Overview
For October, the Book of the Month is Enabling Data: A New Model for Data-Driven Success in Your Organization by David Castro-Gavino and Boyan Angelov. A lot of books we’ve featured recently focus on AI, so it’s refreshing to pick up a book that asks why so many data and AI efforts stall before they ever deliver value. Let’s dive right in.
The book opens with a foreword from Tom Redman that sets a deliberately high bar. The authors take that challenge head on. They’re quick to say this isn’t another framework. It’s a mental model built from patterns they’ve seen across their careers. Angelov kicks things off with Groundhog Day, pointing out that data leaders keep reliving the same problems. His diagnosis is complexity, driven by what he calls “merchants of complexity,” the vendors and consultants who sell us more moving parts than we need.
There’s also a nice, fair case study asking whether data mesh failed. The verdict: The idea was sound, but too many organizations copied it like a cargo cult without doing the enabling work.
The heart of the book is Castro-Gavino’s story of leading the data function at HelloFresh during hypergrowth. It reads less like a polished success story and more like a candid field journal. The reader meets boxes_shipped, a fragile legacy pipeline that failed on the first day of a leadership offsite. From there, we watch the team rebuild trust through four pillars: People, Governance, Technology, and Enablement. The Gold, Silver, and Bronze certification tiers really stand out. Over time, asking whether a metric was “Gold certified” became everyday shorthand for whether you could bet the business on it. The chapter that follows, “The Dark Side of the Role,” is an honest look at why the CDO seat burns through so many leaders. It’s the kind of chapter that makes a practitioner feel seen.
Next, the authors present the Data Manifesto, 14 principles inspired by the Agile Manifesto. Each one ends with a punchy maxim. Standouts include “Fix the system, not the tool,” “A pilot without a path to scale is just theatre,” and the one data modelers will want printed on a mug: “Model early, or reconcile forever.” Together, the principles work like a pocket guide to the daily dilemmas of data work, such as build versus buy, measuring what matters, and avoiding pilotitis.
The Enabling Data Model itself makes a sharp point. Instead of scoring organizations on a maturity ladder, it diagnoses friction: the duplicate metric, the missing owner, the pipeline nobody noticed was broken. The appendices turn this into a practical toolkit, with a diagnostic rubric by pillar, persona interview prompts, a Platform Fit Canvas, and a 0–30–60–90 day execution playbook. An end-to-end example of treating metadata as a product ties it all together.
To conclude, Enabling Data is a must-read for data leaders who are tired of the same conversations and want a way to move forward. It’s especially valuable for CDOs, data strategy folks, and anyone trying to explain why the “invisible” foundational work matters before AI can deliver. The mix of honest storytelling, memorable principles, and usable tools makes this a book you’ll reference again, not just read and shelve.
About the Authors
David Castro-Gavino is a data and AI executive, author and advisor whose career spans five continents and nearly three decades of international leadership. He has built and led data functions at some of the world’s most recognised organisations, including AstraZeneca, HelloFresh, Booking.com and dunnhumby, working across some of the most complex and regulated industries in the world. He speaks, writes, and lectures on data and AI, and advises boards and executive teams on strategy. He is based in London, UK.
Boyan Angelov is a principal consultant at Exxeta, an innovative technology and consultancy firm, and a lecturer on data and AI. His previous books include Elements of Data Strategy and Python and R for the Modern Data Scientist, which he co-authored, and his writing has appeared in outlets such as Handelsblatt and CDO Magazine. Throughout his career he has advised organizations of all sizes on data and AI-powered transformation, in roles ranging from data strategist to CTO. He is based in Berlin, Germany.
