S7 | Ep 24 | Are you a Merchant of Self-Inflicted Complexity? David Castro-Gavino, Executive Director, Head of Data Deployment at AstraZeneca and Boyan Angelov, Principal Strategist at Exxeta — Driven by Data: The Podcast

In Episode 24 of Season 7 of Driven by Data: The Podcast, Kyle Winterbottom is rejoined by David Castro-Gavino, Executive Director, Head of Data Deployment at AstraZeneca, and joined by his co-author Boyan Angelov, Principal Strategist at Exxeta, where they discuss their new book, Enabling Data, and why the data industry is still stuck in Groundhog Day. The same three arguments – who owns that number, is it right, and why does it take so long – have been repeating for thirty years, and rather than fixing them, the industry keeps renaming the problem.

The conversation covers why most complexity in data is self-inflicted, why maturity models are "data theatre" compared to diagnosing friction, and why AI hasn't solved any of this – it has poured fuel on the fire.

They also discuss:

Why the industry has a short collective memory and keeps rediscovering problems solved twenty years ago.
What the three recurring arguments are that every data organisation keeps having.
Why renaming the symptom – big data, data mesh, platforms – never fixes the underlying problem.
How a simple pizza business becomes a data nightmare the moment it goes digital.
Why most complexity in data is self-inflicted, and why that is good news.
Why "technology is not the problem, you are" is deliberately provocative.
What four questions to ask before going back to the market for a new tool.
Why fixing the system, not the tool, is the maxim that matters.
Who the "merchants of complexity" are, and why consultants are usually the culprits.
Why making things simple is the hardest job in data.
What's wrong with using maturity scores as the objective.
Why measuring the wrong things promotes the wrong behaviours.
How to practically find friction by refusing to accept the first answer.
Why friction looks different for an analyst, an engineer and a business leader.
Why not every foundational problem needs to be solved, and how to avoid spending forever in the basement.
Why data teams that don't understand the business are missing the biggest opportunity.
What the cargo cult is, and why copying Spotify's operating model won't make you Spotify.
How the enabling model's four pillars – people, governance, technology and enablement – fit together.
Why the fragility of senior data leadership is structural rather than personal.
Why data doesn't create friction in an organisation, it reveals it – and gets blamed for it.
Why a clear mandate matters more than who the CDO reports to.
Why the industry needs to stop hiring data leaders on a shopping list of technical skills.
How AI has exposed how little progress most companies have actually made on the fundamentals.

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