| change management data analytics: Big Change, Best Path Warren Parry, 2015-10-03 SHORTLISTED: CMI Management Book of the Year Awards 2017 - Management Futures Category Using ground-breaking modelling, Big Change, Best Path brings unique insights to the dynamics and process of organizational change, understanding success and failure, defining and describing the drivers and conditions of change, and the patterns and paths of organizational change. Author Warren Parry from Accenture Strategy shows that a whole new way of managing change is possible, from empirical benchmarking, predictive approaches that highlight the specific actions needed at any point of a change programme, and visualization for senior managers to show how each part of an organization is responding. The author also challenges many of the myths of change management and the dynamics of how organizations respond to change, clearly showing the common pitfalls and misunderstandings. Big Change, Best Path explains a new, more analytical way and process for driving successful change, and presents a ground-breaking vision for the future of how organizations can become more agile and resilient. |
| change management data analytics: Lead and Disrupt Charles A. O’Reilly III, Michael L. Tushman, 2016-03-30 In the past few years, a number of well-known firms have failed; think of Blockbuster, Kodak, or RadioShack. When we read about their demise, it often seems inevitable—a natural part of creative destruction. But closer examination reveals a disturbing truth: Companies large and small are shuttering more quickly than ever. What does it take to buck this trend? The simple answer is: ambidexterity. Firms must remain competitive in their core markets, while also winning in new domains. Innovation guru Clayton M. Christensen has been pessimistic about whether established companies can prevail in the face of disruption, but Charles A. O'Reilly III and Michael L. Tushman know they can! The authors explain how shrewd organizations have used an ambidextrous approach to solve their own innovator's dilemma. They contrast these luminaries with companies which—often trapped by their own successes—have been unable to adapt and grow. Drawing on a vast research program and over a decade of helping companies to innovate, the authors present a set of practices to guide firms as they adopt ambidexterity. Top-down and bottom-up leaders are key to this process—a fact too often overlooked in the heated debate about innovation. But not in this case. Readers will come away with a new understanding of how to improve their existing businesses through efficiency, control, and incremental change, while also seizing new markets where flexibility, autonomy, and experimentation rule the day. |
| change management data analytics: Self-Service Data Analytics and Governance for Managers Nathan E. Myers, Gregory Kogan, 2021-06-02 Project governance, investment governance, and risk governance precepts are woven together in Self-Service Data Analytics and Governance for Managers, equipping managers to structure the inevitable chaos that can result as end-users take matters into their own hands Motivated by the promise of control and efficiency benefits, the widespread adoption of data analytics tools has created a new fast-moving environment of digital transformation in the finance, accounting, and operations world, where entire functions spend their days processing in spreadsheets. With the decentralization of application development as users perform their own analysis on data sets and automate spreadsheet processing without the involvement of IT, governance must be revisited to maintain process control in the new environment. In this book, emergent technologies that have given rise to data analytics and which form the evolving backdrop for digital transformation are introduced and explained, and prominent data analytics tools and capabilities will be demonstrated based on real world scenarios. The authors will provide a much-needed process discovery methodology describing how to survey the processing landscape to identify opportunities to deploy these capabilities. Perhaps most importantly, the authors will digest the mature existing data governance, IT governance, and model governance frameworks, but demonstrate that they do not comprehensively cover the full suite of data analytics builds, leaving a considerable governance gap. This book is meant to fill the gap and provide the reader with a fit-for-purpose and actionable governance framework to protect the value created by analytics deployment at scale. Project governance, investment governance, and risk governance precepts will be woven together to equip managers to structure the inevitable chaos that can result as end-users take matters into their own hands. |
| change management data analytics: Change Management Study Guide , Welcome to the forefront of knowledge with Cybellium, your trusted partner in mastering the cutting-edge fields of IT, Artificial Intelligence, Cyber Security, Business, Economics and Science. Designed for professionals, students, and enthusiasts alike, our comprehensive books empower you to stay ahead in a rapidly evolving digital world. * Expert Insights: Our books provide deep, actionable insights that bridge the gap between theory and practical application. * Up-to-Date Content: Stay current with the latest advancements, trends, and best practices in IT, Al, Cybersecurity, Business, Economics and Science. Each guide is regularly updated to reflect the newest developments and challenges. * Comprehensive Coverage: Whether you're a beginner or an advanced learner, Cybellium books cover a wide range of topics, from foundational principles to specialized knowledge, tailored to your level of expertise. Become part of a global network of learners and professionals who trust Cybellium to guide their educational journey. www.cybellium.com |
| change management data analytics: 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. |
| change management data analytics: Big Data and Analytics Vincenzo Morabito, 2015-01-31 This book presents and discusses the main strategic and organizational challenges posed by Big Data and analytics in a manner relevant to both practitioners and scholars. The first part of the book analyzes strategic issues relating to the growing relevance of Big Data and analytics for competitive advantage, which is also attributable to empowerment of activities such as consumer profiling, market segmentation, and development of new products or services. Detailed consideration is also given to the strategic impact of Big Data and analytics on innovation in domains such as government and education and to Big Data-driven business models. The second part of the book addresses the impact of Big Data and analytics on management and organizations, focusing on challenges for governance, evaluation, and change management, while the concluding part reviews real examples of Big Data and analytics innovation at the global level. The text is supported by informative illustrations and case studies, so that practitioners can use the book as a toolbox to improve understanding and exploit business opportunities related to Big Data and analytics. |
| change management data analytics: Change Management Strategies for Leading Successful Transitions Sam Morgan, 2024-11-12 Navigate the complexities of change with Change Management Strategies for Leading Successful Transitions. This practical guide offers valuable insights into effective change management techniques that help organizations adapt and thrive. Discover strategies for leading change, engaging employees, and overcoming resistance to change. With a focus on practical application and project management, this book equips you with the tools needed to manage transitions successfully and foster a culture of continuous improvement. |
| change management data analytics: ADKAR Jeff Hiatt, 2006 In his first complete text on the ADKAR model, Jeff Hiatt explains the origin of the model and explores what drives each building block of ADKAR. Learn how to build awareness, create desire, develop knowledge, foster ability and reinforce changes in your organization. The ADKAR Model is changing how we think about managing the people side of change, and provides a powerful foundation to help you succeed at change. |
| change management data analytics: 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. |
| change management data analytics: Internet of Things in Business Transformation Parul Gandhi, Surbhi Bhatia, Abhishek Kumar, Mohammad Ali Alojail, Pramod Singh Rathore, 2021-02-03 The objective of this book is to teach what IoT is, how it works, and how it can be successfully utilized in business. This book helps to develop and implement a powerful IoT strategy for business transformation as well as project execution. Digital change, business creation/change and upgrades in the ways and manners in which we work, live, and engage with our clients and customers, are all enveloped by the Internet of Things which is now named Industry 5.0 or Industrial Internet of Things. The sheer number of IoT(a billion+), demonstrates the advent of an advanced business society led by sustainable robotics and business intelligence. This book will be an indispensable asset in helping businesses to understand the new technology and thrive. |
| change management data analytics: Delivering Data Analytics Nicholas Kelly, 2021-12-03 The importance of data analytics is well known, but how can you get end users to engage with analytics and business intelligence (BI) when adoption of new technology can be frustratingly slow or may not happen at all? Avoid wasting time on dashboards and reports that no one uses with this practical guide to increasing analytics adoption by focusing on people and process, not technology. Pulling together agile, UX and change management principles, Delivering Data Analytics outlines a step-by-step, technology agnostic process designed to shift the organizational data culture and gain buy-in from users and stakeholders at every stage of the project. This book outlines how to succeed and build trust with stakeholders amid the politics, ambiguity and lack of engagement in business. With case studies, templates, checklists and scripts based on the author's considerable experience in analytics and data visualisation, this book covers the full cycle from requirements gathering and data assessment to training and launch. Ensure lasting adoption, trust and, most importantly, actionable business value with this roadmap to creating user-centric analytics projects. |
| change management data analytics: Understanding the Theory of Change Management Frameworks for Effective Organizational Transformation Sam Morgan, 2024-11-14 Explore the fundamentals of effective change with Understanding the Theory of Change Management Frameworks for Effective Organizational Transformation. This comprehensive guide delves into the theory of change management, providing frameworks and models that facilitate successful organizational transformation. Learn about strategic planning, the role of leadership, and effective implementation strategies that drive change. This book is essential for anyone looking to enhance their understanding of change processes and foster a culture of adaptability within their organization. |
| change management data analytics: Data Analytics and Artificial Intelligence for Predictive Maintenance in Smart Manufacturing Amit Kumar Tyagi, Shrikant Tiwari, Gulshan Soni, 2024-10-23 Today, in this smart era, data analytics and artificial intelligence (AI) play an important role in predictive maintenance (PdM) within the manufacturing industry. This innovative approach aims to optimize maintenance strategies by predicting when equipment or machinery is likely to fail so that maintenance can be performed just in time to prevent costly breakdowns. This book contains up-to-date information on predictive maintenance and the latest advancements, trends, and tools required to reduce costs and save time for manufacturers and industries. Data Analytics and Artificial Intelligence for Predictive Maintenance in Smart Manufacturing provides an extensive and in-depth exploration of the intersection of data analytics, artificial intelligence, and predictive maintenance in the manufacturing industry and covers fundamental concepts, advanced techniques, case studies, and practical applications. Using a multidisciplinary approach, this book recognizes that predictive maintenance in manufacturing requires collaboration among engineers, data scientists, and business professionals and includes case studies from various manufacturing sectors showcasing successful applications of predictive maintenance. The real-world examples explain the useful benefits and ROI achieved by organizations. The emphasis is on scalability, making it suitable for both small and large manufacturing operations, and readers will learn how to adapt predictive maintenance strategies to different scales and industries. This book presents resources and references to keep readers updated on the latest advancements, tools, and trends, ensuring continuous learning. Serving as a reference guide, this book focuses on the latest advancements, trends, and tools relevant to predictive maintenance and can also serve as an educational resource for students studying manufacturing, data science, or related fields. |
| change management data analytics: Management Decision-Making, Big Data and Analytics Simone Gressel, David J. Pauleen, Nazim Taskin, 2020-10-12 Accessible and concise, this exciting new textbook examines data analytics from a managerial and organizational perspective and looks at how they can help managers become more effective decision-makers. The book successfully combines theory with practical application, featuring case studies, examples and a ‘critical incidents’ feature that make these topics engaging and relevant for students of business and management. The book features chapters on cutting-edge topics, including: • Big data • Analytics • Managing emerging technologies and decision-making • Managing the ethics, security, privacy and legal aspects of data-driven decision-making The book is accompanied by an Instructor’s Manual, PowerPoint slides and access to journal articles. Suitable for management students studying business analytics and decision-making at undergraduate, postgraduate and MBA levels. |
| change management data analytics: Business Intelligence Strategy and Big Data Analytics Steve Williams, 2016-04-08 Business Intelligence Strategy and Big Data Analytics is written for business leaders, managers, and analysts - people who are involved with advancing the use of BI at their companies or who need to better understand what BI is and how it can be used to improve profitability. It is written from a general management perspective, and it draws on observations at 12 companies whose annual revenues range between $500 million and $20 billion. Over the past 15 years, my company has formulated vendor-neutral business-focused BI strategies and program execution plans in collaboration with manufacturers, distributors, retailers, logistics companies, insurers, investment companies, credit unions, and utilities, among others. It is through these experiences that we have validated business-driven BI strategy formulation methods and identified common enterprise BI program execution challenges. In recent years, terms like big data and big data analytics have been introduced into the business and technical lexicon. Upon close examination, the newer terminology is about the same thing that BI has always been about: analyzing the vast amounts of data that companies generate and/or purchase in the course of business as a means of improving profitability and competitiveness. Accordingly, we will use the terms BI and business intelligence throughout the book, and we will discuss the newer concepts like big data as appropriate. More broadly, the goal of this book is to share methods and observations that will help companies achieve BI success and thereby increase revenues, reduce costs, or both. - Provides ideas for improving the business performance of one's company or business functions - Emphasizes proven, practical, step-by-step methods that readers can readily apply in their companies - Includes exercises and case studies with road-tested advice about formulating BI strategies and program plans |
| change management data analytics: Data Driven Jenny Dearborn, 2015-02-02 A how-to guide to boosting sales through predictive and prescriptive analytics Data Driven is a uniquely practical guide to increasing sales success, using the power of data analytics. Written by one of the world's leading authorities on the topic, this book shows you how to transform the corporate sales function by leveraging big data into better decision-making, more informed strategy, and increased effectiveness throughout the organization. Engaging and informative, this book tells the story of a newly hired sales chief under intense pressure to deliver higher performance from her team, and how data analytics becomes the ultimate driver behind the sales function turnaround. Each chapter features insightful commentary and practical notes on the points the story raises, and one entire chapter is devoted solely to laying out the Prescriptive Action Model step-by-step giving you the actionable guidance you need to put it into action in your own organization. Predictive and prescriptive analytics is poised to change corporate sales, and companies that fail to adapt to the new realities and adopt the new practices will be left behind. This book explains why the Prescriptive Action Model is the key corporate sales weapon of the 21st Century, and how you can implement this dynamic new resource to bring value to your business. Exploit one of the last remaining sources of competitive advantage Re-engineer the sales function to optimize success rates Implement a more effective analytics model to drive efficient change Boost operational effectiveness and decision making with big data There are fewer competitive edges to gain than ever before. The only thing that's left is to execute business with maximum efficiency and make the smartest business decisions possible. Predictive analytics is the essential method behind this new standard, and Data Driven is the practical guide to complete, efficient implementation. |
| change management data analytics: Data Analytics in Project Management Seweryn Spalek, 2018-10-25 This book aims to help the reader better understand the importance of data analysis in project management. Moreover, it provides guidance by showing tools, methods, techniques and lessons learned on how to better utilize the data gathered from the projects. First and foremost, insight into the bridge between data analytics and project management aids practitioners looking for ways to maximize the practical value of data procured. The book equips organizations with the know-how necessary to adapt to a changing workplace dynamic through key lessons learned from past ventures. The book’s integrated approach to investigating both fields enhances the value of research findings. |
| change management data analytics: Statistical Process Control and Data Analytics John Oakland, Robert Oakland, 2024-09-02 The business, commercial and public-sector world has changed dramatically since John Oakland wrote the first edition of Statistical Process Control in the mid-1980s. Then, people were rediscovering statistical methods of ‘quality control,’ and the book responded to an often desperate need to find out about the techniques and use them on data. Pressure over time from organizations supplying directly to the consumer, typically in the automotive and high technology sectors, forced those in charge of the supplying, production and service operations to think more about preventing problems than how to find and fix them. Subsequent editions retained the ‘tool kit’ approach of the first but included some of the ‘philosophy’ behind the techniques and their use. Now entitled Statistical Process Control and Data Analytics, this revised and updated eighth edition retains its focus on processes that require understanding, have variation, must be properly controlled, have a capability and need improvement – as reflected in the five sections of the book. In this book the authors provide not only an instructional guide for the tools but communicate the management practices which have become so vital to success in organizations throughout the world. The book is supported by the authors' extensive consulting work with thousands of organizations worldwide. A new chapter on data governance and data analytics reflects the increasing importance of big data in today’s business environment. Fully updated to include real-life case studies, new research based on client work from an array of industries and integration with the latest computer methods and software, the book also retains its valued textbook quality through clear learning objectives and online end-of-chapter discussion questions. It can still serve as a textbook for both student and practicing engineers, scientists, technologists, managers and anyone wishing to understand or implement modern statistical process control techniques and data analytics. |
| change management data analytics: 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 |
| change management data analytics: Data Analytics Initiatives Ondřej Bothe, Ondřej Kubera, David Bednář, Martin Potančok, Ota Novotný, 2022-04-20 The categorisation of analytical projects could help to simplify complexity reasonably and, at the same time, clarify the critical aspects of analytical initiatives. But how can this complex work be categorized? What makes it so complex? Data Analytics Initiatives: Managing Analytics for Success emphasizes that each analytics project is different. At the same time, analytics projects have many common aspects, and these features make them unique compared to other projects. Describing these commonalities helps to develop a conceptual understanding of analytical work. However, features specific to each initiative affects the entire analytics project lifecycle. Neglecting them by trying to use general approaches without tailoring them to each project can lead to failure. In addition to examining typical characteristics of the analytics project and how to categorise them, the book looks at specific types of projects, provides a high-level assessment of their characteristics from a risk perspective, and comments on the most common problems or challenges. The book also presents examples of questions that could be asked of relevant people to analyse an analytics project. These questions help to position properly the project and to find commonalities and general project challenges. |
| change management data analytics: The Data Driven Leader Jenny Dearborn, David Swanson, 2017-10-06 Data is your most valuable leadership asset—here's how to use it The Data Driven Leader presents a clear, accessible guide to solving important leadership challenges through human resources-focused and other data analytics. This engaging book shows you how to transform the HR function and overall organizational effectiveness by using data to make decisions grounded in facts vs. opinions, identify root causes behind your company’s thorniest problems and move toward a winning, future-focused business strategy. Realistic and actionable, this book tells the story of a successful sales executive who, after leading an analytics-driven turnaround (in Data Driven, this book’s predecessor), faces a new turnaround challenge as chief human resources officer. Each chapter features insightful commentary and practical notes on the points the story raises, guiding you to put HR analytics into action in your organization. HR and other leaders cannot afford to overlook the power and competitive advantages of data-driven decision-making and strategies. This book reflects the growing trend of CEOs choosing analytics-minded business leaders to head HR, at a time when workplaces everywhere face game-changing forces including automation, robotics and artificial intelligence. It is urgent that human resources leaders embrace analytics, not only to remain professionally relevant but also to help their organizations successfully navigate this digital transformation. HR professionals can and must: Understand essential data science principles and corporate analytics models Identify and execute effective data analytics initiatives Boost HR and company productivity and performance with metrics that matter Shape an analytics-centric culture that generates data driven leaders Most organizations capture and report data, but data is useless without analysis that leads to action. The Data Driven Leader shows you how to use this tremendous asset to lead your organization higher. |
| change management data analytics: Handbook of Research on Organizational Transformations through Big Data Analytics Tavana, Madjid, 2014-11-30 Big data analytics utilizes a wide range of software and analytical tools to provide immediate, relevant information for efficient decision-making. Companies are recognizing the immense potential of BDA, but ensuring the data is appropriate and error-free is the largest hurdle in implementing BDA applications. The Handbook of Research on Organizational Transformations through Big Data Analytics not only catalogues the existing platforms and technologies, it explores new trends within the field of big data analytics (BDA). Containing new and existing research materials and insights on the various approaches to BDA; this publication is intended for researchers, IT professionals, and CIOs interested in the best ways to implement BDA applications and technologies. |
| change management data analytics: Shaping the Digital Enterprise Gerhard Oswald, Michael Kleinemeier, 2016-09-26 This book sheds light on cross-industry and industry-specific trends in today’s digital economy. Prepared by a group of international researchers, experts and practitioners under the auspices of SAP’s Digital Thought Leadership & Enablement team within SAP’s Business Transformation Services (BTS) unit, the book furthermore presents relevant use cases in digital transformation and innovation. The book argues that breakthrough technologies have matured and hit scale together, enabling five defining trends: hyper-connectivity, supercomputing, cloud computing, a smarter world, and cyber security. It presents in detail how companies are now reimagining their products and services, business models and processes, showcasing how every business today is a digital business. Digitalization, defined as the process of moving to a digital business, is no longer a choice but an imperative for all businesses across all industries and regions. Taking a step toward becoming a digital enterprise is demanding and challenging. The dimensions of customer centricity, leadership and strategy, business models, including offerings (products and services), processes, structure and governance, people and skills, culture, and technology foundation can serve as orientation for digitalization. The articles in this book touch on all dimensions of this digital innovation and transformation framework and offer possible answers to some of the pressing questions that arise when practitioners seek to digitalize their business. |
| change management data analytics: Human Resource Management in the Modern Workplace Dr. Chirag R. Patel, 2022-11-06 Explore modern practices in human resource management with this comprehensive guide. Covering topics from recruitment to employee development, this book provides the tools and knowledge needed for effective HR management in today's dynamic workplace. |
| change management data analytics: Data Science Strategy For Dummies Ulrika Jägare, 2019-06-10 All the answers to your data science questions Over half of all businesses are using data science to generate insights and value from big data. How are they doing it? Data Science Strategy For Dummies answers all your questions about how to build a data science capability from scratch, starting with the “what” and the “why” of data science and covering what it takes to lead and nurture a top-notch team of data scientists. With this book, you’ll learn how to incorporate data science as a strategic function into any business, large or small. Find solutions to your real-life challenges as you uncover the stories and value hidden within data. Learn exactly what data science is and why it’s important Adopt a data-driven mindset as the foundation to success Understand the processes and common roadblocks behind data science Keep your data science program focused on generating business value Nurture a top-quality data science team In non-technical language, Data Science Strategy For Dummies outlines new perspectives and strategies to effectively lead analytics and data science functions to create real value. |
| change management data analytics: Data Analytics and Digital Transformation Erik Beulen, Marla A. Dans, 2023-12-01 Understanding the significance of data analytics is paramount for digital transformation but in many organizations they are separate units without fully aligned goals. As organizations are applying digital transformations to be adaptive and agile in a competitive environment, data analytics can play a critical role in their success. This book explores the crossroads between them and how to leverage their connection for improved business outcomes. The need to collaborate and share data is becoming an integral part of digital transformation. This not only creates new opportunities but also requires well-considered and continuously assessed decision-making as competitiveness is at stake. This book details approaches, concepts, and frameworks, as well as actionable insights and good practices, including combined data management and agile concepts. Critical issues are discussed such as data quality and data governance, as well as compliance, privacy, and ethics. It also offers insights into how both private and public organizations can innovate and keep up with growing data volumes and increasing technological developments in the short, mid, and long term. This book will be of direct appeal to global researchers and students across a range of business disciplines, including technology and innovation management, organizational studies, and strategic management. It is also relevant for policy makers, regulators, and executives of private and public organizations looking to implement successful transformation policies. |
| change management data analytics: Performance Dashboards Wayne W. Eckerson, 2005-10-27 Tips, techniques, and trends on how to use dashboard technology to optimize business performance Business performance management is a hot new management discipline that delivers tremendous value when supported by information technology. Through case studies and industry research, this book shows how leading companies are using performance dashboards to execute strategy, optimize business processes, and improve performance. Wayne W. Eckerson (Hingham, MA) is the Director of Research for The Data Warehousing Institute (TDWI), the leading association of business intelligence and data warehousing professionals worldwide that provide high-quality, in-depth education, training, and research. He is a columnist for SearchCIO.com, DM Review, Application Development Trends, the Business Intelligence Journal, and TDWI Case Studies & Solution. |
| change management data analytics: Applied Big Data Analytics in Operations Management Kumar, Manish, 2016-09-30 Operations management is a tool by which companies can effectively meet customers’ needs using the least amount of resources necessary. With the emergence of sensors and smart metering, big data is becoming an intrinsic part of modern operations management. Applied Big Data Analytics in Operations Management enumerates the challenges and creative solutions and tools to apply when using big data in operations management. Outlining revolutionary concepts and applications that help businesses predict customer behavior along with applications of artificial neural networks, predictive analytics, and opinion mining on business management, this comprehensive publication is ideal for IT professionals, software engineers, business professionals, managers, and students of management. |
| change management data analytics: Digital Transformation in Public Sector Human Resource Management Shava, Elvin, Ndebele, Nduduzo, 2024-07-10 The advent of the Fourth Industrial Revolution (4IR) has created a pressing need for digital transformation in human resources management (HRM) in public institutions. Traditional practices must be updated, preventing institutions from effectively managing their workforce and meeting stakeholder demands. The lack of digitalization leads to inefficiencies, ineffective performance evaluation, and an inability to adapt to the rapidly evolving technological landscape. This gap between existing HR practices and the demands of the digital age poses a significant challenge for public sector organizations. Digital Transformation in Public Sector Human Resource Management offers a comprehensive solution to the challenges faced by public institutions. The book provides practical insights and strategies for aligning HR practices with the modern technological landscape by exploring how digital transformation can revolutionize HRM processes. It demonstrates the benefits of adopting digital technologies and innovative strategies in public sector HRM through real-world examples and case studies. The book guides public sector professionals, policymakers, and academics, helping them navigate the complexities of digital transformation in HRM. |
| change management data analytics: Big Data Analytics P. Krishna Reddy, Ashish Sureka, Sharma Chakravarthy, Subhash Bhalla, 2017-12-04 This book constitutes the refereed conference proceedings of the 5th International Conference on Big Data Analytics, BDA 2017, held in Hyderabad, India, in December 2017. The 21 revised full papers were carefully reviewed and selected from 80 submissions and cover topics on big data analytics, information and knowledge management, mining of massive datasets, computational modeling, data mining and analysis. |
| change management data analytics: The Change Monster Jeanie Daniel Duck, 2002-08-13 A Powerful Look at Corporate Change and Why Mergers, Reorganizations, and Transformations Succeed or Fail “[One of the] best business books of 2001 . . . [a] useful and intelligent tool for coping with the inevitable metamorphoses of business (and life).” —Miami Herald “Provocative imagery . . . useful questions for managers to ask themselves.” —Harvard Business Review “The Change Monster not only talks intelligently about the social dynamics and emotions of people [in change efforts], it does so with wisdom, insight, and practicality.”—Daniel Leemon, executive vice president and chief strategy officer, Charles Schwab Corporation “A practitioner’s primer on revitalization that puts you in the shoes of some who have failed and others who have succeeded. In doing so, Jeanie Daniel Duck graphically delivers her main message to management: Learn to master the emotions and obsessions of those who stand in the way of change, including your own, and once you do, you have your hands on a miraculous engine for change.” —Michael Useem, professor of management and director of the Center for Leadership and Change at the Wharton School, University of Pennsylvania, and author of The Leadership Moment and Leading Up “Duck is an acute and empathetic observer of the changes erupting in the workplace from the convulsive nature of corporate evolution. . . . Jeanie Duck’s terrific book is a . . . useful and intelligent tool for coping with the inevitable metamorphoses of business (and life). Sensitive but tough, Duck’s compassionate wisdom is street smart without a trace of glibness.” —Miami Herald |
| change management data analytics: Computational Intelligence, Data Analytics and Applications Fausto Pedro García Márquez, Akhtar Jamil, Süleyman Eken, Alaa Ali Hameed, 2023-03-14 This book is a compilation of accepted papers presented at the International Conference on Computing, Intelligence and Data Analytics (ICCIDA) in 2022 organized by Information Systems Engineering of the Kocaeli University, Turkey on September 16-17, 2022. The book highlights some of the latest research advances and cutting-edge analyses of real-world problems related to Computing, Intelligence and Data Analytics and their applications in various domains. This includes state of the art models and methods used on benchmark datasets. |
| change management data analytics: Technology Optimization and Change Management for Successful Digital Supply Chains Sabri, Ehap, 2019-03-01 Companies across different industries are launching technology-enabled (digital) business transformation programs to improve their strategic, tactical, and operational supply chain processes. The greatest challenges that they are facing include the lack of preparation and knowledge of the digital transformation life cycle and poorly addressing or neglecting the “people-related” aspects of them. Therefore, improvement initiatives have been short-lived or incomplete, and expected business benefits have not been achieved or materialized. Technology Optimization and Change Management for Successful Digital Supply Chains is a pivotal reference source that provides vital research on the application of digital business transformation programs to improve strategic, tactical, and operational supply chain processes. While highlighting topics such as maturity models, predictive analysis, and communication planning, this publication explores the limited literature in the field of digital supply chain optimization and business transformation, and complements it with practical and proven tactics from the industry. This book is ideally designed for program managers, engineers, students, and practitioners seeking current research on the field’s latest best practices on digital supply chain enablement. |
| change management data analytics: Leading Health Care Transformation Maulik Joshi DrPH, Natalie Erb MPH, Sonia Zhang MPH, Rishi Sikka MD, 2015-07-06 A succinct and practical primer on healthcare transformation, Leading Healthcare Transformation is a key resource for all clinicians in leadership positions. It summarizes high-profile healthcare topics and includes a synopsis of the evidence, examples, lessons learned, and key action steps for each topic covered.Providing cutting-edge insights fro |
| change management data analytics: Data Management and Statistical Analysis Techniques Ronin Myers, 2019-05-19 |
| change management data analytics: Additive Manufacturing Change Management David M. Dietrich, Michael Kenworthy, Elizabeth A. Cudney, 2019-02-04 Additive Manufacturing (AM) has altered manufacturing as we know it, with shortened development time, increased performance, and reduced product costs. Executive management in industry are bombarded by marketing from their competitors showcasing design solutions leveraged through AM. Therefore, executive management ask their project management teams to figure out how to utilize AM within their own company. Clueless on how to approach the problem, managers start learning about AM from experts and become overwhelmed at the highly technical information. Unlike other AM books that focus on the technical output of AM technology, this new book focuses solely on the managerial implementation. Features Presents the impacts of AM technology Provides engaging, practical, and entertaining war stories from the front line of AM industrialization Describes in detail, the significant hurdles in AM certification and implementation Offers templates of proven change management best practices, as practical solutions Omits the technical verbiage that gets in the way of management understanding how the process is implemented |
| change management data analytics: Machine Intelligence and Big Data Analytics for Cybersecurity Applications Yassine Maleh, Mohammad Shojafar, Mamoun Alazab, Youssef Baddi, 2020-12-14 This book presents the latest advances in machine intelligence and big data analytics to improve early warning of cyber-attacks, for cybersecurity intrusion detection and monitoring, and malware analysis. Cyber-attacks have posed real and wide-ranging threats for the information society. Detecting cyber-attacks becomes a challenge, not only because of the sophistication of attacks but also because of the large scale and complex nature of today’s IT infrastructures. It discusses novel trends and achievements in machine intelligence and their role in the development of secure systems and identifies open and future research issues related to the application of machine intelligence in the cybersecurity field. Bridging an important gap between machine intelligence, big data, and cybersecurity communities, it aspires to provide a relevant reference for students, researchers, engineers, and professionals working in this area or those interested in grasping its diverse facets and exploring the latest advances on machine intelligence and big data analytics for cybersecurity applications. |
| change management data analytics: Research Anthology on Cross-Industry Challenges of Industry 4.0 Management Association, Information Resources, 2021-02-05 As Industry 4.0 brings on a new bout of transformation and fundamental changes in various industries, the traditional manufacturing and production methods are falling to the wayside. Industrial processes must embrace modern technology and the most recent trends to keep up with the times. With “smart factories”; the automation of information and data; and the inclusion of IoT, AI technologies, robotics, and cloud computing comes new challenges to tackle. These changes are creating new threats in security, reliability, the regulations around legislation and standardization of technologies, malfunctioning devices or operational disruptions, and more. These effects span a variety of industries and need to be discussed. Research Anthology on Cross-Industry Challenges of Industry 4.0 explores the challenges that have risen as multidisciplinary industries adapt to the Fourth Industrial Revolution. With a shifting change in technology, operations, management, and business models, the impacts of Industry 4.0 and digital transformation will be long-lasting and will forever change the face of manufacturing and production. This book highlights a cross-industry view of these challenges, the impacts they have, potential solutions, and the technological advances that have brought about these new issues. It is ideal for mechanical engineers, electrical engineers, manufacturers, supply chain managers, logistics specialists, investors, managers, policymakers, production scientists, researchers, academicians, and students looking for cross-industry research on the challenges associated with Industry 4.0. |
| change management data analytics: The Data Driven Leader Jenny Dearborn, David Swanson, 2017-09-29 Data is your most valuable leadership asset—here's how to use it The Data Driven Leader presents a clear, accessible guide to solving important leadership challenges through human resources-focused and other data analytics. This engaging book shows you how to transform the HR function and overall organizational effectiveness by using data to make decisions grounded in facts vs. opinions, identify root causes behind your company’s thorniest problems and move toward a winning, future-focused business strategy. Realistic and actionable, this book tells the story of a successful sales executive who, after leading an analytics-driven turnaround (in Data Driven, this book’s predecessor), faces a new turnaround challenge as chief human resources officer. Each chapter features insightful commentary and practical notes on the points the story raises, guiding you to put HR analytics into action in your organization. HR and other leaders cannot afford to overlook the power and competitive advantages of data-driven decision-making and strategies. This book reflects the growing trend of CEOs choosing analytics-minded business leaders to head HR, at a time when workplaces everywhere face game-changing forces including automation, robotics and artificial intelligence. It is urgent that human resources leaders embrace analytics, not only to remain professionally relevant but also to help their organizations successfully navigate this digital transformation. HR professionals can and must: Understand essential data science principles and corporate analytics models Identify and execute effective data analytics initiatives Boost HR and company productivity and performance with metrics that matter Shape an analytics-centric culture that generates data driven leaders Most organizations capture and report data, but data is useless without analysis that leads to action. The Data Driven Leader shows you how to use this tremendous asset to lead your organization higher. |
| change management data analytics: Artificial Intelligence for Business Optimization Bhuvan Unhelkar, Tad Gonsalves, 2021-08-09 This book explains how AI and Machine Learning can be applied to help businesses solve problems, support critical thinking and ultimately create customer value and increase profit. By considering business strategies, business process modeling, quality assurance, cybersecurity, governance and big data and focusing on functions, processes, and people’s behaviors it helps businesses take a truly holistic approach to business optimization. It contains practical examples that make it easy to understand the concepts and apply them. It is written for practitioners (consultants, senior executives, decision-makers) dealing with real-life business problems on a daily basis, who are keen to develop systematic strategies for the application of AI/ML/BD technologies to business automation and optimization, as well as researchers who want to explore the industrial applications of AI and higher-level students. |
CHANGE Definition & Meaning - Merriam-Webster
The meaning of CHANGE is to make different in some particular : alter. How to use change in a sentence. Synonym Discussion of Change.
Change starts here · Change.org
Change.org is an independent, nonprofit-owned organization, funded entirely by millions of users just like you. Stand with Change to protect the power of everyday people making a difference.
CHANGE | English meaning - Cambridge Dictionary
CHANGE definition: 1. to exchange one thing for another thing, especially of a similar type: 2. to make or become…. Learn more.
Change - definition of change by The Free Dictionary
n. 1. The act, process, or result of altering or modifying: a change in facial expression. 2. The replacing of one thing for another; substitution: a change of atmosphere; a change of …
Change - Definition, Meaning & Synonyms | Vocabulary.com
The noun change can refer to any thing or state that is different from what it once was. Change is everywhere in life — and in English. The word has numerous senses, both as a noun and …
Change Definition & Meaning - YourDictionary
To put or take (a thing) in place of something else; substitute for, replace with, or transfer to another of a similar kind. To change one's clothes, to change jobs.
Change: Definition, Meaning, and Examples - usdictionary.com
Dec 2, 2024 · "Change" is an essential term used to refer to a variety of processes or states indicating a difference in condition, position, or state. Embracing and understanding "change" …
What does change mean? - Definitions.net
What does change mean? This dictionary definitions page includes all the possible meanings, example usage and translations of the word change. the process of becoming different. The …
CHANGE Definition & Meaning | Dictionary.com
To change something is to make its form, nature, or content different from what it is currently or from what it would be if left alone. How is change different from alter?
CHANGE - Meaning & Translations | Collins English Dictionary
Master the word "CHANGE" in English: definitions, translations, synonyms, pronunciations, examples, and grammar insights - all in one complete resource.
CHANGE Definition & Meaning - Merriam-Webster
The meaning of CHANGE is to make different in some particular : alter. How to use change in a sentence. Synonym Discussion of Change.
Change starts here · Change.org
Change.org is an independent, nonprofit-owned organization, funded entirely by millions of users just like you. Stand with Change to protect the power of everyday people making a difference.
CHANGE | English meaning - Cambridge Dictionary
CHANGE definition: 1. to exchange one thing for another thing, especially of a similar type: 2. to make or become…. Learn more.
Change - definition of change by The Free Dictionary
n. 1. The act, process, or result of altering or modifying: a change in facial expression. 2. The replacing of one thing for another; substitution: a change of atmosphere; a change of …
Change - Definition, Meaning & Synonyms | Vocabulary.com
The noun change can refer to any thing or state that is different from what it once was. Change is everywhere in life — and in English. The word has numerous senses, both as a noun and …
Change Definition & Meaning - YourDictionary
To put or take (a thing) in place of something else; substitute for, replace with, or transfer to another of a similar kind. To change one's clothes, to change jobs.
Change: Definition, Meaning, and Examples - usdictionary.com
Dec 2, 2024 · "Change" is an essential term used to refer to a variety of processes or states indicating a difference in condition, position, or state. Embracing and understanding "change" …
What does change mean? - Definitions.net
What does change mean? This dictionary definitions page includes all the possible meanings, example usage and translations of the word change. the process of becoming different. The …
CHANGE Definition & Meaning | Dictionary.com
To change something is to make its form, nature, or content different from what it is currently or from what it would be if left alone. How is change different from alter?
CHANGE - Meaning & Translations | Collins English Dictionary
Master the word "CHANGE" in English: definitions, translations, synonyms, pronunciations, examples, and grammar insights - all in one complete resource.
