Risky assumptions and Experiments, where do I start?

Once you have filled in your NEXT Canvas, you are stuck with a pile of stickies filled with assumptions. Do they all need to be tested? Is every single one of them risky? Where do I start?!

There are a couple of tools that can help you prioritize and create order in the chaos. One that is really helpful is the Hilo matrix. In a guest post on Tristan Kromers blog, Dan Toma is writing about how this has been helping teams prioritize on risk in a very easy way.

Once you have written down all of your assumptions on stickies you can use this visual method to decide which things need derisking the most. First, you order your assumptions based on the knowledge you have on that subject. Do you know the facts the mindset, the problems etc… or not at all. Order your stickies along a horizontal axis from left to right. From ‘I know a lot about it’ to ‘I know nothing about it’. Once you have ordered them, add a vertical axis. Going through the middle of the horizontal one, dividing everything into 4 squares. This axis is going from ‘Has low impact on theb business model in the bottom to ‘ Has high impact on business model’ on the top. If you order your stickies as honeslty as possible the right hand top quadrant is now containing all of the assumptions that are most risky and should somehow be tested.

The HiLo matrix by Dan Toma (drawing Esther Gons)

Using this tool to prioritize experiments works really well in combination with our NEXT Canvas. The NEXT canvas is using 8 building blocks and is ordered in such a way that the blocks form steps that correspond with the 4 basic phases in a startup’s journey:

From left to right it determines the order (or proposed order) in which it makes sense to test assumptions first. Moving along the canvas will show you the progress you are making towards product-market fit. Starting your experiments with assumptions that are marked in the top right quadrant of the HiLo matrix AND are in the first step of the canvas is a perfect place to start. Testing risky assumptions on your solution make less sense if you haven’t proven the problem yet.

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