If it were possible to be a professional devil’s advocate or “chief questionologist,” I’d be first in line to apply. One of my key strengths—stemming from persistent curiosity, some innate contrariness, and the ability to see things from multiple perspectives—is to be able to surface assumptions that are either too obvious or too uncomfortable for most people to see.
Identifying and testing assumptions, especially the ones upon which the success of your solution most heavily rely, is tremendously important for the design thinking process. Not only does this part of the process help in creating a natural “reality check” before heading into prototyping and iteration, it also mitigates risk. If your solution depends on one key assumption, and that assumption turns out to be false, all of the work you’ve put into producing your brilliant idea will have been for naught.
Assumptions fall into a few main categories, each of which you should consider when evaluating your solution. By way of an example, let’s say your solution involves an online staff survey to get input about an upcoming organizational change. What types of assumptions should you consider?
- Desirability: Here, we’re assuming someone is willing to do the thing we’re asking them to do. In the survey example, we’re assuming employees will be willing to take the survey, and that the organization’s leaders want to incorporate the feedback into their plans.
- Usability: Usability assumptions have to do with the ability and understanding necessary to enact the solution. For the staff survey, we’re assuming people will be able to successfully complete the survey: They know how to navigate to it, they know how to use the survey tool to indicate their responses, and they have access to a device on which the survey will work properly.
- Feasibility: We’re assuming the solution is technically and culturally possible. For example, we’re assuming we have the technical ability to send and analyze the survey… and that sharing feedback through surveys is acceptable within our organizational culture.
- Viability: This set of assumptions has to do with whether there is value (real or perceived) in the solution. In the case of the survey, do staff think the information will be used in a way that will help the organization? Will the input actually be taken into consideration? Is it worth their time?
- Ethics: We’re assuming it will not cause anyone any harm, or disproportionally affect one person / group over another. Gathering data through surveys might seem fairly neutral, but what if that information is used to make decisions about performance? If the data are linked to individuals, will it single them out in a negative (or positive) way?
Some of these assumptions you can easily find the answers to, and some you might have more control over than others. You can set those aside to focus more specifically on the high-risk assumptions: The ones that are the most unknown, and the most important to demonstrate in order for the solution to succeed. What is considered “high risk” will be very much context-dependent. In some organizations, for example, surveys may already be an established method for gathering input; in those cases, the assumption around viability (value) may be fairly safe to make.
You’ll probably find that you’re better at identifying one or another of these assumptions; personally, I gravitate toward desirability and feasibility. Recognizing your own biases here will help you spend more time with the types of assumptions that you’re not accustomed to seeing… and avoid those hidden assumptions that can be most threatening to your success.