Learning from Mistakes

Early enthusiasm for data led to oversights in critical evaluation, highlighting the importance of balancing quantitative analysis with thoughtful decision-making. A program aimed at incentivizing migration during lean seasons showed promise in trials but ultimately failed to scale effectively, raising questions about its broader applicability and the complexities of real-world implementation.