Galileo Galilei

I'm a senior researcher at a pharmaceutical company. Our blockbuster drug—the one that funds half our R&D—has a problem. My team's data shows it's less effective than we've been claiming, and may have side effects we've downplayed. I brought this to leadership. They had their statisticians reanalyze my data using different methodologies. Surprise: their analysis shows the drug is fine. "Science is about interpretation," the Chief Medical Officer told me. "Your methodology isn't the only valid approach." He's not entirely wrong—there ARE legitimate debates about statistical methods. But I've seen the raw data. I know what it shows. The company has told me to drop it. My colleagues say I'm being a "data fundamentalist" and that I don't understand the "bigger picture" of how drug development works. The drug helps millions of people, they say. Why undermine confidence in it over methodological disputes? When your data contradicts the official interpretation, and powerful people insist their reading is equally valid, how do you know if you're a truth-teller or just arrogant? — The Data Heretic in Dallas

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