Decision Management Systems : A Practical Guide to Using Business Rules and Predictive Analytics

Companies today are their systems. Customers'experience is driven by the behavior of those systems. Product prices, discounts, availability, and eligibility are what the systems say they are, based on their embedded data and logic. Yet most companies rely on operational systems that are purely or largely passive. What if you could make those systems active participants in running the business more effectively? Decision Management makes this possible - and, in this book, the field's leading expert shows business leaders how to take full advantage of it. James Taylor shows how to go beyond traditional, rigid approaches to automating decision-making by integrating operational and analytic technologies to create agile, flexible systems that learn. Through multiple case studies from his own consulting work and IBM's enterprise customers, Taylor demonstrates how to combine technologies such as predictive analytics, optimization and business rules - improving customer service, reducing fraud, managing risk, increasing agility, and driving growth. Decision Management Systemsoffers trusted advice for applying Decision Management to your own problems and environment. Both a practical how-to guide and a framework for planning, it shows how to refocus existing analytics and business rules initiatives for greater long-term value, and overcome the specific obstacles that can derail your Decision Management initiative.

James Taylor is the CEO of Decision Management Solutions, and is the leading expert in how to use business rules and analytic technology to build Decision Management Systems. James is passionate about using Decision Management Systems to help companies improve decision-making and develop an agile, analytic, and adaptive business. He has more than 20 years working with clients in all sectors to identify their highest-value opportunities for advanced analytics, enabling them to reduce fraud, continually manage and assess risk, and maximize customer value with increased flexibility and speed.

In addition to strategy consulting, James has been a keynote speaker at many events for executive audiences, including ComputerWorld’s BI & Analytics Perspectives, Gartner Business Process Management Summit, Information Management Europe, Business Intelligence South Africa, The Business Rules Forum, Predictive Analytics World, IBM’s Business Analytics Forum, and IBM’s CIO Leadership Exchange. James is also a faculty member of the International Institute for Analytics.

In 2007, James wrote Smart (Enough) Systems: How to Deliver Competitive Advantage by Automating Hidden Decisions (Prentice Hall) with Neil Raden, and has contributed chapters on Decision Management to multiple books, including Applying Real-World BPM in an SAP Environment, The Decision Model, The Business Rules Revolution: Doing Business The Right Way, and Business Intelligence Implementation: Issues and Perspectives. He blogs on Decision Management at www.jtonedm.com and has written dozens of articles on Decision Management Systems for CRM Magazine, Information Management, Teradata Magazine, The BPM Institute, BeyeNetwork, InformationWeek, and TDWI’s BI Journal.

He was previously a Vice President at Fair Isaac Corporation, spent time at a Silicon Valley startup, worked on PeopleSoft’s R&D team, and as a consultant with Ernst and Young. He has spent the last 20 years developing approaches, tools, and platforms that others can use to build more effective information systems.

He lives in Palo Alto, California with his family. When he is not writing about, speaking on or developing Decision Management Systems, he plays board games, acts as a trustee for a local school, and reads military history or science fiction.

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