Assumption Map

Use this tool when:

  • You have collected a lot of assumptions and want to prioritize what to test

Overview

Time± 30 minutes
Difficulty3 / 5
People3 - 5
AuthorErik van der Pluijm
License CC BY SA 4.0
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What is it and when should I use it?

In your innovation journey, there will be many moments where you haven’t got enough information to move forward with confidence. Experimentation will help you to find that information, by validating or invalidating assumptions. Experimenting takes time and effort, so it makes a lot of sense to be selective in what to validate first. But how to prioritize?

This Assumption Mapping canvas is a lightweight tool that can help you prioritize your assumptions and to find which one to try to validate first. A perfect tool to use before you start experimenting.

Tool Overview

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  1. Important things that you have evidence for Assumptions that have been (in)validated and have a lot of impact, or that you have evidence for from other sources. These nuggets of information are for you to share with your team.

  2. Important things that you have no evidence for These are the most important. Assumptions that (you think) have a lot of impact on your progress and your project, but that you have no or little evidence of. These need to be validated or invalidated first.

  3. Unimportant things that you have evidence for Assumptions that have been (in)validated or that you have evidence for from other sources, but that don’t have a lot of impact on your progress. These can be safely ‘parked’.

  4. Unimportant things that you have no evidence for Assumptions that (you think) have low impact on your progress and your project, and that you have no or little evidence of. These can be ‘dark horses’ in that you could be wrong about their impact. These can be parked for now, but keep an eye on them for later.

Step-by-step

1 Collect

The first step is to collect the assumptions you want to map. Assumptions can come from anything. They come from your vision, business idea, things your customers say, your choice of business model… They can even be hiding in plain sight: things you take for granted or are biased about could be based on (false) assumptions. Finding assumptions is a big part of your job as an innovator.

To do this, keep a space on your innovation wall during your project where you put sticky notes for your assumptions. You could even use this canvas to map them directly. Convince your team to keep tracking assumptions.

An ‘assumption’ in this context is something that needs to be true in order for your project to be successful. Assumptions come in three categories.

Categories

  1. Desirability: Assumptions that need to be true if your project is going to attract customers
  2. Viability: Assumptions that need to be true if your project is going to become a viable business
  3. Feasibility: Assumptions that need to be true if you are to successfully launch your product.

For example, if you want to create a new app that helps people to invest their savings, some assumptions could be:

  • Potential customers want to invest their money (Desirability)
  • Potential customers trust your app with their money (Desirability)
  • You are able to ask a monthly fee for customers to use your app (Viability)
  • You are able to build a secure app that does not get hacked (Feasibility)

2 Impact

If you ‘collect’ an assumption, put it on the wall. Use color coding to figure out if it is a viability, feasibility, or desirability assumption. Finally, also put on the sticky what parts of your idea would be affected if this assumption were to be invalidated. Would it mean a small adjustment? Back to the drawing board? Or Game Over?

If you keep doing this during your other brainstorming, visioning, and customer understanding sessions, you’ll quickly end up with a lot of assumptions.

If you have a fresh start, look at your vision, customer journey and personas, and your business model canvas or lean canvas to get a first stab. Go over these with your team and try to find the (implicit) assumptions you make. What would need to be true for your idea to work?

3 Evidence Level

The next step is that for each of your assumptions, you want to have an ‘evidence level’. It makes little sense to focus on experiments for assumptions that have a high evidence level.

Evidence Levels

  1. Very High: Validated or Invalidated by your team: This is the highest level of evidence.
  2. High: Validated or Invalidated through research: Here you’ll need to figure out how much you trust the evidence as it is coming from another source.
  3. Medium: There is some data from research that seems to be in agreement.
  4. Low: There is no data or data is not in agreement.

4 Map on the Canvas

Once you have a wall filled with 10-20 assumptions, it’s time to start mapping them. Make sure each assumption is color coded for its category (desirability, viability, feasibility). Also, make sure you have labeled each with ‘no impact’, ‘small adjustment’, ‘back to the drawing board’, and ‘game over’.

Place the sticky notes on the canvas, on the vertical axis. On top, put the ones that have ‘game over’. On the bottom, the ones with ‘no impact’ and ‘small adjustments’.

Next, move the sticky notes on the horizontal axis. THe stickies with ‘high’ and ‘very high’ evidence move all the way to the left. Stickies with ‘low’ evidence move to the right. Find the appropriate position for each.

5 Find the riskiest assumption

There are in essence 5 big groups that each post-it can end up in. Look at the checklist below, and find the post-its that are low-hanging fruit or that are high-risk. Use that to inform your choice.

  • Top left: High evidence and important. These you have likely already validated or thoroughly researched. Make sure the team members have access to this information. Example: results from your initial experiment on desirability shows that customers care about your problem.
  • Bottom left: High evidence, not important. You have maybe validated these and/or decided they will not impact your business. These can be safely ‘parked’. Example: customers have shown you that they don’t really care about the day of the week your email newsletter arrives.
  • Bottom right: Low evidence, not important. You have little information on these, but you think that being wrong about these assumptions won’t have a lot of impact on your business. Example: You don’t know which of two font styles customers prefer for your app. Note: you might be wrong about the impact you assigned to assumptions in this quadrant, so keep an eye on them.
  • Top right: Low evidence and important. This is the most important quadrant. Being wrong about assumptions in this quadrant has the potential to kill your business. These are the ones you need to focus on.

In some cases, multiple assumptions end up close together in the top right quadrant and a discussion will happen. To make this a bit simpler, try to do the following:

  • Desirability beats Viability, and Viability beats Feasibility. Validate desirability assumptions first. Then viability, then feasibility.
  • Try to split the top right quadrant in four new quadrants, and repeat the exercise.
  • If there are still two or more assumptions that end up competing, they are apparently so close together that it doesn’t matter which one to validate first. Pick the one that is easiest to validate.

Warning! In some contexts the order desirability, viability, feasibility might not be true: feasibility could come first. For example, if you already know that laws of physics prevent you from building a anti-gravity device, proving its desirability won’t help you much. The same can be true for contexts with high compliance requirements: if you know it will be against the law, you might want to fix that problem first, before looking at desirability.

6 Next Steps

Use the result as input for your next experiment.

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