Register your product to gain access to bonus material or receive a coupon.
Analytics Across the Enterprise: How IBM Realizes Business Value from Big Data and Analytics
- By Brenda L. Dietrich, Emily C. Plachy, Maureen F. Norton
- Published May 14, 2014 by IBM Press. Part of the IBM Press series.
Book
- Sorry, this book is no longer in print.
eBook
- Your Price: $23.19
- List Price: $28.99
- Includes EPUB and PDF
- About eBook Formats
This eBook includes the following formats, accessible from your Account page after purchase:
EPUB
The open industry format known for its reflowable content and usability on supported mobile devices.
PDF
The popular standard, used most often with the free Acrobat® Reader® software.
This eBook requires no passwords or activation to read. We customize your eBook by discreetly watermarking it with your name, making it uniquely yours.
About
Features
- Shows how to systematically infuse science into the art of business decision-making, leveraging today's latest advances in business analytics
- Reflects powerful lessons learned inside and throughout IBM, as it has pioneered analytics across the enterprise
- Focuses on one of today's best opportunities to improve competitiveness -- as an executive, manager, student, or organization
Description
- Copyright 2014
- Dimensions: 6" x 9"
- Pages: 224
- Edition: 1st
- Book
- ISBN-10: 0-13-383303-8
- ISBN-13: 978-0-13-383303-4
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
Sample Content
Online Sample Chapter
Sample Pages
Download the sample pages (includes Chapter 1 and Index)
Table of Contents
Foreword xix
Preface xxi
Chapter 1: Why Big Data and Analytics? 1
Why IBM Started an Enterprise-Wide Journey to Use Analytics 3
Big Data and Analytics Demystified 4
Descriptive and Predictive Analytics 5
Prescriptive Analytics 6
Social Media Analytics 6
Entity Analytics 7
Cognitive Computing 7
Big Data 8
Why Analytics Matters 9
Governance 10
Proven Approaches 12
Gauging Progress 13
Overview of Nine Journeys 14
Emerging Themes 15
How to Use This Book 17
Endnotes 18
Chapter 2: Creating a Smarter Workforce 21
Perspective: Applying Analytics to the Workforce 21
Challenge: Retaining High-Value Resources in Growth Markets 25
Outcome: Attrition Rate Declined; Net Benefits Exceeded Expectations 26
Challenge: Gaining an Accurate View of What Employees Are Thinking 26
Outcome: Ability to Act on Real Insights About Employees 27
Lessons Learned 29
Endnotes 31
Chapter 3: Optimizing the Supply Chain 33
Perspective: Applying Analytics to the Supply Chain 33
Challenge: Detecting Quality Problems Early 36
Outcome: Significant Cost Savings, Improved Productivity, Improved Brand Value, and Two Awards 38
Challenge: Providing Supply/Demand Visibility and Improved Channel Inventory Management 39
Outcome: Reduced Price Protection Expense, Reduced Returns, and Two Industry Awards 41
Challenge: Improving the Accounts Receivable Business Process and Collector Productivity 41
Outcome: Better Visibility to Track the Total Receivables View Across the Entire Collection Process and Reduction in Labor Cost 43
Challenge: Predicting Disruptions in the Supply Chain 43
Outcome: Number of Listening Events Increased Tenfold and Local Language Listening Proved Valuable 44
Lessons Learned 45
Endnotes 48
Chapter 4: Anticipating the Financial Future 51
Perspective: Big Data and Analytics Increase Value of Finance Team 51
Getting the Basics in Place 52
Creating an Analytics Culture 53
Challenge: Attaining Operational Efficiency, Managing Risk, and Informing Decisions 55
Tracking Spending: The Worldwide Spend Project 55
Outcome: More Efficient and More Effective Spend Forecasting 57
Keeping Up with Reporting Requirements: The Accelerated External Reporting (AER) System 58
Outcome: Improved Statutory and Tax Reporting and Analytics 59
Challenge: Balancing Risk and Reward 59
Country Financial Risk Scorecard 59
Outcome: Country Financial Risk Scorecard Uses Big Data to Monitor Trends and Minimize Risk 61
Challenge: Validating Acquisition Strategy 62
The Mergers and Acquisitions Analytics Project 62
Outcome: Mergers and Acquisitions Analytics Improves Success Rate 62
The Smarter Enterprise Enablement (SEE) Initiative 64
Outcome: SEE Project Transforms Strategic Planning and Its Novel Approach Leads to Patent Applications 64
What’s Next for IBM Finance? 64
Lessons Learned 65
Endnotes 66
Chapter 5: Enabling Analytics Through Information Technology 67
Perspective: Applying Analytics to IT and Enabling Big Data and Analytics Across an Enterprise 67
Challenge: Deciding When to Modernize Servers 69
Outcome: Increase in Application Availability 70
Challenge: Detecting Security Incidents 71
Outcome: Increased Detection of Security Incidents 71
Enabling the Transformation to a Smarter Enterprise 71
Developing Enterprise-Wide Big Data and Analytics Applications 71
Partnering with Business Areas to Develop Social Media Analytic Solutions for Customer-Centric Outcomes 73
Developing an Information Agenda and Processes for Governance and Security of Data 73
Providing a Big Data and Analytics Infrastructure 76
Lessons Learned 77
Endnotes 78
Chapter 6: Reaching Your Market 81
Perspective: Using Analytics to Reach and Engage with Clients 81
A Signature Client Experience 83
Marketing-Related Analytics Hiring Soaring 84
Agility Is Key 84
Challenge: Developing the Data Foundation and Analytics Capability to Enable a Signature Client Experience 85
Outcome: Individual Data Master to Provide Client-Level Insights 87
Challenge: Providing a Real-Time View into Effectiveness of Marketing Actions: Performance Management 87
Outcome: Marketing Efficiencies Realized and Transformation of Marketing Enabled 88
Challenge: Going Beyond Correlation to Determine Causal Effects of Marketing Actions 90
Outcome: System Deals with Special Terms and Conditions Added Grew from 67% to 98% over Three Quarters 90
Challenge: Tapping into Analytics Passion to Provide New Insights to Inform IBM’s Digital Strategy 92
Outcome: Insights from Diverse Teams Provided the Evidence Needed to Make Changes to the Digital Strategy 93
Lessons Learned 94
Endnotes 94
Chapter 7: Measuring the Immeasurable 97
Perspective: Software Development Organization Optimizes the Highly Skilled Workforce 97
Challenge: Creating a Common View of Development Expense to Enable Decision Making 99
Development Expense Baseline Project 99
Outcome: Development Expense Baseline Project Proves That the Immeasurable Can Be Measured 105
Lessons Learned 105
Endnotes 106
Chapter 8: Optimizing Manufacturing 107
Perspective: Applying Analytics to Manufacturing and Product Management 107
Challenge: Scheduling a Complex Manufacturing Process in a Semiconductor Fab 108
Outcome: Reduced Production Times 111
Challenge: Enhancing Yield in the Manufacturing of Semiconductors 111
Outcome: Cost Savings Due to Yield Improvement 112
Challenge: Reducing the Time to Detect Aberrant Events 113
Outcome: Engineers Take Action 114
Challenge: Simplifying the Hardware Product Portfolio 115
Outcome: Significant Reduction of Hardware Product Portfolio 116
Lessons Learned 117
Endnotes 117
Chapter 9: Increasing Sales Performance 121
Perspective: Using Analytics to Optimize Sales Performance--Inside and Out 121
How IBM Approached Leveraging Analytics in Sales Organizations 122
Using Analytics to Build a Business Case for Inside Sales 123
Challenge: Deploying Sellers for Maximum Revenue Growth by Account 124
Outcome: Increased Sales Performance 126
Challenge: Deploying Sellers Within a Territory 126
Outcome: Increased Territory Performance 127
Challenge: Determining the Optimal Sales Coverage Investment by Account 128
Outcome: Increased Revenue and Increased Productivity 130
Online Commerce 130
Challenge: Creating a Smarter Commerce B2B Solution to Drive Cross-Company Efficiencies 132
Outcome: An Analytics-Based, Client-Focused Business Case Wins Approval 133
Lessons Learned 135
Endnotes 137
Chapter 10: Delivering Services with Excellence 139
Perspective: Leveraging Analytics in a Services Business 139
Challenge: Developing New Business 141
Outcome: Increased Signings, Revenue, and Pipeline 142
Challenge: Predicting Risk of Contracts 142
Outcome: Deployment of Financial Risk Analytics 143
Challenge: Optimizing Workforce Performance 143
Outcome: Large Cost Savings, Improved Productivity, and Faster Client Response Times 147
Challenge: Getting Early Warning About Problems 147
Outcome: Timely Intelligence to Delivery Teams to Help Satisfy Clients 148
Lessons Learned 148
Endnotes 149
Chapter 11: Reflections and a Look to the Future 151
The Journey Continues 151
Reflections 153
Transactional Data 155
Simulation 156
Alerts 157
Forecasting 158
The Future 159
Growth of Data 160
Unstructured Data 161
Cognitive Computing 163
Endnotes 164
Appendix A: Big Data and Analytics Use Cases 165
Glossary: Acronyms and Definitions of Key Big Data and Analytics Terms 175
Index 183