Competing with High Quality Data

Competing with High Quality Data

Author: Rajesh Jugulum

Publisher: John Wiley & Sons

Published: 2014-03-10

Total Pages: 243

ISBN-13: 111841649X

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Create a competitive advantage with data quality Data is rapidly becoming the powerhouse of industry, but low-quality data can actually put a company at a disadvantage. To be used effectively, data must accurately reflect the real-world scenario it represents, and it must be in a form that is usable and accessible. Quality data involves asking the right questions, targeting the correct parameters, and having an effective internal management, organization, and access system. It must be relevant, complete, and correct, while falling in line with pervasive regulatory oversight programs. Competing with High Quality Data: Concepts, Tools and Techniques for Building a Successful Approach to Data Quality takes a holistic approach to improving data quality, from collection to usage. Author Rajesh Jugulum is globally-recognized as a major voice in the data quality arena, with high-level backgrounds in international corporate finance. In the book, Jugulum provides a roadmap to data quality innovation, covering topics such as: The four-phase approach to data quality control Methodology that produces data sets for different aspects of a business Streamlined data quality assessment and issue resolution A structured, systematic, disciplined approach to effective data gathering The book also contains real-world case studies to illustrate how companies across a broad range of sectors have employed data quality systems, whether or not they succeeded, and what lessons were learned. High-quality data increases value throughout the information supply chain, and the benefits extend to the client, employee, and shareholder. Competing with High Quality Data: Concepts, Tools and Techniques for Building a Successful Approach to Data Quality provides the information and guidance necessary to formulate and activate an effective data quality plan today.


Competing with High Quality Data

Competing with High Quality Data

Author: Rajesh Jugulum

Publisher: John Wiley & Sons

Published: 2014-03-10

Total Pages: 0

ISBN-13: 9781118342329

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Create a competitive advantage with data quality Data is rapidly becoming the powerhouse of industry, but low-quality data can actually put a company at a disadvantage. To be used effectively, data must accurately reflect the real-world scenario it represents, and it must be in a form that is usable and accessible. Quality data involves asking the right questions, targeting the correct parameters, and having an effective internal management, organization, and access system. It must be relevant, complete, and correct, while falling in line with pervasive regulatory oversight programs. Competing with High Quality Data: Concepts, Tools and Techniques for Building a Successful Approach to Data Quality takes a holistic approach to improving data quality, from collection to usage. Author Rajesh Jugulum is globally-recognized as a major voice in the data quality arena, with high-level backgrounds in international corporate finance. In the book, Jugulum provides a roadmap to data quality innovation, covering topics such as: The four-phase approach to data quality control Methodology that produces data sets for different aspects of a business Streamlined data quality assessment and issue resolution A structured, systematic, disciplined approach to effective data gathering The book also contains real-world case studies to illustrate how companies across a broad range of sectors have employed data quality systems, whether or not they succeeded, and what lessons were learned. High-quality data increases value throughout the information supply chain, and the benefits extend to the client, employee, and shareholder. Competing with High Quality Data: Concepts, Tools and Techniques for Building a Successful Approach to Data Quality provides the information and guidance necessary to formulate and activate an effective data quality plan today.


Competing on Analytics

Competing on Analytics

Author: Thomas H. Davenport

Publisher: Harvard Business Press

Published: 2007-03-06

Total Pages: 243

ISBN-13: 1422156303

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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.


Competing in the Age of AI

Competing in the Age of AI

Author: Marco Iansiti

Publisher: Harvard Business Press

Published: 2020-01-07

Total Pages: 175

ISBN-13: 1633697630

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"a provocative new book" — The New York Times AI-centric organizations exhibit a new operating architecture, redefining how they create, capture, share, and deliver value. Now with a new preface that explores how the coronavirus crisis compelled organizations such as Massachusetts General Hospital, Verizon, and IKEA to transform themselves with remarkable speed, Marco Iansiti and Karim R. Lakhani show how reinventing the firm around data, analytics, and AI removes traditional constraints on scale, scope, and learning that have restricted business growth for hundreds of years. From Airbnb to Ant Financial, Microsoft to Amazon, research shows how AI-driven processes are vastly more scalable than traditional processes, allow massive scope increase, enabling companies to straddle industry boundaries, and create powerful opportunities for learning—to drive ever more accurate, complex, and sophisticated predictions. When traditional operating constraints are removed, strategy becomes a whole new game, one whose rules and likely outcomes this book will make clear. Iansiti and Lakhani: Present a framework for rethinking business and operating models Explain how "collisions" between AI-driven/digital and traditional/analog firms are reshaping competition, altering the structure of our economy, and forcing traditional companies to rearchitect their operating models Explain the opportunities and risks created by digital firms Describe the new challenges and responsibilities for the leaders of both digital and traditional firms Packed with examples—including many from the most powerful and innovative global, AI-driven competitors—and based on research in hundreds of firms across many sectors, this is your essential guide for rethinking how your firm competes and operates in the era of AI.


Competing on Analytics

Competing on Analytics

Author: Thomas H. Davenport

Publisher: Harvard Business Press

Published: 2007

Total Pages: 243

ISBN-13: 1422103323

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"In Competing on Analytics: The New Science of Winning, Thomas H. Davenport and Jeanne G. Harris argue that the frontier for using data has shifted dramatically. Leading companies are doing more than just collecting and storing information in large quantities. They're now building their competitive strategies around data-driven insights that are, in turn, generating impressive business results. Their secret weapon? Analytics: sophisticated quantitative and statistical analysis and predictive modeling supported by data-savvy senior leaders and powerful information technology."--Jacket.


Analytics at Work

Analytics at Work

Author: Thomas H. Davenport

Publisher: Harvard Business Press

Published: 2010

Total Pages: 231

ISBN-13: 1422177696

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As a follow-up to the successful Competing on Analytics, authors Tom Davenport, Jeanne Harris, and Robert Morison provide practical frameworks and tools for all companies that want to use analytics as a basis for more effective and more profitable decision making. Regardless of your company's strategy, and whether or not analytics are your company's primary source of competitive differentiation, this book is designed to help you assess your organization's analytical capabilities, provide the tools to build these capabilities, and put analytics to work. The book helps you answer these pressing questions: What assets do I need in place in my organization in order to use analytics to run my business? Once I have these assets, how do I deploy them to get the most from an analytic approach? How do I get an analytic initiative off the ground in the first place, and then how do I sustain analytics in my organization over time? Packed with tools, frameworks, and all new examples, Analytics at Work makes analytics understandable and accessible and teaches you how to make your company more analytical.


Competing on the Edge

Competing on the Edge

Author: Shona L. Brown

Publisher: Harvard Business Press

Published: 1998

Total Pages: 322

ISBN-13: 9780875847542

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In their startling new book, authors Brown and Eisenhardt contend that to prosper in today's fiercely competitive business environments, a new paradigm--competing on the edge--must be implemented as a new survival strategy. This book focuses on specific management dilemmas and illustrates solutions that work when the name of the game is change.


Big Data at Work

Big Data at Work

Author: Thomas Davenport

Publisher: Harvard Business Review Press

Published: 2014-02-04

Total Pages: 241

ISBN-13: 1422168174

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Go ahead, be skeptical about big data. The author was—at first. When the term “big data” first came on the scene, bestselling author Tom Davenport (Competing on Analytics, Analytics at Work) thought it was just another example of technology hype. But his research in the years that followed changed his mind. Now, in clear, conversational language, Davenport explains what big data means—and why everyone in business needs to know about it. Big Data at Work covers all the bases: what big data means from a technical, consumer, and management perspective; what its opportunities and costs are; where it can have real business impact; and which aspects of this hot topic have been oversold. This book will help you understand: • Why big data is important to you and your organization • What technology you need to manage it • How big data could change your job, your company, and your industry • How to hire, rent, or develop the kinds of people who make big data work • The key success factors in implementing any big data project • How big data is leading to a new approach to managing analytics With dozens of company examples, including UPS, GE, Amazon, United Healthcare, Citigroup, and many others, this book will help you seize all opportunities—from improving decisions, products, and services to strengthening customer relationships. It will show you how to put big data to work in your own organization so that you too can harness the power of this ever-evolving new resource.


Robust Quality

Robust Quality

Author: Rajesh Jugulum

Publisher: CRC Press

Published: 2018-09-03

Total Pages: 120

ISBN-13: 0429877269

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Historically, the term quality was used to measure performance in the context of products, processes and systems. With rapid growth in data and its usage, data quality is becoming quite important. It is important to connect these two aspects of quality to ensure better performance. This book provides a strong connection between the concepts in data science and process engineering that is necessary to ensure better quality levels and takes you through a systematic approach to measure holistic quality with several case studies. Features: Integrates data science, analytics and process engineering concepts Discusses how to create value by considering data, analytics and processes Examines metrics management technique that will help evaluate performance levels of processes, systems and models, including AI and machine learning approaches Reviews a structured approach for analytics execution


Competing on Supply Chain Quality

Competing on Supply Chain Quality

Author: Anna Nagurney

Publisher: Springer

Published: 2016-05-30

Total Pages: 399

ISBN-13: 3319254510

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This book lays the foundations for quality modeling and analysis in the context of supply chains through a synthesis of the economics, operations management, as well as operations research/management science literature on quality. The reality of today's supply chain networks, given their global reach from sourcing locations to points of demand, is further challenged by such issues as the growth in outsourcing as well as the information asymmetry associated with what producers know about the quality of their products and what consumers know. Although much of the related literature has focused on the micro aspects of supply chain networks, considering two or three decision-makers, it is essential to capture the scale of supply chain networks in a holistic manner that occurs in practice in order to be able to evaluate and analyze the competition and the impacts on supply chain quality in a quantifiable manner. This volume provides an overview of the fundamental methodologies utilized in this book, including optimization theory, game theory, variational inequality theory, and projected dynamical systems theory. It then focuses on major issues in today's supply chains with respect to quality, beginning with information asymmetry, followed by product differentiation and branding, the outsourcing of production, from components to final products, to quality in freight service provision. The book is filled with numerous real-life examples in order to emphasize the generality and pragmatism of the models and tools. The novelty of the framework lies in a network economics perspective through which the authors identify the underlying network structure of the various supply chains, coupled with the behavior of the decision-makers, ranging from suppliers and manufacturers to freight service providers. What is meant by quality is rigorously defined and quantified. The authors explore the underlying dynamics associated with the competitive processes along with the equilibrium solutions. As appropriate, the supply chain decision-makers compete in terms of quantity and quality, or in price and quality. The relevance of the various models that are developed to specific industrial sectors, including pharmaceuticals and high technology products, is clearly made. Qualitative analyses are provided, along with effective, and, easy to implement, computational procedures. Finally, the impacts of policy interventions, in the form of minimum quality standards, and their ramifications, in terms of product prices, quality levels, as well as profits are explored. The book is filled with many network figures, graphs, and tables with data.