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Several forces are transforming the structure and content of the marketing profession. Marketers are seeing increasingly faster changes in the marketplace and are barraged with an ever increasing amount of information. While many view traditional marketing as art and some view it as science, the new marketing increasingly looks like engineering. This textbook, combined with a collection of leading-edge software models (available separately) provides the student with the know-how and tools to collect the right information and perform analysis to make better marketing plans, better product designs, and better decisions.
Our purpose in writing this book is to help educate and train a new generation of marketing managers. We aim to train marketing engineers to translate concepts into context-specific operational decisions and actions using analytical, quantitative, and computer modeling techniques. We link theory to practice and practice to theory.
A Note from the Author:
Dear Marketing Engineering Revised Edition 2 User:
The several editions of Marketing Engineering that we have published since 1998 have been aimed at a fairly narrow, somewhat technical audience interested in bringing more scientific rigor to the marketing discipline. Versions of that book were adopted by more than 150 business schools on five continents. In 2007 we published Principles of Marketing Engineering to reach a broader, less technical audience. A key complement of that book, in response to user feedback, was Marketing Engineering for Excel (ME>XL), i.e., our Marketing Engineering software as an Excel Add-in. The response to that effort has been extremely positive and we have abandoned the original Marketing Engineering software platform, the one that produced the software complement to previous editions of this book.
Hence, as the note on the cover indicates, software is not included with the book. More importantly, when we reference software in the book, those references refer to a version of the software that is no longer available.
"I am very excited about this book. Finally marketing can exhibit its scientific muscle and move from opinions-based decision making to data-based decision making. I think this is a very important book that will spawn a new discipline within marketing."
Philip Kotler, Northwestern University
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Gary L. Lilien, who coined the term marketing engineering, is Distinguished Research Professor of Management Science at the Smeal College of Business at Penn State. He is also co-founder and Research Director of the Institute for the Study of Business Markets at Penn State, an organization aimed at fostering research and interchange in nonconsumer markets. He holds three degrees in operations research, from the School of Engineering at Columbia University. Previously, Prof. Lilien was a member of the faculty at the Sloan School at MIT. His research interests are in marketing engineering, market segmentation, new product modeling, marketing-mix issues for business products, bargaining and negotiations, modeling the industrial-buying process and innovation-diffusion modeling.
Prof. Lilien is the author or co-author of 12 books (including Marketing Models with Philip Kotler) and over 80 professional articles. He was Departmental Editor for Marketing for Management Science; is on the editorial board of the International Journal for Research in Marketing and the Journal of Business to Business Marketing; is Functional Editor for Marketing for Interfaces, and is Area Editor for Marketing Science. He is former Editor in Chief of Interfaces. He served as President as well as Vice President/Publications for the Institute of Management Sciences. He is U.S. Coordinator for the European Marketing Academy , was named an inaugural EMAC Fellow and serves on the board of directors of the INFORMS College on Marketing.
Prof. Lilien is a winner of the Alpha Kappa Psi award for the outstanding article in the Journal of Marketing. He was honored as the 2001-2002 Morse Lecturer by the Institute for Operations Research and the Management Sciences (INFORMS), was named one of the inaugural INFORMS Fellows and received the Kimball medal from INFORMS for distinguished contributions to the field of operations research and . He has received honorary doctorates from the University of Liege, the University of Ghent and Aston University.
Prof. Lilien's consulting clients Arcelor, AT&T, BP, Dow, DuPont, Eastman Chemical, Exelon, Federal Reserve Bank, IBM, Pillsbury, Pitney Bowes, Sprint and Xerox and is co-founder of the marketing analytics consulting firm, DecisionPro Inc.
Prof. Lilien is three-time winner and seven-time finalist in the Penn State Squash Club Championship and has substantial collections of fine wines and unusual porcine objects.
Arvind Rangaswamy is the Jonas H. Anchel Professor of Marketing at Penn State, where he is also co-founder and Research Director of the eBusiness Research Center. He received a PhD in marketing from Northwestern University, an MBA from the Indian Institute of Management, Calcutta, and a B.Tech from the Indian Institute of Technology, Madras. Before joining Penn State, he was a faculty member at the J. L. Kellogg Graduate School of Management, Northwestern University, and at the Wharton School, University of Pennsylvania. He is actively engaged in research to develop concepts, methods, and models to improve the efficiency and effectiveness of marketing using information technologies, including such topics as marketing modeling, online customer behavior, personalization, and online negotiations.
Prof. Rangaswamy has published numerous articles in such leading journals as Marketing Science, the Journal of Marketing Research, Management Science, the Journal of Marketing, the International Journal of Research in Marketing, Marketing Letters, Psychometrika, Multivariate Behavioral Research, and the Journal of Economics and Statistics.Excerpt. © Reprinted by permission. All rights reserved.:
Several forces are transforming the structure and content of the marketing manager's job. As a profession, marketing is evolving. It is no longer based primarily on conceptual content. Marketing resembles design engineering—it consists of putting together data, models, analyses, and computer simulations to learn about the marketplace and to design effective marketing plans. While many view traditional marketing as art and some view it as science, the new marketing increasingly looks like engineering (that is, combining art and science to solve specific problems). Our purpose in writing this book is to help educate and train a new generation of marketing managers.
Several key forces are changing the marketer's job:
Marketing managers must learn to function in the rapidly changing environment and to exploit evolving trends. Firms and business schools can help marketing managers to tope in two ways. They can offer traditional, concept-based education and training, with the hope that good people will figure out on their own how to cope with the changing environment. The education-as-usual approach will always have some success—well-motivated and intelligent marketers will figure out how to get reasonable value from the new resources. This approach is analogous to lecturing golf novices on the rules and giving them golf clubs and self-training books. Through study, networking, and observing successful golfers, some novices will become pretty good golfers. Others will become duffers. Still others will quit the game because it seems too hard. The lack of formal training limits development.
Those who want to excel need lessons, especially early on. Hence another way to help marketing managers respond to the changes is to provide information-age-specific education and training. There will always be an important role for marketing concepts, and using the powerful information tools now available requires sound conceptual grounding. But marketers need much more than concepts to fully exploit the resources available to them. They need to move from conceptual marketing to marketing engineering: using computer decision models in making marketing decisions. In this book we integrate concepts, analytic marketing techniques, and operational software to train the new generation of marketers, helping them to become marketing engineers.
OBJECTIVES FOR THE STUDENT
We designed this book for you, the business school student or marketing manager, who seeks the education you need to perform effectively in information-technology-intensive environments. Most traditional books focus on marketing from conceptual, empirical, or qualitative perspectives. With this book we aim to train marketing engineers to translate concepts into context-specific operational decisions and actions using analytical, quantitative, and computer modeling techniques. We link theory to practice and practice to theory.
Our specific objectives for the book are
Our pedagogical philosophy embraces two main principles: learning by doing and end-user modeling. Most of the concepts we describe have software implementation and at least one problem or case you can resolve by using the software. You may make errors and struggle at times, attempting to apply the tools. That is part of the learning-by-doing process; you will learn what the tools and software can do as well as what they cannot do. Traditional methods of teaching in business schools (i.e., lectures and case analyses) do not go far enough in helping students to make decisions, assess risks, and solve problems. The learning-by-doing approach extends traditional marketing education. With model-based tools for decision making, you can learn to anticipate and deal with the potential consequences of your decisions—this will help you improve your strategic thinking, sensitize you to customer needs, force you to anticipate competitive moves, and develop implementation plans. In short, you should not only learn to improve how you make marketing decisions, but also how to derive the maximum benefits from your decisions.
Decision models range from large-scale, enterprise-wide applications to those that can be quickly put together by an individual with an understanding of basic marketing and marketing engineering. We emphasize end-user modeling here. End-user modeling has the characteristics of good engineering: do as good a job as you can with the time and resources you have available.
Good end-user modeling provides direct benefits, permits rapid prototyping for more elaborate approaches, and makes the user a better customer (and critic) of larger, enterprise-wide applications. We are not trying to train you to be a technical specialist. Rather we hope to prepare you to put together technically simple but operationally useful decision models and to become astute users of those models and of the results of models that others have developed.
NEW FOR THE SECOND EDITION
The first edition of Marketing Engineering, published four years ago, had as its objective to provide the background and tools needed to train information-age marketers. Our aim was to help marketing students move from conceptual marketing to marketing engineering—to access and use computer decision models when making marketing decisions. As such, that edition combined 26 different software tools with a two-volume book and tutorial package that implemented our pedagogical philosophy: learning by doing and end-user modeling.
The positive (and negative feedback) associated with the first edition has lead to this second edition. Reviews of the concepts and the tools that we included were very positive. Hence, while we have updated the material and the references, we have changed very little of the core of the book, either in terms of the basic textual material or in terms of specific implementations of our software.
Criticisms of the book were mainly associated with
This second edition addresses these concerns by a redesign of the ME package to be accessible through the Internet. While a single softcover textbook remains, there is no longer a CD-ROM or a tutorial volume included with the text. Cases and exercises have been integrated into the single volume; tutorials (and other electronic components of the text) are now available on the Internet at www.mktgeng.com.
Adopters have three options for accessing the software:
Thus, in this second edition, we have:
The text for the second edition is organized as follows:
Each chapter also contains cases and problem sets that are keyed to the major concepts. We have also created a Web site, www.mktgeng.com, to provide the software for running the models described in the book. The Web site contains tutorials, help files, tips and other resources for using our software and for deriving the maximum benefits from marketing engineering. We update this site frequently to ensure that you will always have access to the latest software and accompanying resources.
In addition, instructors who adopt the book receive videotapes that highlight award-winning marketing engineering applications and the impact that those applications have had at the following firms:
USES OF THE BOOK FOR INSTRUCTORS
We designed this book primarily as a text for a one-semester, capstone MBA course. Students need not have strong backgrounds in quantitative methods; however, it will be helpful if they have some quantitative and marketing background and some facility with microcomputers and related (Windows-based) software. We have used the material successfully in executive programs and in undergraduate classes as well.
As there are 26 software modules (each with a different focus), the book includes twice as much material as can be covered in a normal one-semester course. The software and related problems should be viewed as a menu; students need not use all the software to gain benefits from the material. Indeed we find that students can readily absorb only 6 to 10 modules in a semester. For shorter courses and executive programs, you should make a much more limited selection.
Many of the software modules are intended for general use (i.e., not just for the problem set provided); they can be used for term projects that can provide a very valuable learning experience.
Many of us recognize that reading textbooks or listening to lectures is not the best way to learn marketing decision making. Instead, students should experience marketing in a way that leaves behind enduring lessons. Therefore, the best way for students to learn marketing engineering is to encourage them to use the software, to do the problems, and cases.
The software empowers students to solve marketing problems. We find that classes work best when we keep-lectures to a minimum and have one or two student groups present their problem analyses to the rest of the class, which acts as (skeptical) management. This follows the learning-by-doing philosophy and makes students responsible for their own learning. It also simulates how marketing engineering works in the real world.
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