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AI products require deep analysis at many stages — from opportunity assessment to post-rollout meta-analysis. In this article, I’ll share my personal experience on navigating the analytical complexity of product development and collaborating effectively with data teams. 💣 Here Comes the Challenge What happens when the data science team supporting you needs to answer open-ended questions and extract insights without clear guidance? What happens when you have to go through a dozen reports to get the full picture? What is the role of the Product person there? What happens when the team keeps analyzing and analyzing without ever reaching a conclusion? How do we balance the need for rigor with the need for decisions and action? And what if the analysis yields inconclusive results? 👩 From Data Science to Product Throughout my career, I’ve received analyses from many different perspectives — and earlier, I used to prepare and deliver them myself. I’ve worked with aca...