Any company that has a global supply chain should consider introducing its strategic left hand to its operational right hand. Strategic supply-chain planning that combines aspects of business-strategy formulation with aspects of tactical supply-chain planning can make each far more valuable to the planning effort than either would be alone. Strategic supply-chain planning is the Pegasus of strategy: It can soar, but it also needs to keep its feet on the ground. Although companies routinely weigh long-term supply-chain-related decisions in light of alternative sources of supply, new geographic markets or new products, various levels of management use different approaches, often in isolation. Senior managers make such decisions as part of formulating business strategy; supply-chain planners, as an extension of their tactical supply-chain planning.

How should companies ensure that relevant supply-chain details inform the business-strategy formulation and that strategic direction and the supply chain are in alignment? They can do so through early communication between senior managers and supply-chain planners, which shortens strategy-implementation time while letting each group pursue its forte: senior managers formulating strategy to maximize shareholder value; supply-chain planners running optimization models to minimize total supply-chain costs.

One Company’s Story

Consider a strategic supply-chain planning exercise at a polyvinyl chloride (PVC) manufacturer that we’ll call Acme Vinyl Co. Acme’s North American revenues came from PVC for building (55%), packaging (15%), consumer goods (10%), the electronic industry (10%), the automotive industry (4%) and from non-PVC products (6%). At the end of the 1990s about 4% of those revenues came from Asia. Acme had been seeing revenue growth for several years, mostly as a result of acquiring other PVC manufacturers.

With fragmented spare capacity around North America, a falling stock price and a need to rationalize the postacquisition supply chain, Acme’s leaders considered their options. Some favored consolidating manufacturing into one or two new mega-plants; others suggested closing existing plants or lines. Management chose to do a strategic supply-chain planning exercise to assist decision making.

The Planning Spectrum

Strategic supply-chain planning falls in the middle of a decision-making spectrum that has business-strategy formulation at one end and tactical supply-chain planning at the other. (See “Strategic Supply-Chain Planning and the Planning Spectrum.”) With a focus on fundamental changes in manufacturing and distribution capacity, it is long-term in scope and impact but can benefit from detailed optimization models and advanced planning-and-scheduling (APS) technology that is more often associated with medium- and short-term planning. Used in this strategic context, the tools help determine what would be an appropriate supply-chain configuration for sourcing and which plants or distribution centers should be closed or kept open.

Strategic Supply-Chain Planning and the Planning Spectrum

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In contrast, tactical supply-chain planning is short- or medium-term in scope and impact, with supply-chain planners using past demand to make forecasts for the near term and adjusting these forecasts on the basis of market intelligence or planned promotions. Used in this context, optimization models and APS technology help determine where and when to produce what items and how to distribute them.

Planning Processes and Optimization

Although business-strategy formulation also uses tools and frameworks, it requires much more creativity than tactical planning. The optimum route to maximizing shareholder value is rarely obvious. It takes creative thinking and freewheeling negotiations to identify, understand and agree upon possible actions. Computers and spreadsheets support analysis, but they don’t determine strategy.

For tactical supply-chain planning, the decision options and the factors affecting them (production capacity, distribution capacity, variable costs, demand forecast) are clearly defined. The goal of minimizing total supply-chain costs — for manufacturing, storage and handling, and transportation — is narrower.

Because tactical planners can identify beforehand possible decisions and factors that might affect these decisions — and can build those elements into the software — they can use optimization models that rely on mathematical techniques. The models make recommendations that both minimize costs and help companies meet forecasted demand without exceeding production and distribution capacity. Advanced planning-and-scheduling technologies are available from several companies.1

Business-strategy planners can’t plug clearly defined factors into software as supply-chain planners do, because strategy formulation is, in part, about trying to identify just what those factors are. But strategic supply-chain planning can benefit from appropriately used optimization models because tactical supply-chain models can be extended to include strategic decisions about closing or opening plants and distribution centers. APS vendors offer software for that purpose. The factors rarely change — production capacity, distribution capacity and variable costs. The goal of minimizing cost is extended to include the fixed costs of keeping plants and distribution centers open and the one-time costs of opening new ones and closing existing ones. These more strategic computer models can then guide decision making.

Optimization models for tactical supply-chain planning and models for strategic supply-chain planning differ only slightly in their design, but markedly in their use. Even if supply-chain planners tweak the production and distribution schedule obtained from tactical models to expedite an order to a key customer, they largely retain the model’s recommendation. In contrast, when using a strategic supply-chain model, managers are trying to determine how much the opportunity cost of a particular decision differs from the model’s recommendation.

At General Motors Corp., for instance, Electronic Data Systems Corp. consultants found that 90% of the time, GM managers used their models’ recommendations to benchmark actions that they were likely to consider.2 The candidate decisions were based on qualitative criteria not included in the models. Creating benchmarks in this way is unique to optimization models using linear programming, a method using advanced mathematics to capture all the constraints, such as capacity, and to find the best possible recommendations that would minimize the total operating cost or some other stated objective. Such models guarantee the lowest possible supply-chain cost. Spreadsheet calculations or simulation models cannot provide that sort of benchmarking capability.3

Use of Optimization for Strategic Supply-Chain Planning

A variety of industries have successfully implemented optimization-based tools, including one called Strategic Analysis of Integrated Logistics Systems (SAILS).4 Baxter International Inc. used SAILS software to evaluate consolidation approaches following its 1985 acquisition of American Hospital Supply Corp. SAILS also helped Pet Inc. assess supply-chain synergies from two potential acquisitions. In another case, a personal-computer manufacturer made successful strategic use of an optimization model for its global manufacturing and distribution network.5 GM uses a tool called Production Location Analysis NETwork System (PLANETS) to determine what products to produce —and how, when and where to make them.6 The now defunct Digital Equipment Corp. (DEC) probably lengthened its life by using supply-chain models to decrease costs.7

The Need for a Combined Process

Clumsy integration following mergers or acquisitions points to the dangers of relying on only one type of decision making. M&A business-strategy formulation rarely entails the use of models to optimize the supply chain before and after a merger, even though most operating costs reside in the supply chain. In one study, researchers surveyed 700 high-value international mergers and acquisitions occurring from 1996 to 1998 and found that failure to integrate supply chains was the main reason four out of five deals “failed to enhance shareholder value.”8

Using an optimization model without a good strategy is similarly lacking. DEC’s strategic supply-chain planning system of the early 1990s improved manufacturing, distribution and service, but, without a robust business strategy, the company ultimately succumbed to acquisition by Compaq Computer Corp.9

As supply chains become increasingly global, managers are making more strategic decisions about supply-chain design and reengineering. Thus supply-chain management has evolved from a function garnering little attention or prestige to a highly visible and respected one.10

But improvements in tactical supply-chain planning resulting from the use of technology from advanced planning-and-scheduling software vendors has created unwarranted expectations that, with similar software, senior leaders could delegate strategic supply-chain planning to supply-chain planners. But senior executives’ aloofness from strategic supply-chain planning tools creates the same problems as ignorance of tactical advanced planning-and-scheduling tools. DEC likely relied too much on supply-chain planners. And after Nike Inc.’s $400 million APS technology implementation, $100 million in inventory got misdirected, ultimately triggering a $2.5 billion loss in market capitalization.11

The reason that senior managers keep aloof is lack of knowledge, and even suspicion. Managers at Royal Dutch/Shell Group, for example, harbored a distrust of optimization models that biased the company against using such models in its scenario-planning processes during the early 1980s.12 The extensive detail, rigid structure and managers’ lack of familiarity with optimization models aren’t conducive to the freewheeling discussion that strategy development needs. Moreover, because management education is focusing less on analytical strategic planning and operations research, M.B.A.s rising to the senior ranks since the mid-1980s have shown less and less interest in the technical side of management.13

That’s why they need input from supply-chain planners who are familiar with optimization models. Only through a seamless process that encompasses those who are developing strategy and those who are using detailed supply-chain models can companies align their business strategy and their supply chain.

Scenarios and Scenario Planning

In scenario planning — a flexible process for formulating business strategy — senior managers build internally consistent, alternative views of possible future outcomes, including some that are “unthinkable,” as Herman Kahn suggested in his 1950s examination of Cold War scenarios.14 Typically, to keep the focus on important factors in relation to the long-term future, only a few business scenarios are developed.

Building scenarios is more art than science. The creative input needed from managers differs too much from one company to another for experts to offer more than guidelines.15 (See “Three Approaches to Scenario Planning.”) Leaders creating business strategy use “what if ” situations based on the plausible interplay of factors expected to have long-term effects. The only constraint is plausibility.

Three Approaches to Scenario Planning

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Erik Larsen, professor of management and systems at London’s Cass Business School, has identified three phases of scenario planning. Scenario building involves identifying issues, driving forces and factors that produce uncertainty, then devising rough scenarios that are further fleshed out. In scenario planning, managers evaluate possible decisions, policies and strategies to determine their effects in each scenario, modifying and reevaluating them as necessary. Scanning the business environment involves checking early indicators of change in the environment to see which scenario or combination of scenarios is actually unfolding, thus enabling managers to revise and refine the decisions made earlier in Phase Two.

Consider Acme Vinyl’s scenario planning in light of Larsen’s approach. Acme managers deemed three decisions as likely candidates: first, the rationalization of existing production capacity and the closing of plants or parts of plants, while possibly expanding other plants; second, the concentration of production at one or two new megaplants; and third, the rationalization of the company’s distribution network, the closing of some distribution centers and the opening of others.

They identified four main drivers affecting the company’s prospects: macroeconomic forces that determine growth in the gross national product (GNP) of the United States and Canada and the growth of demand in most sectors; the efforts of western European governments and the European Union to phase out PVC, partly in response to Greenpeace activism; fluctuating oil prices and their impact on the cost of raw material (and the company’s margins); and the cycle of prices for PVC goods.

The managers also predicted business trends: continued U.S. construction growth; slower industrial growth in the United States, Japan and western Europe; rapid growth from 2000 through 2005 in Asia (excluding Japan); a gradual shift from PVC to packaging polymers by major Japanese and western European producers of household goods, chemicals and construction materials; and a reduced use of PVC compounds in the auto industry in western Europe.

After their analysis, the managers developed two business scenarios: a so-called “Official Future” and one referred to as “Sunrise-Sunset.” The Official Future reflected senior managers’ belief that, for at least four or five years, the company’s business would grow at the same rate as the GNP growth of the United States and Canada (about 2% per year). Some sectors, such as electronics and consumer goods, would continue to grow faster than others. Asian demand (excluding Japan) — a small proportion of Acme’s total North American production — would grow as the GNP of Asian countries grew and as Acme achieved greater market penetration. Those trends would continue for 20 years, and U.S. government policies would remain favorable to the PVC industry regardless of which political party was in power. The electronics and consumer-goods businesses and growth in Asian demand would eventually slow down.

The Sunrise-Sunset scenario anticipated that events in western Europe and Japan would lead to a downturn in the U.S. and Canadian PVC industry. Concerned about dioxin emissions from the burning of PVC, state governments would begin to file lawsuits against PVC manufacturers and garbage-incineration companies. Non-PVC polymer production would gain in importance. Meanwhile, a new day would dawn for PVC exports to Asia, where an overwhelming need for buildings, water and sewer lines would increase demand for 20 years despite environmental issues. The total market would expand and Acme would see its market penetration increase, especially in India, China, Thailand and Indonesia, where Acme might even need to build or acquire plants.

Middle Ground

The ideal process adds a step between business-scenario creation and final decisions: using supply-chain planners’ optimization models. (See “Strategic Supply-Chain Planning Using Scenario Planning.”) For each of the business scenarios, supply-chain planners can create multiple detailed model scenarios to run with their supply-chain optimization models. The result: a supply-chain configuration that minimizes the total fixed and variable, long-term supply-chain costs for the particular business scenario.

Strategic Supply-Chain Planning Using Scenario Planning

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How do these model scenarios of supply-chain planning differ from the more familiar business scenarios of scenario planning? Model scenarios feature an array of demand forecasts and tactical production configurations (extra shifts, planned maintenance and the like). The underlying factors are built into optimization models for use with advanced planning-and-scheduling software. Creating model scenarios is straightforward and involves little creativity or discussion. It is similar to a company taking a macro business scenario and creating micro scenarios for business units or regions.16 Only convenience and the time it takes to solve a model scenario constrains how many a company can have for each business scenario.

Linking each business scenario to multiple model scenarios and uniting the creative work of strategy formulation with the analytical, optimization-model approach results in a powerful synergy with “right brain” strategizing joined to “left brain” planning.17

Phase One: Scenario Building

In Phase One, the strategy team identifies the candidate decisions and their attendant uncertainties, then outlines business scenarios. The supply-chain team develops or modifies its supply-chain model on the basis of input from the strategy team regarding possible decisions. The two teams then validate the model. The strategy team garners useful information about the supply chain and updates its notions about how long-term supply-chain configurations affect total supply-chain cost. Next, the strategy team fleshes out the business scenarios using this information and data-on-demand forecasts, plant locations, distribution centers and so on. Finally, the supply-chain team develops multiple model scenarios for each business scenario to run through its software.

After developing the Official Future and Sunrise-Sunset scenarios, Acme’s strategy team met with the supply-chain team. The teams agreed that the supply-chain group should make recommendations for both scenarios to reconfigure the supply chain to minimize the cost of manufacturing, distribution, the closing of old plants and the establishment of new ones. They identified possible locations for megaplants and determined which of the existing plants could be altered or closed; they also identified 14 product families that, in aggregate, totaled several hundred products. Then the supply-chain team, focusing on demand for North American production, developed model scenarios.

Phase Two: Scenario Planning

In Phase Two, the supply-chain team runs the model scenarios and makes scenario-specific recommendations. Then the strategy team modifies its pool of possible decisions, finally choosing one that it then shares with other managers.

Acme’s supply-chain team used software from an APS vendor and ran model scenarios requested by the strategy team. The latter group weighed the resulting recommendations with factors relating to the long-term profitability of the business. As a result, Acme decided to spin off part of the vinyl business as a joint venture with a supplier; it also chose to merge with a non-PVC polymer company.

Phase Three: Scanning the Business Environment

In Phase Three, the strategy team identifies leading indicators (in the case of a company like Acme, it might be housing starts) that enable early detection of which scenario or combination of scenarios is actually unfolding. When the strategy team has determined which scenario is occurring, it informs the supply-chain team. With the new information, that group revises the scenarios and runs the model again to fine-tune its recommendations. The strategy team then revises its decisions and shares them widely so they can be acted on.

Upsides and Downsides

Acme preserved shareholder interests following the exercise and the merger, its stock price remaining level despite the plunging prices of other chemical stocks during the same period. Having executives who formulate business strategy participate in scenario planning was critical to the final decisions, which undoubtedly would have been different had the company used only supply-chain optimization modeling.

But even without optimization-based planning, scenario planning would have elicited the same decision regarding the merger. The main benefit of optimization lies in refining the decisions that emerge from scenario planning, including rationalizing the supply chain.

Whenever a company considers a merger, it must evaluate its own assets accurately (in addition to its target’s) so that its shareholders get the best deal. Acme’s main assets were plants and long-term customer contracts, and supply-chain modeling and optimization helped senior managers understand which, in a merger, could be spun off to increase Acme’s value.

Like any other management tool, however, both scenario planning and optimization modeling can have their downside. Some managers become seduced by colorful future possibilities in scenario planning when they should be focusing on the trends, underlying factors and uncertainties relevant to genuinely possible decisions. Others remain aloof, relying first on consultants and later ignoring the scenarios when making decisions. Similarly, development of a strategic supply-chain planning optimization model sometimes serves no practical use, becoming unwieldy or taking too long to complete because of multiple motives.

Still, the joint use of scenario planning and optimization models is the better road to shareholder value — more effective than using either approach in isolation. Strategic supply-chain planning, like Pegasus, is more than the sum of its parts.

References

1. Suppliers of APS technologies include SAP, i2 Technologies, Manugistics and Logility.

2. R.L. Breitman and J.M. Lucas, “PLANETS: A Modeling System for Business Planning,” Interfaces 17 (January–February 1987): 94–106.

3. Optimization models can be built into spreadsheets by using the Solver feature within Excel, for instance, or by using add-on software, but these models are not comprehensive enough to take into account the scope and detail needed for a global supply-chain model. For such optimization, the cost of APS software, including implementation, may exceed $1 million.

4. A.M. Geoffrion and R.F. Powers, “Twenty Years of Strategic Distribution System Design: An Evolutionary Perspective,” Interfaces 25 (September–October 1995): 105–127.

5. M.A.. Cohen and H.L. Lee, “Strategic Analysis of Integrated Production-Distribution Systems: Models and Methods,” Operations Research 36, no. 2 (1988): 216–228; and M. Cohen and H. Lee, “Resource Deployment Analysis of Global Manufacturing and Distribution Networks,” Journal of Manufacturing and Operations Management 2, no. 2 (1989): 81–104.

6. R. Breitman and J. Lucas, “PLANETS: A Modeling System for Business Planning,” Interfaces 17 (January–February 1987): 94–106.

7. B. Arntzen, G. Brown, T. P. Harrison and L. Trafton, “Global Supply-Chain Management at Digital Equipment Corporation,” Interfaces 25 (January 1995): 69–93.

8. A. Macdonald and D. Beavis, “Seize the Moment — Radical Supply Chain Integration as a Means of Increasing Shareholder Value and Enabling Acquisitions To Deliver on Their Promises,” Manufacturing Engineer 80, no. 4 (2001): 175–178; C. Farrell and R. Melcher, “The Lofty Price of Getting Hitched,” Business Week, Dec. 7, 1997; and D. Henry, “Mergers: Why Most Big Deals Don’t Pay Off,” Business Week, Oct. 14, 2002, 72–78.

9. B. Arntzen, G. Brown, T.P. Harrison and L. Trafton, “Global Supply-Chain Management at Digital Equipment Corporation,” Interfaces 25 (January 1995): 69–93; J. Muller, “Compaq Will Buy Digital in a Record $9.6b Deal,” Boston Globe, Jan. 27, 1998, p. A1; and “Compaq To Acquire Digital for $9.6 Billion,” Compaq press release, Jan. 26, 1998, New York, http://h18020.www1.hp.com/newsroom/pr/1998/pr260198c.html.

10. D.J. Frayer and R.M. Monczka, “Enhanced Strategic Competitiveness Through Global Supply Chain Management,” Annual Conference Proceedings of the Council of Logistics Management (Oak Brook, Illinois: Council of Logistics Management, October 1997): 433–441.

11. J. Greenbaum, “SCM Is Dead, Long Live SCM,” July 16, 2002, http://itmanagement.earthweb.com/columns/entad/article.php/1407831.

12. A.P. de Geus, “The Living Company” (Harvard Business School Press: Boston, 1997), 69.

13. H. Mintzberg, “The Rise and Fall of Strategic Planning” (New York: Free Press, 1994).

14. See M. Porter, “Competitive Advantage: Creating and Sustaining Superior Performance” (Free Press: New York, 1985); B. Melzer, “The Uncertainty Principle,” CIO Insight, June 1, 2001, www.cioinsight.com; and H. Kahn, “Thinking About the Unthinkable” (New York: Horizon Press, 1962).

15. E. Larsen, “What Is Scenario Planning?” teaching note, Cass Business School, London, 2000; P. Schwarz, “The Art of the Long View: Paths to Strategic Insight for Yourself and Your Company” (New York: Doubleday, 1991); P.J.H. Schoemaker, “Multiple Scenario Development: Its Conceptual and Behavioral Foundation,” Strategic Management Journal 14 (March 1993): 193–213; and P.J.H. Schoemaker, “Scenario Planning: A Tool for Strategic Thinking,” Sloan Management Review 36 (winter 1995): 25–40.

16. T.F. Mandel and I. Wilson, “How Companies Use Scenarios: Practices and Prescriptions,” SRI International, Menlo Park, California, report no. 822, spring 1993.

17. H. Mintzberg, “Planning on the Left Side and Managing on the Right,” Harvard Business Review 54 (July–August 1976): 49–59. Also published as H. Mintzberg, “Planning on the Left Side, Managing on the Right,” in “Mintzberg on Management: Inside Our Strange World of Organizations” (New York, Free Press, 1989), pp. 43–55.