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Author: Andrew Greasley
Publisher: Walter de Gruyter GmbH & Co KG
ISBN: 1547400714
Category : Business & Economics
Languages : en
Pages : 423
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Book Description
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.
Author: Andrew Greasley
Publisher: Walter de Gruyter GmbH & Co KG
ISBN: 1547400714
Category : Business & Economics
Languages : en
Pages : 423
Get Book Here
Book Description
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.
Author: Andrew Greasley
Publisher: Walter de Gruyter GmbH & Co KG
ISBN: 1547400692
Category : Business & Economics
Languages : en
Pages : 352
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Book Description
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.
Author: Manuel Laguna
Publisher: CRC Press
ISBN: 1439885281
Category : Business & Economics
Languages : en
Pages : 516
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Book Description
Most textbooks on business process management focus on either the nuts and bolts of computer simulation or the managerial aspects of business processes. Covering both technical and managerial aspects of business process management, Business Process Modeling, Simulation and Design, Second Edition presents the tools to design effective business proce
Author: Andrew Greasley
Publisher: Routledge
ISBN: 1000754367
Category : Business & Economics
Languages : en
Pages : 111
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Book Description
This short textbook consolidates all the key aspects of operations management into a concise and easily accessible reference tool. Comprising the management of creating goods and delivering services to customers, operations management plays an essential role in the success of any organization. This book discusses the main areas of operations management, such as the design of the operations system, including product, process and job design. It also covers the management of operations, including lean operations and supply chain management. Breaking the subject down into its key components, this book provides a core introduction for undergraduate students studying operations management as part of business and management degrees.
Author: Andrew Greasley
Publisher: Taylor & Francis
ISBN: 1000648826
Category : Business & Economics
Languages : en
Pages : 414
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Book Description
While simulation has a vast area of application, this textbook focuses on the use of simulation to analyse business processes. It provides an up-to-date coverage of all stages of the discrete-event simulation (DES) process, covering important areas such as conceptual modelling, modelling input data, verification and validation and simulation output analysis. The book is comprehensive yet uncomplicated, covering the theoretical aspects of the subject and the practical elements of a typical simulation project, demonstrated by cases, examples and exercises. It also shows how simulation relates to new developments in machine learning, big data analytics and conceptual modelling techniques. Guidance is provided on how to build DES models using the Arena, Simio and Simul8 simulation software, and tutorials for using the software are incorporated throughout. Simulation Modelling offers a uniquely practical and end-to-end overview of the subject, which makes it perfect required or recommended reading for advanced undergraduate and postgraduate students studying business simulation and simulation modelling as part of operations research, business analytics, supply chain management and computer science courses.
Author: M. Affan Badar
Publisher: CRC Press
ISBN: 1040261345
Category : Computers
Languages : en
Pages : 488
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Book Description
Businesses have faced a variety of difficulties as a result of the global pandemic, and how they responded to this disruption has affected both their resilience and their ability to get through this crisis. Digital technologies have played a crucial role in addressing these issues and fostering resilience. It is, therefore, imperative to explore options for post-pandemic business transformation and rethinking sustainable development. Handbook of Digital Innovation, Transformation, and Sustainable Development in a Post-Pandemic Era, covers digital innovation and business transformation to build resilience for sustainable development and growth and highlights the impact of supply chain disruptions and solutions to sustain. The handbook stands out for its inclusion of industry cases from various regions across the globe. By presenting the use of big data, blockchain technology, and Industry 4.0, the handbook conveys how to work towards sustainable development and offers self-reliant and sustainable business models. Researchers and practitioners in industrial engineering, engineering management, business management, supply chain management, and digital technologies along with businesses can apply the research and practices covered in the handbook. Chapter 14 of this book is freely available as a downloadable Open Access PDF at http://www.taylorfrancis.com under a Creative Commons Attribution-Non Commercial-No Derivatives (CC-BY-NC-ND) 4.0 license.
Author: Amar Sahay
Publisher: Business Expert Press
ISBN: 1631574809
Category : Business & Economics
Languages : en
Pages : 321
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Book Description
This business analytics (BA) text discusses the models based on fact-based data to measure past business performance to guide an organization in visualizing and predicting future business performance and outcomes. It provides a comprehensive overview of analytics in general with an emphasis on predictive analytics. Given the booming interest in analytics and data science, this book is timely and informative. It brings many terms, tools, and methods of analytics together. The first three chapters provide an introduction to BA, importance of analytics, types of BA-descriptive, predictive, and prescriptive-along with the tools and models. Business intelligence (BI) and a case on descriptive analytics are discussed. Additionally, the book discusses on the most widely used predictive models, including regression analysis, forecasting, data mining, and an introduction to recent applications of predictive analytics-machine learning, neural networks, and artificial intelligence. The concluding chapter discusses on the current state, job outlook, and certifications in analytics.
Author: JUBI R
Publisher: NEHAS PUBLICATIONS
ISBN: 819681142X
Category : Business & Economics
Languages : en
Pages : 367
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Book Description
In today's dynamic and data-driven business landscape, the art and science of Business Analytics have emerged as critical tools for exploration, introspection, and informed decision-making. "Business Analytics," the book at hand, delves into the practices and competencies essential for unraveling the complexities of business performance, facilitating purposeful, intuitive, and expedient decision-making processes. The essence of Business Analytics lies in the extensive exploration of business data, aiming to extract meaningful information usable by managers across various organizational levels. This book positions Business Analytics as a catalyst for fact-based decision-making, elevating accountability in the decision-making process. It defines Business Analytics as a methodical process that involves scrutinizing and summarizing data with the explicit purpose of uncovering hidden predictive insights. This book places a particular emphasis on the science and artistry of business analytics, with a special focus on financial analytics. It not only explores the practical aspects but also lays the theoretical foundations, providing a comprehensive context for various elements of business analytics within specific business situations. A distinctive feature of this book is its commitment to showcasing the implementation of analytics by illustrating how leading companies leverage this power to enhance their investments. Acknowledging that scientific knowledge alone may not suffice for sound decision-making, the book underscores the importance of combining scientific expertise with a deep understanding of the business context and the best available information. Addressing a notable gap in existing literature, this book goes beyond traditional academic texts that predominantly concentrate on quantitative methods. Instead, it extends its reach to cover analytics for non-quantitative managers. In doing so, the book aims to equip a broader audience with the knowledge and tools necessary to harness the benefits of Business Analytics in diverse business scenarios. As you embark on this journey through the pages of "Business Analytics," you will gain insights into the transformative power of analytics in decision-making, and how it has become an indispensable asset for businesses navigating the intricacies of the contemporary corporate landscape.
Author: Amar Sahay
Publisher: Business Expert Press
ISBN: 1631573322
Category : Business & Economics
Languages : en
Pages : 206
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Book Description
Business Analytics: A Data-Driven Decision Making Approach for Business-Part I,/i> provides an overview of business analytics (BA), business intelligence (BI), and the role and importance of these in the modern business decision-making. The book discusses all these areas along with three main analytics categories: (1) descriptive, (2) predictive, and (3) prescriptive analytics with their tools and applications in business. This volume focuses on descriptive analytics that involves the use of descriptive and visual or graphical methods, numerical methods, as well as data analysis tools, big data applications, and the use of data dashboards to understand business performance. The highlights of this volume are: Business analytics at a glance; Business intelligence (BI), data analytics; Data, data types, descriptive analytics; Data visualization tools; Data visualization with big data; Descriptive analytics-numerical methods; Case analysis with computer applications.
Author: Alejandro Peña-Ayala
Publisher: Springer Nature
ISBN: 9819900263
Category : Artificial intelligence
Languages : en
Pages : 299
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Book Description
This book describes theoretical elements, practical approaches, and specialized tools that systematically organize, characterize, and analyze big data gathered from educational affairs and settings. Moreover, the book shows several inference criteria to leverage and produce descriptive, explanatory, and predictive closures to study and understand education phenomena at in classroom and online environments. This is why diverse researchers and scholars contribute with valuable chapters to ground with well-sounded theoretical and methodological constructs in the novel field of Educational Data Science (EDS), which examines academic big data repositories, as well as to introduces systematic reviews, reveals valuable insights, and promotes its application to extend its practice. EDS as a transdisciplinary field relies on statistics, probability, machine learning, data mining, and analytics, in addition to biological, psychological, and neurological knowledge about learning science. With this in mind, the book is devoted to those that are in charge of educational management, educators, pedagogues, academics, computer technologists, researchers, and postgraduate students, who pursue to acquire a conceptual, formal, and practical landscape of how to deploy EDS to build proactive, real- time, and reactive applications that personalize education, enhance teaching, and improve learning!
