Why do organisations still struggle to realise meaningful value from data and artificial intelligence, despite decades of technological progress?
Despite decades of investment in data platforms, analytics tools and artificial intelligence, many organisations still struggle to turn data into real business impact. Too often, data initiatives become trapped in cycles of pilots, fragmented platforms and growing technical complexity, while the promised value remains just out of reach. This book explores why that happens and what organisations must do differently to unlock the true potential of data and AI.
At the centre of the book is the Enabling Data Model, a new mental model for designing organisations where data, analytics and AI can scale. Rather than focusing solely on technology or isolated innovation projects, the model highlights the organisational foundations required for data work to succeed, aligning strategy, governance, technology and people around the shared goal of generating value from data.
Accompanied by a Data Manifesto that articulates the first principles of enabling data, the book helps leaders rethink how data initiatives should be structured, governed and sustained in complex organisations. Readers will gain:
- A clear explanation of why many data and AI initiatives fail to deliver impact
- A new mental model for aligning data capabilities with business strategy and innovation
- Practical tools including diagnostic rubrics, data personas, use case templates and the Platform Fit Canvas to translate ideas into action
Combining strategic insight with practical guidance, this book equips senior data leaders, CDOs, product leaders and analysts with the perspectives and tools needed to move beyond experimentation and build the foundations required for data, analytics and AI to generate lasting business value.
Table of Contents:
Chapter 1: Groundhog Day
Chapter 2: The Promise of AI
Chapter 3: The HelloFresh Data Story
Chapter 4: The Dark Side of the Role
Chapter 5: The Data Manifesto
Chapter 6: A Model in Practice
About the Author :
David Castro-Gavino has nearly three decades of experience helping organisations turn data, analytics and artificial intelligence into real business value. He currently serves as Executive Director at AstraZeneca, where he leads data deployment for Axial, the company’s enterprise-wide ERP transformation. Previously he led the global data transformation at HelloFresh during a period of rapid international growth, establishing the foundations for scalable analytics and AI across the organisation. A regular speaker at international conferences, he has been recognised in the DataIQ 100. He is based in London, UK.
Boyan Angelov is Principal Data Strategist at Exxeta, an innovative technology and consultancy company. He has previously published Elements of Data Strategy and Python and R for the Modern Data Scientist (with Rick J. Scavetta). Throughout his career, he has advised organisations of all sizes on data and AI-powered transformation in roles ranging from data strategist to CTO and Principal. He is based in Berlin, Germany.
