The method of Assumption Mapping can be defined as a design method to understand the hypotheses behind a business concept or idea, scaling desirability, feasibility, and viability. These hypotheses are then mapped on an X and Y axis map to visualize the spectrum of important and evident thoughts vs those that are un-important and non-evident.
We begin with the hypotheses.
Then we map.
After performing secondary research, how can we answer: What do we know is evident about the problem? VS What do we think we know about the problem? These are the arisen thoughts that surface the perfect opportunity for this design exercise.
My team and I had just gone through Stakeholder Mapping and were trying to understand the many different points of view that applied to our problem space. Our own thoughts were brought in to understand and answer questions we had about our client EcoRise, an Austin non-profit organization that offers green curriculum to schools and communities to inspire the next generation of leaders in sustainability.
Now, to craft the hypotheses, we put our thoughts to words by making individual sticky notes, organized by color, reflecting on:
Desirability — What does our user, considering the various stakeholders, want?
Viability––How do we see this problem space? What models are in place?
Feasibility––Where do we see limitations? What is lacking? What is needed?
The sticky notes are then organized onto an Assumption Map by color. To create the map, draw a horizontal axis line labeling known on the left end and unknown on the right end. Draw a vertical axis line labeling important on the top end and unimportant on the bottom. Now, map your assumptions together as a team while in conversation to decide where each hypothesis lies on the spectrum. On our map, black represents desirability, blue represents viability, and green represents feasibility.
Now we assess.
The map showcases many things to our team.
First, the top right quadrant: important & unknown are thoughts ready to be explored. We can create processes and approaches to realize these assumptions.
Secondly, the top left quadrant: important & known are thoughts to be considered in our approach. Are they already implemented?
Third, the bottom left quadrant: known and unimportant are thoughts to take a look at after the unknowns in the top right quadrant are proven.
Fourth, the bottom right quadrant: unknown and important unimportant are hidden or underlying thoughts to be explored in the future that can unearth secondary exploration to the original problem.
The map serves as a growing field of located hypotheses our team can explore and implement in our experiments (phases of interviews, conception, and testing) to gain further knowledge on our problem scope. Allow it to continue to populate throughout the design phases for a sense of clarity and learning over time.
When using this design method approach, keep in mind the advantages and disadvantages of assumption mapping my team and I have experienced.
Advantages––The map brings clarity of our own thoughts and hypotheses that we can approach to learn more and find answers. It is a great tool in the launch phase to understand what our team regards as important vs unimportant to our problem scope, landing us all on the same page. It is a great reference point for checking off learned information as our project progresses, allowing direction to move forward.
Disadvantages––Assumptions may be reinforced in our minds if they are not proven false (possible biases). The map provides intangible thoughts that need to be put to action as the hypotheses reveal what we are seeking, making it difficult to move forward as the unknowns can lead to dead ends. There is still work to be done to find answers through verification and research, and the map can only provide, as it is defined, a map to move forward while the team needs to decide how to travel.
Nonetheless, an Assumption Map is highly recommended in the launch phase of design research as a method to understand how everyone on the team perceives the problem area, scope, or idea to align on how to clarify, organize, and validate the hypotheses through implemented experimentation.
