A Consulting Framework for Assessing Data-Driven and AI-Supported Business Process Optimization Opportunities

1. Introduction 1.1 Background and Motivation 1.2 Research Objectives 1.3 Structure of the Document 2. Theoretical Background 2.1 Business Process Optimization 2.2 Data-Driven Decision Making 2.3 AI in Business Processes 3. Consulting Framework Overview 3.1 Framework Development Approach 3.2 Key Components of the Framework 3.3 Benefits of the Framework 4. Assessment of Current Business Processes 4.1 Analyzing Existing Processes 4.2 Identifying Optimization Opportunities 4.3 Setting Performance Metrics 5. Data Collection and Analysis 5.1 Sources of Business Data 5.2 Data Quality and Preparation 5.3 Analytical Tools and Techniques 6. AI Integration in Business Processes 6.1 Identifying AI Use Cases 6.2 AI Implementation Strategies 6.3 Challenges of AI Integration 7. Case Studies and Practical Applications 7.1 Example Case Study One 7.2 Example Case Study Two 7.3 Lessons Learned from Case Studies 8. Conclusion and Future Directions 8.1 Summary of Findings 8.2 Limitations of the Study 8.3 Suggestions for Future Research