Global judgements and ideas.

The Quantified Workplace: Tracking Affective Labour, for a Change

BBC4 Every Step You Take (17:08+)

I was funded by the British Academy/Leverhulme to carry out research on the Quantified Workplace experiment, carried out in one Rotterdam office. Claudia Hammond visited the office and interviewed me in this documentary.


In 2015, nearly a fifth (18%) of employees in Europe had access to wearable technology at work (ADP, 2015). Now, 1 in 3 companies provide wearable devices to track activity (Jiff, 2016), save money (Daws, 2016) and improve employees’ health and happiness. The ‘quantified work environment’ (Bersin, Mariani and Monahan, 2016) resembles the world of high performance athletes where technology aids people in identifying peak performance times and gaining rapid feedback. Accelerometers, Bluetooth, triangulation algorithms and infrared sensors allow managers to monitor workers far beyond traditional hours logged by swipecards. The benefits of improved productivity and employee wellness have been trumpeted (Campbell, 2015; Verma, 2014; Rackspace, 2014). Increasingly, ‘many wellness programs now address things like emotional well-being, mental health and financial wellness’ (Kohll, 2016). John Deere has been experimenting with a ‘happiness metric’, measuring employee’s morale every two week, checking workers’ motivation, team health and ‘regular pulse checks of the morale of their employees’ (Power, 2016). Call centre data reporting has long been used to view workers’ emotional responses to customers (Bain and Taylor, 2000; Poster, 2011) The Global Corporate Challenge and JawBone Up offer self-tracking packages with dashboards that reveal compared data. A related product, Olivetti Research’s Active Badge and its successors Sociometric Badge and Wearable Sensor Badge, can trigger automatic doors, transmit wearer identities and forward telephone calls. Badges record workers’ movements, speech, proximity and interactions, and analyse voice patterns and non-verbal cues to deduce mood and interpersonal influence (Lindsay, 2015; Olguin et al, 2009).

In 2015, I won a British Academy/Leverhulme small grant I called ‘Agility, Work and the Quantified Self’. The project proposal indicated that I would research ‘The Quantified Workplace’ (hereafter ‘QW’), a study that set up and run by one company from 2015-16. At the beginning of the project, the company distributed Fitbit Charge HR Activity Trackers devices to 30 employees; installed Rescuetime tracking software onto their work computers; and provided individualised dashboards as well as a shared dashboard where all participants could see each other’s progress. Participants received workday lifelog emails asking them to rate their subjective productivity, wellbeing and stress. Importantly, QW occurred during a period of change management as one multinational company absorbed a smaller company of real estate and work design consultants. The smaller company suggested and led the project as part of their way of indicating innovation and good practice to the larger company into which they were being merged. My role was to conduct independent academic research on the study, via surveys and interviews (Lukasz Piwek and Ian Roper were my Co-Investigators on the project).

QW’s manager indicated that the company’s intentions were to help workers adapt to a flexible working environment and to see to what extent employees’ self-awareness, stress, wellbeing and ‘wellbilling’ (which s/he described as being the amount of revenue employees generates for the company), were impacted, occuring during a period of transition. The company was interested in calibrating subjectively and objectively measured productivity to health and activity measures (interview 05/10/15). So workers emotional and physical impacts of corporate merger were potentially evident via self-report obtained by technological devices and self-reports.

In my book, The Quantified Self in Precarity: Work, Technology and What Counts, I argue that all workplace transformations require extra work, but a different kind of work than what might be measured in hours clocked seen in the factory settings. People, in the context of constant transformations, are very often dealing with something scholars call ‘affective’ and ‘emotional’ labour. Hochschild (1983) first labelled the concept of ‘emotional labour’, illustrating self-management of emotion at work, whether it be through suppressing anger or frustration with customers or co-workers, or by providing entertainment and producing joy in others. Hochschild outlined such labour required of cabin crew and in debt collection work (1983). Later, Brook listed ‘nurses, Disneyland workers, retail and childcare workers, schoolteachers, psychotherapists, holiday representatives, call-centre workers, bar staff, waiters and many others’ (2009: 8) as requiring emotional labour. But Firth states that emotion ‘usually refers to an individuated physical feeling (not mental or intellectual) that is passive (not active) and has a more-or-less irrational relationship to the world and outer life’. Firth, building on a large existing literature, contrasts this to affective labour, which is a ‘necessary part of social and ecological assemblages, which passes through the unconscious field’ (2016, 131). These forms of labour, then, become a ‘moral’ obligation in the corporate context. Earlier, Negri (1999) looked at aspects of affect and posits that the use value of such labour cannot be quantified in contemporary conditions in the same way it was during previous eras, because such labour exists in a ‘non-place’, the immaterial. Labour is not directly ‘inside’ capital, nor is it a straightforward ‘nonwaged reproduction of the labourer, added to labour’s use value’ (Clough, 2007: 25) either.  Regardless, these days, work seems to happen constantly, all the time, and is both nowhere and everywhere. Work is now all-of-life. So, how can tracking and monitoring for change management, such as seen in the study conducted here, be measured and understood?

Affective and emotional labour in the Quantified Workplace

The highest rates of increase in the areas of these kinds of extra work measured within the QW project were in the areas of autonomy, desire for coaching and support, and concern for privacy.  ‘Autonomy’ is defined as the level of control workers have over work tasks, schedules and decisions (Wheatley, 2017).  I asked interviewees about their ‘feelings of autonomy’, which I classified as a moderator of emotional and affective labour (see Johnson and Spector, 2007) because it demonstrates areas of intimately personalised change management; where workers, in this case, gain feelings of independence, perhaps both resulting from corporate merger as well as participation in the QW, and act upon them. The improvement of feelings of autonomy coheres with assumptions about the capabilities of electronic devices to empower and automate specific aspects of work that were perhaps once ‘ana-logged’. Simultaneous to this, several participants negatively stated concerns for privacy, sitting alongside positive feelings of autonomy, where the evidence of individualism also paradoxically occurred alongside increased desire for coaching and support. This being the case, several workers took the autonomous choice to stop engaging with the QW, calling into question how this came about and what triggered this response, given the other very positive impressions they held about the process of measuring work-related activities (see Table 1).


Table 1: Summary of themes arising within responses from interviews 1 and 2, with highlights of frequency of categories use as well as percentage of change in frequency between two interviews. (Graph created with help from Lukasz Piwek.)

Withdrawal and resistance

While at the beginning of the project, participants were not sure of the need to set goals for personal involvement in the project, by the end of the project, the number of responses indicating that it would be good to set goals increased by 27%. Many participants had very positive experiences, indicated in these statements during the second interviews:

[From] the dashboard, you can see how your mood was and how stressed you were but also how productive, so I think that’s very interesting and yes, it motivates me, just like I said, to feeling that I was productive.

The whole experiment is quite something, if I tell people about this, I really think, very cool that we’re doing this and yeah, hopefully we’re getting somewhere with it, so… it makes me motivated about having my part in the experiment and it should be a good part and motivated to help and motivated [around] what we’re doing with this project, more about, okay, now I want to see, yeah, what it is really bringing for me.

Workers’ sense of uncertainty about the project, as is evidenced in Table 1, decreased by 70% by the eighth month. Nonetheless, the rate of exit from the project as well as the rate of increase in people indicating they had stopped using the technologies rose. This can be explained by several factors but is probably linked to participants’ difficulties in using the technology. Indeed, responses in the first interviews demonstrate scepticism about the validity of the FitBit’s readings and wishes for more device intelligence, which could in part explain resistance and withdrawal outlined below, including such comments as:

A big question for me and for a few others as well, is uh, how reliable the FitBit is.

…this thing [FitBit] might be more intelligent than just recording my data.

Some respondents in the second interviews indicated frustration:

I don’t get any answers, I just fill in my things, but I don’t get an answer if it’s good or not, I just want to know if I was good and just start working.

I don’t wear the Fitbit very often. And when I will wear it, it is for myself and to see how active I am. It confirmed my thoughts, which I had in the beginning. It is better to change your behaviour based on your feelings rather than a device.

Towards a conclusion

The QW project demonstrates the ways in which management has begun to attempt to measure more and more aspects of people’s lives and work, to the point that people may find it hard to tell the difference between the two. Evidence from my funded research about the QW project demonstrates one example of the methods being used in Industry 4.0 workplaces, where workers are asked to track more aspects of their lives and link them to work and productivity than ever before. Participants’ experiences of this level of intimidate tracking demonstrate rising sensitivities to privacy and explicit exit. These responses may demonstrate the tensions that emerge when all-of-life is digitally tracked.

(To cite from this post, please email Phoebe Moore first at p.moore at


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This entry was posted on August 29, 2017 by .
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