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There is a great chance that, as a Product Manager, you are currently using the wrong definition of ‘hypothesis’. The right one helps to produce knowledge, which you can use afterwards. The wrong one provokes unfounded actions and waste of time and resources.

In previous posts, we discussed how Product Managers create and exploit knowledge to connect business goals with user needs. Now, it’s time to examine how new knowledge is created.

Robust, objective, useful knowledge is created by applying a scientific method, which is actually pretty simple:

1. Observe the situation (phenomenon, data).
2. Propose an explanation (state your hypothesis).
3. Test that explanation to check if it reflects the true causation relationship.
4. Update your explanation and use it to describe a model that can successfully predict outcomes.

As a result, you should get a model that produces predictions that a) can be tested and b) lead to predictable results. In other words, this is the only way to get comprehensive knowledge that can be exploited afterwards.

🚫 “We believe that if we do X metric M will change to N” – is just a prediction template, not a hypothesis statement.

✅ “After observing A, we think that it’s caused by B, that’s why if we do C it should lead to outcome D” – is a correct template for a meaningful and actionable hypothesis.

The good news is that this is also how our mind works: we always have explanations to back up our predictions! We just need to be very cognisant and transparent about them.

That’s another reason why Product Managers should be very skilful knowledge workers. We need to be very clear about what we know and be very honest about what we don’t know.

And the best way to address the unknown part is to apply the scientific method.