Debugging business problems
For product managers and interviewees
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The most successful product managers bring clarity to ambiguity. As PMs at Facebook and Tesla, we encountered many ambiguous challenges: from broad ones such as defining the strategy for expanding Facebook Groups to emerging markets, to narrow ones, such as designing the strategy for Tesla’s maps navigation as autopilot improves.
It’s no surprise then, that these types of questions get asked in the Product Strategy portion of interviews as well, at companies ranging from Google to Facebook to Coinbase. For example:
You’re a PM at Coinbase. Should Coinbase build social features? What types of features?
You’re a PM for YouTube Shorts. You just launched Shorts, but it was not successful. Figure out why and decide what to do next.
Here are some tactics to help you improve your muscle for bringing clarity to ambiguity:
1. Create a tree of theories
When something goes wrong and is unclear, new PMs start with a loose list of theories, but the best PMs create a tree of theories that hang on an overarching success framework.
Let’s say you are the PM for YouTube Shorts, and you launch the product but its not as successful as it could have been. New PMs throw out a number of potential causes for an issue, but great PMs define clear success criteria, making the situation easy to troubleshoot.
2. Decide on the metrics to examine based on what they’ll unlock
When defining metrics to diagnose an ambiguous situation, new PMs want every single metric under the sun, but the best PMs define how the answer to a certain question will materially drive the decision one way or another.
Practice like a scientist, so you can play like an artist
Even though it might seem like a science — in reality, there is no single right way to do things; these are just principles.
For example, you may decide that you don’t want to be specific about your top-line metric for YouTube Shorts, because you’re early in development phase and don’t fully understand how the product works. By keeping the metric broad, you might learn, for example, that your users love YouTube Shorts not for the content, but as a way to discover content creators to follow – defining a crisp metric in this scenario would have siloed yourself. The exercises we suggest above help you practice like a scientist, so you can play like an artist.1