Season 2, Episode 11: Rethinking Transformation: Success Factors, Failure Patterns, and the AI Shift
Eva M. Perez | Sep 2026
Featuring Eva M. Perez, Head of Delivery Excellence Western Europe, L'Oréal
Join us for an insightful conversation with Eva M. Perez as she rethinks what transformation really means, moving beyond buzzwords to the discipline required to make it stick. Despite significant investment in strategy, technology and change programs, many organizations continue to confuse initiatives with true transformation and continue to repeat the same failure patterns as a result.
In this episode, Eva explains why transformation must be treated as a permanent management discipline rather than a one-off project, breaks down the core blind spots that cause even well-funded programs to stall, and shares her perspective on how the rise of AI is set to amplify - not replace - the foundations that make transformation succeed.
Eva M. Perez
Eva M. Perez is the Head of Delivery Excellence for Western Europe at L'Oréal, and a transformation strategist with over 20 years of experience in continuous improvement and transformation across multiple multinationals and industries. She views transformation not as a series of projects, but as a rigorous management discipline - one that organizations must embed into how they operate if they want to realize its full value.
Key Highlights:
- Why transformation is a systemic shift in operating model, resource allocation and human behaviour - not just a project with a start and end date.
- Why transformation should be treated as an ongoing discipline, not a once-off initiative, and the fatigue and regression that follow when it isn't.
- The four blind spots that quietly derail transformation programs: undefined success criteria, misaligned leadership, ignoring the human side of change, and failure to scale.
- Why money can't buy a shortcut to successful transformation - clear goals, aligned leadership and people adoption can't be purchased.
- How AI will act as an amplifier and "magnifying glass" on existing foundations - exposing weak processes rather than fixing them - while reshaping continuous improvement through human-AI collaboration.
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