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留学生论文范文Observations on the present and future of mass customization
Frank T. Piller
Published online: 2 April 2008
_ Springer Science+Business Media, LLC 2008
Abstract A demanding task for many companies today is that of learning toregard customers as individuals, of proactively developing products and servicesaccording to the individual customer preferences, and of subsequently producingand distributing these offerings. Over the last decade, mass customization hasemerged as an effective approach for tackling precisely this task. In this paper,
I discuss the background of mass customization and the elements of this strategy.
I will then comment on the implementation of mass customization in practice. I willend with a brief discussion of alternative strategies in this domain, namely personalizationand matching services.
Keywords Mass customization _ Case examples _ State of the art _Personalization
As in every year, in December 2006 Time Magazine announced their person of theyear, recognizing the person who matters most now. In previous years, this has beenGeorge W. Bush, John F. Kennedy, or Mohandas Gandhi, but also Charles
Lindbergh or Bill Gates. In 2006, this person was you. You, the creative consumer.You, broadcasting your own media on YouTube. You, the engaged tinkerer hackingyour Tivo box to overcome its limits. You, configuring your sneakers to your
preferred running style. You, the co-designer of your personal product. And TimeMagazine was not alone. With the advent of Web 2.0 and social commerceapplications all over the Internet, we recently experience an exploding interest of
F. T. Piller (&)
Technology & Innovation Management Group, RWTH Aachen University, Aachen, GermanyF. T. Piller
MIT Smart Customization Group, Massachusetts Institute of Technology, Cambridge, USA
Int J Flex Manuf Syst (2007) 19:630–636
DOI 10.1007/s10696-008-9042-z
companies and consumers alike for customized products and services. Individualitybecomes the standard. Mass customization, now a concept with a history of almosttwo decades (the term was coined in 1987 by Stan Davis), seems to be becoming thenorm in this century (as predicted by Davis in 1987; Pine 1993; and indeed by
Toffler as early as 1970).
The term mass customization denotes an offering that meets the demands of eachindividual customer, but that can still be produced with mass production efficiency(Piller et al. 2006). ‘‘Today I define Mass Customization as the low-cost, highvolume,efficient production of individually customized offerings’’ (Pine 2007). Toreach this efficiency requirement, a mass customization system is defined by a fixedsolution space, characterized by stable but still flexible and responsive processes. Asa result, the costs associated with mass customization should allow for a price level
that does not imply a switch into an upper market segment. The solution space isutilized by customers who are integrated in the value creation process of themanufacturer by defining, configuring, or modifying their individual solution withinthe given set of choice options. Without the customers’ deep involvement, themanufacturer would be unable to adequately fill each individualized productdemand. Dedicated toolkits should enable the customers to perform this configurationtasks ontheir own.#p#分页标题#e#
A great example of mass customization is American Power Conversion (APC), acase described by Lars Hvam in a special case study issue of the InternationalJournal of Mass Customization (Hvam 2006). APC sells, designs, produces,
delivers, and installs large complex infrastructure systems for data centers, andcomponents for these systems. At the heart of its mass customization strategy of thiscompany are a module-based product range and the use of product configurationsystems for sales and order processing. In addition, the company has implemented amanufacturing concept that involves the mass production of standard components inthe Far East, and customer order-based final assembly at various production sitesaround the world within close customer proximity. The results of applying mass
customization principles included a reduction of the overall delivery time for acomplete system from around 400 to 16 days. Also, production costs weresignificantly reduced. At the same time, the company’s capability for introducing
new products has increased dramatically. Due to the modular system architecture,new component technologies can be integrated within a matter of days, and notmonths as before.
In addition to this best-practice example of mass customization, new promisinginitiatives have been developing during the last year. Indeed, not a month has goneby without a major mass customization initiative by an established company or anew start-up. Some good examples of mass customization in consumer goods thatwere launched in 2007 are Germany’s MyMuesli (customized cereal), Blends For
Friends (create your own tea blend), Conde Nast’s TasteBook (customizedcookbook with your favorite recipes), or John Maeda’s innovative configuratorfor Reebok that turns the favorite song of a user into a custom sneaker style. Asegment of mass customization that has been exploding recently is the market ofuser-created photo books, including providers like Picaboo,LuLu, CeWe, Blurb,
Moo, and many others. Zazzle, Cafepress, and Spreadshirt take a similar approach
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指导留学生论文to selling custom-printed T-shirts, coffee mugs, mouse pads, and more. All thesecompanies reported high double-digit sales growth in the last year.
In business-to-business, FESTO continues to establish its leading position in theautomation industry by increasing its mass customization capabilities. The companymanufactures thousands of highly customized industrial components for clientsaround the world with a lead time of 48 h. But FESTO or APC are still an exceptionrather than the norm. These two companies have entirely been created around theprinciples of mass customization.
Despite significant progress in individual cases, mass customization continues tobe in the stage of a pilot or a marketing idea. I have commented in this journalbefore on the state of mass customization implementation (Piller 2005). In that#p#分页标题#e#
review, I identified a number of challenges that prevent easy implementation ofmass customization in industry. Those challenges included the proposition that acore characteristic of a mass customization system, customer integration in the
configuration process, has been not supported adequately in the past. While masscustomization has been described since a long period of time, adequate systems toperform customer co-design efficiently and effectively have been available for just acouple of years and are just starting to penetrate the market space. Also, theirintroduction is still characterized by a technology-focused rather than a strategyfocusedimplementation.
A recent report, sponsored by two trade publications and Cincom Systems,supports these propositions (Wilson 2007). The study is based on 72 interviews withsenior engineering managers working for manufacturers ofcomplexindustrial,electrical,and transportation equipment and systems. While such an industry-driven
report may be biased by the perspective of a technology vendor, the study provides a
significant exploratory insight into the state of mass customization in manycompanies in the business-to-business domain. The broad majority of managersinterviewed for this report state that requests for customized products have beenincreasing over the last 5 years, and 26% anticipate that the growth rate for suchdemands will be between 25% and 50% in the next 2 years. However, the reportfound that only 67% of build-to-order and engineer-to-order manufacturers had the
capability to exactly calculate the cost to produce customized products, and 73%
had no capability to assess the cost of engineering change orders. Notwithstanding,more than half of the survey respondents believed that they have the ability tocharge a 25% or higher premium with a product customization strategy. Such a
disconnect between pricing assumptions surrounding product customization andtraceable costs is a barrier to sustaining mass customization momentum. The studyalso asked managers about the tools they use to support mass customization. Not
surprisingly, computer-aided design (CAD) is the primary tool used to support thecustomization process (92%). Beyond the CAD system, most manufacturers areusing ad hoc technologies such as spreadsheets (51%) or manual processessupported by documentation (41%). This implies that the customization process is
primarily a drawing-driven effort based on trivial knowledge with heavy engineeringinvolvement in the specification process. Few companies utilize automatedconfiguration systems—a core characteristic of a true mass customization system.Of those who do, 30% use homegrown systems and only 24% use third-party
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packages. These numbers indicate that there is woefully little integration of tools
within the customization process. The lack of integration implies that there is a
significant amount of manual intervention within the customization process,#p#分页标题#e#
requiring time and resources, and leaving significant scope for errors. According to
the study, most engineers believe that product complexity is not the primary barrier
to customization. They cite lack of knowledge of options by the customer (67%) as
the primary barrier to customization efforts. The implication is that the knowledge
required to effectively sell customized products is not being effectively transferred
to the customer. This study proposes that many companies in the business-tobusiness
sphere are still more in the state of a traditional craft customizer (engineerto-
order), but far away from the principle of mass customization of stable processes
(Pine 2007). There are huge opportunities for improvement in sales and operational
effectiveness to be gained by addressing this issue.
The state of mass customization application in industry, as demonstrated in
Wilson (2007), however does not correspond to today’s level of research in the field.
Within the last 2 years, a significant new body of research on mass customization
has appeared in leading journals in engineering, marketing, and management. The
papers accepted for publication in this special issue of the International Journal of
Flexible Manufacturing Systems provide further support to this notion. In addition,
several large conferences on mass customization assembled hundreds of scholars
and managers at Hong Kong, Hamburg, Ypsilanti, Copenhagen, Grand Rapids,
Salzburg, Boston, and Montreal. The prime example of such a conference was the
MCPC 2007 in Boston in October 2007 (mcpc2007.com), organized by the MIT
Smart Customization Group, Massachusetts Institute of Technology. More than 130
academic lectures and many business presentations demonstrated that today the
state of knowledge on mass customization is rather extensive. Many of the open
propositions I put forth in Piller (2005) have been addressed by dedicated research
since the publication. Once this research is adopted by managers, we may see more
sustainable mass customization applications in industry.
There is yet another trend worth of note that is driving the application of mass
customization in industry. Modern information technology is helping managers to
collate and analyze voluminous amounts of data to make smarter decisions based on
the use of growing pools of information-intensive data (Davenport and Harris 2007;
Manyika et al. 2007). Leading companies are exploiting this information to obtain
strategic superiority with a diverse set of management techniques. Intel, for
instance, integrates a ‘‘prediction market’’ with regular short-term forecasting
processes to build more accurate and less volatile estimates of demand. The cement
manufacturer Cemex optimizes loads and routes by combining complex analytic
tools with a wireless tracking and communications network for its trucks#p#分页标题#e#
(Davenport and Harris 2007). In a report on main technology trends that will drive
businesses in 2008, McKinsey, a leading management consultancy company
concluded that these information-driven business processes are not restricted to
internal processes, but also for customer retention and attraction. They state:
The more a company knows about [their customers], the better it is able to
create offerings they want, to target them with messages that get a response,
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and to extract the value that an offering gives them. The holy grail of deep
customer insight—more granular segmentation, low-cost experimentation, and
mass customization—becomes increasingly accessible through technological
innovations in data collection and processing and in manufacturing. (Manyika
et al. 2007:7)
This development has a strong bearing on a strategy that is closely connected with
mass customization: personalization. While customization relates to changing,
assembling, or modifying product or service components according to customers’
needs and desires, personalization is about selecting or filtering information objects
for an individual by using information about the individual (the customer profile)
and then negotiating the selection with the individual. Thus, personalization is
accomplished through a set of recommendations that are consistent with: from a
large set of possibilities, customer-specific choices/options are recommended; from
a technical point of view, automatic personalization or recommendation means
matching meta-information of products or information objects to meta-information
of customers (stored in the customer profile). Personalization is increasingly
considered to be an important ingredient of web applications. In most cases
personalization techniques are used for tailoring information services to personal
user needs. Examples are emerging across a wide range of industries. Amazon.com
stands at the forefront of advanced personalization. Its recommendation engine
correlates the purchase histories of each individual customer with those of others
who made similar purchases to come up with suggestions for things that he or she
might buy. Although the jury is still out on the true value of recommendation
engines, the techniques seem to be paying off: CleverSet, a pure-play recommendation-
engine provider, claims that the 75 online retailers using the engine are
averaging a 22% increase in revenue per visitor (Manyika et al. 2007).
My Virtual Model (mvm.com), a provider of a similar service for fashion
retailers and the appliance industry, reports a 15–45% increase in conversion rate,
and an increase in the average order value of a web shopper of up to 165%. MVM
enables consumers, either on its own site or on the sites of its clients, to build#p#分页标题#e#
themselves a virtual model (an avatar) by selecting different body types, hair styles,
facial characteristics, etc. Consumers also type in their basic measurements so that
the virtual model represents their body measurement. In addition, customers can
specify what kind of fit they prefer (loose, comfort, tight, etc.) so that the recommendations
provided do not only fit the customer in terms of sizes and appearance,
but also in terms of how they feel inside the garment. After they have built their
virtual self, consumers can then virtually try on clothes of various Internet retailers
and see how an item suits their demands. When MVM started offering virtual
avatars in 1999, they looked more like a curious oddity, but now their avatars are
used by more than 12 millions individual users. Companies such as Adidas, Best
Buy, Levis, Sears, and H&M are using these virtual models to generate business and
stronger ties to their customers, lured by the increase in such metrics as average
order value and conversion. These positive effects of recommendation systems can
be seen as the positive effect of assortment productivity (Salvador and Piller 2007).
Assortment productivity can be thought of as the return on the investment a
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company makes in designing and marketing a product assortment. Until recently,
retail value systems were mostly designed and operated under the implicit
assumption that assortment productivity was maximized by having the right products
on the shelf or in the warehouse. To achieve this, many methods and concepts
like quick-response management or fast replenishment have been developed.
However, personalization based on recommendation systems takes another
approach: instead of creating assortments that fit to a changing demand, the idea is
to navigate better the existing assortment in a supply chain, increasing at the same
time both the efficiency of the provider and the service experience of the customer.
A recent example of such personalization service is Zafu.com, a start-up company
in the apparel industry. Finding the right size of a pair of jeans is a challenge
for many women. The answer of mass customization is taking a customer’s measurements
and making a custom pair of jeans for them. Zafu offers a different
approach. From the customer perspective, the experience starts similarly. Zafu asks
women shoppers 11 questions about how they prefer jeans to sit on their hips or
waist to create a body profile. In addition, they ask for some basic body measurements.
But instead of using this information to create a custom cut, they match this
information with a large database of proprietary fitting information about the jeans
of more than 30 major jeans brands. This database contains hundreds of styles, from
broadly marketed Gap to pricey designer labels. The consumer then gets a list of#p#分页标题#e#
ranked results, linked with the brand’s website to purchase. While the service is free
for consumers, Zafu gets its revenue not by selling any products but by receiving a
commission from any referral of a consumer to a retail website. To build their
proprietary database of styles, the company invited hundreds of women who had to
try on 32 different jeans. This gave them both information about women’s shapes
and figures and information about the cuts and fitting secrets of dozens of different
jeans brands. To update this information, Zafu has created a streamlined process so
that new models can easily be integrated into their database and assortment.
Zafu’s personalization service is an alternative model to conventional mass
customization. It may not have the inventory advantages and value prepositions of
mass customization, but is much easier to implement and is a much faster scalable
system. For consumers, such a matching service also implies less waiting time as
well as no price premiums associated with custom products. However, the two
models supplement each other: for most consumers, a better matching service like
MVM or Zafu will provide sufficient value, while for others the ultimate product
will still be the truly custom jean, providing not only perfect fit, but also the
hedonistic satisfaction connected with a custom product. Zafu is well positioned to
profit from this trend. The company is owned by Archtetype, a major enabler of true
mass customization for the clothing industry. Thus, they can easily refer a customer
finding no fitting piece in Zafu’s database of the existing assortment of standard
products to the custom clothing offerings of their partners like Land’s End or Tony
Hilfinger. I predict that we will see many more examples of these personalization
techniques as they offer companies the opportunity to profit more from what they
already have: vast assortments of existing goods. Using personalization and
recommendation services to match individual customers’ preferences with existing
assortments along the entire supply and retail chain could become a boost for both
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productivity and customer satisfaction in mature industries. The result may be a new
understanding of mass customization, beyond its roots in manufacturing and product
design: mass customization, in essence, is to efficiently serve individual customers
uniquely (Pine 2007). In the end, it is the customer who drives the business, and
customers are not differentiating between personalized, customized, or standardized
offerings; they just want to get what they want.
References
Davenport TH, Harris JG (2007) Competing on analytics: the new science of winning. Harvard Business
School Press, Boston#p#分页标题#e#
Davis S (1987) Future perfect. Addison-Wesley, Reading
Hvam L (2006) Mass customization in the electronics industry. Int J Mass Custom 1(4):410–426
Manyika JM, Roberts RP, Sprague KL (2007) Eight business technology trends to watch. McKinsey Q
44(4):1–10
Piller F (2005) Mass customization: reflections on the state of the concept. Int J Flex Manuf Syst
16(4):313–334
留学生论文范文Piller F, Reichwald R, Tseng M (2006) Competitive advantage through customer centric enterprises.
Int J Mass Custom 1(2/3):157–165
Pine BJ (1993) Mass customization. Harvard Business School Press, Boston
Pine BJ (2007) The state of mass customization and why authenticity in business is the next big issue.
B. Joseph Pine II in an interview with Frank Piller. Mass Custom Open Innov News 10(1)
Salvador F, Piller F (2007) Assortment productivity: a new measure for efficiency in supply chains.
Working paper
Toffler A (1970) Future shock. Random House, New York
Wilson J (2007) Best practices mass customization and build-to-order manufacturing. Cincinnati
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