Mass Customization: Metrics and Modularity - Springer Link

The International Journal of Flexible Manufacturing Systems, 16, 287–311, 2004 c 2005 Springer Science + Business Media, Inc. Manufactured in The Netherlands.


Mass Customization: Metrics and Modularity ASHOK KUMAR Grand Valley State University, Grand Rapids, MI

Abstract. Mass customization as a competitive strategy is getting progressively increasing attention in business and academic arenas due to its high potential to provide sustained strategic advantage in a unique fashion. It is well documented that a manufacturing company competes with others in its industry on five dimensions: Price, quality, flexibility, delivery, and service. According to the existing literature, mass customization provides significant strategic advantage in two of these dimensions—price and customization. We, however, argue that when properly implemented, the cellular manufacturing structure associated with the appropriate implementation of mass customization strategy, provides additional competitive value in quality and delivery. Furthermore by virtue of the customer co-design as an integral aspect of mass customization, customer satisfaction also improves under this strategy. Mass customization strategy, therefore, provides competitive advantage in all five competitive dimensions simultaneously—a truly unique strategic accomplishment. We also propose, in this paper, new metrics for mass customization strategy that measure the “mass” as well as the “customization” aspects of this strategy. Finally, we describe in the clearest terms the modus operandi of modularity in product design and the role it plays in bringing about high levels of customization on one hand and economies of scale at component level, on the other. We conclude with remarks that underscore the need for conducting research in the areas at the interface of mass customization and supply chain management. Key Words: mass customization, competitive priority, modularity, metrics

1.

Introduction

The rivalry between the price of a product and the degree of customization built into it is at least as old as the industrial era. Customers and markets are well-versed with the notion that closer a product is in its features, functions, and capabilities to what a customer wants, higher the price that the customer is willing to pay for the product. Alternatively stated, in a free market system, price of a product increases monotonically with the degree of customization built into it. The marginal increases in price depend on the degree to which a customer values marginal increases in product customization. If, however, we presented an option to a customer wherein higher levels of product customization are provided without the corresponding exorbitant price increases, the customer will be delighted. This is precisely what mass customization accomplishes when deployed as a strategy. Piller (2005b) defines mass customization as, “Customer co-design process of products and services, which meet the needs of each individual customer with regard to certain product features. All operations are performed within a fixed solution space, characterized by stable but still flexible and responsive processes. As a result, the costs associated with customization allow for a price level that does not imply a switch in an upper market Segment.” Tseng and Jiao (2001) define mass customization as, “technologies and systems that deliver goods and services that meet individual customer’s needs with near mass production efficiencies.” Other definitions have been coined and/or advanced (Piller, 2003; Tseng and

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Jiao, 2001; Duray, Ward, Milligan, and Berry, 2000; Hart, 1996; Pine, 1993a, b, c; Davis, 1987) and we would refer the readers to Piller’s article in this issue (2005b) that critiques many of the definitions. In most definitions, however, two common threads can be traced: (1) the product delivered to the customer is close to what he/she wants; that is, the product has high level of customization, and (2) the price tag for such a product is not commensurate with the level of customization; the price is much less—indeed, it corresponds to the price tag that the product would command if it was produced in mass production settings. We would, however, like to move beyond the definitions and terminologies and refer the readers interested in the definitional debate on mass customization to Piller (2005b), Piller (2003), Tseng and Jiao (2001), Duray et al. (2000), Hart (1996), Pine (1993c), Davis (1987) among others. Here, our focus would be on developing appropriate metrics for measuring “mass” and “customization” aspects of the strategy. We will also provide a brief but clear understanding of the modus operandi of the mass customization strategy through product modularity and how it plays a role in bringing about the contradictory priorities together. The metrics are significant in that they would help locate a mass customizer on the mass production—customization continuum and set directions for strategic and financial gains through measurable yardsticks. 1.1.

Successful applications of mass customization

Due to the extraordinary potential of mass customization to satisfy two competing priorities simultaneously, it is being embraced by a progressively increasing number of companies. Dell Computer Corporation (Dell for short) is regarded as the ultimate mass customizer. According to Pine (2004), Dell’s cash conversion cycle—the time when a company pays its suppliers to the time payment is received from customers—is negative 37 days when most companies have weeks or months long cash conversion cycle. Due to the modularity of PCs, the customer pays for the custom-configured computer even before the PC begins to assemble. Many of the Dell’s superior performance parameters such as customer service and short delivery lead-times (typically two days), are ascribed to its successful mass customization strategy. There are many other illustrious mass customizers who are registering significant gains in profitability and market share from pursuing a mass customization strategy. McGraw Hill (just in time print system for college books), Lenscrafter (customized glasses in an hour), Motorola (pagers), Hertz (customized rental cars at low rent for its gold card members), Cemex (customized quality cement delivered within two hours), and Nike (fit, style, and functionality), just to name a few. Companies like Amazon have employed the customer co-design aspect of mass customization through their web-site—amazon.com— with great benefit, whereas Yahoo has used it to develop effective portals. Alptekinoglu and Corbett (2004) provide several examples of successful mass customizers: Acumins (multivitamins), ChemStation (detergents), Lands’ End (pants and shirts), Lutro Electronics (lighting systems), Nike (sneakers and shoes), Procter & Gamble (beauty-care products through www.reflect.com), TaylorMade (golf clubs), Ultra Pac (plastic containers), and Yankee Candle (candles). The list goes on. Most of us are familiar with function or sub-routine codes that are used in software programming. These are self-contained software program modules that carry out a specific function in a specific computer language and can be attached to any

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program through a set of core variables. The availability of such modules guarantees that programmers do not waste time in writing programs for repetitive tasks that occur frequently in different contexts. In essence, this is an application of mass customization principles to software programming. Tu et al. (2004) suggest that the four largest software companies in the world—Microsoft (timely delivery for Windows using modularity concept), IBM (Collective Intelligent Bricks), SAP, and Oracle (software cartridges)—have all benefited from application of such mass customization practices, such as modularity and customer co-design. TC2 has installed million-dollar machines in many shopping malls where a willing customer is body-scanned for his/her measurements in a space of two seconds. These measuremts are instantly communicated to the laser guns of the cutting machines in the manufacturing unit (Milan, 1996). The completely customized garment is ready within a matter of hours and delivered to the customer in 3–5 days. The market study shows that, on an average, customer is willing to pay an extra $15 for a pair of customized jeans (as opposed to off-the shelf) and is willing to wait for 3–5 days. TC2 hopes to place this customized information on the back of plastic cards so that customers could directly place orders through the slide of a card. TC2 should, however, be careful about planting information on cards, not only for privacy reasons, but also due to the fact that people’s shapes are constantly changing and the information may be obsolete quickly. In contrast to MC2 , Levi’s mass customization effort did not succeed quite so well since their body-scanning systems of women’s jeans (where the technology was applied first) were “annoying and cumbersome (Milan, 1996)”—an outcome that goes against the spirit of customization. Custom Foot uses electronic scanners, just like TC2 to make custom shoes. In the hospitability industry, Ritz Carlton is far along on the mass customization path (Milan, 1996). Within the automobile industry, Ford, GM, Chrysler, and BMW are dedicating significant efforts and resources to institute mass customization practices in the design and delivery of their products (Suzik, 1999; Salerno, 2001). Duray (2002) has demonstrated, based on a sample of 126 companies, that mass customizers perform financially better than non-mass customizers. Tu, Vonderembse, Ragu-Nathan, and Bhanu Ragu-Nathan (2004) define MBMP (modularity-based manufacturing practices), and based on a sample of 303 companies demonstrate that MBMP have a positive relationship with customer closeness and mass customization capabilities. Simply interpreted, this means that product and process designs consistent with mass customization principles result in superior strategic (increased market share among others) and financial (increased profitability) performance. In short, the potential of mass customization as a unique strategy that delights customers on two conflicting strategic dimensions (price and customization) simultaneously is increasingly being recognized in industrial arena (Pine, 1993, 1995, 2004; Duray and Milligan, 1999; Duray, 2002; Piller, 2005a, 2005b among others). While we are not even close to realizing the full potential of this strategy, we clearly have the momentum and growing awareness of the strategic value of this strategy. 1.2.

Mass customization: A strategy or tactic?

At this point, it is important to state that we believe that mass customization is best implemented as a part of an overall operations strategy. However, examples provided above

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also support the fact that a well thought out and a well implemented mass customization strategy—complete, stand-alone in itself—would still deliver impressive financial results, because of the clear structure of production systems, web-interface for customer co-design, and operational choices associated with such a strategy. Some business scholars and experts may differ. For instance, Milan (1996) considers mass customization as part of a customer specific value chain management system, and views its role as one of the elements of a complete Global Management Paradigm, which is comprised of nine dimensions. We have no disagreement with those who characterize mass customization as a partial strategy, a strategy embedded within another, or even as a tactics or system design element rather than a full fledged strategy. Our view of mass customization is that, irrespective of its role as a strategy or tactics, when properly implemented, it is a formidable strategic weapon that helps improve both—the market share as well as profitability—the two dominant strategic variables that a performance oriented firm aspires to improve. 1.3.

A word of caution

Whereas indicators that mass customization helps improve strategic and financial performance of companies are unambiguous (see description of companies provided earlier in this section, Pine, 1993; Pine, 2004; Duray, 2002; Tu et al., 2004; Piller, 2005a, 2005b), we would like to emphasize that appropriate and rigorous financial and strategic analysis must precede any application of the mass customization strategy. In a review of a National Industrial Bicycle Company’s, choice of strategies, Kotha (1996) found that an optimal combination of mass customization and mass production strategies would perform better than any one of them individually in a rapidly changing dynamic market environment. Within the apparel industry, TC2 has a success story to tell, whereas Levi’s ended up with a poorer performance (Milan, 1996) because their scanning technology was annoying to the customers. Alptekino˘glu and Corbett (2004) develop an intersting theoretical framework for analyzing the impact of mass customization and mass production strategies on a firm’s performance. They model a competition between a mass producer (MP) firm that has finite variety (few standard products) and a mass customizer (MC) firm with infinite variety. Their analysis shows that MP with finite variety can profitably compete despite its disadvantage in fixed cost of technology. 1.4.

More customization not necessarily better

Finally, it must be stated that more customization or more product choice does not automatically mean that the customer will pay a higher price premium (Desmeules, 2002). Based on customer surveys, Schwartz (2000) calls too much choice of products, “a tyranny of choices”; Lehman (1998) calls high product variety levels, “too much of a good thing”. Indeed, the customization literature has essentially established a concave behavior of the level of customization with that of price. An optimum point occurs as a certain level of customization is achieved; beyond that customer is unwilling to respond favorably to increased customization. Thus, a prudent mass customizer would analyze the market data with respect to the customer propensity for customization, the optimality levels that customer

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would respond to in terms of price premium and delayed receipt of product, and the financial implications of adopting a higher customization-level strategy. Having placed the cautionary notes in place, we would hasten to add that there are success examples abound in virtually every industry that has employed mass customization effectively and we have no doubt that, with rare exceptions, a well-thought out and wellimplemented mass customization strategy would deliver both sustained financial and strategic gains. Piller (2005a) provides data that supports the fact that in many consumer product industries, more and more variety is being offered based on customer demand. There is 2% to 16% increase per year in product variety since 1970 in car, bicycle, computer monitors, sneakers, and contact lenses. To provide a perspective of the role and value of mass customization as a part of overall operations/business strategy, we will explore the evolution of the operations strategy landscape over last three decades, in the following section. 2. 2.1.

Mass customization and operations strategy Price as the sole competitive priority

How does a firm compete with another in its industry? Or, more precisely, what are the strategic dimensions on which a manufacturing firm competes with another within its industry? Over the course of approximately last four decades, there has been significant debate and discussion around this question (Skinner, 1969, 1974, and 1996; Clark, 1996; Hayes and Wheelright, 1978, 1979, and 1984; Hayes and Schmenner, 1978; Fine and Hax, 1985; Swamidass, 1986; Davis, 1987; Ferdows and De Meyer, 1990; Garwin, 1992, 1993; Hayes and Pisano, 1996), all articles in Interfaces, Volume 15 (1985), all articles in POMS, Volume 5 (Spring 1996), and more). Prior to the publication of Skinner’s (1969) seminal article that advocated a drastic change in operations strategy formulation, the U.S. manufacturing firms generally pursued a narrow, single-priority competitive strategy that focused on price manipulation to improve profitability and market share. 2.2.

Low cost systems or royal elephants?

Price-based competition required rock-bottom cost operations, which in turn required highest levels of operational efficiency and productivity, to the exclusion of almost every other objective. Consequently, companies pursuing such a strategy were consigned to develop and deploy production systems characterized by high start-up cost (because of the specialized equipment they used), top-down rigid information flow, sequential product layout, high degree of automation, low-skilled tasks, and exploitation of economies of scale. Woodward (1965) in her nine-point framework and Hayes and Wheelright (1979) in their well-known four-point parsimonious framework (job shop, batch, assembly line, and continuous flow) established that there is a systematic connection between a firms’ strategy, manufacturing tasks, and characteristics of production systems. The systems consistent with the price as a competitive priority were great for a firm’s profitability so long as there were mass markets ready to absorb all the production and the customer mindset remained fixated on low price.

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In the absence of mass demand, these systems were royal elephants that looked elegant but had no capability to respond to changing market demands in volume or in the scope of the products. 2.3.

Mercurial markets asking for “differentiated” product

Unfortunately for American manufacturing firms, markets began to display a distinct change in their character since the beginning of seventies. Whereas the American companies were able to dish out a single “standard shoe” that should fit all with great price tag, the customer were demanding a comfortable shoe, a stylistic shoe, a shoe that would fit exactly, and were demanding it NOW, even if it meant a much higher price. The customers were tired of high life-cycle cost of a poor quality product, were sick of standard, run-of-the-mill products with no variety, were tired of being told what is good for them, and were tired of waiting to get the product they wanted. They were willing to pay more for a differentiated product that has better quality, higher customization and/or faster delivery. Unfortunately, the systems designed for low-cost operation could not possibly respond to this changed market dynamic. There was much too much inertia built into the production systems that worked great for price-based competition on at least two counts: These systems had sucked in massive investments as they were automated and specialized to produce a few standard products; and second, they were good only to produce those few standard products. The very systems that were pride and joy of American manufacturing companies, as they delivered huge profits under a compliant mass market environment, became a major liability in a mercurial market that demanded a differentiated product rather than a cheap product. The extant systems were simply unable to deliver what customer wanted. American companies were stuck with their expensive systems. There was a dire need for a fresh look, a new paradigm of operations strategy, and a brand new mindset that would extract American manufacturing mired in production settings that were no good to respond to the changing market needs. 2.4.

More competitive dimensions

Skinner (1969) had witnessed this mismatch between the market needs and available productions systems as well as the profuse one-way bleeding of American manufacturing market share in automobile, electronic, and other high-tech industries towards Japanese manufacturing companies. Under the new market dynamic and “differentiation” mindset, his proposal to expand the set of competitive priorities from a single-dimension (price) to multi-dimensions (price, quality, and return on investment) was not only timely, it was life-saver. Yet, the mindsets of American CEOs were so crystallized around cost-cutting that it took nearly 15 years to heed the message and change strategic course. 2.5.

Quality as the key competitive priority

In mid-eighties, concurrent with the appearance of an entire volume of Interfaces journal (Interfaces, Volume 15, Issue 6, 1985) dedicated to new formulations and paradigms of

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Figure 1.

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Approximate milestones in operations strategy Formulation in American Manufacturing Industry.

operations strategy, the focus of competitive battles shifted from price to quality. The focus could have shifted to customization/flexibility but a highly customized product that doesn’t work would not only be unattractive to customers, it would be disastrous to firm’s financial health. It was, therefore, logical that the U.S. manufacturing companies decided to take on the quality bull by the horns, first. Once focused, it took American companies a short time span of five years to catch up with the Japanese quality, except that Japanese were still moving the targets constantly and systematically everywhere. Yet, the quality gap had unmistakably shrunk and the strategic advantage on account of quality of Japanese automobiles, for instance, was no more as profound as it used to be. Indeed, the notion that Japanese automobiles or electronic goods were automatically superior in quality was no more tenable, at least in any significant measure. By 1987, the debate about the dimensions on which a manufacturing firm competes with another had converged on a set of four distinct but independent priorities: Price, quality, flexibility, and delivery (Swamidass, 1986). Here, flexibility represents scope or variety of products, i.e., to product customization. Delivery also has larger connotations than normally associated with this term; it means the time span from idea to market rather than time from retailer to customer. Figure 1 above maps out major milestones in the evolution of operations strategy landscape. The figure is, by no means, exhaustive, and we apologize if we have missed any significant publications/developments. Also, as is typical in such maps, the dates are approximate.

2.6.

Focused factory

One of the cardinal principles of competition that Skinner (1974) and subsequently others (e.g., Fine and Hax, 1985) had propounded was that no firm should compete on more than one of the four competitive priorities. The logic adduced for this was that the choice of competitive strategy has direct implications for the type of manufacturing system needed to serve that strategy optimally (Woodward, 1965; Hayes and Wheelright, 1979). Furthermore,

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infrastructure also has a bearing on decision-making that must correspond to the competitive strategy. Thus, a marginal reject may be disposed off differently under a strategy that is focused on quality than under a strategy focused on price. The former may dictate a rejection while the latter may try to salvage a marginal reject. To avoid such confusion and keep focus, Skinner (1974) advocated plant within plant (PWP) concept of production systems design where products produced within a plant would all compete on the same priority. This would not only bring consistency and clarity around the production system design, increased efficiency derived from focused plants, but also bring consistency in the decision-making process and infrastructure. Furthermore, it was argued that competing on more than one priority would expand more resources and the resultant cost may not be consistent with the price that market is willing to pay. 2.7.

Flexibility as a key competitive priority

In the late eighties, this wisdom of unflinching dedication to pursue a single-priority based competitive battle was challenged by Japanese companies (De Meyer, Nakane, Miller, and Ferdows, 1989). In a study of Japanese, American, and European manufacturing companies’ strategic trends, De Meyer et al. (1989) concluded that Japanese companies were clearly following a strategy in which “Japanese respondents are apparently focusing on overcoming the traditional conflict between cost-efficiency and flexibility.” To accomplish this they were heavily investing in technology, such as, flexible manufacturing systems, computer-aided manufacturing, and robots. They were constantly looking for ways to reduce cost while maintaining small batch sizes facilitating compeitition on flexibility. In 1990, Ferdows et al. came up with a “Sand Cone” model in which they advocated that manufacturing companies must consider strategies that would improve all four priorities sequentially, eventually competing on all four priorities. They said, “To build cumulative and lasting manufacturing capability, management attention and resources should go first toward enhancing quality. While the efforts to enhance quality are further expanded, attention should be paid to improving the dependability of the production system. While efforts on the previous two are enhanced, production flexibility should be improved. Finally, while all these efforts are further enlarged, attention can be paid to cost efficiency.” This sequential building of a company’s capabilities that allowed companies to compete on all four priorities was termed the Sand Cone model. This was clearly a competitive prescription that did not agree with companies that had cost reduction as their first, and perhaps, the only goal. What Japanese manufacturing companies were trying to accomplish in late eighties— building low-cost, high customization product was exactly what mass customization promised to do, albeit at a much lower production cost. Indeed, the promise of mass customization was more effective since the cost efficiencies were being obtained through modular product design, in addition to technological innovations. Unfortunately, the promise of mass customization remained largely unexplored even though Davis advocated its competitive value in 1987 (Davis, 1987—Future Perfect). We believe that the reason why mass customization did not catch fire in 1987 was that American and European companies were bogged down with product quality problems and were unable to consider a flexibility based competition. De Meyer et al. (1989) point out that, “they [North Americans] seem to be

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betting that by duplicating the Japanese approach of “quality first” and “just in time second” they can ultimately position themselves better for technological breakthroughs that Japanese are attempting.” De Meyer et al. (1989) clearly state: Flexibility has not yet become a major competitive priority for American manufacturers. With quality issues still outside control, and the basics not in place, mass customization was a solution that existed for a problem that U. S. companies were unwilling to embrace. In 1993, the U.S. manufacturing companies were still struggling to adopt flexibility as a competitive priority although its inevitability was clear (Fortune, 1993). In the meanwhile, significant strategic value that could possibly accrue from adopting flexibility as a priority was being frittered away—mass customization was a known cure, but there were no takers. 2.8.

Internet driven operations staretegy paradigm, customer service, and final set of competitieve pririties

Around 1997, Internet began to take hold in the U.S. in a big way and its value as a hub for universal communication became clear. The availability of web-based information brought the entire world together under a small communication hub where anyone could communicate with anyone else with similar interests and goals in a matter of seconds. Search engines like Yahoo, Infoseek, Excite, and others provided unprecedented speed and access to get the information one wanted. On the strategic front, the Internet had two significant impacts: (1) The entry barriers to markets virtually disappeared and (2) The exit barriers also virtually disappeared. An innovative entrepreneur with a differentiated product that beats its competitors on price, quality, flexibility and/or delivery could enter the global market through the web just by creating a web page for a few hundred dollars and a few hours of time, thus overcoming entry barriers with very little resources. Similarly, a well established merchant could and would lose market position completely if his/her product is not good enough to compete due to massive feed backs and information exchanges about companies and products on Internet. The ubiquitous presence of Internet has, therefore, created an aura where companies can no longer afford to compete on just one priority; there is always someone who can compete on all four priorities and win the competitive battle. Yet, another upshot of Internet commerce is that the customer service must necessarily be near-perfect. The cost of poor quality or miscommunication is huge since just the shipping costs associated with the returns of poor quality products could be significant. All in all, Internet has created an environment for customers where they could demand and get a high quality prodcuct, high level of customization, quick delivery of a product—all at the lowest cost. In other words, companies in this age of Internet and e-commerce have no choice but to compete on all four priorities— cost, quality, flexibility, and delivery—and yet provide the best customer service possible. 2.9.

The strategic role of mass customization

There is enough evidence that mass customization can and will play a big role in meeting the demand posed by the stringent competitive environment described above. We have earlier pointed out that mass customization strategy is designed to support mutually contradicting priorities of price and flexibility. An important fact that has escaped the attention of

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strategists and academics is that the production systems associated with successful implementation of mass customization also support the remaining two key priorities—quality and delivery. Given that product modularity is a key element of a mass customization strategy (Pine, 1993a (Stage 5); Pine, 1993b; Duray, 2002; Tu et al., 2004), cellular manufacturing system are best suited for producing modular products. Within the manufacturing systems the production philosophy should be consistent with lean systems that allow minimal waste. In a mass customization strategy, stable and flexible processes are used in a modular fashion—one process dedicated to produce one or more product modules—and combined dynamically to meet the evolving demand of specific product configurations. This is accomplished through cellular manufacturing and there is ample evidence that such manufacturing systems deliver great quality and delivery performance due to the focus associated with each module (Adam, 2002, http://www.epa.gov/lean/thinking/cellular.htm). Finally, due to the customer co-design of the product through Internet, the customer service aspect—which is increasingly a serious consideration in today’s competition—is taken care of as well. Indeed, the delight that each customer enjoys by putting together his/her own product configuration serves the customer service aspect in a big way. Based on the above, we can reasonably conclude that mass customization strategy, when thoughtfully implemented, would produce a winner in all competitive priorities, partly through product design (customization), partly through web-based customer interaction (customer satisfaction), and remaining through appropriate production systems associated with mass customization strategy (cost, quality, and delivery). In its total impact then mass customization is a strategy that comprehensively addresses all the competitive priorities—a distinction that we have not found associated with other strategies. This across-the-board impact of mass customization on a company’s strategic position and its significant potential to obtain sustained competitive advantage was the key motivating factor behind bringing out this issue. 3.

Mass customization and modularity

We believe that modularity in the basic product or service design is essential for mass customization (Pine, 1993a; Pine et al., 1993b (Stage 5); Duray, 2002; Tu et al., 2004). However, the companies like TC2 or Custom Foot do not need modularity to mass customize their products since their advanced scanning technologies allow 100% customization at affordable cost. These technologies support processes whose set up times and set up costs have been reduced to near zero so the economies of scale are unimportant. Also, companies in early stages of mass customization that seek to mass customize in other ways (see Pine, 1993b), may have no immediate need for modular product. With those exceptions, we believe that all companies with marketing multi-feature, multi-functional products would necessarily have to have modularity to achieve economies of scale. 3.1.

Mass customization process

In this section we show how modularity works to create a customized product on one hand and mass production efficiencies on the other. This may be elementary for some, but it

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Figure 2.

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Mass customization through modularity.

is essential to understand why modularity in product design should be integral to a mass customization strategy, especially for multi-feature, multi-functional products. Figure 2 above shows the steps involved in demonstrating how modularity works to provide mass customization. A typical process for mass customization starting from customer co-design until the delivery of the customized product works (Figure 2).

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Step 1: Customer co-designs/configures his/her choice product by picking up levels/options for each feature/function available to him/her within the finite solution space. Step 2: A mapping mechanism identifies and selects from a list all the product modules/components that will be needed to make the configured product. Step 3: Stable and flexible processes are chosen that will fabricate the modules identified in Step 2. This is where modular/cellular processes (one process dedicated to one module) are helpful. Step 4: A dynamic process is developed connecting the above processes in an appropriate sequence. Step 5: A schedule is generated so that each process is triggered when there are enough modules for each process so as to allow the advantage of economies of scale. Step 6: All modules are assembled at the last stage. Step 7: Customized/pre-configured product is delivered to the customer. Note that mass production efficiencies are obtained in step 5 because the same module is ordered by many customers. 3.2.

The customization metrics

Let us assume that a product currently has M distinct functions/features, indexed by m, in which customers could potentially be interested. A modular design of the product will have separate components for each function/feature or for a group of functions. Let’s assume that the product design allows Im, m = 1, . . ., M levels/options for each function/feature m. Therefore, a customer could configure his/her product using any one of the levels/options available for each function feature. In addition there may be a standard/stripped product that would be common in all variants. If an option is not integral to the basic functionalities required in a product (e.g., engine in a car or motherboard or RAM in a PC), the customer may also decline
to have that feature. This means the customer will pick up M levels/options M out of a total of m=1 (Im + 1) available to configure his product. Now, we set forth metrics that measure the “customization” performance of a mass customization strategy. To this end, we define the metric
M Average number o f options/levels per feature/function =
=

m=1

(Im + 1) . M

This metric
represents product  M modularity. Furthermore, a total of m=1 (Im + 1) configurations are possible out of which the customer can pick any one. Then, Maximum number o f pr oduct conf igurations =  =

M 

(Im + 1),

m=1

where  reflects the extent of customization on an ∞ scale. In the literature, this number will correspond to the cardinality of the solution space.

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Let η be the potential customer population for this product. Then,  represents the Average number o f conf igurations per customer =  =

 = η

M m=1

(Im + 1) . η

This last metric could serve as an important benchmark to measure the level of customization that a firm provides to its customers on per customer basis. Here, if a company wants to provide a unique product configuration per customer on an average, then the company should provide enough options/features so that  ≥ 1. Now, let us assume that the maximum number of functions/features on which a customer can be offered a choice is N , while the company actually is offering a choice only on M features. Furthermore, let us assume that maximum number of levels/options for the mth feature is Jm instead of Im . Then, we define the degree of customization,  as follows:
M Degr ee o f Customi zation =  =
Nm=1 m=1

(Im + 1) (Jm + 1)

.

We could also define an alternate measure of mass customization based on the actual and maximum number of product configurations. m=M m=1 Im  p = m=N . m=1 Jm We would, however, strongly recommend using  as the customization measure.  p is based on product of options and as such grows exponentially. Hence, it would not be a practical measure as it would decrease sharply with even slightly less than perfect level of customization (see example later in this section). 3.3.

Mass production metrics

We now define the metric that addresses the “mass” part of a mass customization strategy. Let δ ≤ η be the demand in any planning period or an average demand over sufficient number of planning periods. Let Imax = Max{Im , m = 1, . . . , M}. If each level/option for each feature/function is equally attractive to the customer (in reality, some levels will be more in demand than others), then Average minimum demand per period per level/option =  =

δ . Imax

The above measure computed the minimum average demand based on the largest number of options available for any feature/function. A more balanced measure, however, will be: Average demand per period per level/option =  ∗ =

δ .


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If δ is large enough, this number is large so that each component of the product could be mass produced. This is the “secret of success” of mass customization strategy. Whereas a large number of possible configurations provide an opportunity to the customer to choose one that is closest to the customer’s vision, each level/option (represented by a separate component) will be demanded in large enough numbers so that the economies of scale can be exploited at the component level. So, the mass customizations strategy allows efficiencies of mass production through distribution of demand over a few levels/options while allows high level of customization through modular design of products.

3.4.

The optimal strategy

Finally, the performance of a mass customizations strategy can be measured in two ways: how large is the modularity (
) that increases monotonically with the degree of customization and therefore measures the level of customization accomplished by the strategy, and (2) how large is  ∗ that measures the extent to which economies of scale can be exploited resulting in higher contribution margin or lower price to the customer resulting in larger market share. These two measures move in opposite directions for a given demand level, and therefore an optimal combination must be sought. One needs reliable market and production cost data to do so. If companies can develop a dollar measure of marginal value of modularity and marginal value of production batch size (economies of scale), then, for a given industry, a trade-off equation can be established and optimum computed. We leave expansion of this concept to future researchers.

3.5.

A real world example

Let’s clarify the computations of these metrics through an example. Table 1 has been constructed and modified from a PC Configurator website. In this case, the PC manufacturer is using mass customization as a strategy to provide high level of customization at a low cost. First let’s look at customization related metrics. There are 20 functions or features (M = 20) on which the PC manufacturer is allowing customers a choice of options/levels. Thus, for m = 4, customer has 11 choices to pick from (64 MB, 128 MB, etc.), so that I4 = 11. The total number of levels/options offered is 199. However, the customer has one additional option for each function/feature of not choosing a module/feature/function altogether (although, this will not apply to every module/feature/ function). For instance, there is no choice for a customer to not have a motherboard or ram or a video card). Yet, for sake of generality, we proceed as if there is. Therefore, the degree of modularity in this case,
M
=

m=1

(Im + 1) 219 = = 10.95 M 20

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MASS CUSTOMIZATION: METRICS AND MODULARITY Table 1.

Current level of functions/features and associated levels/options.

Computer Module/function /feature# (m)

Computer Module /function/feature

1 2 3 4 5 6 7 8 9 10

Mother Board CPU CPU Cooling RAM Monitors Case Power Supply Hard Drive Video Card Sound Card

# of options /levels

Computer Module/function /feature# (m)

Computer Module /function/feature

# of options/ /levels

9 14 4 11 11 15 9 21 16 8

11 12 13 14 15 16 17 18 19 20

Speakers CD/DVD ROM Removable Drive Communication Ports Key Boards Mouse Operating Systems Software Case Mods Additional Cooling

11 8 17 4 9 6 4 7 11 4

Thus, this firm is offering a PC whose modularity is about 11. Also,  can be computed =

M 

(Im + 1) = (10 ∗ 15 ∗ · · · ∗ 5) = 9.5 ∗ 1019 ,

m=1

which is the maximum number of configurations possible at the current level. Assuming every one of 6 billion people on planet earth is a potential PC buyer, Average number of configurations per customer = 9.5 ∗ 1019 /6.0 ∗ 109 = 1.6 ∗ 1010 . This means that this PC firm is offering 16 billion configurations per customer! Obviously, there is much more than a unique computer virtually for everyone! A practical number will be lower than this number since many options are never chosen by customers and others are defaulted to a standard one. In order to compute the degree of customization assume that Table 2 modified from the previous one, shows maximum reasonable options per feature/function. Let’s also assume that there are four more features that can be customized for a total of 24. Also, in certain modules such as hard drive, monitors, and removable drive, more options are made available than the current level. The new value of degree of modularity is
M
=

m=1

(Im + 1) 266 = = 11.08. M 24

Furthermore, the degree of customization
M (Im + 1) 219 =  =
Nm=1 = = 0.82. 266 (J + 1) m m=1

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Table 2.

Maximum reasonable functions/features and associated levels/options.

Computer Module/function /feature# (m)

Computer Module /function/feature

1 2 3 4 5 6 7 8 9 10 21 22

Mother Board CPU CPU Cooling RAM Monitors Case Power Supply Hard Drive Video Card Sound Card X21 X22

# of options /levels

Computer Module/function /feature# (m)

Computer Module /function/feature

# of options/ /levels

9 14 4 11 11 20 9 21 16 10 4 7

11 12 13 14 15 16 17 18 19 20 23 24

Speakers CD/DVD ROM Removable Drive Communication Ports Key Boards Mouse Operating Systems Software Case Mods Additional Cooling X23 X24

11 8 24 4 9 6 6 7 11 4 10 6

And m=M m=1  p = m=N m=1

Im + 1 Jm + 1

=

9.5 ∗ 1019 = 0.0001. 9.125 ∗ 1023

This explains why we would not recommend use of  p even though it is a logically valid measure. The mass metrics for this PC manufacturer can easily be computed. Let us assume that the demand for PCs in the United States is 4 million per month and assume that this PC manufacturer commands 30% of market share. Then, since maximum number of options are for Hard disk ( = 21), the minimum average demand per module =  = 4 m ∗ 0.3/21 = 57,143 per month. Also, given the modularity of this PC = 10.95, the Estimated average demand per module =  ∗ = 4m ∗ 0.3/10.95 = 109,600. Clearly, these demand levels correspond to mass production levels of components that satisfy a specific option level and, therefore, bring significant mass production efficiencies. If the PC is a lean company and produces two batches per day of each level, the average production batch size is 109600/30 = 18267. This can bring significant economies of scale. 3.6.

Limitations of the metrics

We have stated earlier in this section that there are at least three types of mass customizers. Mass customizers such as TC2 aim at 100% customization level and, therefore, have infinite modularity. These customizers thrive on their advanced technology that allows minimally

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low set-up costs. On the other end of the spectrum are early mass customizers who have not yet gotten into modularity (Stage 1 through 4 of Pine, 1993). For each of these types of customizers, the metrics developed above would be useless or trivial (i.e., converge to extremes). For the hefty middle, where companies seek mass customization through modularity due to the fact that their products are multi-featured, multi-functional, sensible metrics can be computed and used to evaluate the success of the mass customizations strategy. The metrics suggested in Section 3.4 are useful only in the presence of finite modularity, i.e., when total number of configurations offered (the solution space) is finite. When that is not the case, that is, number of option levels for even a single feature is infinite, these metrics become impractical as they trivially converge to zero or diverge to infinity. To give an example, let us assume that Custom Foot permits a complete customization of its shoe based on a single feature—size. Then, it may need to produce a shoe size of 9.678 for a certain customer. Through an affordable technology that exactly produces the footscan, Custom Foot can produce the exact-size shoe with slightly extra cost that customer is willing to pay. This shoe, however, will have to be produced in the batch size of 1 and therefore, would be extremely expensive if Custom Foot did not have the technology that guaranteed very low or zero set up time and cost. However, by producing shoe size in notches of 1/2 units, a 9.5 or 10, Custom Foot can get the mass volumes of demands for those sizes, irrespective of the technology. The unit cost of producing shoes in large batch sizes will be much less because of the economies of scale obtained from the fact that Custom Foot will get a large batch size production for size 9.5 and 10. This makes shoe affordable to the customer without affecting the comfort too much. The task for Custom Foot in this case would be to find an optimal step between shoe sizes so that each customer gets the most customization at the least cost. We conclude that mass customization strategy is very attractive where economies of scale are used as leverage for reducing unit product cost. In other words, the true strategic and financial potential of mass customization strategy is available in those scenarios where technologies needed for 100% customization are not available or are prohibitively expensive. And, a successful application of mass customization strategy, when that is the case, would inevitably require modularity of product as an essential condition. 3.7.

Other advantages of mass customization strategy

As we have indicated before, mass customization strategy offers across the board improvements in product differentiaton so that a firm can compete better on price, quality, flexibility, delivery, and service. We suggested that mass customization strategy offers improved quality and agility through the production system design that was modular/cellular. We would like to add that additional agility/delivery and cost advantage come through the order processing in a modularity environment. • First, the customer co-design on website allows order communication time to be almost zero. In addition, this direct interaction provides very reliable data about customers’ changing needs and preferences.

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• Second, due to the modular design, the customizing company can delay final production step (assembly) until the demand is placed or is close to being placed. In case of Dell, the assembly begins after the order is in. But in many cases, e.g., HP printers in Asian or European markets, product assembly could be done just a day prior to the demand occurrence when demand levels can be forecasted more accurately than if the demand forecast was needed if the printers were completely manufactured and assembled in the U.S. several weeks prior to the demand. This power of postponement (Fetzinger and Lee, 1997) of production has significant cost savings riding on it through reduced inventory safety stock and reduced delivery lead-times. 4.

In this issue

We believe that despite huge potential of the mass customization strategy to enhance a firm’s competitiveness, the research on the subject is at the lowest leg of the S curve and much remains to be done. We have selected three articles for this issue that take this research further in significant ways. It may be recalled that for this issue, we had expanded the scope of submissions beyond manufacturing; we had invited mass customization related articles both from manufacturing as well as service industries. Provided below is a brief account of what these articles accomplish. 4.1.

Mass customization: Reflections on the sate of the concept

The article by Piller explores and analyzes the current state of application of mass customization as a strategy and the reasons behind its slow adoption in large scale industries. The analysis is particularly relevant since the fundamental value of mass customization in bringing together two rival competitive priorities—price and customization—has been well established in literature. As such, one is inclined to think that most firms would jump at and grab such a strategy and implement post-haste. That has clearly not been the case. The article lays down twelve propositions which essentially constitute a basis for answering the question: Why mass customization is not there yet? The propositions themselves revolve around the questions such as, what prevents customers from buying customized products (assuming they want more choices and the trend shows that, up to a point, they do)? Second, do we have mass customization enabling technologies and if so do they keep the product prices affordable? Finally, the propositions seek to explore the set of factors that would be responsible for success or failure of mass customization strategy. (i) For Piller, customer co-design is the most fundamental aspect (genus) of mass customization, which differentiates it from other customization strategies. The other prominent aspects of a mass customization strategy are a stable and finite solution space, meeting individual needs (customization), and affordable product price for customers. The stable and finite solution space refers to the scope of choices or variants of the product that company makes available to the customer while customer is codesigning its configuration of preference. The affordable prices are derived from the

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limited solution space which is essentially built from the modularity available in product design. Piller, however, also considers those companies that sell a customized product but the low cost of product is obtained not through economies of scale but through advanced technologies that minimize the set up cost close to zero (e.g., MC2 ). (ii) Piller identifies three determinants of the degree of customization of a product or service: Fit, style, and functionality. Customer co-design ensures that the customer gets the highest level of customization from the available solution space. The limited solution space creates opportunities for customer segmentation and, in turn, for affordable prices. (iii) A successful implementation of mass customization strategy requires specific information. For instance, a firm would like to know the mapping between the level of customization and customer’s willingness to pay for increases in customization levels. In other cases, a firm opting for mass customization, would certainly like to know if its customers are willing to wait to get higher levels of customization. Once again, a mapping data is needed as to the amount of wait that customers are willing to undertake to get higher levels of customization. Success of mass customization strategy would clearly depend on how reliably and accurately such data is available. Piller laments that lack of such data is one of the key reasons why mass customization is not there yet. Using twelve thoughtful propositions, Piller invites mass customization researchers to take the field further on the S curve. Furthermore, the answers to these propositions would create a knowledge base that would allow significant insights into what works and what does not—laying clear markers for prospective mass customization practitioner companies. Analysis and responses to these propositions would also answer the fundamental question posed in this article: Why is mass customization not there yet? 4.2.

Process variety modeling for process configuration in mass customization

This article presents a methodology that allows development of process configurations from the available set of modular processes using Object Oriented Petri-nets. To our knowledge, this is the first attempt at using Petri-nets to generate process plans in the context of a mass customization strategy. Modularity of product or service design is at the core of this work. Jiao, Zhang, and Prasanna (2005) assume that the information needed to develop a process plan for a specific variant of a product is available in most companies in the form of generic process structures underlying the production of similar products in a family. This, in turn, implies that companies have already created product families and that the data pertaining to the processes required to manufacture the base product and its variants is already available for each family. Petri-nets with changeable structures can be employed as efficient mechanisms to develop specific process plans for a given product variant. For new mass customizers, this assumption may be somewhat restrictive. However, we do not see this as weakness of the paper. We suggest that the firms which produce a huge variety of products and their variants may follow certain methodologies (e.g., King, 1980; Kumar, 1997; Jiao and Tseng, 1999) to first create a product family classification, generate a cellular structure for process modules, and then use Petri-nets as suggested in this paper for developing optimal process plans on the fly as suggested in this work. The usefulness of

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the Petri-net methodology is established using a two-spindle textile process. The challenge in the determination of an optimal sequence of processes using simulation is to ensure that not only a product (or cohorts in the family) are produced using a feasible sequence of operations but also that all applicable constraints across processes and product variants are complied with. The simulation experiment demonstrates how this is accomplished. 4.3.

Mass customization in videotape duplication and conversion

This article by Heim shows how flexible production structures can be integrated with mass customization objectives. The paper describes a real-world case study of a manufacturer’s videotape duplication and conversion system. A flexible network of heterogeneous, parallel machines is used to duplicate and convert videotapes and other multimedia. There are numerous formats for videotaping applicable to U.S. multimedia applications and international multimedia applications. For instance, in the US, only NTSC format of analog videotaping is allowed. However, within the NTSC format, there are at least twelve options for taping devices. On the international level, there are at least five analog formats such as PAL, SECAM, etc. For each of these five formats, there are twelve different devices that can be used. Soon, we begin to see the enormity of possible combinations of analog taping conversion options. Furthermore, there are at least seven digital video conversion formats, with new ones springing all the time. Given that digital taping has significantly higher longevity, there are significant trends that require analog to digital conversion. All in all, despite the fact that the product solution space is finite (as required by mass customization) a pretty complex production scheduling problem emerges which may be further complicated by the fact that the objectives of these systems may differ from batch to batch. Furthermore, sharing of limited capacity and dynamic nature of the job arrival, tight due dates, and progressively evolving number of analog and digital taping options makes the problem extremely complex. The application of mass customization strategy is validated by the fact that each conversion process is modular and that there are finite number of such processes. The author formulates the problem as a job shop within the framework of an overall three-stage flow-shop problem. The second stage serves as a flexible job shop. Given that such problems are NP-Hard, the author resorts to simulation to arrive at optimal performance schedules. While makespan and flow-time related measures are analyzed using variations of SPT, those looking for analysis and insights related to due-dates based measures may have to wait. The characteristic elements of mass customization—customer co-design, finite solution space, and affordable price—are all neatly integrated in this case study on flexible duplication system. 5. 5.1.

Concluding remarks and future research Across-the-board improvement in all five competitive dimensions

Mass customization is being hailed as the new frontier in operations strategies. It is because the mass customization strategy has demonstrated the potential to provide product customization at the mass production cost levels. We have however, argued that mass

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customization not only excels in providing high level of customization (also called flexibility in operations strategy parlance) at low cost, it also improves quality and delivery speed when properly implemented; that is, when product modules are produced in a cellular manufacturing environment, exploiting the product family cohesion. Furthermore, mass customization requires customer interaction and indeed, customer co-design at the time of ordering the product. Thus, a product produced with the mass customization strategy in place commands a much higher customer satisfaction and, in many cases, happy customers act as ambassadors promoting the company product and practices. We conclude that mass customization improves a firm’s performance on all five priorities—price, quality, flexibility, delivery, and service—simultaneously. That’s why mass customization should be a serious candidate for consideration by all business organizations. 5.2.

Modularity—the essence of mass customization

Modularity in product design supported by stable, flexible, and modular processes is at the heart of a mass customization strategy for most companies. Such companies are those that sell a multi-feature, multi-functional product. Modularity allows calibration of the level of customization of the entire product with respect to each product feature/function. Customer co-design through web or electronic media allows configuration of a product that is close to customers’ needs. However, a significant role of modularity is in allowing firms to produce a pre-configured product at mass production prices. There are mass customization companies such as TC2 and Seiren that deliver a 100% customized product at affordable cost through customer co-design. These companies would have set-up and change-over costs so low (perhaps by virtue of advanced and innovative technology) that economies of scales become irrelevant for such companies. In our view, such companies operate more along the lines of craft production although they could still be branded mass customizers. The distinction, however, is without difference since, in final analysis, such companies are delivering customized product at affordable cost. 5.3.

Metrics for mass customization

We have proposed new metrics in this work. These metrics measure modularity, degree of customization, and the level of exploitation of economies of scale through large batch sizes. The ultimate goal is to find the optimal mix of mass customization and mass production strategies so that the profitability and market share of a company are maximized. We leave this important task for future researchers. Figure 3 may provide a certain lead in developing a conceptual framework for an analysis aimed at the determination of an optimal level of customization. As one moves the product from totally standard to totally customized, the market price increases uniformly but in a concave manner. After a certain level of customization, its marginal utility (as measured in dollars) decreases progressively. However, the cost of production also increases as level of customization increases although under the mass customization strategy the increase is slower. Intuitively, this curve is convex. The optimal customization level occurs where the vertical distance between the value and cost curves is maximum.

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Figure 3.

Optimal level of customization.

In order to determine the optimal level of customization, market data is needed reliably and accurately. In their MCPC’03 paper, Guilabert/Donthu define the customer customization sensitivity level on the basis of six dimensions: 1. 2. 3. 4.

Need for more customized apparel products Wish for more products to be customized In general, customized products/services meet my needs better than standard ones. If the price is similar for standard and customized products/services I would choose customized products/services. 5. If I have to wait to get the latest version of a product/service I’d go to the previous version instead. Is there a cut-off time span that will trigger return to previous version? 6. If I have a choice, I prefer to have customized products/services. This type of data would be needed for the determination of optimal point where mass customization strategy should be targeted. 5.4.

Future research

Finally, we believe that, in terms of knowledge growth, mass customization is at early stages of its development. The strategy was coined in 1987 but was not attractive enough to manufacturing companies as they were struggling to put their quality house in order. Since 1993 the strategy has got significant attention and many success stories have come to surface. Yet, we are nowhere close to where we should be (see Piller, 2005b). Piller has set forth several research directions through twelve propositions that must be pursued to answer why mass customization is not there yet. We would like to add that beyond these propositions, there is a yawning gap between the research and practice needed to make mass customization effective for the entire supply chain. We suggest that academia and industry expend significant resources and effort in conducting research in the following directions of supply chain and mass customization interface:

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