At this year’s Swiss Statistics Meeting, Oscar Thees presented a talk on “Anonymizing Longitudinal Panel Data”. The presentation highlighted the unique privacy challenges posed by panel data, where the accumulation of quasi-identifiers across time makes individuals’ trajectories more unique and therefore more identifiable. Changes in sensitive attributes can also be identifying even when masked. The talk further emphasized the difficulty of preserving data utility while ensuring privacy, as trajectories must remain logically consistent within and across variables. It illustrated these challenges with practical examples and outlined our solution approaches, aiming to raise awareness among stakeholders in statistical offices and the private sector about the importance of addressing these issues effectively.