An assumption is an idea the team has about what users want, but for which there is no clear evidence yet. It should be treated merely as a hypothesis to be tested; if taken as a certain truth without verification, it can ruin the entire project.
Major risks arise when assumptions remain untested. A design based on unconfirmed user hypotheses can address a completely wrong problem or provide an inadequate solution for their real behavior. These discrepancies typically come to light only after the official launch.
Assumptions should not be eliminated completely, as they often serve as the starting point for valuable concepts. A simple hunch regarding a user need can open up a useful direction to explore. Furthermore, identifying a hypothesis early, before writing the first line of code, is far cheaper than discovering an error post-launch. Thus, testing assumptions right from the concept phase is one of the fastest and most efficient ways a team can reduce risks before allocating significant resources.
How should assumptions be addressed?
Any formulated hypothesis must be viewed as an element that requires validation, rather than a viewpoint to be defended. Before basing strategic choices on it, this involves a testing phase through concrete methods, such as individual interviews, usability evaluations, or direct field studies, instead of treating it as a proven fact merely because of internal consensus. In situations where a hypothesis is proposed without preliminary data, the starting point must always be the real needs of the user community, transcending strict business interests or the creative team's vision.
It should also be noted that the audience is not homogeneous. Assuming that every person shares the same requirements, priorities, or behaviors is a major error. Equally risky is extrapolating the opinion of a single participant to the entire community. The optimal solution lies in shaping personas based on concrete research data. In this way, hypotheses remain closely tied to authentic segments, avoiding decision-making based on the loudest opinion in the room.
