Augmented Analytics

Foreword
Preface
Who Should Read This Book?
Learning Objectives
Navigating This Book
Conventions Used in This Book
O’Reilly Online Learning
How to Contact Us
Acknowledgments

1. The Business Transformation
Why Businesses Are Transforming
Factor 1: The Speed of Change
Factor 2: The Convergence of Multiple Technologies
Factor 3: The Importance of Data
Factor 4: Changing Consumer Behavior and Customer Centricity
Industries Heavily Impacted by Digital Transformation
The Consequences for Your Business
There’s No Analytics Transformation Without Augmented Analytics
A Data-Driven Culture
The “People Problem” and the Limits of Upskilling
Conclusion

2. The Analytics Problem
Finding Your Analytics Purpose
Competition and Customer Expectations
Operational Efficiency
Availability and User Friendliness
Innovation
Regulatory Compliance
How to Start Your Analytics Journey
Industry Examples
Ecommerce
Healthcare
Manufacturing
Financial Services
Government
Commercial Insurance
The Concept of Analytical Maturity
Determine Your Current—and Future—Data Maturity
Stage 1: Data Reactive
Stage 2: Data Active
Stage 3: Data Progressive
Stage 4: Data Fluent
Conclusion

3. Understanding Augmented Analytics
Definition
The Five I’s of Augmented Analytics
Overcoming the Limitations of Traditional Analytics Approaches
Augmented Workflows
The Benefits of Augmented Analytics
AA Gives Nonexpert Users a Better Experience
Automated Integration Provides More Complete Insights
AA Gives Faster, More Efficient Insights
Standardization Reduces Human Errors and Bias for Better Insights
AA Tools Are Easier to Scale Up
AA Reaches Further Afield to Generate Unexpected Insights
Overcoming Bias
Key Enablers of Augmented Analytics
Automation and AI
Artificial Intelligence: The Five Archetypes
The Limitations of Augmented Analytics
The Challenges of Augmented Analytics
Conclusion

4. Preparing People and the Organization for Augmented Analytics
Tailoring Augmented Analytics for Different Organizational Roles
Analytics Leader
Analytics Translator
Analytics User
Analytics Professional
Analytics Transformation Manager
Summary of Key Roles
The Center of Excellence
Creating a Center of Excellence
Approaches to Organizing a CoE
Driving Transformational Change with the Influence Model
Fostering Understanding and Conviction
Reinforcing with Formal Mechanisms
Developing Talent and Skills
Role Modeling
Cultivating a Data-Literate Culture
Cultivating Analytics Awareness
Storytelling with Data
Embracing Data-Driven Management
Leading in the Age of AI
The Enablement Program
Training Formats for Analytics Leaders
Training Formats for Analytics Translators
Data Literacy Training
Technical Training
Conclusion

5. Augmented Workflows
Types of Workflow Augmentation
Fixed-Rule, High-Confidence Augmentation
Idea and Insight Enrichment
Conversational Augmentation
Contextual Augmentation
Collaborative Augmentation
The Analytics Use-Case Approach: Finding Workflows to Augment
Phase 1. Idea: The Initial Spark
Phase 2. Concept: Structuring the Idea
Phase 3. Proof of Concept: Testing the Waters
Phase 4. Prototyping: Shaping the Concept
Phase 5. Pilot: The Test Run
Phase 6. Product: Full Deployment
Making the Make-or-Buy Decision
Decision Scenarios
Overarching Success Factors
Balancing Automation and Integration
The Use-Case Library
Technical Requirements for Implementing AA
Infrastructure Setup Challenges
IT System Integration Challenges
Governance Challenges
Conclusion

6. Augmented Frames
Business Objects and Frame Units
Understanding Frames
Key Features of Frames
Frame Types
Frame Engines
Frame Engine Types
Attribute Aggregation
Engine Interfaces
Result Objects
Implementation Challenges
Frame Agent
Dissolving Frames
Identifying Types
Translating Frame Units
Enriching Frames
Orchestrating Calls
Standardizing Results
Central Repository
Monitoring and Performance Analysis
User Access and Security
User Interface
Frame Dissolver
Frame Adapter
Dealing with Group Variables
Dealing with Bottom-up Business Object Structures
Dealing with Unconnected Business Objects
Frame Creator
Case Study: AP/TP Frame Engine
Infrastructure and Technology
An Iterative Approach to Introducing Augmented Frames
Iteration 1: Free Frames and Frame Engines
Iteration 2: A Frame Agent and Frame Adapter
Iteration 3: The Frame Dissolver, ID Frames, and Indexed Frames
Iteration 4: Static Frames
Iteration 5: Dynamic Frames
Iteration 6: The Frame Creator
Iteration Wrap-up
Conclusion

7. Applied Examples
The Underwriting Process
Types of Augmented Workflows in Underwriting
The Workflows in Detail
Example 1: Location Workflow
Situation and Problem Statement
Solution Overview
Solution Breakdown
Example Summary
Example 2: Benchmarking Workflow
Situation and Problem Statement
Solution Overview
Solution Breakdown
Example Summary
Example 3: Proposal Workflow
Situation and Problem Statement
Solution Overview
Solution Breakdown
Example Summary
Example 4: Improved Forecasting in Agile Projects
Situation and Problem Statement
Solution Overview
Solution Breakdown
Example Summary
Example 5: Quick Sales Intelligence
Situation and Problem Statement
Solution Overview
Solution Breakdown
Example Summary
Conclusion

Index
About the Authors