In consciousness science, theories often differ not only in the account of consciousness they arrive at, but also with respect to how they understand their starting point. Some approaches begin with experimentally gathered data, whereas others begin with phenomenologically gathered data. In this paper, I analyse how the most influential phenomenology-first approach, namely the Integrated Information Theory of consciousness, fits its phenomenologically gathered data with explanatory hypotheses. First, I show that experimentally driven approaches hit an explanatory roadblock, since we cannot (...) tell, at the present stage, which model of consciousness is best. Then, I show that IIT’s phenomenology-first approach implies a self-evidencing explanation according to which consciousness can be explained by starting from consciousness itself. I claim that IIT can take advantage of the virtuous circularity of this reasoning, but it also faces a data-fitting issue that is somehow similar to that faced by experiment-driven approaches: we are not given enough information to decide whether the explanatory hypotheses IIT employs to explain its phenomenological data are in fact best. I call this problem “the self-evidencing problem” for IIT, and after introducing it, I propose a possible way for IIT to solve it. (shrink)