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| data analytics simulation strategic decision making solution: Analytics, Operations, and Strategic Decision Making in the Public Sector Evans, Gerald William, Biles, William E., Bae, Ki-Hwan G., 2019-02-15 Analytics for the public sector involves the application of operations research and statistical techniques to solve various problems existing outside of the private sector. The use of analytics for the public sector results in more efficient and effective services for the clients and users of these systems. Analytics, Operations, and Strategic Decision Making in the Public Sector is an essential reference source that discusses analytics applications in various public sector organizations, and addresses the difficulties associated with the design and operation of these systems including multiple conflicting objectives, uncertainties and resulting risk, ill-structured nature, combinatorial design aspects, and scale. Featuring research on topics such as analytical modeling techniques, data mining, and statistical analysis, this book is ideally designed for academicians, educators, researchers, students, and public sector professionals including those in local, state, and federal governments; criminal justice systems; healthcare; energy and natural resources; waste management; emergency response; and the military. |
| data analytics simulation strategic decision making solution: Simulation and Wargaming Charles Turnitsa, Curtis Blais, Andreas Tolk, 2022-02-15 Understanding the potential synergies between computer simulation and wargaming Based on the insights of experts in both domains, Simulation and Wargaming comprehensively explores the intersection between computer simulation and wargaming. This book shows how the practice of wargaming can be augmented and provide more detail-oriented insights using computer simulation, particularly as the complexity of military operations and the need for computational decision aids increases. The distinguished authors have hit upon two practical areas that have tremendous applications to share with one another but do not seem to be aware of that fact. The book includes insights into: The application of the data-driven speed inherent to computer simulation to wargames The application of the insight and analysis gained from wargames to computer simulation The areas of concern raised by the combination of these two disparate yet related fields New research and application opportunities emerging from the intersection Addressing professionals in the wargaming, modeling, and simulation industries, as well as decision makers and organizational leaders involved with wargaming and simulation, Simulation and Wargaming offers a multifaceted and insightful read and provides the foundation for future interdisciplinary progress in both domains. |
| data analytics simulation strategic decision making solution: Decision Intelligence Analytics and the Implementation of Strategic Business Management P. Mary Jeyanthi, Tanupriya Choudhury, Dieu Hack-Polay, T P Singh, Sheikh Abujar, 2022-01-01 This book presents a framework for developing an analytics strategy that includes a range of activities, from problem definition and data collection to data warehousing, analysis, and decision making. The authors examine best practices in team analytics strategies such as player evaluation, game strategy, and training and performance. They also explore the way in which organizations can use analytics to drive additional revenue and operate more efficiently. The authors provide keys to building and organizing a decision intelligence analytics that delivers insights into all parts of an organization. The book examines the criteria and tools for evaluating and selecting decision intelligence analytics technologies and the applicability of strategies for fostering a culture that prioritizes data-driven decision making. Each chapter is carefully segmented to enable the reader to gain knowledge in business intelligence, decision making and artificial intelligence in a strategic management context. |
| data analytics simulation strategic decision making solution: Competing on Analytics Thomas H. Davenport, Jeanne G. Harris, 2007-03-06 You have more information at hand about your business environment than ever before. But are you using it to “out-think” your rivals? If not, you may be missing out on a potent competitive tool. In Competing on Analytics: The New Science of Winning, Thomas H. Davenport and Jeanne G. Harris argue that the frontier for using data to make decisions has shifted dramatically. Certain high-performing enterprises are now building their competitive strategies around data-driven insights that in turn generate impressive business results. Their secret weapon? Analytics: sophisticated quantitative and statistical analysis and predictive modeling. Exemplars of analytics are using new tools to identify their most profitable customers and offer them the right price, to accelerate product innovation, to optimize supply chains, and to identify the true drivers of financial performance. A wealth of examples—from organizations as diverse as Amazon, Barclay’s, Capital One, Harrah’s, Procter & Gamble, Wachovia, and the Boston Red Sox—illuminate how to leverage the power of analytics. |
| data analytics simulation strategic decision making solution: HBR Guide to Data Analytics Basics for Managers (HBR Guide Series) Harvard Business Review, 2018-03-13 Don't let a fear of numbers hold you back. Today's business environment brings with it an onslaught of data. Now more than ever, managers must know how to tease insight from data--to understand where the numbers come from, make sense of them, and use them to inform tough decisions. How do you get started? Whether you're working with data experts or running your own tests, you'll find answers in the HBR Guide to Data Analytics Basics for Managers. This book describes three key steps in the data analysis process, so you can get the information you need, study the data, and communicate your findings to others. You'll learn how to: Identify the metrics you need to measure Run experiments and A/B tests Ask the right questions of your data experts Understand statistical terms and concepts Create effective charts and visualizations Avoid common mistakes |
| data analytics simulation strategic decision making solution: Big Data Analytics Using Multiple Criteria Decision-Making Models Ramakrishnan Ramanathan, Muthu Mathirajan, A. Ravi Ravindran, 2017-07-12 Multiple Criteria Decision Making (MCDM) is a subfield of Operations Research, dealing with decision making problems. A decision-making problem is characterized by the need to choose one or a few among a number of alternatives. The field of MCDM assumes special importance in this era of Big Data and Business Analytics. In this volume, the focus will be on modelling-based tools for Business Analytics (BA), with exclusive focus on the sub-field of MCDM within the domain of operations research. The book will include an Introduction to Big Data and Business Analytics, and challenges and opportunities for developing MCDM models in the era of Big Data. |
| data analytics simulation strategic decision making solution: Business Process Modeling, Simulation and Design Manuel Laguna, Johan Marklund, 2018-12-07 Business Process Modeling, Simulation and Design, Third Edition provides students with a comprehensive coverage of a range of analytical tools used to model, analyze, understand, and ultimately design business processes. The new edition of this very successful textbook includes a wide range of approaches such as graphical flowcharting tools, cycle time and capacity analyses, queuing models, discrete-event simulation, simulation-optimization, and data mining for process analytics. While most textbooks on business process management either focus on the intricacies of computer simulation or managerial aspects of business processes, this textbook does both. It presents the tools to design business processes and management techniques on operating them efficiently. The book focuses on the use of discrete event simulation as the main tool for analyzing, modeling, and designing effective business processes. The integration of graphic user-friendly simulation software enables a systematic approach to create optimal designs. |
| data analytics simulation strategic decision making solution: Business Process Modeling, Simulation and Design, Second Edition Manuel Laguna, Johan Marklund, 2013-04-25 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 processes and the management techniques to operate them efficiently. New to the Second Edition Three completely revised chapters that incorporate ExtendSim 8 An introduction to simulation A chapter on business process analytics Developed from the authors’ many years of teaching process design and simulation courses, the text provides students with a thorough understanding of numerous analytical tools that can be used to model, analyze, design, manage, and improve business processes. It covers a wide range of approaches, including discrete event simulation, graphical flowcharting tools, deterministic models for cycle time analysis and capacity decisions, analytical queuing methods, and data mining. Unlike other operations management books, this one emphasizes user-friendly simulation software as well as business processes, rather than only manufacturing processes or general operations management problems. Taking an analytical modeling approach to process design, this book illustrates the power of simulation modeling as a vehicle for analyzing and designing business processes. It teaches how to apply process simulation and discusses the managerial implications of redesigning processes. The ExtendSim software is available online and ancillaries are available for instructors. |
| data analytics simulation strategic decision making solution: Smart Sustainable Cities of the Future Simon Elias Bibri, 2018-02-24 This book is intended to help explore the field of smart sustainable cities in its complexity, heterogeneity, and breadth, the many faces of a topical subject of major importance for the future that encompasses so much of modern urban life in an increasingly computerized and urbanized world. Indeed, sustainable urban development is currently at the center of debate in light of several ICT visions becoming achievable and deployable computing paradigms, and shaping the way cities will evolve in the future and thus tackle complex challenges. This book integrates computer science, data science, complexity science, sustainability science, system thinking, and urban planning and design. As such, it contains innovative computer–based and data–analytic research on smart sustainable cities as complex and dynamic systems. It provides applied theoretical contributions fostering a better understanding of such systems and the synergistic relationships between the underlying physical and informational landscapes. It offers contributions pertaining to the ongoing development of computer–based and data science technologies for the processing, analysis, management, modeling, and simulation of big and context data and the associated applicability to urban systems that will advance different aspects of sustainability. This book seeks to explicitly bring together the smart city and sustainable city endeavors, and to focus on big data analytics and context-aware computing specifically. In doing so, it amalgamates the design concepts and planning principles of sustainable urban forms with the novel applications of ICT of ubiquitous computing to primarily advance sustainability. Its strength lies in combining big data and context–aware technologies and their novel applications for the sheer purpose of harnessing and leveraging the disruptive and synergetic effects of ICT on forms of city planning that are required for future forms of sustainable development. This is because the effects of such technologies reinforce one another as to their efforts for transforming urban life in a sustainable way by integrating data–centric and context–aware solutions for enhancing urban systems and facilitating coordination among urban domains. This timely and comprehensive book is aimed at a wide audience across science, academia industry, and policymaking. It provides the necessary material to inform relevant research communities of the state–of–the–art research and the latest development in the area of smart sustainable urban development, as well as a valuable reference for planners, designers, strategists, and ICT experts who are working towards the development and implementation of smart sustainable cities based on big data analytics and context–aware computing. |
| data analytics simulation strategic decision making solution: Data Analytics Applied to the Mining Industry Ali Soofastaei, 2020-11-12 Data Analytics Applied to the Mining Industry describes the key challenges facing the mining sector as it transforms into a digital industry able to fully exploit process automation, remote operation centers, autonomous equipment and the opportunities offered by the industrial internet of things. It provides guidelines on how data needs to be collected, stored and managed to enable the different advanced data analytics methods to be applied effectively in practice, through use of case studies, and worked examples. Aimed at graduate students, researchers, and professionals in the industry of mining engineering, this book: Explains how to implement advanced data analytics through case studies and examples in mining engineering Provides approaches and methods to improve data-driven decision making Explains a concise overview of the state of the art for Mining Executives and Managers Highlights and describes critical opportunity areas for mining optimization Brings experience and learning in digital transformation from adjacent sectors |
| data analytics simulation strategic decision making solution: Responsible Business Annemieke Roobeek, Jacques de Swart, Myrthe van der Plas, 2018-06-03 Until recently, profit has been the driving force for most business decisions. However, business leaders must now look more widely at their actions to assess the impact of these on people both inside and outside the organization as well as the environment. Responsible Business provides a seven step framework that eliminates internal bias and can be used to make decisions that increase profits, benefit staff and protect the environment as a whole. This means that personal values, ethics and morals can be aligned with business goals and overall company strategy. Responsible Business will enable business leaders to answer questions including: What values should be attached to financial and non-financial aspects of business decisions? How can these values be translated into concrete manageable actions? Which decisions best suit the strategic goals of the organization? Readers will have access to the business simulator tool which removes the complexity, ambiguity and stress of business decisions to allow leaders to manage the competing priorities in their organization and confidently make the best investment decisions for their business. With diverse case studies from organizations who have benefited from this approach, this book is essential reading for everyone needing to evaluate their investment decisions. |
| data analytics simulation strategic decision making solution: Build Like It's the End of the World Sandeep Ahuja, Patrick Chopson, 2024-09-18 Authoritative roadmap to the design and construction of a carbon-positive built environment Build Like It’s the End of the World stands as a compelling manifesto for the AEC industry, confronting the urgent challenges of climate change with actionable solutions. Authored by Sandeep Ahuja and Patrick Chopson, this text embarks on a journey to redefine the future of our built environment. Through a lens of decarbonization, it challenges established norms and introduces a new benchmark for sustainable design and construction. This book not only advocates for a radical shift in design and construction philosophy but also provides a concrete blueprint for achieving carbon-positivity in our projects and practices. The authors bring their extensive experience and research to the forefront, offering a guide that marries rigorous analytical methods with practical applications. It is a call to action, urging professionals and students alike to embrace innovative technologies and strategies that can lead to significant changes in how we conceive and construct our spaces. Within its pages, readers will find: A comprehensive strategy for carbon-positive design: a detailed blueprint showcases step-by-step how sustainable practices can be integrated into projects, drawing on the authors’ vast experience and thorough research. Engaging tools for practical implementation: bridging the gap between high-level sustainability goals and their execution, providing readers with learning objectives, instructional activities, and compelling case studies. Insights on embedding sustainable practices: it offers valuable perspectives on incorporating carbon-positive principles into existing workflows, highlighting the simplicity and profound impact of these efforts. The economic and cultural case for sustainable buildings: demonstrating the viability and necessity of carbon-positive buildings, emphasizing the importance of a cultural shift towards decarbonization in the construction industry. Build Like It’s the End of the World is an essential read for anyone in the AEC field looking to navigate the complexities of decarbonization of buildings. It serves as a powerful testament to the role of technology and strategic innovation in transforming the industry, guiding us towards a future where our buildings play a pivotal role in the health of our planet. |
| data analytics simulation strategic decision making solution: Strategic Engineering for Cloud Computing and Big Data Analytics Amin Hosseinian-Far, Muthu Ramachandran, Dilshad Sarwar, 2017-02-13 This book demonstrates the use of a wide range of strategic engineering concepts, theories and applied case studies to improve the safety, security and sustainability of complex and large-scale engineering and computer systems. It first details the concepts of system design, life cycle, impact assessment and security to show how these ideas can be brought to bear on the modeling, analysis and design of information systems with a focused view on cloud-computing systems and big data analytics. This informative book is a valuable resource for graduate students, researchers and industry-based practitioners working in engineering, information and business systems as well as strategy. |
| data analytics simulation strategic decision making solution: Engineering Analytics Luis Rabelo, Edgar Gutierrez-Franco, Alfonso Sarmiento, Christopher Mejía-Argueta, 2021-09-26 Engineering analytics is becoming a necessary skill for every engineer. Areas such as Operations Research, Simulation, and Machine Learning can be totally transformed through massive volumes of data. This book is intended to be an introduction to Engineering Analytics that can be used to improve performance tracking, customer segmentation for resource optimization, patterns and classification strategies, and logistics control towers. Basic methods in the areas of visual, descriptive, predictive, and prescriptive analytics and Big Data are introduced. Industrial case studies and example problem demonstrations are used throughout the book to reinforce the concepts and applications. The book goes on to cover visual analytics and its relationships, simulation from the respective dimensions and Machine Learning and Artificial Intelligence from different paradigms viewpoints. The book is intended for professionals wanting to work on analytical problems, for Engineering students, Researchers, Chief-Technology Officers, and Directors that work within the areas and fields of Industrial Engineering, Computer Science, Statistics, Electrical Engineering Operations Research, and Big Data. |
| data analytics simulation strategic decision making solution: Spatial Intelligence for a Greener Planet Kuldeep Chaurasia, Pradeep Kumar Garg, Arun P V, Yingewi Yan, 2024-12-26 With rapid advancements in AI, this book reveals how AI can be a powerful tool in reducing pollution and fostering sustainability. It highlights the integration of geospatial techniques with AI for enhancing capabilities in mapping, analysis, and mitigation of environmental pollution. Starting with foundational concepts in AI, geospatial technology, and pollution, the book addresses air, water, soil and thermal pollution, emphasizing their harmful impacts. Through real-world case studies and advanced research, it showcases AI and geospatial technology's revolutionary role in pollution mitigation, exploring AI-driven sensors, satellite imagery, and associated networks for precise and efficient pollution monitoring and management. |
| data analytics simulation strategic decision making solution: Research Anthology on Big Data Analytics, Architectures, and Applications Management Association, Information Resources, 2021-09-24 Society is now completely driven by data with many industries relying on data to conduct business or basic functions within the organization. With the efficiencies that big data bring to all institutions, data is continuously being collected and analyzed. However, data sets may be too complex for traditional data-processing, and therefore, different strategies must evolve to solve the issue. The field of big data works as a valuable tool for many different industries. The Research Anthology on Big Data Analytics, Architectures, and Applications is a complete reference source on big data analytics that offers the latest, innovative architectures and frameworks and explores a variety of applications within various industries. Offering an international perspective, the applications discussed within this anthology feature global representation. Covering topics such as advertising curricula, driven supply chain, and smart cities, this research anthology is ideal for data scientists, data analysts, computer engineers, software engineers, technologists, government officials, managers, CEOs, professors, graduate students, researchers, and academicians. |
| data analytics simulation strategic decision making solution: Business Modeling and Software Design Boris Shishkov, 2018-06-29 This book constitutes the proceedings of the 8th International Symposium on Business Modeling and Software Design, BMSD 2018, held in Vienna, Austria, in July 2018. The 14 full papers and 21 short papers selected for inclusion in this book deal with a large number of research topics: (i) Some topics concern Business Processes (BP), such as BP modeling / notations / visualizations, BP management, BP variability, BP contracting, BP interoperability, BP modeling within augmented reality, inter-enterprise collaborations, and so on; (ii) Other topics concern Software Design, such as software ecosystems, specification of context-aware software systems, service-oriented solutions and micro-service architectures, product variability, software development monitoring, and so on; (iii) Still other topics are crosscutting with regard to business modeling and software design, such as data analytics as well as information security and privacy; (iv) Other topics concern hot technology / innovation areas, such as blockchain technology and internet-of-things. Underlying with regard to all those topics is the BMSD’18 theme: Enterprise Engineering and Software Engineering - Processes and Systems for the Future. |
| data analytics simulation strategic decision making solution: Handbook of Research on Strategic Performance Management and Measurement Using Data Envelopment Analysis Osman, Ibrahim H., 2013-08-31 Organizations can use the valuable tool of data envelopment analysis (DEA) to make informed decisions on developing successful strategies, setting specific goals, and identifying underperforming activities to improve the output or outcome of performance measurement. The Handbook of Research on Strategic Performance Management and Measurement Using Data Envelopment Analysis highlights the advantages of using DEA as a tool to improve business performance and identify sources of inefficiency in public and private organizations. These recently developed theories and applications of DEA will be useful for policymakers, managers, and practitioners in the areas of sustainable development of our society including environment, agriculture, finance, and higher education sectors. |
| data analytics simulation strategic decision making solution: Innovative Technology at the Interface of Finance and Operations Volodymyr Babich, John R. Birge, Gilles Hilary, 2022-06-09 This book examines the challenges and opportunities arising from an assortment of technologies as they relate to Operations Management and Finance. It contains primers on operations, finance, and their interface. Innovative technologies and new business models enabled by those technologies are changing the practice and the theory of Operations Management and Finance, as well as their interface. These technologies and business models include Big Data and Analytics, Artificial Intelligence, Machine Learning, Blockchain, IoT, 3D printing, sharing platforms, crowdfunding, and crowdsourcing. The book will be an attractive choice for PhD-level courses and for self-study. |
| data analytics simulation strategic decision making solution: Big Data Analytics Strategies for the Smart Grid Carol L. Stimmel, 2014-07-25 By implementing a comprehensive data analytics program, utility companies can meet the continually evolving challenges of modern grids that are operationally efficient, while reconciling the demands of greenhouse gas legislation and establishing a meaningful return on investment from smart grid deployments. Readable and accessible, Big Data Analytics Strategies for the Smart Grid addresses the needs of applying big data technologies and approaches, including Big Data cybersecurity, to the critical infrastructure that makes up the electrical utility grid. It supplies industry stakeholders with an in-depth understanding of the engineering, business, and customer domains within the power delivery market. The book explores the unique needs of electrical utility grids, including operational technology, IT, storage, processing, and how to transform grid assets for the benefit of both the utility business and energy consumers. It not only provides specific examples that illustrate how analytics work and how they are best applied, but also describes how to avoid potential problems and pitfalls. Discussing security and data privacy, it explores the role of the utility in protecting their customers’ right to privacy while still engaging in forward-looking business practices. The book includes discussions of: SAS for asset management tools The AutoGrid approach to commercial analytics Space-Time Insight’s work at the California ISO (CAISO) This book is an ideal resource for mid- to upper-level utility executives who need to understand the business value of smart grid data analytics. It explains critical concepts in a manner that will better position executives to make the right decisions about building their analytics programs. At the same time, the book provides sufficient technical depth that it is useful for data analytics professionals who need to better understand the nuances of the engineering and business challenges unique to the utilities industry. |
| data analytics simulation strategic decision making solution: Strategic Risk, Intelligence And Digital Transformation Eduardo Rodriguez, 2024-03-19 In this book, the study of strategic risk is not only for its control and mitigation using analytics and digital transformation in organizations, but also it is about the strategic risks that digital transformation can bring to organizations. Strategic risk control is one of the goals in creating intelligent organizations and at the same time it is part of the appetite for creating smarter organizations to support organizations' development. Knowledge that is created by data analytics and the capacity to operationalize that knowledge through digital transformation can produce potential sustainable competitive advantages.The core of the volume is connecting data analytics and artificial intelligence, risk management and digitalization to create strategic intelligence as the capacity of adaptation that organizations need to compete and to succeed. Strategic intelligence is a symbiotic work of artificial intelligence, business intelligence and competitive intelligence. Strategic risk is represented by the probability of having variations in the performance results of the organizations that can limit their capacity to maintain sustainable competitive advantages. There is an emphasis in the book about the conversion of models that support data analytics into actions to mitigate strategic risk based on digital transformation.This book reviews the steps that organizations have taken in using technology that connects the data analytics modeling process and digital operations, such as the shift from the use of statistical learning and machine learning for data analytics to the improvement and use of new technologies. The digitalization process is a potential opportunity for organizations however the results are not necessarily good for everyone. Hence, organizations implement strategic risk control in cloud computing, blockchain, artificial intelligence and create digital networks that are connected internally and externally to deal with internal and external customers, with suppliers and buyers, and with competitors and substitutes. The new risks appear once new knowledge emerges and is in use, but at the same time the new knowledge supports the initiatives to deal with risks arising from novel ways of competing and collaborating. |
| data analytics simulation strategic decision making solution: The Analytics Process Eduardo Rodriguez, 2017-02-17 This book is about the process of using analytics and the capabilities of analytics in today’s organizations. Cutting through the buzz surrounding the term analytics and the overloaded expectations about using analytics, the book demystifies analytics with an in-depth examination of concepts grounded in operations research and management science. Analytics as a set of tools and processes is only as effective as: The data with which it is working The human judgment applying the processes and understanding the output of these processes. For this reason, the book focuses on the analytics process. What is intrinsic to analytics’ real organizational impact are the careful application of tools and the thoughtful application of their outcomes. This work emphasizes analytics as part of a process that supports decision-making within organizations. It wants to debunk overblown expectations that somehow analytics outputs or analytics as applied to other concepts, such as Big Data, are the be-all and end-all of the analytics process. They are, instead, only a step within a holistic and critical approach to management thinking that can create real value for an organization. To develop this holistic approach, the book is divided into two sections that examine concepts and applications. The first section makes the case for executive management taking a holistic approach to analytics. It draws on rich research in operations and management science that form the context in which analytics tools are to be applied. There is a strong emphasis on knowledge management concepts and techniques, as well as risk management concepts and techniques. The second section focuses on both the use of the analytics process and organizational issues that are required to make the analytics process relevant and impactful. |
| data analytics simulation strategic decision making solution: AI and Data Analytics Applications in Organizational Management Merlo, Tereza Raquel, 2024-02-07 Within information sciences and organizational management, a pressing challenge emerges; How can we harness the transformative power of artificial intelligence (AI) and data analytics? As industries grapple with a deluge of data and the imperative to make informed decisions swiftly, the gap between data collection and actionable insights widens. Professionals in various sectors are in a race to unlock AI's full potential to drive operational efficiency, enhance decision-making, and gain a competitive edge. However, navigating this intricate terrain, laden with ethical considerations and interdisciplinary complexity, has proven to be a formidable undertaking. AI and Data Analytics Applications in Organizational Management, combines rigorous scholarship with practicality. It traverses the spectrum from theoretical foundations to real-world applications, making it indispensable for those seeking to implement AI-driven data analytics in their organizations. Moreover, it delves into the ethical and societal dimensions of this revolution, ensuring that the journey toward innovation is paved with responsible considerations. For researchers, scholars, and practitioners yearning to unleash the potential of AI in organizational management, this book is the key to not only understanding the landscape but also charting a course toward transformative change. |
| data analytics simulation strategic decision making solution: Advancements in Intelligent Process Automation Thangam, Dhanabalan, 2024-10-01 In the current fast-paced business environment, organizations face the challenge of improving operational efficiency and driving innovation while dealing with complex technological landscapes. Many organizations require assistance exploiting intelligent process automation's full potential (IPA). This is often due to a need for more comprehensive understanding or clear implementation strategies. As a result, they need to help their workflows, optimize resources, and adapt effectively to changing market demands. Advancements in Intelligent Process Automation bridges this gap by providing a holistic view of IPA, encompassing RPA, AI, and ML, among other key technologies. Through real-world case studies, strategic guidelines, and interdisciplinary perspectives, the book offers actionable insights that are not just theoretical, but practical and implementable. This ensures that organizations seeking to implement IPA can do so seamlessly, without feeling overwhelmed or unsure. Addressing ethical and regulatory considerations ensures responsible AI practices and compliance, fostering a sustainable approach to automation. |
| data analytics simulation strategic decision making solution: Navigating Unpredictability: Collaborative Networks in Non-linear Worlds Luis M. Camarinha-Matos, |
| data analytics simulation strategic decision making solution: Hands-On Prescriptive Analytics Walter R. Paczkowski, 2024-10-17 Business decisions in any context—operational, tactical, or strategic—can have considerable consequences. Whether the outcome is positive and rewarding or negative and damaging to the business, its employees, and stakeholders is unknown when action is approved. These decisions are usually made under the proverbial cloud of uncertainty. With this practical guide, data analysts, data scientists, and business analysts will learn why and how maximizing positive consequences and minimizing negative ones requires three forms of rich information: Descriptive analytics explores the results from an action—what has already happened. Predictive analytics focuses on what could happen. The third, prescriptive analytics, informs us what should happen in the future. While all three are important for decision-makers, the primary focus of this book is on the third: prescriptive analytics. Author Walter R. Paczkowski, Ph.D. shows you: The distinction among descriptive, predictive, and prescriptive analytics How predictive analytics produces a menu of action options How prescriptive analytics narrows the menu of action options The forms of prescriptive analytics: eight prescriptive methods Two broad classes of these methods: non-stochastic and stochastic How to develop prescriptive analyses for action recommendations Ways to use an appropriate tool-set in Python |
| data analytics simulation strategic decision making solution: Creating Value with Big Data Analytics Peter C. Verhoef, Edwin Kooge, Natasha Walk, 2016-01-08 Our newly digital world is generating an almost unimaginable amount of data about all of us. Such a vast amount of data is useless without plans and strategies that are designed to cope with its size and complexity, and which enable organisations to leverage the information to create value. This book is a refreshingly practical, yet theoretically sound roadmap to leveraging big data and analytics. Creating Value with Big Data Analytics provides a nuanced view of big data development, arguing that big data in itself is not a revolution but an evolution of the increasing availability of data that has been observed in recent times. Building on the authors’ extensive academic and practical knowledge, this book aims to provide managers and analysts with strategic directions and practical analytical solutions on how to create value from existing and new big data. By tying data and analytics to specific goals and processes for implementation, this is a much-needed book that will be essential reading for students and specialists of data analytics, marketing research, and customer relationship management. |
| data analytics simulation strategic decision making solution: Marketing Strategy Robert W. Palmatier, Shrihari Sridhar, 2020-12-31 Marketing Strategy offers a unique and dynamic approach based on four underlying principles that underpin marketing today: All customers differ; All customers change; All competitors react; and All resources are limited. The structured framework of this acclaimed textbook allows marketers to develop effective and flexible strategies to deal with diverse marketing problems under varying circumstances. Uniquely integrating marketing analytics and data driven techniques with fundamental strategic pillars the book exemplifies a contemporary, evidence-based approach. This base toolkit will support students' decision-making processes and equip them for a world driven by big data. The second edition builds on the first's successful core foundation, with additional pedagogy and key updates. Research-based, action-oriented, and authored by world-leading experts, Marketing Strategy is the ideal resource for advanced undergraduate, MBA, and EMBA students of marketing, and executives looking to bring a more systematic approach to corporate marketing strategies. New to this Edition: - Revised and updated throughout to reflect new research and industry developments, including expanded coverage of digital marketing, influencer marketing and social media strategies - Enhanced pedagogy including new Worked Examples of Data Analytics Techniques and unsolved Analytics Driven Case Exercises, to offer students hands-on practice of data manipulation as well as classroom activities to stimulate peer-to-peer discussion - Expanded range of examples to cover over 250 diverse companies from 25 countries and most industry segments - Vibrant visual presentation with a new full colour design |
| data analytics simulation strategic decision making solution: Decision Management Systems James Taylor, 2011-10-13 A very rich book sprinkled with real-life examples as well as battle-tested advice.” —Pierre Haren, VP ILOG, IBM James does a thorough job of explaining Decision Management Systems as enablers of a formidable business transformation.” —Deepak Advani, Vice President, Business Analytics Products and SPSS, IBM Build Systems That Work Actively to Help You Maximize Growth and Profits Most companies rely on operational systems that are largely passive. But what if you could make your systems active participants in optimizing your business? What if your systems could act intelligently on their own? Learn, not just report? Empower users to take action instead of simply escalating their problems? Evolve without massive IT investments? Decision Management Systems can do all that and more. In this book, the field’s leading expert demonstrates how to use them to drive unprecedented levels of business value. James Taylor shows how to integrate operational and analytic technologies to create systems that are more agile, more analytic, and more adaptive. Through actual case studies, you’ll learn how to combine technologies such as predictive analytics, optimization, and business rules—improving customer service, reducing fraud, managing risk, increasing agility, and driving growth. Both a practical how-to guide and a framework for planning, Decision Management Systems focuses on mainstream business challenges. Coverage includes Understanding how Decision Management Systems can transform your business Planning your systems “with the decision in mind” Identifying, modeling, and prioritizing the decisions you need to optimize Designing and implementing robust decision services Monitoring your ongoing decision-making and learning how to improve it Proven enablers of effective Decision Management Systems: people, process, and technology Identifying and overcoming obstacles that can derail your Decision Management Systems initiative |
| data analytics simulation strategic decision making solution: Enterprise Risk Management Stefan Hunziker, 2019-05-17 This textbook demonstrates how Enterprise Risk Management creates value in strategic- and decision-making-processes. The author introduces modern approaches to balancing risk and reward based on many examples of medium-sized and large companies from different industries. Since traditional risk management in practice is often an independent stand-alone process with no impact on decision-making processes, it is unable to create value and ties up resources in the company unnecessarily. Herewith, he serves students as well as practitioners with modern approaches that promote a connection between ERM and corporate management. The author demonstrates in a didactically appropriate manner how companies can use ERM in a concrete way to achieve better risk-reward decisions under uncertainty. Furthermore, theoretical and psychological findings relevant to entrepreneurial decision-making situations are incorporated. This textbook has been recommended and developed for university courses in Germany, Austria and Switzerland. |
| data analytics simulation strategic decision making solution: Advances in Production Management Systems. Smart Manufacturing and Logistics Systems: Turning Ideas into Action Duck Young Kim, Gregor von Cieminski, David Romero, 2022-09-16 This two-volume set, IFIP AICT 663 and 664, constitutes the thoroughly refereed proceedings of the International IFIP WG 5.7 Conference on Advances in Production Management Systems, APMS 2022, held in Gyeongju, South Korea in September 2022. The 139 full papers presented in these volumes were carefully reviewed and selected from a total of 153 submissions. The papers of APMS 2022 are organized into two parts. The topics of special interest in the first part included: AI & Data-driven Production Management; Smart Manufacturing & Industry 4.0; Simulation & Model-driven Production Management; Service Systems Design, Engineering & Management; Industrial Digital Transformation; Sustainable Production Management; and Digital Supply Networks. The second part included the following subjects: Development of Circular Business Solutions and Product-Service Systems through Digital Twins; “Farm-to-Fork” Production Management in Food Supply Chains; Urban Mobility and City Logistics; Digital Transformation Approaches in Production Management; Smart Supply Chain and Production in Society 5.0 Era; Service and Operations Management in the Context of Digitally-enabled Product-Service Systems; Sustainable and Digital Servitization; Manufacturing Models and Practices for Eco-Efficient, Circular and Regenerative Industrial Systems; Cognitive and Autonomous AI in Manufacturing and Supply Chains; Operators 4.0 and Human-Technology Integration in Smart Manufacturing and Logistics Environments; Cyber-Physical Systems for Smart Assembly and Logistics in Automotive Industry; and Trends, Challenges and Applications of Digital Lean Paradigm. |
| data analytics simulation strategic decision making solution: CBAP / CCBA Certified Business Analysis Study Guide Susan Weese, Terri Wagner, 2017-01-04 The bestselling CBAP/CCBA study guide, updated for exam v3.0 The CBAP/CCBA Certified Business Analysis Study Guide, Second Edition offers 100% coverage of all exam objectives for the Certified Business Analysis Professional (CBAP) and Certification of Competency in Business Analysis (CCBA) exams offered by the International Institute of Business Analysis (IIBA). Detailed coverage encompasses all six knowledge areas defined by the Guide to Business Analysis Body of Knowledge (BABOK): Planning and Monitoring, Elicitation, Requirements Management and Communication, Enterprise Analysis, Requirements Analysis, and Solution Assessment and Validation, including expert guidance toward all underlying competencies. Real-world scenarios help you align your existing experience with the BABOK, and topic summaries, tips and tricks, practice questions, and objective-mapping give you a solid framework for success on the exam. You also gain access to the Sybex interactive learning environment, featuring review questions, electronic flashcards, and four practice exams to help you gauge your understanding and be fully prepared exam day. As more and more organizations seek to streamline production models, the demand for qualified Business Analysts is growing. This guide provides a personalized study program to help you take your place among those certified in essential business analysis skills. Review the BABOK standards and best practices Master the core Business Analysis competencies Test your preparedness with focused review questions Access CBAP and CCBA practice exams, study tools, and more As the liaison between the customer and the technical team, the Business Analyst is integral to ensuring that the solution satisfies the customer's needs. The BABOK standards codify best practices for this essential role, and the CBAP and CCBA certifications prove your ability to perform them effectively. The CBAP/CCBA Certified Business Analysis Study Guide, Second Edition provides thorough preparation customizable to your needs, to help you maximize your study time and ensure your success. |
| data analytics simulation strategic decision making solution: Evolutionary Multi-Criterion Optimization Kalyanmoy Deb, Erik Goodman, Carlos A. Coello Coello, Kathrin Klamroth, Kaisa Miettinen, Sanaz Mostaghim, Patrick Reed, 2019-02-28 This book constitutes the refereed proceedings of the 10th International Conference on Evolutionary Multi-Criterion Optimization, EMO 2019 held in East Lansing, MI, USA, in March 2019. The 59 revised full papers were carefully reviewed and selected from 76 submissions. The papers are divided into 8 categories, each representing a key area of current interest in the EMO field today. They include theoretical developments, algorithmic developments, issues in many-objective optimization, performance metrics, knowledge extraction and surrogate-based EMO, multi-objective combinatorial problem solving, MCDM and interactive EMO methods, and applications. |
| data analytics simulation strategic decision making solution: Research Anthology on Decision Support Systems and Decision Management in Healthcare, Business, and Engineering Management Association, Information Resources, 2021-05-28 Decision support systems (DSS) are widely touted for their effectiveness in aiding decision making, particularly across a wide and diverse range of industries including healthcare, business, and engineering applications. The concepts, principles, and theories of enhanced decision making are essential points of research as well as the exact methods, tools, and technologies being implemented in these industries. From both a standpoint of DSS interfaces, namely the design and development of these technologies, along with the implementations, including experiences and utilization of these tools, one can get a better sense of how exactly DSS has changed the face of decision making and management in multi-industry applications. Furthermore, the evaluation of the impact of these technologies is essential in moving forward in the future. The Research Anthology on Decision Support Systems and Decision Management in Healthcare, Business, and Engineering explores how decision support systems have been developed and implemented across diverse industries through perspectives on the technology, the utilizations of these tools, and from a decision management standpoint. The chapters will cover not only the interfaces, implementations, and functionality of these tools, but also the overall impacts they have had on the specific industries mentioned. This book also evaluates the effectiveness along with benefits and challenges of using DSS as well as the outlook for the future. This book is ideal for decision makers, IT consultants and specialists, software developers, design professionals, academicians, policymakers, researchers, professionals, and students interested in how DSS is being used in different industries. |
| data analytics simulation strategic decision making solution: Customer Centricity Peter Fader, 2012 Not all customers are created equal. Despite what the tired old adage says, the customer is not always right. Not all customers deserve your best efforts: in the world of customer centricity, there are good customers...and then there is pretty much everybody else. Upending some of our most fundamental beliefs, renowned behavioral data expert Peter Fader, Co-Director of The Wharton Customer Analytics Initiative, helps businesses radically rethink how they relate to customers. He provides insights to help you revamp your performance metrics, product development, customer relationship management and organization in order to make sure you focus directly on the needs of your most valuable customers and increase profits for the long term. |
| data analytics simulation strategic decision making solution: Smart Enough Systems James Taylor, Neil Raden, 2007-06-29 “Automated decisions systems are probably already being used in your industry, and they will undoubtedly grow in importance. If your business needs to make quick, accurate decisions on an industrialized scale, you need to read this book.” Thomas H. Davenport, Professor, Babson College, Author of Competing on Analytics The computer-based systems most organizations rely on to support their businesses are not very smart. Many of the business decisions these companies make tend to be hidden in systems that make poor decisions, or don’t make them at all. Further, most systems struggle to keep up with the pace of change. The answer is not to implement newer, “intelligent” systems. The fact is that much of today’s existing technology has the potential to be “smart enough” to make a big difference to an organization’s business. This book tells you how. Although the business context and underlying principles are explained in a nontechnical manner, the book also contains how-to guidance for more technical readers. The book’s companion site, www.smartenoughsystems.com, has additional information and references for practitioners as well as news and updates. Additional Praise for Smart (Enough) Systems “James Taylor and Neil Raden are on to something important in this book–the tremendous value of improving the large number of routine decisions that are made in organizations every day.” Dr. Hugh J. Watson, Chair of Business Administration, University of Georgia “This is a very important book. It lays out the agenda for business technology in the new century–nothing less than how to reorganize every aspect of how a company treats its customers.” David Raab, President, ClientXClient “This book is an important contribution to business productivity because it covers the opportunity from both the business executive’s and technologist’s perspective. This should be on every operational executive’s and every CIO’s list of essential reading.” John Parkinson, Former CTO, Capgemini, North American Region “This book shows how to use proven technology to make business processes smarter. It clearly makes the case that organizations need to optimize their operational decisions. It is a must-have reference for process professionals throughout your organization.” Jim Sinur, Chief Strategy Officer, Global 360, Inc. |
| data analytics simulation strategic decision making solution: Intersections in Simulation and Gaming: Disruption and Balance Anjum Naweed, Lorelle Bowditch, Cyle Sprick, 2019-08-26 This book constitutes the refereed proceedings of the Australasian Simulation Congress, ASC 2019, held in Gold Coast, Australia in September 2019. The 10 papers presented were carefully reviewed and selected from 17 submissions. They provide a forum for sharing progresses in the areas of human dimensions; gaming experience; design and application; search and rescue; defence-oriented technology and training. |
| data analytics simulation strategic decision making solution: Text Mining in Practice with R Ted Kwartler, 2017-07-24 A reliable, cost-effective approach to extracting priceless business information from all sources of text Excavating actionable business insights from data is a complex undertaking, and that complexity is magnified by an order of magnitude when the focus is on documents and other text information. This book takes a practical, hands-on approach to teaching you a reliable, cost-effective approach to mining the vast, untold riches buried within all forms of text using R. Author Ted Kwartler clearly describes all of the tools needed to perform text mining and shows you how to use them to identify practical business applications to get your creative text mining efforts started right away. With the help of numerous real-world examples and case studies from industries ranging from healthcare to entertainment to telecommunications, he demonstrates how to execute an array of text mining processes and functions, including sentiment scoring, topic modelling, predictive modelling, extracting clickbait from headlines, and more. You’ll learn how to: Identify actionable social media posts to improve customer service Use text mining in HR to identify candidate perceptions of an organisation, match job descriptions with resumes, and more Extract priceless information from virtually all digital and print sources, including the news media, social media sites, PDFs, and even JPEG and GIF image files Make text mining an integral component of marketing in order to identify brand evangelists, impact customer propensity modelling, and much more Most companies’ data mining efforts focus almost exclusively on numerical and categorical data, while text remains a largely untapped resource. Especially in a global marketplace where being first to identify and respond to customer needs and expectations imparts an unbeatable competitive advantage, text represents a source of immense potential value. Unfortunately, there is no reliable, cost-effective technology for extracting analytical insights from the huge and ever-growing volume of text available online and other digital sources, as well as from paper documents—until now. |
| data analytics simulation strategic decision making solution: Machine Learning for Sustainable Development Kamal Kant Hiran, Deepak Khazanchi, Ajay Kumar Vyas, Sanjeevikumar Padmanaban, 2021-07-19 The book will focus on the applications of machine learning for sustainable development. Machine learning (ML) is an emerging technique whose diffusion and adoption in various sectors (such as energy, agriculture, internet of things, infrastructure) will be of enormous benefit. The state of the art of machine learning models is most useful for forecasting and prediction of various sectors for sustainable development. |
| data analytics simulation strategic decision making solution: Data Strategy in Colleges and Universities Kristina Powers, 2019-10-16 This valuable resource helps institutional leaders understand and implement a data strategy at their college or university that maximizes benefits to all creators and users of data. Exploring key considerations necessary for coordination of fragmented resources and the development of an effective, cohesive data strategy, this book brings together professionals from different higher education experiences and perspectives, including academic, administration, institutional research, information technology, and student affairs. Focusing on critical elements of data strategy and governance, each chapter in Data Strategy in Colleges and Universities helps higher education leaders address a frustrating problem with much-needed solutions for fostering a collaborative, data-driven strategy. |
Data and Digital Outputs Management Plan (DDOMP)
Data and Digital Outputs Management Plan (DDOMP)
Building New Tools for Data Sharing and Reuse through a …
Jan 10, 2019 · The SEI CRA will closely link research thinking and technological innovation toward accelerating the …
Open Data Policy and Principles - Belmont Forum
The data policy includes the following principles: Data should be: Discoverable through catalogues …
Belmont Forum Adopts Open Data Principles for Environme…
Jan 27, 2016 · Adoption of the open data policy and principles is one of five recommendations in A Place to …
Belmont Forum Data Accessibility Statement an…
The DAS encourages researchers to plan for the longevity, reusability, and stability of the data attached to their …
Data and Digital Outputs Management Plan (DDOMP)
Data and Digital Outputs Management Plan (DDOMP)
Building New Tools for Data Sharing and Reuse through a …
Jan 10, 2019 · The SEI CRA will closely link research thinking and technological innovation toward accelerating the full path of discovery-driven data use and open science. This will …
Open Data Policy and Principles - Belmont Forum
The data policy includes the following principles: Data should be: Discoverable through catalogues and search engines; Accessible as open data by default, and made available with …
Belmont Forum Adopts Open Data Principles for Environmental …
Jan 27, 2016 · Adoption of the open data policy and principles is one of five recommendations in A Place to Stand: e-Infrastructures and Data Management for Global Change Research, …
Belmont Forum Data Accessibility Statement and Policy
The DAS encourages researchers to plan for the longevity, reusability, and stability of the data attached to their research publications and results. Access to data promotes reproducibility, …
Climate-Induced Migration in Africa and Beyond: Big Data and …
CLIMB will also leverage earth observation and social media data, and combine them with survey and official statistical data. This holistic approach will allow us to analyze migration process …
Advancing Resilience in Low Income Housing Using Climate …
Jun 4, 2020 · Environmental sustainability and public health considerations will be included. Machine Learning and Big Data Analytics will be used to identify optimal disaster resilient …
Belmont Forum
What is the Belmont Forum? The Belmont Forum is an international partnership that mobilizes funding of environmental change research and accelerates its delivery to remove critical …
Waterproofing Data: Engaging Stakeholders in Sustainable Flood …
Apr 26, 2018 · Waterproofing Data investigates the governance of water-related risks, with a focus on social and cultural aspects of data practices. Typically, data flows up from local levels …
Data Management Annex (Version 1.4) - Belmont Forum
A full Data Management Plan (DMP) for an awarded Belmont Forum CRA project is a living, actively updated document that describes the data management life cycle for the data to be …
