Compensatory data work: the invisible labour of ‘working around’ data failures and breakdowns

One of the presumptions underpinning our research is that digital data in schools is not ‘working’ as smoothly, seamlessly and/or successfully as it might. As such, an important line of inquiry within each of our case study schools will be documenting examples of data glitches, impasses and breakdowns – a sub-set of what we have referred to before as ‘data frictions’.

Of course, we are not looking for these cases of data failure with an expectation of being able to easily ‘fix’ whatever is going wrong. Instead, we hope that investigating these situations will provide rich insights into how datafied schools function practically on a day-to-day basis – particularly in terms of the invisible work that staff and students undertake in order to maintain and sustain data-driven processes regardless of their flaws.

As Lippert & Verran (2018) observe, the compensatory work that takes place around digital data to ‘keep the show on the road’ is usually glossed over in discussions of datafied society – yet “human actors, and potentially artificial actors, too, are partially well aware of tensions and frictions within their numbers, data or algorithms” (p.9). As such, we need to pay close attention to how staff and students are working to manage gaps, incompatibilities and other dysfunctional processes relating to the use of data within their schools.

This will undoubtedly include instances when staff and students have to “effect clunky connections and work-arounds” to circumvent systems and protocols (Lippert & Verran 2018, p.4). In addition to these awkward ‘fixes’ and ‘fudges’ will be unavoidable bouts of pretending, glossing over, and working around. This will also include implicit collective understandings that everybody needs to simply carry on regardless when a particular data-driven system does not quite do what it is meant to.

Rather than gloss over such behind-the-scenes work, the aim of our research project is to first highlight these practices, and then consider what they tell us about the realities of how digital data plays out within schools. Paying close attention to these data frictions is a first step towards considering how people’s everyday engagements with digital data might be reconfigured and (perhaps even) improved.



Lippert, I. & Verran, H. (2018). After Numbers? Innovations in Science and Technology Studies’ analytics of numbers and numbering. Science & Technology Studies, 31(4):2-12