As the title suggests, this book is about analytical business process modeling and design. It is the result of several years of teaching a business process design and simulation course at the undergraduate and the MBA levels in the Leeds School of Business at the University of Colorado at Boulder. We have also drawn from one of the author’s experiences delivering a simulation course in the Industrial Engineering and Management program at Lund University in Sweden.
The main motivation for writing this textbook stems from our struggle to find a book that approaches business process design from a broad, quantitative modeling perspective. The main objective with this book is thus to provide students with a comprehensive understanding of the multitude of analytical tools that can be used to model, analyze, understand, and ultimately design business processes. We believe that the most flexible and powerful of these tools, although not always the most appropriate, is discrete event simulation.
The wide range of approaches covered in this book include graphical flowcharting tools, deterministic models for cycle time analysis and capacity decisions, and analytical queuing methods, as well as the use of data envelopment analysis (DEA) for benchmarking purposes. What distinguishes this textbook from general operations management (OM) books, most of which cover many of the same topics, is its focus on business processes as opposed to just manufacturing processes or general OM problems, and its emphasis on simulation modeling using state-of-the-art commercial simulation software. Essentially, Business Process Modeling, Simulation, and Design can be thought of as a hybrid between traditional books on process management, operations management, and simulation. Although it would be desirable for all students in operations management to take several courses in each of these topics, the reality is that few business school curricula today allow that. In our experience, simulation especially tends to be shoved to the side simply because it is perceived to be too technical. However, our firm belief, manifested by our writing of this book, is that this need not and should not be the case. The rapid development of user-friendly simulation software with graphical interfaces has made the use of simulation accessible even to those lacking computer programming skills, and it provides a great medium for illustrating and understanding implications of capacity restrictions and random variation on process performance. Furthermore, the growing interest in simulation-based tools in industry suggests that an understanding of simulation modeling, its potential as well as its limitations for analyzing and designing processes, is of key importance for students looking for a future career in operations management.
Before proceeding with a discussion of how we picture this book being used, it is worthwhile to summarize what the book is not. It is not a traditional, qualitatively oriented book on process management, although we dedicate one chapter to these important issues. It is not a traditional book on operations management, although it covers some of the traditional tools found in most OM books. Furthermore, it is not a traditional book on simulation, although discrete event simulation is used extensively. It is a book that attempts to bring these topics together by placing an analytical modeling perspective on process design and particularly emphasizing the power of simulation modeling as a vehicle for analyzing and designing business processes.
This textbook is ideal for a one-semester undergraduate or MBA course within an operations management business school curriculum. The MBA course typically would cover some of the more advanced topics in greater depth, such as DEA (which does not require that students have some previous exposure to linear programming, but it is helpful) simulation optimization, and queuing. The MBA course also could include a more involved simulation project. In addition, we envision this book being used for an undergraduate course in industrial engineering or within an engineering management program. In terms of requirements, the textbook assumes that students have taken a basic course in business statistics. However, if students have been exposed to a! basic course in operations management and have some prior knowledge of quantitative techniques, this gives an additional opportunity to explore some of the topics covered in this textbook in more detail. In terms of how to cover the material, we recommend following the chapter sequence.
The text is organized as follows.
The simulation modeling is done entirely with the Extend software, enabling the students to work hands-on with models of their own. A potential criticism associated with this software-integrated approach is that the acquired knowledge may be thought of as being software dependent. However, our experience is that after initially investing some time in understanding the software, the main challenge and learning lie in creating abstract models of processes, a conceptual framework that is software independent. Furthermore, because the functionality of most modern simulation software is very similar, exposure to one product promotes a valuable understanding of the potential and limitations of simulation modeling in general.
The textbook includes a CD with a student version of Extend OR V6 and the Excel add-in for solving DEA problems. For instructors, an additional CD is available that includes solutions to end-of-chapter problems, prebuilt Extend models, and some additional simulation exercises/projects with suggested solutions.
There are many individuals among our colleagues, families, and friends who have contributed to this book as sources of inspiration, encouragement, and support. Our deepest gratitude goes to all of you. Others have had a more direct influence on this book, and we take this opportunity to express our appreciation for their valuable help. Special thanks go to Pat Diamond and others at Imagine That Inc., who worked with us on the simulation models and allowed us to distribute the student version of Extend LT with our text. We would also like to thank the following reviewers, who provided many valuable suggestions in shaping this textbook:
George E. Monahan, University of Illinois
Charles Munson, Washington State University
C. Surrender Reddy, Saginaw Valley State University
Joseph Sarkis, Clark University
Shane J. Schvaneveldt, Weber State University
Our gratitude also goes to past and present students in the undergraduate and graduate programs at the Leeds School of Business who have helped shape this book into what it is today. Special thanks go to Marco Better for helping us put together the instructor’s manual. We are indebted to our Leeds School of Business colleagues Thomas Vossen, Cathleen S. Burns, and David E. Monarchi for providing helpful criticism and feedback on earlier drafts.
And thank you to Tom Tucker at Prentice Hall who encouraged us to pursue this project and provided help and advice along the way. Finally, our thanks to Maureen Wilson and Dawn Stapleton at Prentice Hall, and Jennifer Welsch at BookMasters, who capably guided our manuscript through production. Thank you for making this book a reality!