S7 | Ep 21 | What being Advisor to a FTSE 100 UK CEO for 10 yrs Taught me about Data Insights with Michael Ross, Data Agitator & NED — Driven by Data: The Podcast

In Episode 21 of Season 7 of Driven by Data: The Podcast, Kyle Winterbottom is joined by Michael Ross, Data Agitator & Non-Executive Director at Domestic & General and Policy Expert. They discuss why so many consumer and retail businesses fail to turn data into commercial value, because they run on averages and siloed metrics that hide where money is actually being won and lost.

Drawing on a career spanning McKinsey, Figleaves, eCommera and DynamicAction, and years advising CEOs across the Abu Dhabi Investment Authority's portfolio, Michael makes the case for de-averaging: measuring distributions rather than averages, tracking failure modes rather than outcomes, and using driver trees to connect financial results back to the controllable inputs that leaders can actually change.

They also discuss:

Why Michael's "viewed availability" epiphany at Figleaves exposed a 93% in-stock figure that was really 70%.
How siloed teams create a hidden "coordination tax" that quietly erodes commercial performance.
Why nobody owning the end-to-end customer journey is still the single biggest issue in most businesses.
What separates the CEOs who thrive in a data world: strategic vision paired with "30,000 feet and two inches" of detail.
Why "that's where the money is" is the real reason CEOs must get into the commercial engine.
How the finance function quietly failed to become the owner of integrated, decision-driving data.
Why averages are the enemy of commercial performance, and what to measure instead.
How de-averaging an LTV:CAC ratio of 12 revealed that 70% of spend was acquiring customers above their lifetime value.
Why bidding on your own brand terms on Google is often just a "navigation tax."
What "spill and spoil" are, and how the airline and hotel industries measure their two failure modes.
How Premier Inn's headline 80% occupancy hid hotels that were either 60% or 100% full.
Why measuring failure metrics drives a far higher-quality conversation than chasing an average upwards.
What driver trees are, and how a 1920s DuPont technique connects outcomes to controllable inputs.
Why Amazon deliberately spends little time on financial outcomes and focuses on controllable inputs.
Why conversion rate is "the CEO's metric" and a recipe for disaster when handed two levels down.
How dashboards full of averages and filters create the "illusion of insight" rather than action.
Why the best dashboards are the ones that "create a compulsion to act."
How de-averaging package utilisation turns one meaningless number into clear churn risks and upsell opportunities.
Why data teams so rarely get to this work, and how the "build the foundations" mandate traps them.
Why so many data transformations end with "nothing's changed" and an eighteen-month reset.

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