Dynamic Modeling for Business Management: An Introduction

319 Pages·2004·5.482 MB·English

by  Bernard McGarvey, Bruce Hannon (eds.)

Modeling Dynamic Systems
Series Editors
Matthias Ruth
Bruce Hannon
Springer
New York
Berlin
Heidelberg
Hong Kong
London
Milan
Paris
Tokyo
Bernard McGarvey Bruce Hannon
Dynamic Modeling
for Business
Management
An Introduction
With 166 Illustrations and a CD-ROM
Bernard McGarvey Bruce Hannon
Process Engineering Center Department of Geography
Drop Code 3127 220 Davenport Hall, MC 150
Eli Lilly and Company University of Illinois
Lilly Corporate Center Urbana, IL 61801
Indianapolis, IN 46285 USA
USA
Series Editors:
Matthias Ruth Bruce Hannon
Environmental Program Department of Geography
School of Public Affairs 220 Davenport Hall, MC 150
3139 Van Munching Hall University of Illinois
University of Maryland Urbana, IL 61801
College Park, MD 20742–1821 USA
USA
Cover illustration: Top panel––The model with the controls on ORDERING and SELLING.Bot-
tom panel––Photo by William F. Curtis.
Library of Congress Cataloging-in-Publication Data
Hannon, Bruce M.
Dynamic modeling for business management: an introduction / Bruce Hannon,
Bernard McGarvey.
p. cm.
ISBN 0-387-40461-9 (cloth: alk. paper)
1. Management—Mathematical models. 2. Digital computer simulation.
I. McGarvey, Bernard. II. Title.
HD30.25.H348 2003
519.7(cid:1)03—dc21 2003054794
ISBN 0-387-40461-9 Printed on acid-free paper.
©2004 Springer-Verlag New York, Inc.
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Series Preface
The world consists of many complex systems, ranging from our own bodies to
ecosystems to economic systems. Despite their diversity, complex systems have
many structural and functional features in common that can be effectively simu-
lated using powerful, user-friendly software. As a result, virtually anyone can ex-
plore the nature of complex systems and their dynamical behavior under a range
of assumptions and conditions. This ability to model dynamic systems is already
having a powerful influence on teaching and studying complexity.
The books in this series will promote this revolution in “systems thinking” by
integrating skills of numeracy and techniques of dynamic modeling into a variety
of disciplines. The unifying theme across the series will be the power and sim-
plicity of the model-building process, and all books are designed to engage the
reader in developing their own models for exploration of the dynamics of systems
that are of interest to them.
Modeling Dynamic Systems does not endorse any particular modeling para-
digm or software. Rather, the volumes in the series will emphasize simplicity of
learning, expressive power, and the speed of execution as priorities that will facil-
itate deeper system understanding.
Matthias Ruth and Bruce Hannon
v
Preface
The problems of understanding complex system behavior and the challenge of
developing easy-to-use models are apparent in the field of business management.
We are faced with the problem of optimizing economic goals while at the same
time managing complicated physical and social systems. In resolving such prob-
lems, many parameters must be assessed. This requires tools that enhance the col-
lection and organization of data, interdisciplinary model development, trans-
parency of models, and visualization of the results. Neither purely mathematical
nor purely experimental approaches will suffice to help us better understand the
world we live in and shape so intensively.
Until recently, we needed significant preparation in mathematics and computer
programming to develop, run, and interpret such models. Because of this hurdle,
many have failed to give serious consideration to preparing and manipulating
computer models of dynamic events in the world around them. Such obstacles
produced models whose internal workings generally were known to only one per-
son. Other people were unsure that the experience and insights of the many ex-
perts who could contribute to the modeling project were captured accurately. The
overall trust in such models was limited and, consequently, so was the utility. The
concept of team modeling was not practical when only a few held the high degree
of technical skill needed for model construction. And yet everyone agreed that
modeling a complex management process should include all those with relevant
expertise.
This book, and the methods on which it is built, will empower us to model and
analyze the dynamic characteristics of human–production environment interac-
tions. Because the modeling is based on the construction of icon-based diagrams
using only four elementary icons, the modeling process can quickly involve all
members of an expert group. No special mathematical or programming experi-
ence is needed for the participants. All members of the modeling team can con-
tribute, and each of them can tell immediately if the model is capturing his or her
special expertise. In this way, the knowledge of all those involved in the question
can be captured faithfully and in an agreeable manner. The model produced by
such a team is useful, and those who made it will recommend it throughout the
organization.
vii
viii Preface
Such a model includes all the appropriate feedback loops, delays, and uncer-
tainties. It provides the organization with a variety of benefits. The modeling ef-
fort highlights the gaps in knowledge about the process; it allows the modeling of
a variety of scenarios; it reveals normal variation in a system; and, of course, it
gives quantitative results. One of the more subtle values of team modeling is the
emergence of a way of analogously conceiving the process. The model structure
provides a common metaphor or analogous frame for the operation of the process.
Such a shared mental analogue greatly facilitates effective communication in the
organization.
Our book is aimed at several audiences. The first is the business-school student.
Clearly, those being directly prepared for life in the business world need to ac-
quire an understanding of how to model as well as the strengths and limitations of
models. Students in industrial engineering often perform modeling exercises, but
they often miss the tools and techniques that allow them to do group dynamic
modeling. We also believe that students involved in labor and industrial relations
should be exposed to this form of business modeling. The importance of the dy-
namics of management and labor involvement in any business process is difficult
to overstate. Yet these students typically are not exposed to such modeling. In
short, we want this book to become an important tool in the training of future pro-
cess and business managers.
Our second general audience is the young M.B.A., industrial engineer, and
human-resources manager in their first few years in the workplace. We believe
that the skills acquired through dynamic modeling will make them more valued
employees, giving them a unique edge on their more conventionally trained col-
leagues. This book is an introductory text because we want to teach people the
basics before they try to apply the techniques to real-world situations. Many
times, the first model a person will build is a complex model of an organization.
Problems can result if the user is not grounded in the fundamental principles. It is
like being asked to do calculus without first doing basic algebra.
Computer modeling has been with us for nearly 40 years. Why then are we so
enthusiastic about its use now? The answer comes from innovations in software
and powerful, affordable hardware available to every individual. Almost anyone
can now begin to simulate real-world phenomena on his or her own, in terms that
are easily explainable to others. Computer models are no longer confined to the
computer laboratory. They have moved into every classroom, and we believe they
can and should move into the personal repertoire of every educated citizen.
The ecologist Garrett Hardin and the physicist Heinz Pagels have noted that an
understanding of system function, as a specific skill, must and can become an in-
tegral part of general education. It requires recognition that the human mind is
not capable of handling very complex dynamic models by itself. Just as we need
help in seeing bacteria and distant stars, we need help modeling dynamic sys-
tems. For instance, we solve the crucial dynamic modeling problem of ducking
stones thrown at us or safely crossing busy streets. We learned to solve these
problems by being shown the logical outcome of mistakes or through survivable
accidents of judgment. We experiment with the real world as children and get hit
Preface ix
by hurled stones; or we let adults play out their mental model of the conse-
quences for us, and we believe them. These actions are the result of experimen-
tal and predictive models, and they begin to occur at an early age. These models
allow us to develop intuition about system behavior. So long as the system re-
mains reasonably stable, this intuition can serve us well. In our complex social,
economic, and ecological world, however, systems rarely remain stable for long.
Consequently, we cannot rely on the completely mental model for individual or
especially for group action, and often, we cannot afford to experiment with the
system in which we live. We must learn to simulate, to experiment, and to pre-
dict with complex models.
Many fine books are available on this subject, but they differ from ours in im-
portant ways. The early book edited by Edward Roberts, Managing Applications
of System Dynamics (Productivity Press, 1978),is comprehensive and yet based
on Dynamo, a language that requires substantial effort to learn. Factory Physics,
by Wallace Hopp and Mark Spearman (Irwin/McGraw-Hill, 1996), focuses on the
behavior of manufacturing systems. They review the past production paradigms
and show how dynamic modeling processes can improve the flow of manufactur-
ing lines. Business Dynamics,by John Sterman (Irwin/McGraw-Hill, 2000), is a
clear and thorough exposition of the modeling process and the inherent behavior
of various if somewhat generic modeling forms.
In a real sense, our book is a blend of all three of these books. We focus on the
use of ithink®, with its facility for group modeling, and show how it can be used
for very practical problems. We show how these common forms of models apply
to a variety of dynamic situations in industry and commerce. The approach we
use is to start from the simplest situation and then build up complexity by ex-
panding the scope of the process. After first giving the reader some insight into
how to develop ithink models, we begin by presenting our view of why dynamic
modeling is important and where it fits. Then we stress the need for system per-
formance measures that must be part of any useful modeling activity. Next we
look at single- and multistep workflow processes, followed by models of risk
management, of the producer/customer interface, and then supply chains. Next
we examine the tradeoffs between quality, production speed, and cost. We close
with chapters on the management of strategy and what we call business learning
systems.By covering a wide variety of topics, we hope to impress on the reader
just how easy it is to apply modeling techniques in one situation to another that
initially might look different. We want to stress commonality, not difference!
In this book, we have selected the modeling software ithink with its icono-
graphic programming style. Programs such as ithink are changing the way in
which we think. They enable each of us to focus and clarify the mental model we
have of a particular phenomenon, to augment it, to elaborate it, and then to do
something we cannot otherwise do: find the inevitable dynamic consequences
hidden in our assumptions and the structure of the model. ithink and the Mac-
intosh, as well as the new, easy-to-use, Windows®-based personal computers, are
not the ultimate tools in this process of mind extension. However, the relative
ease of use of these tools makes the path to freer and more powerful intellectual
x Preface
inquiry accessible to every student. Whether you are a whiz at math or somewhat
of a novice is irrelevant. This is a book on systems thinking and on learning how
to translate that thinking into specific, testable models.
Finally, we wish to thank Tina Prow for a thorough edit of this book.
Bernard McGarvey, Indianapolis, Indiana, and
Bruce Hannon, Urbana, Illinois
Summer 2003
Contents
Series Preface v
Preface vii
Chapter1. Introduction to Dynamic Modeling 1
1.1 Introduction 1
1.2 Static, comparative static, and dynamic models 3
1.3 Model components 5
1.4 Modeling in ithink 7
1.5 The detailed modeling process 18
Chapter2. Modeling of Dynamic Business Systems 21
2.1 Introduction 21
2.2 Making the organization more manageable:
Systems and processes 23
2.3 Creating and using a model 26
2.4 Structural complexity: Amarket share model 31
2.5 Complexity due to random variation: An order control process 38
2.6 Further benefits of dynamic modeling 42
2.7 Organizing principle of this book 45
Chapter3. Measuring Process Performance 48
3.1 Introduction 48
3.2 Financial measures of performance 49
3.3 The basic profit model 49
3.4 The role of time, borrowing, and lending 51
3.5 Choosing among alternatives 55
3.6 Optimizing at the level of the firm 59
3.7 Issues with financial measures 62
3.8 Beyond process output measures 64
3.9 The process model approach 66
xi
xii Contents
Chapter4. Single-Step Processes 76
4.1 Introduction 76
4.2 The basic process model and Little’s Law 77
4.3 Queuing systems 86
4.4 Transient queuing behavior 101
4.5 Further modeling with queuing systems 104
Chapter5. Multistep Serial Workflow Processes 106
5.1 Introduction 106
5.2 Modeling multistep processes in ithink 108
5.3 Specifying models/modeling objectives 109
5.4 An uncoupled process: An order handling process 110
5.5 Atightly coupled process: Afast food restaurant process 121
5.6 Other configurations 129
5.7 Material control systems 131
Chapter6. Multistep Parallel Workflow Processes 140
6.1 Introduction 140
6.2 Parallel queuing models: Designing a checkout system 141
6.3 Resource implications: The fast food restaurant revisited 144
6.4 Telephone call center model: Balking 149
6.5 Machine repair model 154
6.6 Batching: Alaboratory analysis model 162
Chapter7. The SupplierInterface: Managing Risk 170
7.1 Introduction 170
7.2 First-moment managers 171
7.3 Second-moment managers 171
7.4 Third-moment managers 175
7.5 Fourth-moment managers 176
Chapter8. CustomerInterface 179
8.1 Introduction 179
8.2 Controlling the inventory level: Make-to-Stock model 180
8.3 The Make-to-Order process: Customer interface 187
Chapter9. The Tradeoffs Among Quality, Speed, and Cost 192
9.1 Introduction 192
9.2 Model development 193
9.3 The tradeoffs 195
9.4 Coping with uncertainty 198