Logistics Network Modeling Yields Higher ROA

April 1, 2001
Fortune 500 firms anticipate 11 percent cost reductions.

Logistics Network Modeling Yields Higher ROA

Fortune 500 firms anticipate 11 percent cost reductions.

by Richard F. Powers, Ph.D.

Your board has asked you to increase your company's return on assets (ROA) to at least 20 percent. Your current ROA is 15 percent, with sales of $1 billion, assets of $667 million, profits of $100 million, and logistics costs of $100 million.

You recommend a logistics network modeling project to generate and quantify options.

Your justification is the immense economic value to be gained, especially with a cross-organizational goal, such as maximizing shareholder value.

• Why model? Fortune 500 companies reduce annual logistics costs by $23 million or 11 percent.

• To what end? A logistics infrastructure must maximize both profit and capital turnover while meeting customer demand and service objectives.

• How best to begin? Commit to providing policy guidance and supplying information.

• Corporate benefits are these: increasing ROA, decreasing logistics costs and achieving higher after-tax profit.


Successful logistics optimization requires the following:

• Logistics network modeling software that handles global complexity;

• Data defining the existing logistics network;

• Corporate policies and in-country plans for production and distribution;

• A working group charged with carrying out the global logistics strategy study;

• "Make or buy" evaluations covering products, distribution centers, transport, etc.;

• Modeling expertise.

Using capital investment to raise profits

An oil company targets entry into Asia with new products. Prior experience suggests marketing through a local distributor, but the tax structure is not favorable. Significant tax reductions are available if certain levels of capital investment are made in the host country. The crucial determination is product volume, or throughput, in the host country that reaps tax reductions and raises profit margins to outweigh reduction in capital turnover. The result: higher profitability.

Try a test. How can a $1 billion firm raise ROA by 49 percent?

Here's a simple exercise in logistics finance. A global manufacturing company has:

Annual sales, $1B (assume no increase)

Total assets, $667M

Profit, $100M

Logistics cost, $100M

From these, we compute:

ROA = Profit Margin x Capital Turns

ROA = 10% x 1.5

ROA = 15%

The board expects a 20 percent ROA

One director attended a CLM (Council of Logistics Management) conference and learned that savings in logistics operating costs are typically in the 10 percent to 15 percent range from conducting a logistics network optimization project. Further, substantial reductions in assets are achieved by outsourcing logistics functions, rationalizing logistics infrastructure, and eliminating non-productive inventory.

The logistics network modeling project is approved. After four months of careful data collection, the optimization model is validated and scenario modeling begins. In two weeks, 30 scenarios are run and evaluated. Off-line analysis tests feasibility. The recommendations project these results:

Assuming no increase in sales (a conservative consideration, because of the element of better service):

Sales, $1B

Total Assets, $500M

Profit, $112M

Logistics cost, $88M

Adding new values into ROA calculations:

Profit margin = 11.2%

Capital turns = 2.0

ROA = Profit Margin x Capital Turns = 22.4%

Rationalizing logistics infrastructure and practices exceeds the original ROA of 15 percent and even the target ROA of 20 percent, attaining an ROA of 22.4 percent, an increase in ROA of 49 percent! In a survey, INSIGHT's clients, (a large group of FORTUNE 500 companies) saved 11 percent of logistics costs representing $23 million annually.

What shapes global strategy?

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? This objective implies specific issues or questions:

Should we make or buy certain products or components? Specific concerns:

• Manufacturing locations;

• Products at specific location;

• Sources of raw material and components;

• Modes of transportation for product lines;

• Private fleet of vehicles.

Distribution facilities: Which? Where? How many? Decisions needed:

• Mission of each distribution center (DC);

• Size of DC and material handling equipment;

• Own DCs or use third-party providers;

• How to deploy inventory throughout the logistics network;

• Full-line or partial-line distribution centers;

• Cross-dock operations to reduce inventory while saving on freight cost;

• Additional factors: taxes, duties, drawback, local content, in-country investment, or offset trade.

Success begins with you

The first, and most critical, ingredient of success is support and commitment from top management. A steering committee of senior executives sets the policy and decision parameters for modeling. It must represent each key functional area and supply data and resources as required. The committee establishes a working group to perform both data collection and modeling analysis.

A final step comes in determining whether outside help is required. The company may own a license for logistics network optimization. If you go with outside help, licensing software, included as part of the consulting project, enables in-house modeling capability developed during the project to serve on a continuing basis.

The steering committee's initial decisions guide the scope. Policy issues must be resolved to guide the working group. Examples:

• Buy (OEM), contract out, or manufacture own products?

• Run distribution centers (DCs) or evaluate third-party logistics (3PLs)?

• Foreign operations-joint ventures, marketing agreement, infrastructure expansion?

Material handling requirements

If all manufacturing and distribution is in-house, significant material handling requirements exist for the optimal network. If you outsource everything, then material handling is a third-party responsibility. Material handling questions include:

• How do customers receive products? (full pallets to DCs or individual pieces directly to customers?)

• Do we "make to order" or "make to stock?" Should final assembly, labeling, kitting, etc., be done at DCs close to customers?

• High percentage of demand from a small percentage of fast-moving items? Must we guard or refrigerate? Seasonal issues such as fertilizer for spring? (Perhaps one large DC stocks everything, and several highly automated DCs stock fast movers.)

• Decide country locations, component sources or assembly operations? Tax and duty information? How much investment is required for local operations or tax incentives? Where, within countries, is the best target area because of availability of parts, roads, rail, labor, material, etc?

For example, say a large pharmaceutical company is faced with the classic issue of doing business in European Union countries. There was a manufacturing operation, or DC, in almost every country in Europe due to tax and duty requirements, or because of market perceptions and cultural differences among countries. Unified regulations justify a new logistics strategy for Europe. Labeling, and perhaps packaging, requires localization, because of language. Greatly reduced handling and inventory costs make a single larger, more complex facility a big contributor to profit in Europe.

Higher ROA guaranteed

A sound, well-developed logistics strategy virtually guarantees better ROA. Developing such a strategy, without using advanced optimization modeling tools, is next to impossible because of the complexity, amount of data, and time required to conduct manual analysis.

About the author

Dr. Richard F. Powers is co-founder, president and CEO of INSIGHT, which develops and implements optimization-based management support systems. Prior to founding INSIGHT, Dr. Powers was awarded the Defense Superior Service medal for his management of the largest distribution system study ever undertaken by the Department of Defense, which included computer modeling. He was awarded a Ph.D. in management information systems from U. Minnesota, an M.B.A. in distribution management from Michigan State, and a B.A. from Rice. Call INSIGHT offices in Virginia at (703) 366-3061 or in Oregon at (541) 388-6998. On the Web, visit www.INSIGHT-MSS.com.

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