Nowadays, most companies want to be data-driven. Every year, more and more money is poured into data gathering and data analytics departments to facilitate decision-making processes. Although this seems like a sensible strategy and something to strive for, what does being data-driven mean and is it something that we should want? More crucially, how is it possible that even though the investments in data-driven decision-making increase, most companies do not see an equal increase in their performance?
In data-driven decision-making, the data is at the core of the decision to be made. Data analysist and scientists are the most important employees in a data-driven company. After all, whatever the result of their analysis is, it will impact decisions. Even though data analysis is not a deterministic process and requires estimates, decisions, and interpretations, the results of data analysis in data-driven companies is seen as the truth.
However, this means that data is looking for a purpose. The reason that academic research starts with a literature review and hypothesizing before gathering additional data, is that it is very robust. It avoids explaining coincidental correlation as causation. More importantly, it avoids taking the data at face value and thereby misinterpreting the underlying relationship that may or may not exists.
Therefore, Stefano Puntoni, a former professor of marketing at the Rotterdam School of Management, Erasmus University, recommends turning it around. Instead of data-driven decision-making, companies should strive for decision-driven data analytics. The difference is that the decision is now the focal point of conducting the data analysis. Rather than empowering data analysts and scientists, this empowers managers whose job it is to make decisions.
