Argument: businesses should use scientific method in studying big data

Sociologist Duncan Watts explains how businesses should go about analyzing big data:

A scientific mind-set takes as its inspiration the scientific method, which at its core is a recipe for learning about the world in a systematic, replicable way: start with some general question based on your experience; form a hypothesis that would resolve the puzzle and that also generates a testable prediction; gather data to test your prediction; and finally, evaluate your hypothesis relative to competing hypotheses.

The scientific method is largely responsible for the astonishing increase in our understanding of the natural world over the past few centuries. Yet it has been slow to enter the worlds of politics, business, policy, and marketing, where our prodigious intuition for human behavior can always generate explanations for why people do what they do or how to make them do something different. Because these explanations are so plausible, our natural tendency is to want to act on them without further ado. But if we have learned one thing from science, it is that the most plausible explanation is not necessarily correct. Adopting a scientific approach to decision making requires us to test our hypotheses with data.

While data is essential for scientific decision making, theory, intuition, and imagination remain important as well—to generate hypotheses in the first place, to devise creative tests of the hypotheses that we have, and to interpret the data that we collect. Data and theory, in other words, are the yin and yang of the scientific method—theory frames the right questions, while data answers the questions that have been asked. Emphasizing either at the expense of the other can lead to serious mistakes…

Even here, though, the scientific method is instructive, not for eliciting answers but rather for highlighting the limits of what can be known. We can’t help asking why Apple became so successful, or what caused the last financial crisis, or why “Gangnam Style” was the most viral video of all time. Nor can we stop ourselves from coming up with plausible answers. But in cases where we cannot test our hypothesis many times, the scientific method teaches us not to infer too much from any one outcome. Sometimes the only true answer is that we just do not know.

To summarize: the scientific method provides ways to ask questions and receive data regarding answering these questions. It is not perfect – it doesn’t always produce the answer or the answers people are looking for, it may only be as good as the questions asked, it requires a rigorous methodology – but it can help push forward the development of knowledge.

While there are businesses and policymakers using such approaches, it strikes me that such an argument for the scientific method is especially needed in the midst of big data and gobs of information. In today’s world, getting information is not a problem. Individuals and companies can quickly find or measure lots of data. However, it still requires work, interpretation, and proper methodology to interpret that data.

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