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Why does predicting the future get harder as organizations collect more data? In this talk from CDOIQ Nordic Symposium 2026, I unpack what I call The Prediction Paradox: when data volume increases, certainty often decreases—because trust, ownership, and decision habits aren’t keeping up. You’ll learn: Why “more dashboards” often creates less clarity (the dashboard paradox) How organizations slip into decision laundering (gut decision first, data justification later) Why AI/LLMs can amplify confusion when data foundations are weak The cultural and leadership behaviors that quietly undermine data quality A practical alternative: start with the 10 most important decisions, then build the minimum data needed to make them faster and better Key ideas mentioned: Data ownership: “everyone is responsible” usually means no one is responsible The 70% rule: decide when you have enough to move—perfection is expensive One-way vs two-way door decisions: stop treating reversible decisions like irreversible bets The hidden cost of waiting: the cost of inaction If this resonates, leave a comment: where does your organization struggle most—trust, ownership, decision speed, or culture? #data #analytics #leadership #ai #decisionmaking #datastrategy #cdo #cdioq