Data-driven decision making can lead to paralysis. Last week, the FDA and CDC committees couldn't make a decision about the booster shots because (complete) data was not available. Well, making decisions in the absence of complete data is a process of imagination and deep thinking, one that puts hypothesis development at the center and humans continue to prevail over machines in the process. To avoid such a paralysis, more focus can be put on developing and rethinking hypotheses and their likelihoods. In emergent problems, an in-depth discussion on hypotheses and likelihoods is probably more helpful than an obsession to access complete data. Otherwise, by defining complete data as a prerequisite, as it would be in data-driven decision making, we will continue to be paralyzed looking into the future. If we turn to data-informed decision making, however, hypotheses would take more control (not gut feeling but properly developed hypotheses*). We could then make decisions to be improve