A lightweight 4-step process that guides product leaders from data gathering to hard strategic choices, using narratives and use to turn insights into actionable product strategy.
The core of this piece is a four-step framework that moves a product leader from raw data to concrete strategic bets. It starts with gathering market, customer, product and business inputs, then forces you to turn those inputs into a narrative that explains why the future will look a certain way. The third step asks you to identify the choices that give the highest return, and the final step pushes you to make hard, narrowing decisions that focus the product.
Step one stresses that strategy is not a guess-it is built on enough data to move forward without getting stuck for weeks. The author likens it to assembling a puzzle, warning against endless research and encouraging an iterative mindset that accepts pivots as new information arrives.
In step two the narrative is formed by filtering signal from noise, like weighing AI-related job redundancy data against historical patterns of technology creating new roles. The author stresses conviction in hypotheses and uses the term strategic narrative to capture the insight plus a future hypothesis.
Step three turns narratives into concrete options, asking what unique advantages or moats exist and what flywheels could be built. The author recommends spending double the expected time on this ideation. The final step is a litmus test: if a choice feels easy, it is probably not the right one. The framework forces you to articulate the choice, target, rationale, alignment with business goals, execution plan and success metrics. The result is a focused, actionable product strategy that can be revisited as conditions change.
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