Nadia Sotiropoulou

What happens when the data is messy, the evidence is contradictory, and the stakes couldn't be higher? Three months after returning from maternity leave, Nadia Sotiropoulou was diagnosed with breast cancer - and spent the next nine months as the stakeholder in the most consequential analytical project of her career. Her oncologist was the analyst; she had to decide, six times over, on data that was lagging, conflicting, and never specific to her. Medical evidence, it turns out, looks a lot like corporate data. Rather than waiting for a perfect dataset, Nadia applied Bayesian reasoning in real time - starting from clinical-trial priors and updating them as her own results arrived - to make high-stakes calls under pressure. This session turns that experience into three practical lessons for any analytics leader: why you should give stakeholders a position, not just the facts; how to lead in an era where GenAI has turned every stakeholder into a rogue analyst; and why the numbers alone can never make the decision. We’ll land on the importance of building teams that prize directionally-correct-and-timely over perfect-but-late.