Intuition

As we invest more time in understanding a problem, engaging with data, and interacting with users, the subconscious knowledge we accumulate enhances our intuitive sense, resulting in faster decision-making and improved situational awareness—what we often refer to as efficiency in familiar contexts. The only way to refine this skill is through extended experience. However, it is equally important to stay attuned to evolving behaviors. Continuously monitor whether the data points you are examining serve as accurate proxies or representations of the problem, and ensure that the anecdotes convey the same narrative.

Product Managers often make the mistake of relying too much on intuition early in their careers, building features without proper validation. This results in a significant gap between their assumptions and the reality on the ground. Beginning from the desk, they may track the wrong metrics or use proxies that are no longer relevant for understanding user behavior, also leading to analysis paralysis. Not being on the front lines can turn the job into a desk job. For experienced Product Managers, a common challenge is the tendency to overly rely on intuition, even when data and anecdotes point toward a different narrative.

Anecdotes help in forming hypotheses, guiding the selection of relevant data points and metrics to validate. When data signals a message, delve deeper with anecdotes; if anecdotes offer a different perspective, cross-check with the data and adjust metrics to validate new hypotheses, uncovering insights that contribute to building context. Over time, as familiarity with this context grows, intuition becomes a key driver for faster and more informed judgments.

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My inspiration to write this post was sparked by a quote from Jeff Bezos during the Lex Friedman Podcast, which I found very relatable:

"I have a saying which is when the data and the anecdotes disagree, the anecdotes are usually right. And and it doesn't mean you just slavishly go follow the anecdotes then it means you go examine the data because it's usually not that the data is being miscollected. It’s usually that you’re not measuring the right thing”