Calling Bullshit on Big Data?

After nearly 20 years in the public discourse, the term “Big Data” is still teetering on the cusp (or maybe stumbling over the threshold?) of true ubiquity. Yes, you see the term everywhere. But how well is it understood? Has the era of “Big Data” finally arrived? Or is it over? What’s the “big” deal anyway?

The headline and photo caption for Michelle Nijhuis’s piece in The New Yorker, “How to Call B.S. on Big Data: A Practical Guide,” are tantalizingly dismissive: we’re overwhelmed and “information-addled” and “Big Data” is routinely used to confuse and deceive the public. Nijhuis’s actual article is a bit more nuanced, and the University of Washington course that she profiles is even more so: bullshit is pervasive and nothing new; “Big Data” just provides some new tools for crafting and expressing it, potentially more convincing than others because of their supposed objectivity. As Nijhuis summarizes: “While data can be used to tell remarkably deep and memorable stories, Bergstrom told me, its apparent sophistication and precision can effectively disguise a great deal of bullshit.”

The course that Carl Bergstrom and Jevin West designed for the University of Washington Information School is actually meant to address the phenomenon of bullshit “in the age of Big Data.” Their explicit goal is to equip students to “Remain vigilant for bullshit contaminating your information diet,” and “Recognize said bullshit whenever and wherever you encounter it.” But Bergstrom and West acknowledge that data can illuminate as well as obscure meaning. They expect their students to be able to meet data scientists on their own terms—knowledgeably and critically.

So what can a business leader take away from this discussion? Is Big Data just a load of B.S.? Here are some key points to keep in mind:

  1. It’s not easy.
    Peter Drucker, as insightful as he was, spent three decades trying to understand the role of information workers, and went to his grave still searching for ways to grasp and refine these new ways of working. If harnessing information for business value were easy, Drucker or someone like him would have solved it already.
  2. Just because we haven’t solved it yet doesn’t mean it’s not worth doing.
    Rome figured out how to deliver water effectively. Boston delivers water effectively. Some of our technology is remarkably similar to the Romans’; some isn’t. In a spirit of progressive elaboration, we continue to tackle this very old problem, and every little investment pays benefits down the road.
  3. Don’t get hung up on names: focus on the goal of unlocking value.
    The phrase “Big Data” isn’t really a description of a particular size or kind of data. It’s a narrative device, telling us that we’re looking at a new dimension of opportunity. Think of it as a hook to help us as business leaders envision the possibilities embedded in the information we have on deposit. The goal is to keep focusing on the goals of value and alignment.
  4. Healthy skepticism is good…
    …and it’s important for colleges and universities to emphasize that. We need to be able to tell the difference between snake oil and real medicine—and we assuredly want to pass that skill along to our kids. At the same time, though, don’t let skepticism turn into a Jedi Mind Trick—the droids you’re looking for are really there. Call bullshit on the bullshitters, but remain vigilant for real value.
  5. B.S. is, was, and always will be.
    Where there is information, where there is communication, there will be bullshit. But guess what? There is real value in information as well—always has been, and always will be. And our job is to find it.

The bottom line is this: in business we don’t yet have a good solution for extracting the value of information on deposit. Terms like “Big Data” describe our current understanding of that information, and they can help galvanize us for future. Yes, that information can be aggregated in ways that are deceptive and/or deliberately confusing, but that doesn’t mean it’s worthless. Don’t lose patience; don’t lose nerve—true value is out there!



PIER Working Paper 12-037, “On the Origin(s) and Development of the Term ‘Big Data,'” by Francis X. Diebold, Penn Institute for Economic Research, September 2012.

“I’m A Data Guy And I Don’t Get Why Everyone’s Obsessed With Data” by Alex Kirk on LinkedIn Pulse, December 2016.

“How to Call B.S. on Big Data: A Practical Guide” by Michelle Nijhuis in The New Yorker, June 2017.

“Calling Bullshit in the Age of Big Data” by Carl Bergstrom and Jevin West, 2017.

“Calling Bullshit in the Age of Big Data: Syllabus with links to readings” by Carl T. Bergstrom and Jevin West, University of Washington, Spring 2017.


Photo credit:
Adam Sherez

Published by

Elizabeth Albee

Data and information strategist with a passion for driving companies toward success by harnessing information to power innovation.

3 thoughts on “Calling Bullshit on Big Data?”

  1. I was hoping you might drill down to the facts of how much erroneous, incomplete, context-less data there is for Big Data to try to make sense of. No data quality, no Big Data insights. It is DIFFICULT to get Leadership to invest in making data meaningful. What is your take?


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