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| Foreword | |
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| Preface | |
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| Acknowledgments | |
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| About the Authors | |
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| Introduction | |
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| The Smart Enough Systems Manifesto | |
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| Operational Decisions Are Important | |
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| Organizations are perceived through the lens of the decisions they make | |
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| Lots of small decisions add up | |
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| All decisions an organization makes should be managed as though they are deliberate | |
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| Operational Decisions Can and Should Be Automated | |
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| High-volume, operational decisions can and should be automated | |
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| Traditional technology approaches won't succeed in automating decisions | |
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| The overall effectiveness of automated decisions must be measured, tracked, and improved over time | |
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| Taking Control of Operational Decisions Is Increasingly a Source of Competitive Advantage | |
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| The Need for Smart Enough Systems | |
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| The Importance of Operational Decisions | |
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| Strategy Drives Decision Making | |
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| Strategy Is Not Static | |
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| Operational Decisions Matter | |
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| Operational Decisions Are Under Pressure | |
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| Operational Decision Making as a Corporate Asset | |
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| Characteristics of Operational Decisions | |
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| Characteristics of Corporate Assets | |
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| Introducing Smart Enough Systems | |
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| Characteristics of Smart Enough Systems | |
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| Current Approaches Fail | |
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| Decision Management Is Required | |
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| Introducing SmartEnough Logistics | |
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| Enterprise Decision Management | |
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| Introducing Enterprise Decision Management | |
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| The EDM Process | |
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| The EDM Definition | |
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| Key Features | |
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| Characteristics of Decision-Making Problems | |
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| Operational Decisions | |
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| Hidden Decisions | |
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| Finding Hidden Decisions | |
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| Enterprise Decision Management and Smart Enough Systems | |
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| The ROI for Enterprise Decision Management | |
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| Cost Reductions | |
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| Revenue Growth | |
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| Strategic Control | |
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| Costs of Enterprise Decision Management | |
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| Introducing Decision Yield | |
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| Why Aren't My Systems Smart Enough Already? | |
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| How Did We Get Here? | |
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| Problems with Data | |
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| The Reporting Gap | |
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| Enter the Data Warehouse | |
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| Business Intelligence | |
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| Operational Business Intelligence | |
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| Data Mining, Predictive Reporting, and Operations Research | |
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| Problems with Programs | |
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| The Weight of Legacy Code | |
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| Artificial Intelligence and Expert Systems | |
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| 4GLs and Other User-Friendly Tools | |
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| Business Rules | |
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| Buying Solutions | |
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| Processes and Services | |
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| Moving at the Speed of People | |
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| The Training and Adoption Lag | |
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| Procedure Manuals and Intranets | |
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| Knowledge Management | |
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| SmartEnough's Experience | |
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| Core Concepts | |
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| Introduction | |
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| Finding the Right Decisions | |
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| Decision Services | |
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| Data and Analytics | |
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| Data Requirements for Decision Making | |
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| Data Requirements for Analytic Insight | |
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| Uses for Analytic Models | |
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| Business Rules | |
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| Adaptive Control | |
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| Deployment | |
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| More Information | |
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| Data and Analytics | |
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| Architectural Overview of Data and Analytics | |
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| Concepts in Applying Analytics | |
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| Different Types of Data | |
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| Internal and External Data | |
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| Event-Based and Stored Data | |
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| Characteristics of Predictive Analytic Models | |
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| Modeling Techniques | |
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| Lift | |
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| Scorecards | |
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| Variables | |
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| Standards | |
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| Technology for Managing Data and Analytic Models | |
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| Operational Databases | |
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| Data Warehouses | |
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| Content Management Systems | |
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| Search Engines | |
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| Business Intelligence and Performance Management | |
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| Stream-Processing-Engines | |
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| Repositories | |
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| Data Preparation Tools | |
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| Modeling Tools | |
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| Model Deployment | |
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| Automated Tuning | |
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| The Model Development Process | |
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| Determine the Desired Outcome | |
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| Determine Data Requirements | |
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| Prepare the Data | |
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| Conduct Data Mining and Analysis | |
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| Develop the Model | |
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| Validate the Model | |
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| Deploy the Model | |
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| Tune the Model | |
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| Business Rules | |
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| Architectural Overview | |
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| Concepts in Business Rules | |
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| Business Rules | |
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| Rule Syntax | |
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| Decision Flows | |
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| Patterns | |
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| Rule Sets | |
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| Rule Set Metaphors | |
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| Execution Modes | |
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| Semantics and Business Rules | |
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| Metadata and Business Rules | |
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| Model-Driven Design and Business Rules | |
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| Rule Standards | |
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| Business Rules Technology | |
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| Repositories | |
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| Design Tools | |
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| Business User Rule Maintenance Applications | |
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| Rule Templates | |
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| Deployment Management | |
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| The Rule Development Process | |
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| Rule Development | |
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| Rule Validation and Testing | |
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| Rule Maintenance | |
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| Rule Deployment | |
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| Adaptive Control | |
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| Architectural Overview | |
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| Concepts in Adaptive Control | |
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| Champion/Challenger Approach | |
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| Experimental Design | |
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| Optimization Techniques | |
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| Decision Models | |
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| Efficient Frontier | |
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| Business Simulation | |
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| Adaptive Control Technology | |
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| Modeling Tools | |
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| Optimization Engine or Solver | |
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| Production Environment | |
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| Simulation/Testing Environment | |
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| Tools for Business Users | |
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| The Adaptive Control Process | |
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| Champion/Challenger Setup | |
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| Experimental Design | |
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| Decision Analysis | |
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| Optimization Model Design | |
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| Simulation | |
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| Readiness Assessment | |
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| Overview of Readiness Assessment | |
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| Business and IT Collaboration | |
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| Data Readiness | |
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| Analytic Understanding | |
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| Willingness to Change | |
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| Management Focus on Operations | |
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| Getting There from Here | |
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| Themes in EDM Adoption | |
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| Adopting EDM | |
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| Piecemeal Approach | |
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| A First Business Rules Project | |
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| A First Analytic Project | |
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| Building Critical Foundations for EDM | |
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| Local Decision Management | |
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| Integrating Rules and Analytics | |
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| Using Champion/Challenger | |
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| Expansion | |
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| Improve the Decision Management Foundations | |
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| Overlapping and Adjacent Problems | |
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| Broaden the Analytic Base | |
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| Manage Scenarios | |
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| Steady State: Enterprise Decision Management for Real | |
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| What SmartEnough Logistics Did | |
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| Readiness Assessment | |
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| Using Pieces | |
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| Decision Management | |
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| Expansion | |
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| EDM Adoption | |
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| Extending EDM | |
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| Integrated Decision Models | |
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| Time-Sequenced Decisions | |
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| Automated Modification of Decisions | |
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| Bringing Text into the Mainstream | |
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| Independent Agents | |
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| EDM and the IT Department | |
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| Complementing, Solving, and Enabling | |
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| Decision Services and the EDM Ecosystem | |
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| Concepts in Deploying Decision Services | |
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| Deployment Process | |
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| Complementing Your IT Architecture | |
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| Building on SOA | |
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| Completing Application Decomposition | |
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| Avoiding Brain-Dead Processes | |
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| Better Decisions, Not Just Better Data | |
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| Using Customer Interests and Social Media | |
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| Solving IT Problems | |
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| Ending Maintenance as You Know It | |
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| The Requirements Tar Pit | |
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| Channel Consistency | |
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| Multiplatform Consistency | |
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| Commodity Enterprise Applications | |
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| Enabling IT Capabilities | |
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| Self-Service | |
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| Making Mobile Matter | |
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| Smart Event Processing and Business Activity Monitoring | |
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| Model-Driven Engineering | |
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| Smart Outsourcing | |
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| Corporate Performance Management | |
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| Extending Your Software Development Life Cycle to Support EDM | |
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| General Approach to Adapting an SDLC | |
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| Rational Unified Process and UML | |
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| Agile Approaches | |
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| Closing Thoughts | |
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| Recap: Smart Enough Systems | |
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| Why Now? | |
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| What Next? | |
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| Decision Yield as a Way to Measure ROI | |
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| Overview of Decision Yield | |
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| Measuring Decision Yield | |
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| Develop Questions to Assess Decision Performance | |
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| Calculate Your Yield for the Five Dimensions | |
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| Compare Your Decision Yield to Others | |
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| Using Decision Yield to Drive Planning | |
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| Conduct a Decision Audit | |
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| Optimize Decision Performance over Time | |
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| Evaluate Specific Opportunities | |
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| Closing Thoughts | |
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| Index | |