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The Definitive Guide to Enterprise-Level Analytics Strategy, Technology, Implementation, and ManagementOrganizations 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.
Contents
Foreword and Acknowledgments xiiJack PhillipsAbout the Authors xivIntroduction: The New World of Enterprise AnalyticsThomas H. DavenportPart I: Overview of Analytics and Their ValueChapter 1 What Do We Talk About When We Talk About Analytics? 9Thomas H. DavenportChapter 2 The Return on Investments in Analytics 19Keri E. PearlsonPart II: Application of AnalyticsChapter 3 Leveraging Proprietary Data for Analytical Advantage 37Thomas H. DavenportChapter 4 Analytics on Web Data: The Original Big Data 47Bill FranksChapter 5 The Analytics of Online Engagement 71Eric T. PetersonChapter 6 The Path to "Next Best Offers" for Retail Customers 83Thomas H. Davenport, John Lucker, and Leandro DalleMulePart III: Technologies for AnalyticsChapter 7 Applying Analytics at Production Scale 97James TaylorChapter 8 Predictive Analytics in the Cloud 111James TaylorChapter 9 Analytical Technology and the Business User 123Thomas H. DavenportChapter 10 Linking Decisions and Analytics for Organizational Performance 135Thomas H. DavenportPart IV: The Human Side of AnalyticsChapter 11 Organizing Analysts 157Robert F. Morison and Thomas H. DavenportChapter 12 Engaging Analytical Talent 179Jeanne G. Harris and Elizabeth CraigChapter 13 Governance for Analytics 187Stacy Blanchard and Robert F. MorisonChapter 14 Building a Global Analytical Capability 203Thomas H. DavenportPart V: Case Studies in the Use of AnalyticsChapter 15 Partners HealthCare System 215Thomas H. DavenportChapter 16 Analytics in the HR Function at Sears Holding Corporation 233Carl SchleyerChapter 17 Commercial Analytics Culture and Relationships at Merck 241Thomas H. DavenportChapter 18 Descriptive Analytics for the Supply Chain at Bernard Chaus, Inc. 249Katherine Busey and Callie YoussiIndex 255
