Understanding Well-being Data

chapter 5 Getting a sense of Big Data and well-being


Another major reason why we need to ask critical questions about Big Data and well-being concerns the financial value of knowing more about people and the financial value of the systems that sort people for public services and welfare distribution [1]. Beyond public services, the value of the new ways that Big Data can work is not just in knowing more about people, but because of the potential this knowledge has to orient people’s thinking through suggestion and in some high-profile cases to manipulate what they do. They enable marketers to sell you products you might be most tempted by, knowing when you might be most susceptible too, based on your previous sales or what else you’ve looked at [2]. They also enable political campaigns to target their messages in the same way and change voting behaviour [3]. The recent Cambridge Analytica scandal saw Facebook implicated in not only the unethical use of people’s data, and knowledge it had on their behaviour, but in misinformation that is thought to have changed the results of the US presidential election 2016 and Brexit in the UK the same year.

The first and second waves of well-being [4] from Chap. 2, and to which we keep returning, evolved as historical moments in which data capabilities married policy-makers’ aims: improving the way we think about measuring human progress. Similarly, well-being metrics became more viable because well-being methodologies were evolving in a way that politicians saw as favourable. Political will and academic developments work with evolving infrastructure and technological development to enable datasets to be created with more detailed and nuanced information about quality of life. These factors work together for new methodologies to generate new kinds of data and analytical approaches which then, by extension, affect research and policy-making, which in turn impact upon our quality of life.

The increasing emphasis on Big Data as ‘the new oil’[5] (a misnomer, of course) is not because datasets are ‘better’ (which would need some qualification) or because the technologies are new (though admittedly this is partly why it has become such a fixation). Instead, ‘Big Data’ datasets offer data with different qualities than more traditional data acquired by surveys. This means big datasets offer capacity to answer different research questions—or answer the same research questions differently. Most importantly, they have been called the new oil because: (1) ‘data powers today’s most profitable corporations, just like fossil fuels energized those of the past’ [6] and (2) this means these qualities can be financialised.

The amount of data on individuals that are now collected is almost impossible to visualise in our minds. The growing number of devices and sensors means we are generating more and more data than can be collected: the International Data Corporation predicts that by 2025, the total amount of digital data created worldwide will rise to 163 zettabytes [7]. That is 1021 (1,000,000,000,000,000,000,000 bytes) or one trillion Gigabytes. The European Commission forecasted the European ‘data market’ to be worth as much as €106.8 billion by 2020 [8]. These kinds of numbers reinforce the importance of looking at Big Data as social phenomena—with social effects, but how new are large datasets about people and populations?


  1. Eubanks 2018[]
  2. Turow 2011[]
  3. Avila 2019; Bates et al. 2016; Murgia 2017[]
  4. Bache and Reardon 2013[]
  5. This is largely credited to the 2017 article in the Economist, ‘The world’s most valuable resource is no longer oil, but data’ (The Economist 2017).[]
  6. Matsakis 2019[]
  7. Coughlin 2018[]
  8. Ram and Murgia 2019[]