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Foreword and Acknowledgments | |
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About the Authors | |
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Introduction: The New World of Enterprise Analytics | |
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Overview of Analytics and Their Value | |
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What Do We Talk About When We Talk About Analytics? | |
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Why We Needed a New Term: Issues with Traditional Business Intelligence | |
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Three Types of Analytics | |
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Where Does Data Mining Fit In? | |
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Business Analytics Versus Other Types | |
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Web Analytics | |
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Big-Data Analytics | |
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Conclusion | |
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The Return on Investments in Analytics | |
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Traditional ROI Analysis | |
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The Teradata Method for Evaluating Analytics Investments | |
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An Example of Calculating the Value | |
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Analytics ROI at Freescale Semiconductor | |
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Application of Analytics | |
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Leveraging Proprietary Data for Analytical Advantage | |
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Issues with Managing Proprietary Data and Analytics | |
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Lessons Learned from Payments Data | |
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Endnote | |
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Analytics on Web Data: The Original Big Data | |
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Web Data Overview | |
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What Web Data Reveals | |
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Web Data in Action | |
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Wrap-Up | |
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The Analytics of Online Engagement | |
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The Definition of Engagement | |
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A Model to Measure Online Engagement | |
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The Value of Engagement Scores | |
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Engagement Analytics at PBS | |
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Engagement Analytics at Philly.com | |
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The Path to "Next Best Offers" for Retail Customers | |
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Analytics and the Path to Effective Next Best Offers | |
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Offer Strategy Design | |
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Know Your Customer | |
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Know Your Offers | |
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Know the Purchase Context | |
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Analytics and Execution: Deciding on and Making die Offer | |
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Learning from and Adapting NBOs | |
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Technologies for Analytics | |
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Applying Analytics at Production Scale | |
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Decisions Involve Actions | |
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Time to Business Impact | |
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Business Decisions in Operation | |
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Compliance Issues | |
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Data Considerations | |
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Example of Analytics at Production Scale: YouSee | |
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Lessons Learned from Other Successful Companies | |
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Endnote | |
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Predictive Analytics in the Cloud | |
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Business Solutions Focus | |
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Five Key Opportunities | |
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The State of the Market | |
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Pros and Cons | |
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Adopting Cloud-Based Predictive Analytics | |
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Endnote | |
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Analytical Technology and the Business User | |
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Separate but Unequal | |
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Staged Data | |
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Multipurpose | |
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Generally Complex | |
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Premises- and Product-Based | |
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Industry-Generic | |
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Exclusively Quantitative | |
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Business Unit-Driven | |
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Specialized Vendors | |
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Problems with the Current Model | |
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Changes Emerging in Analytical Technology | |
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Creating the Analytical Apps of the Future | |
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Summary | |
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Linking Decisions and Analytics for Organizational Performance | |
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A Study of Decisions and Analytics | |
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Linking Decisions and Analytics | |
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A Process for Connecting Decisions and Information | |
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Looking Ahead in Decision Management | |
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Endnotes | |
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The Human Side of Analytics | |
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Organizing Analysts | |
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Why Organization Matters | |
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General Goals of Organizational Structure | |
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Goals of a Particular Analytics Organization | |
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Basic Models for Organizing Analysts | |
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Coordination Approaches | |
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What Model Fits Your Business? | |
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How Bold Can You Be? | |
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Triangulating on Your Model and Coordination Mechanisms | |
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Analytical Leadership and the Chief Analytics Officer | |
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To Where Should Analytical Functions Report? | |
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Building an Analytical Ecosystem | |
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Developing the Analytical Organization Over Time | |
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The Bottom Line | |
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Endnotes | |
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Engaging Analytical Talent | |
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Four Breeds of Analytical Talent | |
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Engaging Analysts | |
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Arm Analysts with Critical Information About the Business | |
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Define Roles and Expectations | |
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Feed Analysts' Love of New Techniques, Tools, and Technologies | |
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Employ More Centralized Analytical Organization Structures | |
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Governance for Analytics | |
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Guiding Principles | |
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Elements of Governance | |
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You Know You're Succeeding When | |
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Building a Global Analytical Capability | |
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Widespread Geographic Variation | |
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Central Coordination, Centralized Organization | |
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A Strong Center of Excellence | |
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A Coordinated "Division of Labor" Approach | |
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Other Global Analytics Trends | |
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Endnotes | |
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Case Studies in the Use of Analytics | |
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Partners HealthCare System | |
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Centralized Data and Systems at Partners | |
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Managing Clinical Informatics and Knowledge at Partners | |
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High-Performance Medicine at Partners | |
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New Analytical Challenges for Partners | |
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Centralized Business Analytics at Partners | |
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Hospital-Specific Analytical Activities: Massachusetts General Hospital | |
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Hospital-Specific Analytical Activities: Brigham & Women's Hospital | |
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Endnotes | |
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Analytics in the HR Function at Sears Holdings Corporation | |
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What We Do | |
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Who Make Good HR Analysts | |
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Our Recipe for Maximum Value | |
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Key Lessons Learned | |
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Commercial Analytics Culture and Relationships at Merck | |
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Decision-Maker Partnerships | |
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Reasons for the Group's Success | |
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Embedding Analyses into Tools | |
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Future Directions for Commercial Analytics and Decision Sciences | |
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Descriptive Analytics for the Supply Chain at Bernard Chaus, Inc | |
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The Need for Supply Chain Visibility | |
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Analytics Strengthened Alignment Between Chaus's IT and Business Units | |
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Index | |