You may need to go back to your Assumptions Map and pick off the next lot of assumptions that you want to test.įurther, not all your experiments will be conclusive. You'll no doubt learn new things, which will lead you to either create a new Assumptions Map based on new information or create a new hypothesis and test to more conclusively test your assumption. It's important to note that during this process you would have zoomed in to one or more assumptions, but that doesn't mean you have covered everything. Whether your experiment was True/False or inconclusiveĪny notable quotes or notes from the experiment The second half of the template is where you can record your experiment findings. It's designed this way to keep everything on one board for ease and traceability. Typically on an Assumptions Map, you want to invest your time in tackling the assumptions in the top-right corner first - the important and unknown assumptions. Once you've mapped out your assumptions on the Assumption Map, your next step is to prioritize them. Therefore the latter would have a higher importance than the former. However, the assumption that people are comfortable enough to get into a stranger's car, if that was found to be untrue, Uber's business model would crumble. This is a great feature but if it wasn't technically possible to do it wouldn't be the end of Uber as a concept. I sometimes frame this as risk: It can make it easier for people new to assumptions mapping grasp the idea - i.e. high risk = high importance.Īn example of importance might be, say, Uber's ability to show in real time where your ride is located. If found to be incorrect, would that make the opportunity no longer worth exploring? This seeks to understand how vital the assumption is to the problem area, opportunity or solution. The y-axis, on the other hand, is a scale of importance - from 'low importance’-to-‘high importance'. Is there supporting data, or are we guessing?Īre there indications that suggest this exists, or is it a gut feeling? We feel it's correct, but we do not have any data to support it. This represents how much evidence we have on an assumption.ĭo we have existing research on it from past projects? Personally, I like to keep things simple and just brainstorm all the assumptions we can think of.įrom there, as the name suggests, we need to turn things into a 'map' - into a 2x2 matrix, to be more precise, like below.Īn Assumptions Map comprises of two axes.Īlong the x-axis is a spectrum from unknown to known. You can colour code or step through each of these lenses if you find it valuable to do so. Or risk orientated - is this idea durable enough to survive changes in the future?Īlso framed as testing the desirability, viability, feasibility and adaptability of the opportunity. Technical - can we technically do this? Is it possible with this tech? etcīusiness-related - is the business model sustainable? Will people pay for it? How much can we charge? etc. Those unfamiliar with Assumptions Mapping, it's a tool used to map and prioritize the assumptions you have around your chosen problem/opportunity area.Ĭustomer/User related - their behaviours, needs, motivations, etc Whenever I'm doing discovery, it almost always starts with an Assumptions Mapping exercise.Īssumptions Mapping is from the Strategyzer book ' Testing Business Ideas'.
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