As reported on Strategyzer | Corporate Innovation Strategy, Tools & Training:
You’ve finally managed to get your teams excited about experimentation. But how do you focus that excitement into designing experiments that matter? We’ve observed newly motivated teams running landing pages or interviews, only to ignore the riskiest assumptions in their strategy. While testing can be a powerful tool, you’ll need to focus your teams’ experimentation efforts on high-risk areas. Otherwise, you’ll miss your window of opportunity and end up wasting your time.
Learn more about Assumptions Mapping by signing up for our masterclass on Testing Business Ideas.
An introduction to Assumptions Mapping
Assumptions Mapping is a team exercise where desirability, viability, and feasibility hypotheses are made explicit and prioritized in terms of importance and evidence. I was first introduced to the idea of mapping risk this way while working with Jeff Gothelf and Josh Seiden, co-authors of Lean UX. I tested it with countless teams while applying the principles of design thinking. Assumptions Mapping has since been adopted by everyone from Google and their Design Sprint process to Federal Governments and their security strategies.
To understand the risk and uncertainty of your idea you need to ask: “What are all the things that need to be true for this idea to work?” This will allow you to identify all four types of hypotheses underlying a business idea: desirability, feasibility, viability, and adaptability.
- Desirability: Does the market want this idea?
- Feasibility: Can we deliver at scale?
- Viability: Is the idea profitable enough?
- Adaptability: Can the idea survive and adapt to a changing environment?
Write down your hypotheses
We define a hypothesis as an assumption that is testable, precise and discrete.
When you are first writing these out, they may not always be well-formed. Instead of infinitely refining your statements, we recommend that teams write these down as best they can use the “We believe that…” format. This format helps you shift mentally to the idea of testing. The idea that you might be wrong in your beliefs. You can always refine these statements later after you’ve mapped them out.
If you already have a Business Model Canvas, simply write these down on sticky notes surrounding it. Use a different colour for each theme (desirable, viable, feasible) so that you can see what types of risk you have at a glance. This will also make it easier, later on, to match experiments to your risk using the experiment library.
Don’t forget your Value Proposition Canvases. It is just as important to write down the hypotheses of your Value Proposition Canvases to deep dive into your desirability risks.
Draw your 2×2 diagram
x-Axis: Evidence
We use the labels of “have evidence” and “no evidence”. After facilitating this with hundreds of teams, we realized it all comes down to evidence. It’s not about who is the loudest or who gets paid the most. It’s about having observable evidence, qualitative or quantitative, to support your hypothesis.
y-Axis: Importance
On the y-axis, we use the labels of “important” and “unimportant”. You may be thinking that you have only written down the important hypotheses, so this is redundant. However, in our experience, not everything is the most critical. By asking yourself “which hypothesis, if proven wrong will cause our business idea to fail” you’ll be able to determine which are the most important.
Map out your hypotheses on the 2×2 diagram
Start with your desirability hypotheses, then move on to your feasibility, viability hypotheses and finally your adaptability hypotheses.
Once you have a few hypotheses mapped, it tends to go faster. You can ask “Is this more or less important? Do we have a greater amount of evidence?”
Focus on the top right quadrant for experimentation
The hypotheses in the top right quadrant contain your beliefs that are critical for success and yet have the least amount of evidence to support them. You’ll want your teams to focus their near term experimentation here, instead of working on things that are unimportant and already have evidence. This is how you can help them focus on experiments that matter.
Source: Strategyzer | Corporate Innovation Strategy, Tools & Training
Author: David J Bland
Date: 2020 08 05
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