Enterprise Analytics Optimize Performance Process & Decisions Through Big Data

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.

Normal 0 false false false MicrosoftInternetExplorer4 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.

The Definitive Guide to Enterprise-Level Analytics Strategy, Technology, Implementation, and Management

• From the International Institute for Analytics, the world’s premier analytics research organization

• Proven best practices for choosing projects and technology, building analytics organizations, and measuring ROI

• Brand-new case studies from finance, healthcare, technology, retail, manufacturing, and beyond

As businesses recognize the immense potential of analytics, they are increasingly treating it as an enterprise resource and an enterprise priority. Now, the world’s leading researchers on large-scale analytics have brought together today’s best practices for planning, implementing, managing, and succeeding with analytics on an enterprise level.

Drawing on their pioneering work at the International Institute for Analytics, the authors illuminate the entire analytics lifecycle, addressing technology, applications, operations, governance, strategy, and more. They offer actionable solutions for leveraging proprietary data, gaining a new 360-degree view of the customer, measuring engagement in actionable ways, optimizing “next best offers,” applying analytics at production scale, using cloud resources, and linking analytics directly to business performance. Then, in a full section on the crucial human side of analytics, they address everything from building and governing analytics organizations to integrating analytics throughout global businesses.

Whether you’re an analyst, manager, strategist, executive, or technology vendor, this book will help you implement large-scale analytics faster, avoid crucial missteps, and capture far more value.

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.

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.

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