Business Process Analytics : Modeling, Simulation, and Design: Fourth Edition
(2025)- Abstract
The fourth edition of this widely
used textbook offers a new perspective. Previously titled Business
Process Modeling, Simulation and Design, as the new title suggests, this
book is about analytical business process modeling and design. However,
this new edition introduces analytics to the title and to the
presentation. The main objective of this book is 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. The most flexible and powerful of these tools,
although not always the most appropriate, is discrete-event simulation.
The wide range of approaches covered... (More)The fourth edition of this widely
(Less)
used textbook offers a new perspective. Previously titled Business
Process Modeling, Simulation and Design, as the new title suggests, this
book is about analytical business process modeling and design. However,
this new edition introduces analytics to the title and to the
presentation. The main objective of this book is 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. 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 machine
learning. The authors focus on business processes as opposed to just
manufacturing processes or general operations management problems and
emphasize on simulation modeling using state-of-the-art commercial
simulation software. Business Process Analytics: Modeling, Simulation,
and Design can be thought of as a hybrid between traditional books on
process management, operations management, and simulation. The growing
interest in simulation-based tools suggests that an understanding of
simulation modeling, its potential as well as its limitations for
analyzing and designing processes, is of key importance to students
looking for a future career in operations management. Changes from the
previous edition include the following: • New section on data-driven
process improvement (with data visualization) • Added a subsection of
control charts to the 6-sigma section • Replaced business process
reengineering with business process management • Updated all text,
figures, examples, and exercises to ExtendSim10 (current version) • MThe
fourth edition of this widely used textbook offers a new perspective.
Previously titled Business Process Modeling, Simulation and Design, as
the new title suggests, this book is about analytical business process
modeling and design. However, this new edition introduces analytics to
the title and to the presentation. The main objective of this book is 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. 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 machine learning. The authors focus on business processes as opposed
to just manufacturing processes or general operations management
problems and emphasize on simulation modeling using state-of-the-art
commercial simulation software. Business Process Analytics: Modeling,
Simulation, and Design can be thought of as a hybrid between traditional
books on process management, operations management, and simulation. The
growing interest in simulation-based tools suggests that an
understanding of simulation modeling, its potential as well as its
limitations for analyzing and designing processes, is of key importance
to students looking for a future career in operations management.
Changes from the previous edition include the following: • New section
on data-driven process improvement (with data visualization) • Added a
subsection of control charts to the 6-sigma section • Replaced business
process reengineering with business process management • Updated all
text, figures, examples, and exercises to ExtendSim10 (current version) •
More coverage on design of experiments • More coverage of machine
learning and neural networks TABLE OF CONTENTS.The
fourth edition of this widely used textbook offers a new perspective.
Previously titled Business Process Modeling, Simulation and Design, as
the new title suggests, this book is about analytical business process
modeling and design. However, this new edition introduces analytics to
the title and to the presentation. The main objective of this book is 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. 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 machine learning. The authors focus on business processes as opposed
to just manufacturing processes or general operations management
problems and emphasize on simulation modeling using state-of-the-art
commercial simulation software. Business Process Analytics: Modeling,
Simulation, and Design can be thought of as a hybrid between traditional
books on process management, operations management, and simulation. The
growing interest in simulation-based tools suggests that an
understanding of simulation modeling, its potential as well as its
limitations for analyzing and designing processes, is of key importance
to students looking for a future career in operations management.
Changes from the previous edition include the following: • New section
on data-driven process improvement (with data visualization) • Added a
subsection of control charts to the 6-sigma section • Replaced business
process reengineering with business process management • Updated all
text, figures, examples, and exercises to ExtendSim10 (current version) •
More coverage on design of experiments • More coverage of machine
learning and neural networks TABLE OF CONTENTS.The fourth edition of this widely
used textbook offers a new perspective. Previously titled Business
Process Modeling, Simulation and Design, as the new title suggests, this
book is about analytical business process modeling and design. However,
this new edition introduces analytics to the title and to the
presentation. The main objective of this book is 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. 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 machine
learning. The authors focus on business processes as opposed to just
manufacturing processes or general operations management problems and
emphasize on simulation modeling using state-of-the-art commercial
simulation software. Business Process Analytics: Modeling, Simulation,
and Design can be thought of as a hybrid between traditional books on
process management, operations management, and simulation. The growing
interest in simulation-based tools suggests that an understanding of
simulation modeling, its potential as well as its limitations for
analyzing and designing processes, is of key importance to students
looking for a future career in operations management. Changes from the
previous edition include the following: • New section on data-driven
process improvement (with data visualization) • Added a subsection of
control charts to the 6-sigma section • Replaced business process
reengineering with business process management • Updated all text,
figures, examples, and exercises to ExtendSim10 (current version) •
- author
- Laguna, Manuel and Marklund, Johan LU
- organization
- publishing date
- 2025
- type
- Book/Report
- publication status
- published
- subject
- edition
- 4
- pages
- 619 pages
- publisher
- CRC Press/Balkema
- external identifiers
-
- scopus:86000252503
- ISBN
- 9781032595429
- 9781040120781
- DOI
- 10.1201/9781032617237
- language
- English
- LU publication?
- yes
- id
- 35bca4e7-57ed-4bed-a8ab-75e9b085dbc1
- date added to LUP
- 2025-06-27 09:52:56
- date last changed
- 2025-06-27 09:53:58
@book{35bca4e7-57ed-4bed-a8ab-75e9b085dbc1,
abstract = {{<p>The fourth edition of this widely <br>
used textbook offers a new perspective. Previously titled Business <br>
Process Modeling, Simulation and Design, as the new title suggests, this<br>
book is about analytical business process modeling and design. However,<br>
this new edition introduces analytics to the title and to the <br>
presentation. The main objective of this book is to provide students <br>
with a comprehensive understanding of the multitude of analytical tools <br>
that can be used to model, analyze, understand, and ultimately design <br>
business processes. The most flexible and powerful of these tools, <br>
although not always the most appropriate, is discrete-event simulation. <br>
The wide range of approaches covered in this book include graphical <br>
flowcharting tools, deterministic models for cycle time analysis and <br>
capacity decisions, and analytical queuing methods, as well as machine <br>
learning. The authors focus on business processes as opposed to just <br>
manufacturing processes or general operations management problems and <br>
emphasize on simulation modeling using state-of-the-art commercial <br>
simulation software. Business Process Analytics: Modeling, Simulation, <br>
and Design can be thought of as a hybrid between traditional books on <br>
process management, operations management, and simulation. The growing <br>
interest in simulation-based tools suggests that an understanding of <br>
simulation modeling, its potential as well as its limitations for <br>
analyzing and designing processes, is of key importance to students <br>
looking for a future career in operations management. Changes from the <br>
previous edition include the following: • New section on data-driven <br>
process improvement (with data visualization) • Added a subsection of <br>
control charts to the 6-sigma section • Replaced business process <br>
reengineering with business process management • Updated all text, <br>
figures, examples, and exercises to ExtendSim10 (current version) • MThe<br>
fourth edition of this widely used textbook offers a new perspective. <br>
Previously titled Business Process Modeling, Simulation and Design, as <br>
the new title suggests, this book is about analytical business process <br>
modeling and design. However, this new edition introduces analytics to <br>
the title and to the presentation. The main objective of this book is to<br>
provide students with a comprehensive understanding of the multitude of<br>
analytical tools that can be used to model, analyze, understand, and <br>
ultimately design business processes. The most flexible and powerful of <br>
these tools, although not always the most appropriate, is discrete-event<br>
simulation. The wide range of approaches covered in this book include <br>
graphical flowcharting tools, deterministic models for cycle time <br>
analysis and capacity decisions, and analytical queuing methods, as well<br>
as machine learning. The authors focus on business processes as opposed<br>
to just manufacturing processes or general operations management <br>
problems and emphasize on simulation modeling using state-of-the-art <br>
commercial simulation software. Business Process Analytics: Modeling, <br>
Simulation, and Design can be thought of as a hybrid between traditional<br>
books on process management, operations management, and simulation. The<br>
growing interest in simulation-based tools suggests that an <br>
understanding of simulation modeling, its potential as well as its <br>
limitations for analyzing and designing processes, is of key importance <br>
to students looking for a future career in operations management. <br>
Changes from the previous edition include the following: • New section <br>
on data-driven process improvement (with data visualization) • Added a <br>
subsection of control charts to the 6-sigma section • Replaced business <br>
process reengineering with business process management • Updated all <br>
text, figures, examples, and exercises to ExtendSim10 (current version) •<br>
More coverage on design of experiments • More coverage of machine <br>
learning and neural networks TABLE OF CONTENTS.The<br>
fourth edition of this widely used textbook offers a new perspective. <br>
Previously titled Business Process Modeling, Simulation and Design, as <br>
the new title suggests, this book is about analytical business process <br>
modeling and design. However, this new edition introduces analytics to <br>
the title and to the presentation. The main objective of this book is to<br>
provide students with a comprehensive understanding of the multitude of<br>
analytical tools that can be used to model, analyze, understand, and <br>
ultimately design business processes. The most flexible and powerful of <br>
these tools, although not always the most appropriate, is discrete-event<br>
simulation. The wide range of approaches covered in this book include <br>
graphical flowcharting tools, deterministic models for cycle time <br>
analysis and capacity decisions, and analytical queuing methods, as well<br>
as machine learning. The authors focus on business processes as opposed<br>
to just manufacturing processes or general operations management <br>
problems and emphasize on simulation modeling using state-of-the-art <br>
commercial simulation software. Business Process Analytics: Modeling, <br>
Simulation, and Design can be thought of as a hybrid between traditional<br>
books on process management, operations management, and simulation. The<br>
growing interest in simulation-based tools suggests that an <br>
understanding of simulation modeling, its potential as well as its <br>
limitations for analyzing and designing processes, is of key importance <br>
to students looking for a future career in operations management. <br>
Changes from the previous edition include the following: • New section <br>
on data-driven process improvement (with data visualization) • Added a <br>
subsection of control charts to the 6-sigma section • Replaced business <br>
process reengineering with business process management • Updated all <br>
text, figures, examples, and exercises to ExtendSim10 (current version) •<br>
More coverage on design of experiments • More coverage of machine <br>
learning and neural networks TABLE OF CONTENTS.The fourth edition of this widely <br>
used textbook offers a new perspective. Previously titled Business <br>
Process Modeling, Simulation and Design, as the new title suggests, this<br>
book is about analytical business process modeling and design. However,<br>
this new edition introduces analytics to the title and to the <br>
presentation. The main objective of this book is to provide students <br>
with a comprehensive understanding of the multitude of analytical tools <br>
that can be used to model, analyze, understand, and ultimately design <br>
business processes. The most flexible and powerful of these tools, <br>
although not always the most appropriate, is discrete-event simulation. <br>
The wide range of approaches covered in this book include graphical <br>
flowcharting tools, deterministic models for cycle time analysis and <br>
capacity decisions, and analytical queuing methods, as well as machine <br>
learning. The authors focus on business processes as opposed to just <br>
manufacturing processes or general operations management problems and <br>
emphasize on simulation modeling using state-of-the-art commercial <br>
simulation software. Business Process Analytics: Modeling, Simulation, <br>
and Design can be thought of as a hybrid between traditional books on <br>
process management, operations management, and simulation. The growing <br>
interest in simulation-based tools suggests that an understanding of <br>
simulation modeling, its potential as well as its limitations for <br>
analyzing and designing processes, is of key importance to students <br>
looking for a future career in operations management. Changes from the <br>
previous edition include the following: • New section on data-driven <br>
process improvement (with data visualization) • Added a subsection of <br>
control charts to the 6-sigma section • Replaced business process <br>
reengineering with business process management • Updated all text, <br>
figures, examples, and exercises to ExtendSim10 (current version) • </p>}},
author = {{Laguna, Manuel and Marklund, Johan}},
isbn = {{9781032595429}},
language = {{eng}},
publisher = {{CRC Press/Balkema}},
title = {{Business Process Analytics : Modeling, Simulation, and Design: Fourth Edition}},
url = {{http://dx.doi.org/10.1201/9781032617237}},
doi = {{10.1201/9781032617237}},
year = {{2025}},
}