How JP Morgan ships faster, measures better: experimentation in the age of AI
Blog post from GrowthBook
Kevin Yang's exploration of experimentation at JPMorgan Chase reveals a perspective that values the insights gained from failed experiments as much as, if not more than, the successes. While his team estimates that successful experiments have generated over a billion dollars, Yang emphasizes that the true value lies in the lessons learned from failures, which prevent potentially harmful changes from being implemented at scale. At Chase, where his team supports about 100 product teams running 300 experiments annually, the focus is on building a culture that appreciates the importance of control groups and pre-planned responses to failure, which help avoid confirmation bias and ensure informed decision-making. This approach is particularly crucial in the AI era, where rapid iteration and customization demand rigorous measurement to avoid compounding mistakes. Yang's insights underscore the importance of a balanced decision framework that values trust and customer satisfaction over raw engagement metrics, highlighting the necessity of planning for failure to foster innovation.
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