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Decision Management Systems: A Practical Guide to Using Business Rules and Predictive Analytics
- By James Taylor
- Published Sep 16, 2011 by IBM Press. Part of the IBM Press series.
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Description
- Copyright 2012
- Dimensions: 6" x 9"
- Edition: 1st
- eBook
- ISBN-10: 0-13-288443-7
- ISBN-13: 978-0-13-288443-3
"A very rich book sprinkled with real-life examples as well as battle-tested advice.”
—Pierre Haren, VP ILOG, IBM
"James does a thorough job of explaining Decision Management Systems as enablers
of a formidable business transformation.”
—Deepak Advani, Vice President, Business Analytics Products and SPSS, IBM
Build Systems That Work Actively to Help You Maximize Growth and Profits
Most companies rely on operational systems that are largely passive. But what if you could make your systems active participants in optimizing your business? What if your systems could act intelligently on their own? Learn, not just report? Empower users to take action instead of simply escalating their problems? Evolve without massive IT investments?
Decision Management Systems can do all that and more. In this book, the field’s leading expert demonstrates how to use them to drive unprecedented levels of business value. James Taylor shows how to integrate operational and analytic technologies to create systems that are more agile, more analytic, and more adaptive. Through actual case studies, you’ll learn how to combine technologies such as predictive analytics, optimization, and business rules—improving customer service, reducing fraud, managing risk, increasing agility, and driving growth.
Both a practical how-to guide and a framework for planning, Decision Management Systems focuses on mainstream business challenges.
Coverage includes
- Understanding how Decision Management Systems can transform your business
- Planning your systems “with the decision in mind”
- Identifying, modeling, and prioritizing the decisions you need to optimize
- Designing and implementing robust decision services
- Monitoring your ongoing decision-making and learning how to improve it
- Proven enablers of effective Decision Management Systems: people, process, and technology
- Identifying and overcoming obstacles that can derail your Decision Management Systems initiative
Sample Content
Table of Contents
Foreword by Deepak Advani xv
Foreword by Pierre Haren xviii
Preface xix
Acknowledgments xxiii
Part I The Case for Decision Management Systems 1
Chapter 1 Decision Management Systems Are Different 3
Agile 4
Analytic 8
Adaptive 15
Chapter 2 Your Business Is Your Systems 19
Changing Expectations 20
Changing Scale 23
Changing Interactions 25
Chapter 3 Decision Management Systems Transform
Organizations 29
A Market of One 30
Always On 33
Breaking the Ratios 36
Crushing Fraud 39
Maximizing Assets 41
Maximizing Revenue 44
Making Smart People Smarter 45
Conclusion 46
Chapter 4 Principles of Decision Management Systems 47
Principle #1: Begin with the Decision in Mind 48
Principle #2: Be Transparent and Agile 57
Principle #3: Be Predictive, Not Reactive 60
Principle #4: Test, Learn, and Continuously Improve 63
Summary 67
Part II Building Decision Management Systems 69
Chapter 5 Discover and Model Decisions 71
Characteristics of Suitable Decisions 72
A Decision Taxonomy 81
Finding Decisions 87
Documenting Decisions 99
Prioritizing Decisions 111
Chapter 6 Design and Implement Decision Services 115
Build Decision Services 116
Integrate Decision Services 147
Best Practices for Decision Services Construction 152
Chapter 7 Monitor and Improve Decisions 157
What Is Decision Analysis? 158
Monitor Decisions 159
Determine the Appropriate Response 167
Develop New Decision-Making Approaches 176
Confirm the Impact Is as Expected 184
Deploy the Change 187
Part III Enablers for Decision Management Systems 189
Chapter 8 People Enablers 191
The Three-Legged Stool 191
A Decision Management Center of Excellence 196
Organizational Change 206
Chapter 9 Process Enablers 211
Managing a Decision Inventory 211
Adapting the Software Development Lifecycle 215
Decision Service Integration Patterns 221
A Culture of Experimentation 222
Moving to Fact-Based Decisioning 228
The OODA Loop 232
Chapter 10 Technology Enablers 235
Business Rules Management Systems 235
Predictive Analytics Workbenches 238
Optimization Systems 243
Pre-Configured Decision Management Systems 244
Data Infrastructure 247
A Service-Oriented Platform 255
Epilogue 263
Bibliography 267
Index 273