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This reminds me a lot of the discussion of the scientific method by Karl Popper, and David Deutsch who was very influenced by Popper. "Being data-driven" sounds very empirical. Just look at the data, and see what you find in it. But you can't just let the data "speak for itself" without an explanation or a theory that interprets the data. Popper in Conjectures and Refutations: > Observation is always selective. It needs a chosen object, a definite task, an interest, a point of view, a problem. And its description presupposes a descriptive language ... which in its turn presupposes interests, points of view, and problems. Deutsch, in The Beginning of Infinity, emphasizes the importance of conjecture, and the role of observation as refuting or criticising those conjectures: > Where does [knowledge] come from? Empiricism said that we derive it from sensory experience. This is false. The real source of our theories is conjecture, and the real source of our knowledge is conjecture alternating with criticism. We create theories by rearranging, combining, altering and adding to existing ideas with the intention of improving upon them. The role of experiment and observation is to choose between existing theories, not to be the source of new ones. We interpret experiences through explanatory theories, but true explanations are not obvious. To bring this back to the subject of the article, I might suggest that it's possible to be "data driven" without a sound explanation or theory that the data is either interpreted through, or used to criticise. Or maybe such theories do exist, but are left implicit. |