How to Build Hypothesis Trees

In my post about opening cases, I talk about how to take an ambiguous problem and build an initial structure / issue trees around it. Usually they look something like this:

Market Entry

Issue trees are a good way to structure cases, but there is an even better way, called a hypothesis tree.

In today’s article we will discuss what a hypothesis tree is, why they’re more useful than issue trees, when to use them, and how to construct them.

What is a Hypothesis Tree?

Hypothesis Tree

A hypothesis tree is the set of all MECE hypotheses that can explain a particular problem.

Instead of organizing your analysis around issues or areas such as the customers / competition / company, you directly organize problem solving around hypotheses.

Why are they more useful than Issue Trees?

Hypothesis trees are much more direct than issue trees. Because you’re organizing around hypotheses, every question you ask / area you explore will be much more focused towards uncovering the issues.

However, they suffer from a weakness. If the situation is ambiguous or you don’t understand the industry well you won’t be able to generate a collectively exhaustive set of hypotheses.

In that case, use an issue tree instead.

How do we construct them?

They’re much the same as issue trees, except each branch of the hypothesis tree is a hypothesis. Let’s examine what this would look like for a case where you have to improve sales force productivity:

Hypothesis Tree 2

(credit: Ian Davis, The McKinsey Approach to Problem Solving)

The only thing I would add to the above diagram is the data that you’d need to examine the validity of each hypothesis.

Conclusion

A hypothesis tree is another way to structure your analysis. It’s much more direct than the typical way of structuring, but it can only be used when you understand the situation well enough to come up a collectively exhaustive set of hypotheses.

As a result, it’s a pretty safe bet for profitability, sales, and cost related cases but for the others it’s safer to use an issue tree.

Hope it helps!

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3 thoughts on “How to Build Hypothesis Trees

  1. Thanks for sharing this post.

    Just one thing – the McKinsey example here looks more like an issue tree. One of the key reason being, any of the end nodes can be implemented independently and they will be able to increase their sales force productivity to varying levels. That negates the fact that all the nodes have to be true in order for pivot node to be true.

    I came across the following video which gave a very good example of a hypothesis tree. Check it out!!

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