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Dynamic Modeling for Business Management: An Introduction / Edition 1

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Overview

Modeling is a tool used by savvy business managers to understand the processes of their businesses and to estimate the impact of changes. Dynamic Modeling for Business Management demonstrates dynamic modeling techniques beginning with fundamental processes and advancing to more complex business models. Discussions of modeling emphasize its practical use for decision-making and in implementing change for measurable results. Readers will learn both manufacturing and service-oriented business processes through hands-on lessons. They will then be able to manipulate additional models to test their knowledge and address issues specific to their own businesses and interests. Some of the topics covered include workflow management, supply-chain management, and business strategy.

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Product Details

  • ISBN-13: 9780387404615
  • Publisher: Springer New York
  • Publication date: 1/8/2004
  • Series: Modeling Dynamic Systems Series
  • Edition description: 2004
  • Edition number: 1
  • Pages: 308
  • Product dimensions: 0.75 (w) x 9.21 (h) x 6.14 (d)

Table of Contents

Preface
Chapter 1. Introduction to ITHINK
1.1 Introduction
1.2 Static, comparative static, and dynamic models
1.3 Model components
1.4 Modeling in ITHINK
1.5 The detailed modeling process
Chapter 2. Modeling of Dynamic Business Systems
2.1 Introduction
2.2 Making the organization more manageable-systems and processes
2.3 Creating and using a model
2.4 Structural complexity-a market share model
2.5 Complexity due to random variation-an order control process
2.6 Further benefits of dynamic modeling
2.7 Organization principle of this book
Chapter 3. Measuring Process Performance
3.1 Introduction
3.2 Financial measures of performance
3.3 The basic profit model
3.4 The role of time, borrowing, and lending
3.5 Choosing among alternatives
3.6 Optimizing at the level of the firm
3.7 Issues with financial measures
3.8 Beyond process output measures
3.9 The process model approach

Chapter 4. Single-Step Processes
4.1 Introduction
4.2 The basic process model and Little's Law
4.3 Queuing systems
4.4 Transient queuing behavior
4.5 Further modeling with queuing systems
Chapter 5. Multistep Serial Workflow Processes
5.1 Introduction
5.2 Modeling multistep processes in ITHINK
5.3 Specifying models/modeling objectives
5.4 An uncoupled process-an order handling process
5.5 A tightly coupled process-a fast food restaurant process
5.6 Other configurations
Chapter 6. Multistep parallel workflow processes
6.1 Introduction
6.2 Parallel queuing models-designing a checkout system
6.3 Resource implications-the fast food restaurant revisited
6.4 Telephone call center model-balking
6.5 Machine repair model
6.6 Batching-a laboratory analysis model
Chapter 7. The Supplier Interface: Managing Risk
7.1 Introduction
7.2 First-moment managers
7.3 Second-moment managers
7.4 Third-moment managers7.5 Fourth-moment managers
Chapter 8. Customer Interface
8.1 Introduction
8.2 The basic Make-to-Stock model-controlling the inventory level
8.3 The Make-to-Order process- customer interface
Chapter 9. The Tradeoffs between Quality, Speed, and Cost
9.1 Introduction
9.2 Model development
9.3 The tradeoffs
9.4 Coping with uncertainty
Chapter 10. Modeling Supply Chains
10.1 Introduction
10.2 Introduction to the Beer Game
10.3 The Beer Game model
10.4 Further analysis of the Beer Game model
10.5 Modifications to the basic model
10.6 Using the Beer Game model in game mode
Chapter 11. The Dynamics of Management Strategy: an Ecological Metaphor
11.1 Introduction
11.2 Hierarchy in nature
11.3 A model demonstrating the hierarchical nature of an expanding business
Chapter 12. Modeling Improvement Processes
12.1 Introduction
12.2 Learning curves
12.3 Modeling an improvement process
12.4 Model results
12.5 Other types of learning curves
Appendix A. Modeling Random Variation in Business Systems
A.1 Introduction
A.2 The uniform distribution
A.3 The triangular distribution
A.4 The normal distribution-common cause process variation
A.5 The exponential distribution-equipment failure times
A.6 The Poisson distribution-modeling defects in products
A.7 The pass/fail and binomial distribution-product failures
A.8 Bimodal distributions-parallel process flows
A.9 Custom distributions
A.10 The relative comparison of random variation
Appendix 2. Discussion of the Actual Profiles for the Examples of Chapter 2
Appendix B. Economic Value Added
Appendix C. Derivation of Equations 6.2, 6.3, and 6.4
Appendix 8A Optimization Techniques for the Customer Interface Model
Index

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