S7 | Ep 4 | Why Data & AI Transformation Fails Without Decision Transformation with Peter Everill, Head of Data Product at IAG Loyalty

In Episode 4, of Season 7 of Driven by Data: The Podcast, Kyle Winterbottom was joined by Peter Everill, Head of Data Product at IAG, where they discuss why most organisations still invest heavily in data, analytics and AI capabilities without ever connecting that work to the handful of decisions that truly move business performance. They break down why the future of data transformation is really decision transformation, sharing a practical five-layer framework that links performance visibility, root cause, budget trade-offs, automated decisioning and enterprise optimisation directly to P&L impact, which includes;Why the real purpose of data and AI is not building outputs, but improving the decisions that materially change business performance.How Peter’s career shifted from historical reporting into transforming decisions and workflows that directly influence operating models.Why the biggest capability gap in most organisations is linking technical capability to strategy, commercial priorities and P&L outcomes.How starting with business decisions instead of tools helps avoid the common trap of capability-first transformation.Why stakeholder requests that cannot be tied to action or performance change should rarely make the roadmap.How bottom-up demand creates sprawl, fragmented priorities and lots of activity that never ladders up to enterprise value.What the five decision layers are that connect data transformation directly to P&L impact.Why performance visibility is the first step to stop leadership teams debating numbers instead of making decisions.How root cause analysis becomes the turning point where prioritisation, ownership and commercial focus become clear.Why smarter budget trade-offs matter more than simply asking for more investment.How AI creates the most value when it improves decision quality before automating workflows at scale.Why automating workflows without improving the decision just helps organisations get to the wrong answer faster.How enterprise optimisation exposes where one team’s success is unintentionally creating cost or lost sales elsewhere.Why local optimisation inside siloed teams often damages enterprise performance without leaders realising it.How making performance problems visible requires executive sponsorship because transparency can create organisational tension.Why root cause is usually the point where leaders realise they still lack clarity on what really drives performance.How both business leaders and data leaders should start by focusing on one decision that matters most.