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Design strategy and its interface with manufacturing and marketing: a conceptual framework.

Kenan-Flagler Business School. University of North Carolina at Chapel Hill. His research interests include the joint formulation of marketing and manufacturing strategies, and the concept of focused manufacturing. Before returning to school, Mr. Bozarth was a systems engineer at IBM.

Richard H. Deane ("Manufacturing and Marketing Interdependence in the New Venture Firm: An Empirical Study") is Professor and Chairman of the Department of Management at Georgia State University. He was formerly Associate Professor of Industrial and Systems Engineering at The Georgia Institute of Technology. Dr. Deane received his Ph.D. in Industrial Engineering from INTRODUCTION(1)

A business must identify its customers' needs, develop appropriate products to satisfy those needs, and (barring "Hollow Corporations" (Jones (1986))) have a manufacturing system to make its products profitably. Three functional areas that support these activities of a business are marketing, design, and manufacturing. To be competitive, each one of these areas needs to be managed strategically. Marketing has traditionally played an important role in business strategy, because it is seen as being close to the customer, and, until recently, manufacturing has played only a reactive role in the strategy formulation process (Hill (1989), Hayes and Wheelright (1984)). Now the strategic role of manufacturing is recognized and attempts are being made to put manufacturing strategy in its proper perspective (Adam and Swamidass (1989)). Manufacturing and marketing, however, are only two of the three links necessary to complete the design-manufacturing-marketing chain, the chain that connects the product, the producer and the customer. Although a business strategy is not complete without a design strategy to develop the product in the first place, the concept of design as a strategic weapon has been almost nonexistent (Meikle (1989)).

Design, manufacturing, and marketing must be managed strategically, but that is not enough. The successful performance of each of these functions, as well as the performance of the whole, is necessary to gain a competitive advantage. Therefore, a business organization needs to recognize the important interfaces between these three major functions. Unfortunately, what is observed in most organizations is a widening gap between design and the rest of the business (Meikle (1989)). In this paper we attempt to bridge this gap by:

(1) defining "design" as a strategic activity to facilitate its participation in the corporate debate, and;

(2) presenting a conceptual framework which integrates design with manufacturing and marketing as equal partners to support the overall corporate mission.


"Product design is a strategic activity, by intention or by default" (Whitney (1988)). A business has to compete to ensure its survival. The dimensions of competition are: price, quality, reliability, flexibility, service and delivery speed. In the manufacturing strategy literature, these dimensions are known as "content variables" (Adam and Swamidass (1989)). Yet, we believe, they are not dominated by manufacturing or marketing decisions alone. In fact, major commitments to these dimensions are usually made during the design stage of a product's development. A large portion of the production costs can be determined at the design stage. Similarly quality cannot be "manufactured in" unless it has previously been "designed in." Product design is also the key stage in defining a product's reliability. It can be used strategically to ensure flexibility of market response, to facilitate improved service levels and to compress concept-to-market cycle time.

Design should also be recognized for its own unique contribution to competitiveness. This is because design introduces new competitive priorities such as new product development, timely introduction of new products from conception to market delivery, and the invention of attractive secondary features for an existing product. For these competitive priorities the roles of manufacturing and marketing are that of followers which must successfully interface with the design innovators. This will be clear as we explore the concept of design quality (e.g., performance, features, reliability, durability, aesthetics, etc.) later. A company that fails to use product design as a strategic element of its business strategy is missing a big opportunity and starting the race from a position of disadvantage.

The simplistic product design approach, "let's introduce some product in the market now and improve it later," is no longer a viable option. A product's design is a decision of strategic importance and, as such, can have fatal consequences. In many cases, because of short product life cycles and the lead-time from product design to final market, the opportunity to improve never comes. The global character of today's competition forces examination of different design strategies for different markets. Such strategies need to be developed quickly and should be appropriately integrated with other functional strategies. Yet, years of neglect have made the linkage between design and the rest of the business very weak at best.

There exists very little awareness of design as a strategic business activity among the academic community and practitioners of business. To break down the barriers between design and the rest of the business, a common language is needed. Design is not just an engineering activity taking place behind high walls far away from corporate headquarters and manufacturing facilities. Design is a business function and a source of competitive strength.


The literature that relates to design and design strategy can be classified into three major categories: manufacturing strategy (MS), design for manufacture (DFM), and quality function deployment (QFD).

The manufacturing strategy (MS) literature recognizes the strategic role of manufacturing and emphasizes increased interaction between manufacturing and marketing to gain competitive advantage (Skinner (1969, 1974), Hayes and Wheelright (1984), Hayes, Wheelright, and Clark (1989)). Hill (1989) defines the concept of manufacturing strategy from a pragmatic point of view and presents a very good framework for integrating manufacturing and marketing strategies. However, most of the literature in this area assumes design as given and as requiring resources that manufacturing does not control. Consequently, the authors do not address the strategic role of design in business strategy, and have not integrated design strategies with manufacturing and marketing strategies.

The design for manufacture (DFM) literature is substantial and can be classified into two major categories based on the functional focus of the content, i.e., DFM with a business focus, and DFM with an engineering focus.

The DFM literature with a business focus (Whitney (1988), Dumaine (1989), and Takeuchi and Nonaka (1986)), emphasizes the strategic nature of design by pointing out that design influences the flexibility of sales strategies, speed of field repair, and efficiency of manufacturing. It also discusses the organizational issues related to design team structuring. The DFM literature with an engineering thrust (Stool (1988), and Burling, Bartels, Barbara, O'Neill, and Pennine (1989)) discusses "design-for manufacture" methodologies and the use of computer-aided systems. The DFM literature, in general, focuses on how to design products that are easier to manufacture. Unfortunately, this literature leaves marketing issues out of the discussion.

The quality function deployment (QFD) concept emphasizes increased interaction between engineering design and marketing to facilitate communication of customers' needs to the product designers (Hauser, and Clausing (1988)). QFD supports interaction between marketing and design groups throughout the product development cycle, assuring that design decisions are made with full knowledge of all technical and market trade-off considerations (Fine (1989)). However, the literature in this area bypasses the issue of manufacturing which is the vital strategic link in the design-manufacturing-marketing chain.

Research in the area of manufacturing strategy (MS), design for manufacturability (DFM), and quality function deployment (QFD) promotes integration among design, manufacturing, and marketing in pairs, i.e., MS between manufacturing and marketing, DFM between design and manufacturing, and QFD between marketing and design. Even more, in most cases a rather narrow definition of product design, that of engineering design is used. However, the natural flow of the product from the designer's desk to the manufacturer's work bench to the customer's hand emphasizes the need for interaction among all three functions.

In addition a broader view of product design, one that includes not only engineering aspects but also ergonomic and industrial design principles, must prevail. A comprehensive framework to integrate all three functional strategies during the business strategy formulation process and to recognize explicitly the fundamental role of product design is nowhere to be found in the current literature.


While most people would agree that design is important, there is no agreement on how to define it. The word design is usually used in a very broad context. At the one extreme it "is identified with the most superficial elements of style" such as "designer hairstyle," "designer jeans," etc., and at the opposite extreme it is related, at least by implication, to all scientific and technological advancements. However, none of these approaches can be used to define design in a way that is beneficial to both business and the general public (Meikle (1989)).

In this article, when we talk about design we mean product design, and when we refer to design strategy we mean product design strategy. By product design we mean the entire process and combined effort of engineering, industrial, and human factor design specialists that finally result in the creation of a product, often in prototype form.

Design strategy is a plan of action to gain competitive advantage through product design. That can occur either through the design of new products that create new markets or through supporting existing market needs better than the design function of the competitors. For example, a competitive edge could be the result of a technological breakthrough that creates a new market (Xerox plain paper copier) or it could be the result of an innovative application of existing technology (Macintosh personal computer). The role of product design in creating new markets has always been recognized, but for most businesses design strategy concentrates on the second of these two roles, i.e., doing it better than the competition. The time-based and global nature of today's competition makes it crucial to emphasize the role of design in creating new markets.

As shown in Figure 1, the process consists of two stages and can be used iteratively until the desired result is achieved. It begins by asking how a product competes in the marketplace. The dimensions of competition, without our list being necessarily exhaustive, are: price, quality, speed, flexibility, and service. A product can compete on price. It can also compete on the speed of product development. These are very straight-forward concepts and require no further elaboration. However, the concept of competing on quality is slightly more complex. This is because the word "quality" has different meanings to different people. We subscribe to the definition given by Garvin (1984). Accordingly, the quality dimension will consist of eight separate dimensions--performance, features, reliability, conformance, durability, serviceability, aesthetics, and perceived quality--to facilitate understanding of the influence of product design on quality. Therefore, we look at an expanded set of competitive dimensions: price, speed, flexibility, performance, feature, reliability, conformance, durability, serviceability, aesthetics, and perceived quality. Depending on the product and the market segment in which we are competing, any one or any combination of these dimensions can be used strategically to achieve a product positioning and market differentiation necessary to gain competitive advantage.

Price positioning is limited by production cost. Studies reveal that up to 80% of production costs can be determined at the design stage (Corbett (1986)). Consequently, product design can and should be used strategically to achieve a desired price positioning. For example, in the early 1970s, Japanese automakers entered the low end subcompact segment of the United States automobile market primarily based on their ability to design autos that cost less to manufacture.

Competition on product development speed, i.e., the ability to deliver new products to the market fast, is catching on. Time-based strategy, as the new approach is called, often pays off in product development even if it means going over budget. An economic model developed by the McKinsey & Co. management consulting firm shows that high-technology products that come to market six months late, but on budget, will suffer a 33% profit reduction over a five-year period. In contrast, coming out on time and 50% over budget cuts profit only by 4% (Dumaine (1989)). To compete on speed, companies must learn to compress the concept-to-market lead time by introducing new technology fast and by improving their ability to introduce changes rapidly at the design stage.

Flexibility is the ability to respond to uncertain changes in the market place. For our purposes, we concentrate on three types of flexibility. These are volume flexibility (i.e., the ability to respond to demand changes), product flexibility (i.e., the ability to introduce new products), and lead time flexibility (i.e., the ability to respond to customers' orders fast). Lead time flexibility is necessary to compete on the delivery speed. Product design influences all three types of flexibilities. While the effects of sound product design strategies on the last two is apparent, that might not be so for volume flexibility. The effect of product design on volume flexibility becomes more apparent, however, when we consider how a product designed with easy-to-manufacture features can increase the effectiveness of the manufacturing process.

The performance of a product is primarily determined by its design. Its features, reliability, durability, serviceability and aesthetics are all established at the design stage. This is why they are often grouped together as design quality. The fits and tolerances specified at the design stage also influence its conformance quality. Perceived quality of a new product can be influenced by establishing a reputation for outstanding product design, as for example, the automobiles manufactured by Mercedes-Benz of Germany. Thus, product design is a key strategic resource to achieve positioning across any of the competitive dimensions.

Strategic Positioning on the Complexity/Innovation Matrix

The discussion above indicates that product design decisions, by intention or by default, position firms along important competitive dimensions. In order to manage design strategically, we need to understand what level of design effort is needed to achieve a particular position along these dimensions of competition.

An aggregate measure of the design effort is required for analyzing and understanding all the strategic alternatives that can be pursued to gain a competitive advantage in an existing product-market segment and to identify new product-market segments. Towards this end we define two fundamental variables of product design activity, complexity and innovation, as the "basic design variables." We have used the word "basic" to emphasize the fact that these two variables are, in most cases, adequate to define a design task, and all of the eleven dimensions of competition mentioned earlier can be mapped appropriately on a point of a two dimensional grid built on the complexity and innovation dimensions.

Complexity of a system is defined by the number of elements in that system and by the level of interactions among these elements (Cooper, Sinha and Sullivan (1990)). For example, a product with a larger number of components is more complex than a similar product with fewer components. That is photocopying machine is more complex in design than a coffee maker because it has more parts in it. Also, the complexity is increased if the components in one product have a higher level of interaction than those of another product. Thus, a photocopying machine is more complex than a PBX telephone switching center even though they may have the same number of components. The components in a photocopying machine must interact with each other to perform its designed function while the connectors in a PBX are mounted in separate banks with no required interaction (in fact, they are not supposed to interact with each other).

Innovation is defined as the incorporation of new ideas and technology (Foster 1986). The level of innovation is measured by the degree of change an innovation brings in comparison to the existing level of "performance" of a product concept. For example, depending on the degree of change, the level of innovation may be measured along a continuum between two points defined as incremental (where it involves only small changes such as the addition of wipers to the headlights of an automobile) and radical (where it involves large scale changes such as the introduction of front wheel drive and an anti-lock braking system).

Complexity in itself is not necessarily undesirable. It is often a necessary component in building or maintaining competitive advantage (Hagel (1988)). For example, Raychem Corporation, a company that supplies technology-intensive products, makes products that are complicated to design and manufacture and consequently, lend a competitive advantage (Taylor (1990)).

Similarly, innovation in itself is not always desirable. A high rate of innovation that leads to short product life cycles may not always be desirable from a business perspective. Also, unmanaged innovation at the product development stage is a potential cause of delays in product introduction, and consequently, creates lost opportunities that occur under time based competition.

Note that complexity and innovation, as defined above are relative concepts and any measurement scheme must reflect this property. Two possible ways to position a design strategy along the two dimensions are:

(1) comparison with respect to past product designs of the specific company for the same (or similar) products, and

(2) comparison with respect to the competition (i.e., with respect to competing products in the current or future markets).

For example, we can compare the audio cassette players manufactured by Philips today with the cassette players they designed earlier. Also, we can compare similar Philips products with those of its competitors such as JVC, Sony, AKAI, Dual, Grundig, and Panasonic. Appropriateness of a particular scheme will depend on the nature of the decision and the realities of the market. When a company laces weak competition, or introduces new products in a segment where the company has had success, the use of the first scheme might be more appropriate. The second comparison scheme might apply better to cases of aggressive entrance in markets dominated by other firms.

To facilitate understanding of the concept presented, we shall use as a visual aid a two-by-two matrix with the vertical axis representing complexity and the horizontal axis representing level of innovation. For each of the dimensions, appropriate positioning of the existing product, as well as that of competitors' products, identifies threats and opportunities and provides a basis for strategic planning. This two-dimensional mapping scheme also highlights the consistency of the design strategies.

As an example, in Figure 2, we have mapped the order-winners and qualifiers for three different printers. Our source of information is the well known IBM Proprinter case (March (1988) and (1991), Gomory (1989)). The framework contrasts the design task of IBM Proprinter with that of its competitors based in South East Asia (such as EPSON) in the low cost ($200 to $300) PC segment of the market, and also with the traditional high-performance main line IBM printer products. We find that IBM has been consistently following a high-complexity/high-innovation design strategy for its main line printer products which offered high performance and many features at a very high price (starting at $5000). These machines were primarily purchased by corporate data processing centers. On the other hand, the South East Asian manufacturers were following a high complexity/low innovation strategy. The low level of performance (e.g., 80 characters per second printing speed) and the basic features (i.e., dot matrix with tractor feed) they offered required very little innovation and called for a low complexity design. Instead they were using a complex design (e.g., 150-200 components with only about 50 working components) with numerous fasteners, springs and pulleys. Yet they were successful in achieving low cost production due to their labor cost advantage, IBM analyzed the competitors' products and identified this inconsistency as an opportunity. In response, IBM then introduced its Proprinter with a low-complexity/high-innovation strategy. It offered better features (e.g., near-letter quality with front feed options) and better performance (e.g., 200 cps). As a consequence of the low complexity design, it also achieved a higher level of reliability (e.g., one failure predicted every 20 years) at a competitive price. IBM achieved this high quality-price position by using only about 60 components compared to the 150-200 different components used by its competitors, and this required a very high level of innovation by IBM's designers. Clearly the design task for the IBM Proprinter was different from the design process involved with its traditional printer products.

The strategic insights gained at this first stage of design strategy formulation are used as inputs for the next stage, where we shall consider the choice of a suitable design infrastructure to accomplish a product design task.

However, before we move into the design infrastructure discussion, we need to understand the relationships between each one of the dimensions of competition and the basic design variables, i.e., for a specific situation how the multiple competitive dimensions will be mapped onto a point in the complexity-innovation matrix. To map a product design on the complexity-innovation matrix, we need to define two independent relationships--one for the complexity variable and its dependence on the competitive dimensions, and the other for the respective relationship of the innovation variable for each one of the dimensions of competition (i.e., cost, quality, speed, flexibility, service) in which we are interested.

Some of these relationships are easily recognizable and very general in nature across all product categories. For example: cost (price) is a direct exponential function of complexity (Hagel (1988)). That is, the higher the complexity of a product, the higher the cost will be. The increase in cost will be much higher than the corresponding increase in the level of complexity.

Sometimes these relationships are not clear. For example, the inverse relationship between cost and innovation level is not readily apparent. This is because a higher level of innovation may bring on an increase in the level of some of the other dimensions of competition, such as serviceability, that is reflected in lower cost. The discussion that follows provides some general observations on the nature of the relationships between the competitive design dimensions and the two basic design variables of our framework.

Speed is defined as the time it takes from the development of a product concept until the product reaches the market. Design changes are unavoidable in the product development stage. However, frequent design changes are the major source of project delays. The ability to introduce design changes rapidly is a necessity for a time-based strategy. When competing on speed, it is desirable to have products with low levels of complexity because it is easier to introduce changes in a simple design with functional independence than in a complex design with a large number of interdependent functional. However, achieving a desired level of performance with a simple design depends on a company's ability to adapt to new technology fast, thus, requiring a high level of innovation at the product design stage. As a general note, keep in mind the complexity-speed negative and innovation-speed positive correlations.

Flexibility is the ability to respond to market changes and it is generally viewed as dominated by manufacturing decisions. However, higher levels of the three types of flexibility, i.e., volume flexibility, product range flexibility, and lead time flexibility, are easier to achieve with simple products. Product complexity increases the burden on the manufacturing system, because more components or tighter assembly require more sophisticated controls (e.g., inventory, quality etc.) and entail higher chances of costly mistakes. For high volume this usually results in the need for more dedicated (i.e., mass production) processes. Low volume requires a flexible manufacturing system (FMS). In either case, such options are expensive. In general, simple product design can result in increased flexibility.

Performance usually refers to the primary operating characteristics of a product. For an automobile, these would be traits like acceleration, handling, fuel consumption, and comfort; for a stereo system, they would include frequency response, signal-to-noise ratio, and the ability to reproduce recorded music faithfully without appreciable distortion. Features are the secondary characteristics that supplement the product's basic functions. For an automobile, these would be sunroof, customized wheel-cover, etc.; for a stereo system, they would include remote control, high speed dubbing, etc. Features are also necessary for the human factor design to improve user interface. For example, the pull-down menus and the point-and-click mouse greatly enhanced the user interface for the personal computers designed by Apple Computer, Inc. Performance and features of a product directly follow from the creativity and skill of the design efforts. An increased level of innovation is required to achieve higher performance and better features. Higher levels of performance and increased number of features raise the level of complexity of a design. For example: consider a high performance internal combustion engine with four valves per cylinder. It requires a higher level of technological innovation to improve the operating characteristic of such an engine, which usually brings added complexity through an increased number of components to support these improvements.

Reliability is an engineering design and technology related product characteristic that reflects the probability of a product failing within a specified period of time. To meet the desired reliability of a product for a given cost level, complexity is reduced, For example: a system consisting of a single component having 10% probability of failure is more reliable than a system consisting of 100 components operating in series, each having the same 10% probability of failure. The probability of the system failure for the first case is only 10% compared to the 99.99% chance of system failure for the second case. Of course, designing an equivalent system with a single component having only a 10% probability of failure will require a high degree of innovation.

Reliability can also be enhanced by the use of components at less-than-rated capacity or by the use of component redundancy. In the above example, if we have a system with 100 components in parallel, the probability of system failure would decline to almost 0%. Many types of defense equipment fall in this category. The complexity of such systems having high redundancy levels increases with the increase of reliability, and we should not forget the associated cost trade-off. There are some smart product designs, mostly based on engineering ingenuity, where the product itself is designed to diagnose and, in some cases, to repair some or its field failures or to signal the user of needed repair. In this product category, higher levels of complexity and innovation lead to an increased level of reliability. An example of such a product would be the super-chip (Collingwood (1990)).

The question that arises from the above discussion is whether it is possible to map the reliability position onto the complexity-innovation matrix independent of other dimensions, and in particular, of the cost dimension. Actually, the same question could arise while mapping some of the other dimensions as well. Our answer is "no" for most cases. Still, it can be done in a sequential fashion. What is the appropriate sequence? This question should be part of the corporate debate. The most valuable characteristic of our proposed way of formulating design strategy is the fact that it structures the debate in a concrete and consistent way.

Conformance is the degree to which a product's operating characteristics match preestablished design standards and is perhaps the most important manufacturing-related dimension of competition. Loose specifications which are easier to meet, are less complex than tighter specifications. However, relaxation of these specifications without sacrificing performance of other dimensions may require a higher level of innovation. It is essential to understand that conformance to design specifications is not just the job of the manufacturing engineers and managers striving, sometimes hopelessly, to achieve unrealistic tolerance targets. All aspects of product design, not just tolerance setting, affect the level of conformance that can be achieved during manufacturing and passed on to the customer.

Strategic positioning along some of the competitive dimensions anti emphasis on achieving the desired level of conformance through clever parameter setting during the design phase, can reduce the manufacturing effort required to meet a target conformance level (Taguchi (1987), Taguchi and Clausing (1990)). For example, modifying the chemical composition of the plastics to be used for molding a product can make it less sensitive to temperature control during manufacturing and avoid a mold sticking problem. When positioning conformance on the complexity-innovation matrix, the mental task on the product design strategist is enormous, because, at the same time, he/she should consider the manufacturing implications.

Durability is the amount of abuse a product can absorb during its economic life and still meet performance expectations. Increased level of durability is usually associated with increased levels of innovation at the design stage because it involves innovative use of materials and processes. This may also create an increased level of complexity. For example, consider the corrosion resistance techniques used during auto body manufacture. The rust proofing process of some of the industry leaders use up to nine different coats and involves such exotic technology as electrostatic painting techniques.

Serviceability is the speed, courtesy, and competence of repair a company provides for its products in the field. The servicing of products in the field seems to be so remote from the product design activity that in many cases companies fail to recognize the close and important interaction between serviceability and product design. Often service is simply regarded as an after-the-sale activity of the marketing department. On the contrary, serviceability of a product is inherent in its design. Many products are so complex that they require user training, periodic maintenance, or both (Cohen and Lee (1990)). It is much easier and faster to carry out repair work on a simple product. The serviceability can also he improved by a modular design, where a failure can be confined to the module in which it originates. This type of design usually calls for a higher level of innovation.

Aesthetics is the combination of product attributes that best matches the preferences of a specified consumer. Here, we refer to individual preferences. It might seem there can be no general relationship between aesthetics and the two variables of design, i.e., complexity and innovation. Yet, the mass appeal of the aerodynamic revolution of the 1930s and the more recent success of the Sony Walkman suggests that there is a general relationship that says "simple is beautiful." However, achieving a heightened state of beauty from a simple design calls for a very high level of innovation at the product design stage.

Perceived quality is an indirect measure used by customers in the absence of complete information about a product's attributes for comparing brands (Garvin (1984)). A higher level of innovation may be required to design products to affect consumers' perceptions positively. Sometimes this may increase the complexity level of a product, as people tend to associate complexity with other dimensions of competition such as higher performance. However, it should be noted that reputation is a primary contributor to perceived quality and can only be built by selling well designed products over a very long period of time.

Selecting the Design Infrastructure

The first step in formulating a design strategy is to define a design task by positioning a product concept consistently along all the competitive dimensions in the market segment of interest. A consistent positioning leads to a unique position on the complexity-innovation matrix.

The next issue is how to manage complexity and innovation to achieve the desired positioning, i.e., to accomplish the defined design task in the most effective way. To deliver the product design strategy, we need to develop an infrastructure to create an environment that will match the required design task. This is an important proactive step for managing design strategically and is entirely different from the traditional reactive mode of design operations currently encountered in most businesses. The decisions that need to be made for the development of a design infrastructure can be classified into two major categories:

(1) structuring a design organization (or design team),

(2) developing a design support system (or design tools)

The design organization refers to the organizational structure necessary to achieve the target position on the design matrix. There is no one general organizational structure that is suitable for managing all levels of complexity and innovation. For example, when an organizational structure that has been designed to deal with a high level of complexity (or innovation), is employed to deal with a low complexity (or innovation) situation, an inefficient utilization of expensive resources may result.

In the literature, advocates of specific product development approaches lay out the pros and cons of various alternatives. We believe that a sequential approach (Dixon and Duffy (1990)) is suitable for managing a high level of complexity and it can best be supported by a functional organization. A team approach (Takeuchi, and Nonaka (1986)) is suitable for projects requiring a high level of innovation and it can best be supported by a product-focused organization. A concurrent approach (Nevins, and Whitney (1989)) covers the middle ground and it can best be implemented by a matrix organization. A sequential approach places less demand on design resources than that required either by a team or a concurrent approach, but usually requires longer development time.

A particular product positioning may call for a particular approach to product design. It is not likely that a common organizational structure will support all three of these approaches to product development with equal efficiency.(*) For example, when IBM abandoned its traditional sequential product development strategy in favor of a team approach for its Proprinter project, it also developed a new organizational structure to implement the team approach (March (1988) and (1991), Gomory (1989)). Our framework emphasizes the importance of struggling with the issue of organizational design and forces trade-offs to be considered during the strategic debate.

The design support system refers to the tools and techniques to be used to support the design task. An extensive set of tools are at the designer's disposal such as structured planning, design axioms, design for manufacture guidelines, design for assembly methods, design for analysis principles, Taguchi method, computer-aided design, group technology, and quality function deployment (Mallick, and Kouvelis (1992)). A partial list of these tools and techniques is presented in Table 1. Some of these tools and techniques can be employed to control complexity. Consider the following two design axioms: the first demands that each functional requirement of a product is satisfied independently by some aspect, feature, or component within the design. The second says that a good design maximizes simplicity, i.e., it provides the required functions with minimal complexity. According to these axioms a design problem is to be defined in terms of functional requirements and constraints. The solution to the design problem results from translating these functional requirements into design parameters in accordance with the axioms of good design, thus maintaining a low level of complexity (Suh, Bell, and Gosserd (1978)).

Some of these tools and techniques can be used to control both complexity and innovation level. Consider the design for analysis principle which says that designers should be constrained to work only with those designs (of products or systems) that can be analyzed easily and quickly by simple tools. For example, the PADL (Part and Assembly Description Language) developed by Xerox can constrain a designer to use only a Boolean combination of simple geometrical primitive solids (e.g., orthogonal blocks, cylinders, wedges and cones etc.) to describe an object. A study revolving 128 mechanical parts in a table top copier revealed that designers tend to produce better designs when constrained to use simpler modeling tools than if they are allowed to use tools with greater modeling capability (Suri and Shimizu (1989)). IBM used design for manufacture guidelines to reduce complexity and encourage innovation by banning the use of springs, fasteners and pulleys and by encouraging reduction in the number of parts used during the design stage of their now-famous Proprinter (March (1988) and (1991), Gomory (1989)). Therefore, by specifying design support tools, it is possible to manage complexity and innovation for a specified design task.

Some of these tools and techniques can encourage innovation and control complexity during the product design process. Consider the design for manufacture guideline that asks for use of modular product options to improve flexibility of future feature enhancement (Walleigh (1989)). This guideline can be used to control innovation level by specifying the nature, timing and the number of such feature enhancements.


As a part of the overall business strategy, a business organization interested in a particular product-market segment has to position itself along the competitive dimensions of price, performance, features, reliability, durability, aesthetics, perceived quality, conformance, product development speed, flexibility and service. Depending on the product-market segment of interest, some of these dimensions may be qualifiers to enter a market and the remaining dimensions may be necessary to win orders (Hill (1989)). These order-winners and qualifiers are the integrating threes in design, manufacturing, and marketing. Specified levels across each of these dimensions of competition serve as a set of objectives that need to be supported by a combined effort of design, manufacturing, and marketing.

It is important to recognize the interrelationships that exist between design, manufacturing, and marketing. This reveals the opportunities and the trade-offs involved in the effort to balance the resources needed to implement design, manufacturing, and marketing strategies that lead to a desired position along the dimensions of competition with optimal cost and flexibility of planning. Failure to recognize such interrelationships among these three functional areas leads to inferior business strategies as a natural consequence of the resulting suboptimization of corporate resources.

As an example, consider a company selling a product in a market where perceived quality is the order-winner. The company may spend a large amount of money on promoting the product's image. The marketing effort in this case can be made more effective by designing the product with a quality appearance. In this case, it is possible to get more out of the same advertising dollar by treating design strategically and recognizing its relationship with marketing. Or consider the example of Ford's Taurus project. Members of "Team Taurus"--designers (engineers, industrial and human-factor specialists), manufacturing specialists, and marketing experts--started working together early in the product development process. In that project it was reported to be unusual for one functional group to create problems for another (Taylor (1988)). The product design team revived the aerodynamic concept, marketing emphasized the aerodynamic look in its promotion and manufacturing was able to reproduce faithfully the quality that was designed in. As a result, Ford was able to fight its way to market leadership in Europe for the first time. In the United States, its "jellybeans," as the popular press dubbed its new range of aerodynamic cars, quickly restored several precious points of market share that had been lost to General Motors and to the Japanese (Lorenz (1986), Patton 1987)).

The framework proposed here suggests a structured approach to corporate decision makers to link design strategy with marketing and manufacturing. The framework, as shown in Figure 3, extends Hill's (1989) manufacturing strategy framework to incorporate design strategy as defined earlier in this paper. Five basic steps are required to establish the linkage between design, manufacturing, and marketing. Each of these five steps will be illustrated using the empirical data available on the IBM Proprinter case (see March (1988) and (1991), Gomory (1989)). However, some of these steps will not be dealt with in detail because they have already been treated extensively in the existing literature.

Step 1: Defining corporate objectives and the business strategy. Corporate objectives may be different for each firm, reflecting the unique nature of the business and its strategic awareness and vision (see Porter (1980) for further discussion on corporate and business strategy). For example, when IBM experienced a much larger than anticipated growth in the personal computer market it wanted to extend its printer business into the low-end PC segment. Beside economic reasons, the decision to enter the low-end printer segment was perceived as a means to generate organizational learning and confidence in low-cost design and manufacture. The IBM Proprinter was a pilot project to venture into the low-end printer market dominated by Asian competitors, especially the Japanese.

Step 2: Establishment of order-winners and qualifiers. At this stage the relevant dimensions of competition are defined as order-winners and qualifiers by asking how a product competes in the market segment of interest. For a detailed discussion on establishing order-winning criteria refer to Hill (1989). However, this framework is different as it focuses on all the relevant dimensions of competition and not just on the dimensions dominated by manufacturing alone. However, like Hill's framework, this is the crucial step in this framework because the set of order-winners and qualifiers links the corporate marketing proposals and commitments to the design and manufacturing processes and to the supporting infrastructure. For example, in the IBM Proprinter case price and reliability are qualifiers. However, a product with superior performance and features will win orders.

Step 3: Formulation of marketing strategy. The marketing strategy is the logic by which the business unit expects to achieve its marketing objectives. Marketing strategy consists of making decisions on corporate marketing expenditures, marketing mix, and marketing allocations in relation to expected environmental and competitive conditions (see Kotler (1984) for further discussion on marketing strategy). For example, in contrast to the industrial segment of the printer market where lBM had little or no competition, the low-end segment of the printer market was characterized by intense competition with Japanese manufacturers holding an 80% market share. The low price printers sold in this market had low performance (printing speed 80 cps) and minimal features. Therefore, IBM's marketing strategy was to differentiate itself with better performance (200 cps, near-letter quality) and features (front feed in addition to conventional pin feed), while maintaining price parity with the competition.

Step 4: Formulation of a manufacturing strategy. The concept of manufacturing strategy is also not very well defined. We subscribe to the role of manufacturing strategy as presented by Hill (1989):

(1) to provide a process technology edge, and/or

(2) to support the company's market needs better than the manufacturing function of its competitors.

The implementation and control of manufacturing strategy is a two part process as shown in Figure 3. It starts with a process choice and then goes on to select an appropriate infrastructure to support the process choice. In the Proprinter project, the task of IBM manufacturing was to maintain low manufacturing costs while providing a higher level of conformance quality. IBM neutralized the labor cost advantage enjoyed by the competition by eliminating the labor component through automated (robotized) manufacturing and control. The manufacturing task was supported by a clever design that reduced part count and eliminated difficult-to-automate components such as screws and pulleys. The design was so successful that an individual assembly worker could put a Proprinter together in just three and one-half minutes.

Step 5: Formulation of a design strategy. This step involves two phases:

(1) positioning of the product design along the complexity and innovation dimensions, and

(2) identifying the appropriate design infrastructure to support the product design task for the targeted strategic positioning.

As mentioned earlier, the design task for the Proprinter was defined by low complexity and high innovation. Even though the project progressed sequentially at the concept development stage, a concurrent product development strategy was implemented using a matrix organization with a heavyweight project leader. The project team was multidisciplinary with participation from marketing, manufacturing and design. In addition to engineers, the design team also received vital inputs from the industrial and human-factor design specialists. CADAM, an IBM in-house CAD/CAM system was used to integrate the design team with the outside vendors and suppliers. This design support tool helped to foster innovation through better communication. Other design support systems used were design-for-manufacture and design-for-automated assembly guidelines. They were used to ensure feasibility of robotized manufacturing through reduction of complexity in design.

In this case IBM successfully identified the design task that was necessary to support the manufacturing and marketing strategies. The company was also very successful in developing an appropriate infrastructure for accomplishing this task through the design of a new organization structure and through judicial use of various design support systems.

There are two different ways the framework proposed here can be used to facilitate participation of design, manufacturing and marketing in the corporate strategic debate. Following the steps mentioned in a sequential fashion, the implication for product design and manufacturing process of a specific marketing strategy can be assessed. That helps to make clear the design and manufacturing trade-offs involved, as well as the demands on the organizational resources (either of the design or of the manufacturing functions) imposed by marketing. Such a procedure is extremely helpful for the evaluation of short term marketing strategies. However, during the corporate debate, the framework should be used differently. At this time the sequential execution of the above five steps will then provide only input for the relevant tradeoffs of different strategies.

Whenever the resulting trade-offs are unsatisfactory due to a misfit between any two of the functional strategies (i.e., marketing-design, marketing-manufacturing, and design-manufacturing), reiterations between the above steps are required until the mismatch disappears or reaches an acceptable level for the cases where some degree of mismatch is unavoidable. Such an exercise is extremely helpful in learning the extent of the consequences that functional interface mismatch causes and it provides inputs vital to the strategic debate.


Product design is a strategic business activity that affects the efficient operation of the entire business. We presented a precise definition of product design and design strategy from a business perspective. The conceptual framework proposed here can facilitate formulation of design strategy and its integration with manufacturing and marketing strategies. The IBM Proprinter case is a good example of how the framework can be used effectively to highlight important design trade-offs and to bring out issues related to the design-manufacturing-marketing interface during the corporate debate. The framework is easy to understand, and it utilizes already existing business terminology to facilitate easier acceptance by the business community. This is a significant step towards integrating design and the other functions of a business organization.

Product design has traditionally been treated as an unstructured process and very little qualitative and quantitative research exists in this area to date. It will prove to be a very interesting and challenging area as companies recover from the "marketing myopia" of the 60s and the "financial follies" of the 70s and come to terms with the fact that a company must compete on the basis of the product it sells.


* The design of organizational structure to manage a target level of complexity and innovation is itself a very complex organizational science issue and is an interesting research topic by itself. Any reasonable treatment of this area is beyond the scope of this discussion and interested readers are referred to Mallick and Kouvelis (1992).


This research is funded in part by the Corporate Design Foundation, Boston, Massachusetts, under the Design Leadership Program.


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* STRUCTURED PLANNING |Owen (1987)~. * AXIOMATIC APPROACH |Suh et al (1978)~. * DESIGN FOR MANUFACTURE GUIDELINES |Stoll (1988)~. * DESIGN FOR ASSEMBLY GUIDELINES |Boothroyd and Dewhurst (1983)~. * DESIGN FOR ANALYSIS PRINCIPLE |Suri & Shimizu (1989)~. * TAGUCHI METHOD |Taguchi (1978)~. * GROUP TECHNOLOGY |Kusiak (1990)~. * QUALITY FUNCTION DEPLOYMENT |Hauser & Clausing (1988)~. * COMPUTER AIDED DESIGN |Burling et al. (1987), StoIl (1988)~.

Author Profiles

William L. Berry ("Linking Strategy Formulation in Marketing and Operations: Empirical Research" and "Factory Focus: Segmenting Markets from an Operations Perspective") is the Belk Professor of Business Administration in the Kenan-Flagler School of Business at the University of North Carolina at Chapel Hill. His teaching and research focus on international manufacturing, manufacturing strategy and manufacturing control systems. He has taught in Europe, Central and South America, and was visiting professor at the International Institute for Management Development in Lausanne, Switzerland. He is past-president of the Operations Management Association and the Decision Sciences Institute. His most recent book is Manufacturing Planning and Control Systems (third edition), published in 1992.

Joseph D. Blackburn ("Time and Product Variety Competition in the Book Distribution Industry") is Professor of Operations Management in the Owen Graduate School of Management, Vanderbilt University. He is also Director of the Operations Round Table--an academic-business research partnership funded to study current issues in operations management. He received his Ph.D. from Stanford University, an M.S. from the University of Wisconsin and a B.S. from Vanderbilt University. Dr. Blackburn has served on the faculties of the University of Chicago and Boston University and was a visiting professor at Stanford University. His book Time-Based Competition: The Next Battleground in America, Manufacturing was published in 1991 by Business One-Irwin.

Cecil Bozarth ("Factory Focus: Segmenting Markets from an Operations Perspective") is a Ph.D. Candidate at the
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Title Annotation:Special Issue on Linking Formulation in Marketing and Operations: Empirical Research
Author:Fitzsimmons, James A.; Kouvelis, Panagiotis; Mallick, Debasish N.
Publication:Journal of Operations Management
Date:Jul 1, 1991
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