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Enterprise Analytics: Optimize Performance, Process, and Decisions Through Big Data
- By Thomas H. Davenport, International Institute for Analytics
- Published Sep 13, 2012 by FT Press. Part of the FT Press Operations Management series.
- Copyright 2013
- Dimensions: 6" x 9"
- Pages: 288
- Edition: 1st
- Book
- ISBN-10: 0-13-303943-9
- ISBN-13: 978-0-13-303943-6
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Product Author Bios
THOMAS H. DAVENPORT, (Cambridge, MA) co-founder and Director of Research of the International Institute for Analytics, a world renowned thought leader and executive advisor on analytics. His book, Analytics at Work: Smarter Decisions, Better Results, was named a must-read for 2010 by CIO Insight. Davenport holds a Ph.D. from Harvard University, taught at Harvard Business School, and led research centers at McKinsey and CSC. He is President's Distinguished Professor of Information Technology and Management at Babson College; senior advisor, Deloitte Analytics, Deloitte Touche Tohmatsu; and member, Board of Sponsors, MIT Center for Information Systems.
The Definitive Guide to Enterprise-Level Analytics Strategy, Technology, Implementation, and Management
Organizations are capturing exponentially larger amounts of data than ever, and now they have to figure out what to do with it. Using analytics, you can harness this data, discover hidden patterns, and use this knowledge to act meaningfully for competitive advantage. Suddenly, you can go beyond understanding “how, when, and where” events have occurred, to understand why – and use this knowledge to reshape the future. Now, analytics pioneer Tom Davenport and the world-renowned experts at the International Institute for Analytics (IIA) have brought together the latest techniques, best practices, and research on analytics in a single primer for maximizing the value of enterprise data. Enterprise Analytics is today’s definitive guide to analytics strategy, planning, organization, implementation, and usage. It covers everything from building better analytics organizations to gathering data; implementing predictive analytics to linking analysis with organizational performance. The authors offer specific insights for optimizing supply chains, online services, marketing, fraud detection, and many other business functions. They support their powerful techniques with many real-world examples, including chapter-length case studies from healthcare, retail, and financial services. Enterprise Analytics will be an invaluable resource for every business and technical professional who wants to make better data-driven decisions: operations, supply chain, and product managers; product, financial, and marketing analysts; CIOs and other IT leaders; data, web, and data warehouse specialists, and many others.Author's Site
Author suggested site: www.iianalytics.com
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4 of 4 people found the following review helpful
Varied collection of essays on enterprise analytics, By
This review is from: Enterprise Analytics: Optimize Performance, Process, and Decisions Through Big Data (FT Press Operations Management) (Hardcover)
Customer review from the Amazon Vine™ Program (What's this?)
This book is a collection of eighteen essays on enterprise analytics by fourteen different authors, ten written or co-written by the editor, who also wrote "Competing on Analytics: The New Science of Winning" with Jeanne G. Harris, and "Analytics at Work: Smarter Decisions, Better Results" with Robert Morison and the aforementioned author (see my reviews), both of whom contributed to this book as well. The topics in this text are a bit more varied than in the earlier efforts of the editor. Rather than focusing on how analytics can be utilized to compete in the marketplace, as was the case in the first book, this latest entry moves in the direction of the second book, which is how to practice analytics. Not in the sense of in-the-trenches toolsets or statistical methods, but at a level more akin to enterprise architecture.After providing an overview of analytics, the authors direct the reader to topics such as applications and technologies of analytics (approximately 50% of... Read more
2 of 2 people found the following review helpful
Lectures, Meanders, Pontificates, But Does Not Educate, By
This review is from: Enterprise Analytics: Optimize Performance, Process, and Decisions Through Big Data (FT Press Operations Management) (Hardcover)
Customer review from the Amazon Vine™ Program (What's this?)
Or, how a book on Big Data, Enterprise Analytics, and technology neatly skirts any meaningful discussion of Big Data, Enterprise Analytics, and technology.While a few chapters stand out for their reasoning and clarity, what is jarringly absent from this book is any meaningful, technical discussion about Big Data itself. Without such a discussion, most of the book's content can be recycled with minimum effort ten years from now and applied to the next big thing in technology. Even assuming that this book is targeted at decision makers and so-called C-level executives, an absence of the nuances and complexities of Big Data mean that executives will be as clueless on that dimension of Big Data knowledge after reading the book as before. If you are responsible for selling sausages, you had jolly well get a look at the sausage factory, if not work there a day. Big Data, Unstructured Data, the Cloud - if these three buzzwords were not enough, you can add the salsa-ish... Read more
2 of 3 people found the following review helpful
Big Data, or, How I survived the Great Flood, By
This review is from: Enterprise Analytics: Optimize Performance, Process, and Decisions Through Big Data (FT Press Operations Management) (Hardcover)
Customer review from the Amazon Vine™ Program (What's this?)
These essays are all basic surveys of major topics for enterprise analytics. We see in simple terms what data reveals about markets, traffic and customers. If you are already more than ankle deep in analytics, this book may be rather too introductory. If you are not, you may want to read on, at least for a short while. For the rest of us, the survey is comprehensive and the topics are current. As the mathematics of quantitative analysis do not evolve so quickly, the tools do, as is market access, e.g. mobile devices. Big Data is pushing to the periphery to reach for more data faster. Your car, your store, and your wallet are in play. While I mention Big Data often, the book is intended to focus more on analytics than scale. Scale just seems to barge in all the same.For over a dozen years, informational date has been overtaking transactional data. In fact, informational data now spawns transactional data, as you see in the unregulated markets of derivatives and... Read more |
Table of Contents
Foreword and Acknowledgments xii
Jack Phillips
About the Authors xiv
Introduction: The New World of Enterprise Analytics
Thomas H. Davenport
Part I: Overview of Analytics and Their Value
Chapter 1 What Do We Talk About When We Talk About Analytics? 9
Thomas H. Davenport
Chapter 2 The Return on Investments in Analytics 19
Keri E. Pearlson
Part II: Application of Analytics
Chapter 3 Leveraging Proprietary Data for Analytical Advantage 37
Thomas H. Davenport
Chapter 4 Analytics on Web Data: The Original Big Data 47
Bill Franks
Chapter 5 The Analytics of Online Engagement 71
Eric T. Peterson
Chapter 6 The Path to “Next Best Offers” for Retail Customers 83
Thomas H. Davenport, John Lucker, and Leandro DalleMule
Part III: Technologies for Analytics
Chapter 7 Applying Analytics at Production Scale 97
James Taylor
Chapter 8 Predictive Analytics in the Cloud 111
James Taylor
Chapter 9 Analytical Technology and the Business User 123
Thomas H. Davenport
Chapter 10 Linking Decisions and Analytics for Organizational Performance 135
Thomas H. Davenport
Part IV: The Human Side of Analytics
Chapter 11 Organizing Analysts 157
Robert F. Morison and Thomas H. Davenport
Chapter 12 Engaging Analytical Talent 179
Jeanne G. Harris and Elizabeth Craig
Chapter 13 Governance for Analytics 187
Stacy Blanchard and Robert F. Morison
Chapter 14 Building a Global Analytical Capability 203
Thomas H. Davenport
Part V: Case Studies in the Use of Analytics
Chapter 15 Partners HealthCare System 215
Thomas H. Davenport
Chapter 16 Analytics in the HR Function at Sears Holding Corporation 233
Carl Schleyer
Chapter 17 Commercial Analytics Culture and Relationships at Merck 241
Thomas H. Davenport
Chapter 18 Descriptive Analytics for the Supply Chain at Bernard Chaus, Inc. 249
Katherine Busey and Callie Youssi
Index 255
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