required to conduct manual analysis.