The Brexit Vote: Why Big Data Failed



  • Traditional polling is often skewed towards population centers. Better to survey a diverse population.
  • The Brexit data collected didn’t reflect the strong division or deep anger of those most likely to vote “remain."
  • Data needs to be both statistically relevant data AND also reflect the nature of the real world.


On the eve and day of the UK "Brexit" vote, source after source cited "Big Data" as showing that the UK would vote to stay in the European Union. As we now know, that was wrong. What happened? Numbers do not lie; big data always tells the truth. The question is: What truth is it telling? 

This is a classic example of what experienced marketers have seen for years: you have to ask the right questions to the right people to get the right answers. In the business world, we have seen many examples where businesses structure their data mining according to their pre-conceived prejudices and wind up with answers that prove their prejudices right, but yield the wrong results.

In the Brexit case, the information relied on traditional polling, betting, and social media. Due to cost and ease of access, traditional polling is often skewed towards population centers — in this case, the London area, which everyone knew would vote to remain in the EU. Betting does reflect a better cross section of the population, but we have no way of knowing who is placing the bets or how diverse that population may be, though there is evidence that the people who bet on political items like this are people who have greater financial resources and think they understand the outcome. Social media provides good statistics but is heavily dependent on the younger generation, who we already knew were heavily in favor of remaining, as opposed to the older generation, which was in favor of leaving. 

The data was not wrong; it just was not answering the questions people wanted answered.

There were many reasons why people would want to leave the European Union, chief among them a stifling bureaucracy and socialist approach that has contributed to an economic malaise that has plagued Europe for years. But that is not the real reason for the exit vote. The exit vote hinged on the huge divide between the "haves" and the "have-nots." From the standpoint of the "have-nots," this is manifested in anger over immigration. Whatever the reality, immigrants are seen as "taking our jobs" and threatening security. Sound familiar? The people who hold these beliefs are very angry, and angry people vote, even when the weather is bad.

Ultimately, big data did not fail. The people driving the data collection failed, and this provides an important lesson for the future: you need not only statistically relevant data but also data that reflects the nature of the real world. In this case, the data collected didn’t reflect the strong division or deep anger of those most likely to vote “remain.” Just because the data is there does not mean it tells the right story.


The views expressed are those of the author and not necessarily The University of Texas at Austin.

About The Author

John Highbarger

Lecturer, Department of Marketing at the McCombs School of Business

John Highbarger joined the faculty of the Marketing Department in 2003, after retiring as Global Managing Partner in the Strategy Practice of...

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