Data Science – can we hold off on the buzzwords for a little while, please?

Tom Breur

28 May 2017

Data Science is a burgeoning field – great! Having been part of this wonderful community for over two decades, now, I am more than ever convinced we are making a difference in the way businesses are run. For the better. From the top, this shift to basing decisions more on numbers has played a big role. Nowadays, executives are expected to quantify claims, and to provide a more colorful elaboration on their annual reports and quarterly results. Stock market analysts now expect a much “richer” story when companies present their results. From the bottom, Lean startups move at lightning speed and change the way businesses get run across the market. Keep up or stay behind and become irrelevant. This dynamic is at the root of why the pace of market change keeps picking up.

Change happens, we can all agree to that. That being said, I would argue that terminology we use to describe activities in our profession changes a whole lot faster than the nature of our work justifies… I’ve been doing data science for over 20 years, although the term “data science” itself was (supposedly) only coined in 2008 by DJ Patil. With so many buzzwords floated, we certainly draw a lot of attention, but I would argue that we also create a lot of confusion. Proliferation of terms leads to ambiguity about their meanings and distinctive characteristics, which then leads to (legitimate!) skepticism. Unless you work in the field, it is impossible to keep up with the all the new terms. How are colleagues that get exposed to so many new catchy phrases expected to understand what is going on?

Peter Drucker said that if you really want to understand a topic, then try teaching it first. I myself like to say that unless you can explain something to your grandmother, using simple words, then you probably don’t fully grasp it, yet. Why don’t we try clarifying a term, rather than labeling that activity? My argument is that this will do much more for understanding and appreciation than coining a new term. Moreover, do we actually need all of the contemporary buzzwords? How about instead describing what we do, and how that might add value?

Old terms like “Business Intelligence”, or “Decision Support” have gone completely out of vogue, yet imho still seem remarkably descriptive. Unless something truly new and different emerges, why throw in more names? Isn’t that how Marketing (in itself a reputable profession, btw) earned itself a questionable reputation? I propose that instead we talk about substantive contributions, rather than sprinkle more “magic” onto these conversations. At the end of the day, it is all about the data, isn’t it?



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