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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. 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