Hast du Fragen, Tipps, Lob oder Kritik? Deine Rückmeldung hilft uns, CeDe.ch noch besser zu machen. Wir freuen uns deshalb über jede Nachricht und beantworten alle E-Mails schnell, kompetent und gerne. Vielen Dank!
Diese Seite verwendet Cookies. Erfahren Sie in unserer Datenschutzerklärung mehr darüber, wie wir Cookies einsetzen und wie Sie Ihre Einstellungen ändern können. OK
Modelling is a tool used by savvy business managers to understand the processes of their business and to estimate the impact of changes. Dynamic Modelling for Business Management applies dynamic modelling to business management, using accessible modelling techniques that are demonstrated starting with fundamental processes and advancing to more complex business models. Discussions of modelling emphasize its practical use for decision making and implementing change for measurable results. Readers will learn about both manufacturing and service-oriented business processes using hands-on lessons. Then will then be able to manipulate additional models to try out their knowledge and address issues specific to their own businesses and interests.
PrefaceChapter 1. Introduction to ITHINK1.1 Introduction 1.2 Static, comparative static, and dynamic models1.3 Model components1.4 Modeling in ITHINK 1.5 The detailed modeling processChapter 2. Modeling of Dynamic Business Systems2.1 Introduction2.2 Making the organization more manageable-systems and processes2.3 Creating and using a model2.4 Structural complexity-a market share model2.5 Complexity due to random variation-an order control process2.6 Further benefits of dynamic modeling2.7 Organization principle of this bookChapter 3. Measuring Process Performance3.1 Introduction3.2 Financial measures of performance3.3 The basic profit model3.4 The role of time, borrowing, and lending3.5 Choosing among alternatives3.6 Optimizing at the level of the firm3.7 Issues with financial measures3.8 Beyond process output measures3.9 The process model approachChapter 4. Single-Step Processes4.1 Introduction4.2 The basic process model and Little's Law4.3 Queuing systems4.4 Transient queuing behavior4.5 Further modeling with queuing systemsChapter 5. Multistep Serial Workflow Processes 5.1 Introduction5.2 Modeling multistep processes in ITHINK5.3 Specifying models/modeling objectives5.4 An uncoupled process-an order handling process5.5 A tightly coupled process-a fast food restaurant process5.6 Other configurationsChapter 6. Multistep parallel workflow processes6.1 Introduction6.2 Parallel queuing models-designing a checkout system6.3 Resource implications-the fast food restaurant revisited6.4 Telephone call center model-balking6.5 Machine repair model6.6 Batching-a laboratory analysis modelChapter 7. The Supplier Interface: Managing Risk7.1 Introduction 7.2 First-moment managers7.3 Second-moment managers7.4 Third-moment managers7.5 Fourth-moment managersChapter 8. Customer Interface 8.1 Introduction8.2 The basic Make-to-Stock model-controlling the inventory level8.3 The Make-to-Order process- customer interfaceChapter 9. The Tradeoffs between Quality, Speed, and Cost9.1 Introduction9.2 Model development9.3 The tradeoffs9.4 Coping with uncertaintyChapter 10. Modeling Supply Chains10.1 Introduction10.2 Introduction to the Beer Game10.3 The Beer Game model10.4 Further analysis of the Beer Game model10.5 Modifications to the basic model10.6 Using the Beer Game model in game modeChapter 11. The Dynamics of Management Strategy: an Ecological Metaphor11.1 Introduction11.2 Hierarchy in nature11.3 A model demonstrating the hierarchical nature of an expanding businessChapter 12. Modeling Improvement Processes12.1 Introduction12.2 Learning curves12.3 Modeling an improvement process12.4 Model results12.5 Other types of learning curvesAppendix A. Modeling Random Variation in Business SystemsA.1 IntroductionA.2 The uniform distributionA.3 The triangular distributionA.4 The normal distribution-common cause process variationA.5 The exponential distribution-equipment failure timesA.6 The Poisson distribution-modeling defects in productsA.7 The pass/fail and binomial distribution-product failuresA.8 Bimodal distributions-parallel process flowsA.9 Custom distributionsA.10 The relative comparison of random variationAppendix 2. Discussion of the Actual Profiles for the Examples of Chapter 2 Appendix B. Economic Value AddedAppendix C. Derivation of Equations 6.2, 6.3, and 6.4Appendix 8A Optimization Techniques for the Customer Interface ModelIndex
Dynamic Modeling for Business Management applies dynamic modeling to business management, using accessible modeling techniques that are demonstrated starting with fundamental processes and advancing to more complex business models. Discussions of modeling emphasize its practical use for decision making and implementing change for measurable results. Readers will learn about both manufacturing and service-oriented business processes using hands-on lessons. They will then be able to manipulate additional models to try out 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.