In “The End of Theory: The Data Deluge Makes the Scientific Method Obsolete”, Chris Anderson argues that theory may be irrelevant in a world of big data:
“This is a world where massive amounts of data and applied mathematics replace every other tool that might be >brought to bear. Out with every theory of human behavior, from linguistics to sociology. Forget taxonomy, >ontology, and psychology. Who knows why people do what they do? The point is they do it, and we can track and >measure it with unprecedented fidelity. With enough data, the numbers speak for themselves.”
When I first started by Ph.D. program ten years ago at Virginia Tech, I would have argued that theory is irrelevant; that, if the data gives the result, then it’s not important to know why. This mentality reflects a very practice-based or industry-based approach to research. I used to believe that organizations don’t really need to understand why a best practice works, just that it works. Leave the why to the ivory tower academics. After doing research for ten years, I look back at myself from 10 years and think my line of thinking is folly. Theory is important. Theory tells us the why. Theory provides boundaries for understanding a phenomenon. Without theory, we don’t know why a statistically significant result holds true. If we don’t know why, we can’t tell whether or not this result will hold true in another scenario with different conditions or even a future scenario with the exact same conditions. Without knowing why, research can’t tell whether the same result will happen again in the future.