The VALUE DRIVEN DATA Workbook: Practical exercises, templates, and tools for data value creation

ENDORSEMENTS FOR VALUE DRIVEN DATA
ABOUT THE AUTHOR
ACKNOWLEDGEMENTS
INTRODUCTION
PART ONE
VISION: DISCOVERING AND CAPTURING DATA VALUE OPPORTUNITIES
Chapter 01
	Enhancing Understanding of Data Vision
		Exercise 1: Defining Data Value
		Exercise 2: Interpreting Data Vision
		Exercise 3: Differentiating Data Vision
		Exercise 4: Macro Data Vision
		Exercise 5: Separating Signal from Noise
		Exercise 6: Signal from Noise Optimization Techniques
Chapter TWO
	Capturing Data Visions
		Exercise 1: Identifying Budget Challenges
		Exercise 2: Reframing Budget Challenges
		Exercise 3: Time Horizon and Budget Challenges
		Exercise 4: Current State Assessments
		Exercise 5: First Principle Thinking
		Exercise 6: Vision Perspectives and Leadership Style
Chapter THREE
	Why Data Visions of All Size Matter
		Exercise 1: Understanding Data Accessibility Challenges
		Exercise 2: Analysing Data Granularity and Timeliness
		Exercise 3: Identifying Data Quality Issues
		Exercise 4: Recognizing Foundational Data Analysis Challenges
		Exercise 5: Exploring Data Vision Breakdown
		Exercise 6: Clear Goals Analysis
		Exercise 7: Tangible Purpose Exploration
		Exercise 8: Enriching Data Vision Techniques
		Exercise 9: Strategic Decision Enhancement
		Exercise 10: Reflection and Application
Chapter FOUR
	The Destructive Impact of Data Vision Misalignment
		Exercise 1: Evaluating Current Data Capabilities
		Exercise 2: Identifying Challenges with Data Vision Alignment
		Exercise 3: Detecting and Defusing Data Vision Displacement
		Exercise 4: Embracing Alternative Viewpoints
		Exercise 5: Framework for Disruption Detection
		Exercise 6: Unlocking the Power of Diversity
		Exercise 7: Phenomenology and Alignment
CHAPTER FIVE
	Simplifying Data Vision Misalignments
		Exercise 1: Understanding the Three-Step Process for Data Vision Alignment
		Exercise 2: Conceptualizing Data Vision Alignment
		Exercise 3: Analysing the Streamlined Three-Step Process
		Exercise 4: Identifying Obstacles to Data Vision Alignment
		Exercise 5: Examining Speed as a Key Factor in Data Vision Alignment
		Exercise 6: Uncovering Data Quality Matters in Data Vision Alignment
		Exercise 7: Addressing Technology and Infrastructure Concerns
		Exercise 8: Reflecting on Data Vision Alignment Challenges
		Exercise 9: Applying the Streamlined Approach to Data Vision Alignment
PART TWO
OBSTACLES: THE THINGS THAT STAND BETWEEN DATA VISIONS AND DATA VALUE REALIZATION
Chapter SIX
	Obstacles of the Past
		Exercise 1: Reflection on Heritage and Legacy Data Platforms
		Exercise 2: Exploring Data Use within a Legacy System Context
		Exercise 3: Shifting from Obstacles to Opportunities
		Exercise 4: Legacy Data for Decision-Making
		Exercise 5: Heritage Skills and Capabilities
		Exercise 6: Complacencies from Past Successes
		Exercise 7: Data Quality Assessment
		Exercise 8: Measuring Data Quality Impact
		Exercise 9: The Value of Timeliness
		Exercise 10: Overcoming Resistance to Change
		Exercise 11: Evaluating Buy vs. Build Trade-offs
Chapter SEVEN
	Enhancing Understanding of Obstacles of the Future
		Exercise 1: Reflecting on Misunderstandings and Mistaken Assumptions
		Exercise 2: Identifying Disconnects Resulting from Mistaken Assumptions
		Exercise 3: Analysing Misplaced Assumptions Driving Inappropriate Solutions
		Exercise 4: Addressing Unknown Obstacles
		Exercise 5: Understanding Personal Data Protection
		Exercise 6: Reflection and Analysis
		Exercise 7: Case Study Analysis
		Exercise 8: Applying Strategies
		Exercise 9: Reflection and Action Plan
Chapter EIGHT
	Obstacles of the Present
		Exercise 1: Skills Matrix Analysis
		Exercise 2: Leadership Competency Assessment
		Exercise 3: Task Distribution Analysis
		Exercise 4: Decision Leadership Assessment
		Exercise 5: Reflection on Data Strategy
		Exercise 6: Responsible Leadership for High-Performing Teams
		Exercise 7: Overcoming Complexity and Complications
		Exercise 8: Seeing Beyond the Challenges
		Exercise 9: Fixing a Flying Plane - Transition and Migration
		Exercise 10: Reflection on Growth Limiting Factors
		Exercise 11: Analysing Obstacles for Future Growth
		Exercise 12: Critical Steps for Ensuring the \"Right\" Speed of Execution
		Exercise 13: Reducing Defensiveness for Collaborative Efforts
		Exercise 14: Addressing Budgetary and Funding Issues
		Exercise 15: Utilising the VOV Model for Commercial Value Connectivity
		Exercise 16: Understanding Minimum and Maximum Viability
PART THREE
VALUE: IDENTIFYING, CAPTURING AND COMMUNICATING DATA VALUE
Chapter NINE
	Capturing Data Value Propositions
		Exercise 1: Understanding Data Value Propositions
		Exercise 2: Bottom-Line Value (BLV) Optimization
		Exercise 3: Top-Line Value (TLV) Optimization
		Exercise 4: Cost Avoidance Value (CAV)
		Exercise 5: Understanding Data Costs
		Exercise 6: A Business Stakeholder Perspective of Data Value Capture
		Exercise 7: RTB and CTB Optimization
		Exercise 8: Reflecting on Data Value Propositions
		Exercise 9: Applying Data Strategies
		Exercise 10: Evaluating Data Analytics Initiatives
		Exercise 11: Case Study Analysis
Chapter TEN
	Measuring Data Value for Business Case and Operational Assurance
		Exercise 1: Macro vs. Micro Data Value Measurement
		Exercise 2: Understanding Business Stakeholder Perspectives
		Exercise 3: Assessing Data Value in a Multifaceted Operation
		Exercise 4: Articulating Data Value Propositions
		Exercise 5: Addressing Cost-Avoidance through Data Value
		Exercise 6: Macro-Level Data Value Measurement
		Exercise 7: Generating a Data Value Business Case
		Exercise 8: Reflection and Application
		Exercise 9: Macro and Micro Approaches to Data Value Measurement
		Exercise 10: Stakeholder Perspectives on Data Value Measurement
		Exercise 11: Generating a Data Value Business Case
		Exercise 12: Data Value for Different Departments
Chapter ELEVEN
	Understanding the Data Value Measurement Lifecycle
		Exercise 1: Estimation Phase
		Exercise 2: Delivery Phase
		Exercise 3: Operations Phase
		Exercise 4: The Triple BAT Model for Data Value Measurement
		Exercise 5: The Application of the Triple BAT Model
		Exercise 6: Milestones of the Data Value Measurement Lifecycle
		Exercise 7: Challenges in Data Value Estimation
		Exercise 8: Challenges in Data Value Validation
		Exercise 9: Challenges in Data Value Monitoring
Chapter TWELVE
	Enhancing Understanding of Data Value Profits and Losses
		Exercise 1: Vision and Value Proposition
		Exercise 2: Understanding the Impact of Returns
		Exercise 3: Estimating Value Returns on Investment
		Exercise 4: Identifying Challenges for Data Value P&L
		Exercise 5: Reflecting on the Challenges for a Data Value P&L
		Exercise 6: Simplifying Data Value Assessment
		Exercise 7: Increasing Resource Autonomy
		Exercise 8: Reducing Interdependencies
		Exercise 9: Overcoming Traditional Obstacles with Silos
		Exercise 10: Case Study Analysis
		Exercise 11: Essential Preconditions for a Data Value P&L
		Exercise 12: Reflection and Application
		Exercise 13: Group Discussion
		Exercise 14: Action Plan
Chapter THIRTEEN
	Presenting Data Value to Executives and the Board
		Exercise 1: Presentation Structure Analysis
		Exercise 2: Unexpected Findings
		Exercise 3: Identifying Obstacles
		Exercise 4: Focusing on Ambitious Visions and Associated Value
		Exercise 5: Transforming Data through Connected Organisational Silos
		Exercise 6: Role Analysis and Reflection
		Exercise 7: Technology Platforms and Data Transformation
		Exercise 8: People and Culture in Data Transformation
		Exercise 9: Decoupled Data Value Framework
		Exercise 10: Unpacking Data Value Presentation Slides
CONCLUSION: BRINGING IT ALL TOGETHER
YOUR JOURNEY CONTINUES: BUILDING ON \"VALUE DRIVEN DATA\"
	Empower Yourself
	Empower Others