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Analytics Across the Enterprise: How IBM Realizes Business Value from Big Data and Analytics

Book Description

How to Transform Your Organization with Analytics: Insider Lessons from IBM’s Pioneering Experience

Analytics is not just a technology: It is a better way to do business. Using analytics, you can systematically inform human judgment with data-driven insight. This doesn’t just improve decision-making: It also enables greater innovation and creativity in support of strategy. Your transformation won’t happen overnight; however, it is absolutely achievable, and the rewards are immense.

This book demystifies your analytics journey by showing you how IBM has successfully leveraged analytics across the enterprise, worldwide. Three of IBM’s pioneering analytics practitioners share invaluable real-world perspectives on what does and doesn’t work and how you can start or accelerate your own transformation. This book provides an essential framework for becoming a smarter enterprise and shows through 31 case studies how IBM has derived value from analytics throughout its business.

Coverage Includes

  • Creating a smarter workforce through big data and analytics

  • More effectively optimizing supply chain processes

  • Systematically improving financial forecasting

  • Managing financial risk, increasing operational efficiency, and creating business value

  • Reaching more B2B or B2C customers and deepening their engagement

  • Optimizing manufacturing and product management processes

  • Deploying your sales organization to increase revenue and effectiveness

  • Achieving new levels of excellence in services delivery and reducing risk

  • Transforming IT to enable wider use of analytics

  •  “Measuring the immeasurable” and filling gaps in imperfect data

  • Whatever your industry or role, whether a current or future leader, analytics can make you smarter and more competitive. Analytics Across the Enterprise shows how IBM did it--and how you can, too.

    Learn more about IBM Analytics

    Table of Contents

    1. About This eBook
    2. Title Page
    3. Copyright Page
    4. Praise for Analytics Across the Enterprise
    5. Dedication Page
    6. Contents
    7. Foreword
    8. Preface
      1. Color Images
    9. Acknowledgments
    10. About the Authors
    11. 1. Why Big Data and Analytics?
      1. Why IBM Started an Enterprise-Wide Journey to Use Analytics
      2. Big Data and Analytics Demystified
      3. Why Analytics Matters
      4. Governance
      5. Proven Approaches
      6. Gauging Progress
      7. Overview of Nine Journeys
      8. Emerging Themes
      9. How to Use This Book
      10. Endnotes
    12. 2. Creating a Smarter Workforce
      1. Perspective: Applying Analytics to the Workforce
      2. Challenge: Retaining High-Value Resources in Growth Markets
      3. Challenge: Gaining an Accurate View of What Employees Are Thinking
      4. Lessons Learned
      5. Endnotes
    13. 3. Optimizing the Supply Chain
      1. Perspective: Applying Analytics to the Supply Chain
      2. Challenge: Detecting Quality Problems Early
      3. Challenge: Providing Supply/Demand Visibility and Improved Channel Inventory Management
      4. Challenge: Improving the Accounts Receivable Business Process and Collector Productivity
      5. Challenge: Predicting Disruptions in the Supply Chain
      6. Lessons Learned
      7. Endnotes
    14. 4. Anticipating the Financial Future
      1. Perspective: Big Data and Analytics Increase Value of Finance Team
      2. Challenge: Attaining Operational Efficiency, Managing Risk, and Informing Decisions
      3. Challenge: Balancing Risk and Reward
      4. Challenge: Validating Acquisition Strategy
      5. What’s Next for IBM Finance?
      6. Lessons Learned
      7. Endnotes
    15. 5. Enabling Analytics Through Information Technology
      1. Perspective: Applying Analytics to IT and Enabling Big Data and Analytics Across an Enterprise
      2. Challenge: Deciding When to Modernize Servers
      3. Challenge: Detecting Security Incidents
      4. Enabling the Transformation to a Smarter Enterprise
      5. Lessons Learned
      6. Endnotes
    16. 6. Reaching Your Market
      1. Perspective: Using Analytics to Reach and Engage with Clients
      2. Challenge: Developing the Data Foundation and Analytics Capability to Enable a Signature Client Experience
      3. Challenge: Providing a Real-Time View into Effectiveness of Marketing Actions: Performance Management
      4. Challenge: Going Beyond Correlation to Determine Causal Effects of Marketing Actions
      5. Challenge: Tapping into Analytics Passion to Provide New Insights to Inform IBM’s Digital Strategy
      6. Lessons Learned
      7. Endnotes
    17. 7. Measuring the Immeasurable
      1. Perspective: Software Development Organization Optimizes the Highly Skilled Workforce
      2. Challenge: Creating a Common View of Development Expense to Enable Decision Making
      3. Lessons Learned
      4. Endnotes
    18. 8. Optimizing Manufacturing
      1. Perspective: Applying Analytics to Manufacturing and Product Management
      2. Challenge: Scheduling a Complex Manufacturing Process in a Semiconductor Fab
      3. Challenge: Enhancing Yield in the Manufacturing of Semiconductors
      4. Challenge: Reducing the Time to Detect Aberrant Events
      5. Challenge: Simplifying the Hardware Product Portfolio
      6. Lessons Learned
      7. Endnotes
    19. 9. Increasing Sales Performance
      1. Perspective: Using Analytics to Optimize Sales Performance—Inside and Out
      2. Challenge: Deploying Sellers for Maximum Revenue Growth by Account
      3. Challenge: Deploying Sellers Within a Territory
      4. Challenge: Determining the Optimal Sales Coverage Investment by Account
      5. Online Commerce
      6. Challenge: Creating a Smarter Commerce B2B Solution to Drive Cross-Company Efficiencies
      7. Lessons Learned
      8. Endnotes
    20. 10. Delivering Services with Excellence
      1. Perspective: Leveraging Analytics in a Services Business
      2. Challenge: Developing New Business
      3. Challenge: Predicting Risk of Contracts
      4. Challenge: Optimizing Workforce Performance
      5. Challenge: Getting Early Warning About Problems
      6. Lessons Learned
      7. Endnotes
    21. 11. Reflections and a Look to the Future
      1. The Journey Continues
      2. Reflections
      3. The Future
      4. Endnotes
    22. A. Big Data and Analytics Use Cases
    23. Glossary: Acronyms and Definitions of Key Big Data and Analytics Terms
      1. A
      2. B
      3. C
      4. D
      5. E
      6. F
      7. G
      8. H
      9. I
      10. J
      11. L
      12. M
      13. N
      14. O
      15. P
      16. Q
      17. R
      18. S
      19. T
      20. U
      21. V
      22. W-Z
    24. Index