AI-Enabled Analytics for Business. Lawrence S. Maisel. Читать онлайн. Newlib. NEWLIB.NET

Автор: Lawrence S. Maisel
Издательство: John Wiley & Sons Limited
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Жанр произведения: Зарубежная деловая литература
Год издания: 0
isbn: 9781119736097
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       Lawrence S. MaiselRobert J. ZwerlingJesper H. Sorensen

      Published by John Wiley & Sons, Inc., Hoboken, New Jersey.

      Published simultaneously in Canada.

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       Library of Congress Cataloging-in-Publication Data is Available:

      ISBN 978-111-9736-080 (Hardback)

      ISBN 978-111-9736-103 (ePDF)

      ISBN 978-111-9736-097 (epub)

      Cover Design: Wiley

      Cover Image: © DNY59/Getty Images

       I would like to dedicate this book to my wife Claudia, whose endless patience, bright smile, and intelligence have always been a source of inspiration. I also want to acknowledge my parents and brother, who provided gentle guidance and love. I especially want to thank my children, Nicole, Dana, and Jonathan, who inspire and always bring out the best in me.

       To Dana, forever in my heart.

       Lawrence S. Maisel

       This book is dedicated in loving memory of my mother, Joy, the merriment of my grandmother, Tess, and the wisdom and discipline of my grandfather, Ruby. The best of life and the greatest of gifts I have are from my sister, Alice, wife, Val, and daughter, Megan.

       Robert J. Zwerling

       This book was written in memories of my parents, who patiently helped me learn. I also want to acknowledge my wife, Anne. Without you this would not be possible.

       Jesper H. Sorensen

      We thank Kent Bearden, Jonathan Morgan, and Lisa Tapp for sharing their experiences and helping us learn the ways AI and analytics contribute to improving their operations. With gratitude, we also acknowledge the support and editorial assistance of Sheck Cho and Susan Cerra of Wiley, which enabled us to complete this book.

      Everywhere you turn, you hear or read about artificial intelligence (AI) and the emerging importance of digital transformation. To be competitive in modern business, decision-making needs to evolve into a more objective, insightful, and unbiased process that is powered by the application of AI-enabled analytics.

      We have written AI-Enabled Analytics for Business: A Roadmap for Becoming an Analytics Powerhouse for executives to gain a solid understanding of AI and analytics that will give clarity, vision, and voice to integrating them in business processes that will be impactful and increase business performance.

      Today, there is more promise than practice in implementing AI and analytics for data-driven decisions. As you will learn, there are twice as many analytics failures than successes, and there are twice as many successes that are abandoned rather than sustained. The good news is that almost all failure can be traced back to executive decisions that are entirely avoidable and easily identified.

      Further, AI is not the sole purview of big companies, big data, and big data projects that seek to boil the ocean. The butcher, baker, and candlestick maker can all incorporate AI to increase productivity, reduce workforce, retain higher-skilled talent, and enhance the customer's experience. In fact, AI and analytics are better done incrementally, building on each success to scale the business to become an analytics powerhouse.

      In Part I, we cover the fundamentals of AI and analytics, beginning in Chapter 1 to untangle the many seemingly synonymous terms, partitioning tools that do and do not do analytics, and the ROI of AI. It is essential to know the difference between analysis, which is the application of arithmetic on data to yield information, and analytics, which is the application of mathematics on data to yield insights. In Chapter 2, we illuminate why analytics is essential in business and share Noble Prize-winning research that recognizes the limitations of human decision-making based on biased intuition and gut feel, and why analytics must be included as the essential unbiased component. Chapter 3 discusses myths and misconceptions regarding the approach to analytics, and Chapter 4 takes you through several applications of AI and analytics across different business functions.

      In Part II, we define the Roadmap for how to implement AI-enabled analytics for data-driven decisions and the contributions of executives for becoming an analytics powerhouse. Chapter 5 is the fulcrum of this book and delivers a detailed discussion of analytics as more than a tool—it is a culture with four components: Mindset, People, Processes, and