Simulating Business Processes for Descriptive, Predictive, and Prescriptive Analytics / Andrew Greasley.

Format:

Book

Author/Creator:

Greasley, Andrew, Author.

Contributor:

Assi, Anand, Contributor.

Greasley, Andrew, Contributor.

Musa, Emmanuel, Contributor.

Smith, Chris M., Contributor.

Vallejos, Melissa Venegas, Contributor.

Wang, Yucan, Contributor.

Language:

English

Subjects (All):

Decision making--Simulation methods.

Decision making.

Management--Statistical methods.

Management.

Business intelligence.

Physical Description:

1 online resource (x, 341 pages) : illustrations

Place of Publication:

Berlin ; Boston : De Gruyter, [2019]

Language Note:

In English.

Summary:

This book outlines the benefits and limitations of simulation, what is involved in setting up a simulation capability in an organization, the steps involved in developing a simulation model and how to ensure that model results are implemented. In addition, detailed example applications are provided to show where the tool is useful and what it can offer the decision maker. In Simulating Business Processes for Descriptive, Predictive, and Prescriptive Analytics, Andrew Greasley provides an in-depth discussion of Business process simulation and how it can enable business analytics How business process simulation can provide speed, cost, dependability, quality, and flexibility metrics Industrial case studies including improving service delivery while ensuring an efficient use of staff in public sector organizations such as the police service, testing the capacity of planned production facilities in manufacturing, and ensuring on-time delivery in logistics systems State-of-the-art developments in business process simulation regarding the generation of simulation analytics using process mining and modeling people's behavior Managers and decision makers will learn how simulation provides a faster, cheaper and less risky way of observing the future performance of a real-world system. The book will also benefit personnel already involved in simulation development by providing a business perspective on managing the process of simulation, ensuring simulation results are implemented, and that performance is improved.

Contents:

Frontmatter

Preface

Acknowledgments

About the Author

Contents

Chapter 1. Analytics and Simulation Basics

Chapter 2. Simulation and Business Processes

Chapter 3. Build the Conceptual Model

Chapter 4. Build the Simulation

Chapter 5. Use Simulation for Descriptive, Predictive and Prescriptive Analytics

Chapter 6. Case Study: A Simulation of a Police Call Center

Chapter 7. Case Study: A Simulation of a "Last Mile" Logistics System

Chapter 8. Case Study: A Simulation of an Enterprise Resource Planning System

Chapter 9. Case Study: A Simulation of a Snacks Process Production System

Chapter 10. Case Study: A Simulation of a Police Arrest Process

Chapter 11. Case Study: A Simulation of a Food Retail Distribution Network

Chapter 12. Case Study: A Simulation of a Proposed Textile Plant

Chapter 13. Case Study: A Simulation of a Road Traffic Accident Process

Chapter 14. Case Study: A Simulation of a Rail Carriage Maintenance Depot

Chapter 15. Case Study: A Simulation of a Rail Vehicle Bogie Production Facility

Chapter 16. Case Study: A Simulation of Advanced Service Provision

Chapter 17. Case Study: Generating Simulation Analytics with Process Mining

Chapter 18. Case Study: Using Simulation with Data Envelopment Analysis

Chapter 19. Case Study: Agent-Based Modeling in Discrete-Event Simulation

Appendix A

Appendix B

Index

Notes:

Includes bibliographical references (pages 336-337) and index.

Description based on online resource; title from PDF title page (publisher's Web site, viewed 06. Apr 2020)

ISBN:

9781547400690

1547400692

OCLC:

1125186018