Nowadays, the competitive situation of companies is characterized by a very strong orientation towards product
individualization. The change from a seller to a buyer market has led to a saturation situation within the industrial
goods’ markets where the offer by far exceeds the demand. Companies have to struggle to gain new customers.
This major change has increased the customer’s power, which has driven companies to differentiate their
products from those of competitors by offering individualized problem solutions (Nilles, 2002). The customer’s
expectations with respect to services and physical products have also dramatically risen. Therefore, companies
tend to increasingly fragment the markets, sometimes to an extreme level, to where each market is occupied by
only one customer (“markets of one”).
The individualization trend is mainly ascribed to social changes. The high growth of population was a key factor
for the emergence of the mass production system, one century ago. But nowadays, especially in the industrial
nations, the demographic development shows the population to be steadily decreasing. Simultaneously, wealth
and the demand for luxury continuously increase. Psychologists know that in the postmodern era, the need for
change and novelty is becoming as important as survival for human beings. The human behavior is essentially
determined by the individual principles and is rarely oriented on the behavior of the others (self-determination).
It is also well known that if more and more people possess the same object, then the possession of this object is
no longer interesting and loses its attractiveness (Piller, 1998). All of these reasons have contributed to a need
for individualization and the demand for products that exactly meet the individual expectations of customers.
Another important trend in the business world is the continuous decreasing of the product life cycles. Consequently,
the timeframes for product amortization are considerably reduced. At the same time, the costs of
research and development steadily increase because of higher technological complexity of products (Nilles,
2002). In addition, the ability of fulfilling individual customer needs necessitates the capability of producing a
large number of product variants, which induces high costs at both operations- and manufacturing-related tasks.
In effect, in contrast to the mass production system, in which the economies of scale can be fully utilized, the
individualization of customer requirements usually involves a loss of efficiency. On the other hand, globalization
and deregulation of markets as well as the rapid diffusion of e-commerce and e-business over the Internet has
led to more intensive and aggressive competition. This has also forced companies to develop strategies in order
to resist strong price pressures, especially from those companies that are producing in low-wage countries.
The challenge that manufacturing companies have to face is to provide individualized products and services
while maintaining a high cost efficiency. To be successful, companies have to address both of these perspectives,
which are necessary for gaining a competitive advantage. The manufacturing of products according to
individual customer needs is referred to as product customization. Whereas customization does not necessarily
imply a focus on the cost perspective, in this book we will concentrate on both product customization and cost
efficiency, namely mass customization, which is a new business paradigm that is very challenging for manufacturing
companies.
Mass customization is a business strategy that aims at fulfilling individual customer needs with near mass
production efficiency (Pine, 1993). Whereas the literature includes many contributions that discuss the strategic
benefits of mass customization, there are large deficits concerning its implementation in practice. Companies that
want to pursue this strategy need a set of practical tools in order to make mass customization work efficiently.
The main problem is about how to be able to produce a large number of customer-oriented product variants by
simultaneously providing prices that do not considerably differ from those of mass products.
Providing customers with individualized products at affordable prices is the main goal of mass customization.
However, customers generally accept paying premium prices compared to standard products because they honor
the additional benefits of customized products. Therefore, if mass customization fails in providing customers
with an optimal or a better solution than any mass products, then the product resulting from the customization
process will have, from the customer’s perspective, no more additional value than any other standard product.
As a result, an optimal understanding of customer needs is a necessary requirement for the success of the strategy.
In fact, the focus on customers is not new and not only specific to mass customization. Concepts such as
“customer orientation”, “close to the customer”, “customer segmentation”, “niche marketing” and “customer
relationship management” reveal the importance of the customer. However, during the pursuit of mass customization,
customers have to be seen as partners in the value creation, which implies a deeper customer-supplier
relationship. The customer provides a valuable input in the production process and is considered to be a “prosumer”
as coined by Toffler (1980).
Unfortunately, although the focus on the customer’s perspective is a well-known issue, the customer in the
specific context of mass customization is still misunderstood. Customers are provided with a high number of
product variants and are generally supposed to have the capability of making a rational decision. But this is not
true because customers are not able to make optimal choices in extensive choice environments. Thus, models
for a better conception of customer needs and preferences are required because the customer is a key factor that
considerably determines the success or failure of the strategy. Furthermore, a customer orientation through customization
tends to trigger increasing costs because of variety and complexity requirements (Blecker, Friedrich,
Kaluza, Abdelkafi, & Kreutler, 2005).
Due to the fact that it is necessary to satisfy the customer, the only chance to meet this challenge is to reduce
the customizing costs during the product modeling process. The universal remedy for this is to design, implement,
and use a supporting computer system. A computer system is, once implemented, the best way to cope with
the problem, because it automates main parts of product designing and producing. This reduces complexity and
human efforts, which in the end lead to lower costs. Even if the additional investment for creating such systems
is taken into account, the cost-cutting effect of mass-customization supporting systems will exceed this by far.
Furthermore, the advances realized in information technology are critical enablers, which make this strategy
function efficiently. Information systems can be implemented to support diverse activities in the mass-customization
value chain. They assist customers during the product specification phase in order to lead them in a
fast-paced manner to the product variants corresponding to their individual requirements. Modern information
systems, which support open innovation, even enable customers to participate actively in the product design. In
addition, mass customization information systems contribute to helping companies mitigate excessive product
variety and increase cost efficiency on the shop floor and logistics through optimal product modeling, production
planning, and scheduling.
Another upcoming logistical challenge is caused by the companies’ ambitions of focusing on core competences
and therefore reducing the level of vertical integration. Increasing efforts for coordinating the product’s
supply chain are an inevitable consequence. Logistical issues like planning deliveries of raw materials as well as
semi-finished goods become more important. Information systems can support companies in their supply chain
management and furthermore promote the automation in the company (Blecker & Friedrich, 2006).
Although the need for supporting information systems becomes obvious, suitable tools for addressing this
relevant issue in the specific case of mass customization are missing. Therefore, the intention of this book is
to bridge the gap between demand and supply in order to provide information and managerial tools that aim at
coping with all of the depicted problems.
This book is divided into three sections. The first section (Chapter I-IV) deals with the ways of product
configuration and modeling for mass customization as well as the existing benefits and challenges for mass
customization, especially in engineer-to-order companies. Furthermore, the functionality and features of the
Supply Chain Operations Reference Model in terms of scope and modularity to support an “open variant process
model” are investigated.
The second section (Chapter V-IX) starts with a presentation of frameworks in the course of mass customization.
Afterwards, mass customization information systems are organized across the supply chain.
Finally, this book’s last part (Chapter X-XIII) examines several new approaches for mass customization like
Scenario-based, Knowledge-based and Fuzzy Cognitive Maps and gives an outlook on future developments in
the field of information technology for mass customization.
More detailed, this book includes the following:
Section I - Theory of Information Technology for Mass Customization
Chapter I (Mass Customization with Configurable Products and Configurators: A Review of Benefits and Challenges)
provides a systematic review of literature on how mass customization with configurable products and the
use of configurators affect companies. Configurable products are an important way to achieve mass customization.
A configurable product is designed once, and this design is used repetitively in the sales-delivery process
to produce specifications of product individuals meeting customer requirements. Configurators are information
systems that support the specification of product individuals and the creation and management of configuration
knowledge, therefore being prime examples of information systems supporting mass customization. However,
to the best of our knowledge, there is no systematic review of literature on how mass customization with con-
figurable products and the use of configurators affects companies. This chapter focuses on benefits that can be
gained and challenges that companies may face. A supplier can move to mass customization and configuration
from mass production or from full customization. The chapter also reviews benefits and challenges from the
customer perspective. Finally, the future research directions, open challenges, and problems are identified.
Chapter II (Product Modeling and Configuration Experiences) attempts to present an alternative for product
modeling based on applied research activities. The model proposed is based on a concept supported by different
views: functional, technological, and physical. With the aim of making the model learner-friendly, the chapter
also presents an industrial case applied in the lift industry. The specific problems, the model used, the implementation
carried out, and the results obtained are described in detail. The objective is to make a contribution
based on the industrial practice to one of the basic enablers for product configuration. The final aim is to speed
up the supply-chain process in mass customization scenarios.
Chapter III (Product Configuration in ETO Companies) reviews how mass customization and product con-
figuration can benefit engineer-to-order companies. The relevant main literature in the area is reviewed to identify
the benefits. Furthermore, the challenges of implementing product configuration in an engineer-to-order company
are described. Finally, a number of suggestions for meeting these challenges are presented. In addition, a case
description is introduced which supports that product configuration can benefit engineer-to-order companies even
though there are a number of challenges to be met. The chapter concludes that engineer-to-order companies can
certainly benefit from product configuration by improving business process efficiency as well as information
quality and ultimately improving the company’s competitive advantage.
Chapter IV (Open Variant Process Models in Supply Chains) will elaborate on complexity in supply chains
and the implications on supply chain design. It investigates the specific requirements of supply chain processes
in terms of flexibility versus standardization, evaluating the feasibility of designing, customizing, assessing,
and improving logistics processes within a framework provided by process reference models. Mass customization
and, in particular, a configuration approach for financial services will be discussed for their applicability
for reducing complexity in a process environment. Process reference frameworks will be used as elements of
an “open variant process model”. The Supply Chain Operations Reference model defined by the Supply Chain
Council as the major cross-industry standard for supply chain management will be discussed for its usefulness
and shortcomings in “process mass customization”, with a focus on systems implementation.
Section II - Frameworks for Mass Customization
Chapter V (An Associative Classification-Based Recommendation System for Personalization in B2C ECommerce
Applications) presents an associative classification-based recommendation system to support online
customer decision-making when facing a huge amount of choices. Recommendation systems have been recently
introduced to e-commerce sites in order to solve the information overload and mass confusion problem. This
chapter applies knowledge discovery techniques to overcome the drawback of conventional recommendation
systems approaches. The framework of the associative classification-based recommendation system has been
addressed in this chapter. The system analysis, design, and implementation issues in an Internet programming
environment are also presented. Taking the advantage of accumulative knowledge from historical data, the ef-
ficiency and effectiveness of B2C e-commerce applications are improved.
Chapter VI (Knowledge-Based Recommender Technologies Supporting the Interactive Selling of Financial
Services) presents the knowledge-based recommender environment Koba4MS (Knowledge-based Advisors for
Marketing and Sales) which allows a flexible mapping of product, marketing, and sales knowledge to the representation
of a recommender knowledge-base. In Koba4MS diagnosis, personalization and knowledge acquisition
techniques are integrated to provide an infrastructure for the interactive selling of financial services. Those require
deep knowledge about the product domain as well as about potential wishes and needs of customers. In this
context, sales representatives can differ significantly in their expertise and level of sales knowledge. Therefore,
financial service providers ask for tools supporting sales representatives in the dialog with the customer.
Chapter VII (Developing Interoperability in Mass Customisation Information Systems) proposes a standardbased
framework to assist industrial organizations to develop interoperability in mass customization information
systems. After identifying the major challenges for business and information systems in mass customization,
the authors propose an innovative standard-based conceptual architecture for a combined model-driven and
services-oriented platform. The chapter concludes by describing a global methodology for integration of models
and applications, to enhance an enterprise’s interoperability in the support of mass customization practices,
keeping the same organization’s technical and operational environment, improving its methods of work and the
usability of the installed technology through harmonization, and integration of the enterprise models in use by
customers, manufacturers, and suppliers.
Chapter VIII (An Agent-Based Information Technology Architecture for Mass Customized Markets) presents
a Web-enabled, agent-based information system model to support mass-customized markets. Furthermore, a
distributed, real-time, Java-based, mobile intelligent information system is presented. This interfaces with firms’
existing IT infrastructures, follows a build-to-order production strategy, and integrates order-entry with supply
chain, manufacturing, and product delivery systems. The model provides end-to-end visibility across the entire
supply chain, allows for a collaborative and synchronized production system, and supports an event-based
manufacturing environment. The system introduces four general purpose intelligent agents to support the entire
mass-customization process. The adoption of this approach by a semiconductor manufacturing firm resulted in
reductions in product lead time (by half), buffer inventory (from five to two weeks), and manual transactions (by
80%). Similarly, the adoption by a leading automotive manufacturer resulted in a 51% total inventory reduction
while increasing plant utilization by 30%. These results verify that the successful adoption of this system can
reduce inventory and logistic costs, improve delivery performance, increase manufacturing facilities utilization,
and provide a higher overall profitability.
Chapter IX (Critical Role of Supply Chain Decoupling Point in Mass Customisation from its Upstream and
Downstream Information Systems Point of View) concentrates on the role of supply chain decoupling point.
Therefore, this chapter introduces different levels of customization and mass operations as well as three types
of mass customization. It argues that in each mass customization type, information systems in upstream and
downstream of the decoupling point can be varied. Consequently, information flows in different types of mass
customization have been examined. This analysis is an endeavor to organize mass customization information
systems across the supply chain; it can also be a useful structure for future researches in this area as well.
Section III – Innovative Information Technology Approaches for Mass Customization
Chapter X (From Strategy Definition to Product Derivation Using a Scenario-Based Architecting
Approach) presents a set of scenario-based methods and techniques to support the development of system
architectures that are more future-proof, and are also advantageous for mass customization. These
methods and techniques have originally been developed for highly-customized professional systems, in
particular medical imaging equipment. The chapter introduces mass customization as a business strategy
that aims at satisfying, in a timely and cost-effective manner, the various needs of different customers. For
that purpose, a system architecture is needed that supports two different kinds of variability: Variability
in space provides a range of different products where each addresses the specific needs of an individual
customer; and variability in time allows the products to evolve and thus meet new requirements. In
defining such an architecture, two issues should be considered. One is how to anticipate the most likely
changes in the external business environment, and hence in the customers’ future needs. The other is
whether the architecture can address these changes effectively.
Chapter XI (Research Issues in Knowledge-Based Configuration) gives an overview on the current
research issues in the domain of knowledge-based configuration technology. Knowledge-based
configuration systems have made their way into industrial practice. Nowadays, all major vendors of
configuration systems rely on some form of declarative knowledge representation and intelligent search
techniques for solving the core configuration problem, due to the inherent advantages of that technology:
On the one hand, changes in the business logic (configuration rules) can be accomplished more easily
because of the declarative and modular nature of the knowledge bases, while on the other hand highly optimized,
domain-independent problem-solving algorithms are available for the task of constructing
valid configurations.
As the development has not come to an end as, in a world that becomes increasingly automated and
wired together, constantly new challenges for the development of intelligent configuration systems
arise, this chapter provides a view on future research issues: Web-based configurators are being made
available for large heterogeneous user groups, the provision of mass-customized products requires
the integration of companies along a supply chain, and configuration and reconfiguration of services
becomes an increasingly important issue, just to name a few. Finally, this chapter summarizes the state
of the art, recent achievements, novel approaches, and open challenges in the field of knowledge-based
configuration technology.
Chapter XII (Mass Customisation of Services and Processes Based on Fuzzy Cognitive Maps) draws
on the theory of Fuzzy Cognitive Maps to propose a modeling approach for mass customization of
services. The proposed model integrates concepts from service quality, and customer preferences with
business process and IT capabilities models. The model presented in this chapter is, to the best of our
knowledge, the only fuzzy service model for mass customization that provides the means to consider the
business objectives for service customization, associates them with specific business areas, and suggests
opportunities for mass customization. In contrast to other service design and management approaches,
the proposed model is dynamic, exhibits flexibility and responsiveness to environmental changes and
customizability to specific organizational contexts, and allows the development of planning scenarios.
Chapter XIII (Applying Service CAD System to Value Customization) introduces a new concept, value
customization, to increase the level of customer satisfaction. It presents methodologies and practice for
designers to customize value in a service in industrial operation based on the discipline of Service Engineering.
Service Engineering aims at creating more value largely by knowledge and service contents
rather than just materialistic contents. Specifically, an information system named Service Explorer, an
implementation of the methodologies, is applied to an Italian accommodation industry. After the application, five redesign options such as introducing a new service system with cash-back and a system of renting
various goods were generated. Through this, the effectiveness of Service Engineering for value customization
is suggested. This chapter addresses the importance of identifying value to be provided with specific customers
based on their particular requirements, which has only briefly been discussed in researches of mass customization.
In addition, both service activities and physical products can be crucial to realize value. Several further
research issues such as general design methods for value customization were also identified.
This book provides the latest research results in the field of information systems for mass customization. This
book describes the state-of-the-art, innovative theoretical frameworks, advanced and successful implementations
as well as the latest empirical research findings in the area of mass customization information technology.
Furthermore, new concepts and methods for successful mass customization are presented (like Scenario- and
Knowledge-based approaches). The main objective is to bridge theory and practice, on the one hand, and to fill
research gaps and answer open questions, on the other hand. The book improves the understanding of the problems
that are encountered during the conception of information systems for mass customization. Furthermore,
it provides solution approaches for the mitigation of these problems and simultaneously highlights new directions
for future research. Therefore, it is not only a must for researchers and graduate students but also provides
practitioners with the latest application-oriented results.
References
Blecker, T., Friedrich, G., Kaluza, B., Abdelkafi, N., & Kreutler, G. (2005). Information and management systems
for product customization. New York: Springer Science+Business Media, Inc.
Blecker, T., & Friedrich, G. (Eds.). (2006). Mass customization – Challenges and solutions. New York: Springer
Science+Business Media, Inc.
Nilles, V. (2002). Effiziente Gestaltung von Produktordnungssystemen – Eine theoretische und empirische Untersuchung.
Ph.D. dissertation, University Munich, Munich.
Piller, F. T. (1998). Kundenindividuelle Massenproduktion – Die Wettbewerbsstrategie der Zukunft. Munich:
Wien, Hanse.
Pine II, B. J. (1993). Mass customization: The new frontier in business competition. Boston: Harvard Business
School Press.
Toffler, A. (1980). The third wave. New York: William Morrow & Co., Inc.