Confronting Precarious Work

Beyond social security for platform workers
Kaveri Medappa, Rajorshi Ray, Mohammad Sajjad Hussain
Issue: November 6, 2020

Kaveri Medappa is a doctoral student in the School of Global Studies, University of Sussex. Rajorshi Ray is a doctoral student in the Department of Humanities and Social Sciences, IIT Kanpur. Mohammad Sajjad Hussain is a doctoral student in the Department of Sociology, Delhi School of Economics.

Food delivery bikes in Delhi: India's new labour laws fail to bring exploitative labour conditions under scrutiny | Barry Pousman (CC BY 2.0)

The precarisation of labour is written into the very logic of platform business models. Ignoring this, and focusing only on social security measures to protect workers, normalises exploitative labour conditions as the 'future of work'.

On 22 September, over widespread protests, the Lok Sabha passed three contentious labour codes, on industrial relations, occupational safety and health, and social security. Included in the code on social security was a set of measures for app-based workers1, whose lives had been brought into sharper focus by Covid-19 as they found themselves either out of work or cast as front-line workers providing ‘essential’ services to affluent urban residents. Since the pandemic began, there have been waves of protests by workers of the food delivery app Swiggy and of platform-based drivers across different cities in India amidst signs of deterioration of their work conditions.

But the code on social security held cues as to the perfunctory nature of measures to protect these sets of workers. It discusses setting up a National Social Services Board to recommend and monitor schemes for “unorganised workers, gig workers and platform workers.” The broad thematic areas for these schemes include life, disability and accident insurance, health and maternity benefits, old age protection, and creche services. The schemes, as and when they are formulated, will be funded through a combination of contributions from workers, state governments, the central government, and “aggregators”, with the contribution from aggregators limited to 2% of their “turnover” and 5% of “amount paid or payable by an aggregator to gig workers and platform workers” ( p.70). (This plan is uncannily similar to a proposal by Uber's CEO in opposition to a law which grants app-based drivers labour rights in California.)

Left unaddressed is a deeper malaise: the ‘lean’ operational logics of platform businesses propped up by speculative finance capital. Consistently declining and unpredictable incomes and worsening quality of work are features written into the very structure of these business models. A sole focus on social security measures could serve to normalise and encourage exploitative labour conditions; labour conditions that have been progressively eroding over the past few decades in India.

Using the rhetoric of flexibility and technological innovation, platforms are institutionalising precarity.

We draw on our year-long, ethnographic research in Bangalore, Hyderabad, and Kanpur with close to 200 male, platform–dependent drivers and food delivery workers, to show how some of the biggest platforms in India are further entrenching labour informality. Using the rhetoric of flexibility and technological innovation, platforms are institutionalising precarity.

Drawing from in-depth qualitative interviews, observations, ride-alongs and auto-ethnography, we discuss how flexibility is exercised by platforms and not by workers, and at what costs workers survive the flexibility demanded of them. We show why it is critical that we look at the platform business model and its financing to understand the experiences of workers, and argue that token social security measures will do nothing to address the more deep-rooted problems that workers face.

Platform Capitalism – Of good guesses and big bets

Instead of having a sustainable business plan for the medium and long term, start-ups work with “good guesses”, frequently adapting business decisions to respond to the market and to reduce exposure to risks. Crucial to understanding the business models and operational decisions is the principle of being ‘lean’, having to be agile and dynamic. Enabling this leanness is an asset-light principle which dictates that new age businesses respond to market cues better if they minimise capital-intensive costs, including on labour.

In the early and mid stage funding phases,2 these platforms pursue growth before profits and burn cash, spending more money than they earn, to aggressively attract users, to ‘scale’ and capture market share, and to drive out competition through predatory pricing. The more users—customers, drivers and delivery workers, restaurants—on the platforms, the more value created for users through ‘network effects’. Access to greater amounts of data builds smarter algorithms and allows these businesses to optimise operational costs.

Continued access to large amounts of venture capital (VC) and private equity funds has been instrumental in companies such as Uber, Ola, Swiggy, and Zomato achieving scale, exhibiting risk taking capacities as well as bringing about behavioural changes amongst its users. A combination of heady visions, speculation and calculative bets pushes these investors to continue funding loss-making platforms.

Valuations [...] act as a performative metric to build hype around a platform, attract more funding, and to trigger ‘liquidity events’.

The speculative aspect emerges from the belief that at least a few of their investments will become monopolies, and the huge gains from a handful of investments would outstrip losses from others (This is the case in the online food delivery sector in India, which after a spate of closures and acquisitions has essentially become the playground of two businesses, Swiggy and Zomato.3) Calculative bets could be in timely exits from ventures or becoming monopoly funders themselves. For instance, Softbank and its vision fund control 90% of the ride-hail market in the world through their investments.

Growth and the amassing of data—mostly produced by workers—becomes key in enhancing start-up valuations, raising further rounds of funding (Van Doorn and Badger 2020), and hastening opportunities for early investors and funders to liquidate their investments with profit (Kenny and Zysman 2018). Although valuations do not reflect actual revenue or profits, they act as a performative metric to build hype around a platform, attract more funding, and trigger ‘liquidity events’, which include start-ups buying each other, investors selling their stakes, or the platform announcing an Initial Public Offering (IPO) (Langley and Leyshon 2017).

Platforms resist increasing costs to price sensitive consumers as they might switch to rival platforms [... rather, they] reduce operating losses by cutting workers’ pay and remuneration rates.

As these heavily capitalised and financialised platforms enter their late stage funding rounds, attracting more funding or announcing a liquidity event requires them to find ways to show new funders future prospects of profits. In India, an unlisted company needs to show 3 years of profits in order to be eligible to file an IPO. Platforms resist increasing costs to price sensitive consumers as they might switch to rival platforms (Choudary 2018). In India, where labour supply is abundant, platforms choose to reduce operating losses by cutting workers’ pay and remuneration rates.

It is on the backs of low-valued workers with little negotiating power that the ‘disruptive’ and ‘lean’ platform model is premised. Seemingly abstract boardroom decisions to scale, pivot, or decrease burn rate have very real, material consequences on the lives of workers.

Flexibility: For whom?

“How much you earn is up to you.” “You can log in or log off whenever you like.” “Your earnings depend on your hard-work.” These were some of the pitches of flexibility and freedom app-based workers remembered hearing from managers when they were “on-boarded” onto platforms.

In those early growth stages, during 2012-16, drivers in India were attracted by Uber and Ola with very high incentives.

“Like sheep we all fell into the ditch,” Hanumanthu, a 38 year old driver who migrated from a village in Bellary to Bangalore in 2015 to work for Uber told us. (All names of workers have been changed to protect their identity.)

Many drivers had aspired to become owners of cars themselves, and were encouraged to take loans to buy vehicles.

Drivers like him remember earning close to Rs 5,000 a day during the first few years (2013-16) of Uber and Ola operating in the city. They were offered handsome referral bonuses for getting others to join. Many drivers had aspired to become owners of cars themselves, and were encouraged to take loans to buy vehicles. Similarly, attracted by the promises of high incomes and freedom from subordination, most food-delivery workers had typically quit their previous low-paying, contract-based jobs. Like the drivers, they too invested heavily in motorbikes and other costs related to migrating and living in cities.

Contrary to what platforms claim, an overwhelming majority of our respondents (between 75% and 90% ) depended on app-based delivery work and driving as the sole source of income and worked “full-time” for platforms. Youngsters between 18 and 35 formed a resounding majority of food delivery workers. Amongst drivers it was more common to find workers between 30 and 40, although Bangalore and Kanpur also attracted a considerable number of very young, first-time migrants.

They had no warning that the growth phase would not last forever.

What is kept from workers during training, nor spelt out in the technically worded “terms and conditions” (in English), is that the promised remuneration would steadily decrease and the incentives harder to achieve. Nor would workers have control over how much work they receive or when they receive it: this is allocated through algorithms.

For workers it means feeling trapped in exploitative work sold as being entrepreneurial. 

Since 2016, drivers have seen a steep reduction in payments and steadily increasing commission rates to be paid to the platform. Hanumanthu pointed out that auto-rickshaws in Bangalore get better per kilometre fares (Rs.13.5) than app-based drivers (Rs.8 to 10 per km). Incentives are a fifth of what they were three years ago. The platform now charges a commission of anything between a quarter to 30% of their earnings.

Workers had little ‘freedom’ or ‘flexibility’ but simply had to comply with the platform’s decision.

Hanumanthu had bought three additional cars on loan, but unable to keep up with EMI payments over the last two years, he has had to sell them at a loss. He is left with a single car which he drives, and has a year remaining on its loan repayment. By December 2019, it had become difficult for him to take home even Rs.800 a day despite working 12 to 14 hours.

“Who would think that they would trap us like this? Now we can’t even leave this work with all the loans that we have.”

Food-delivery workers have similar stories. Swiggy workers in Bangalore recounted how per order rates have been steadily decreasing since 2017, the third year of the platform’s operation: from Rs 50 to Rs 40, and further down to Rs.30 in 2018-19. Joinees after June 2019 have it worse: they receive only Rs.15 per order. In Chennai and Hyderabad, Swiggy reduced minimum per-order rates to Rs.15 in August 2020 from Rs.35 earlier.

Conditions of work also change without any consultations with “partners”. In February 2020, following a liquidity event, the purchase of UberEats by Zomato, workers logged into their accounts to find that four localities lit up on their “map” instead of one. From a four kilometre radius for deliveries, the distance which workers had to travel increased to 10-14 kilometres. This meant longer distances to travel, more expenses on fuel and more time wasted on deliveries in localities less known to them. Incentives continue to be reduced. Cancelling more than one order per day in Zomato results in being ineligible for the day’s incentives. In mid-March, even as workers were starting to suffer decreasing orders due to the spread of Covid-19 in India, Zomato further slashed incentives across cities for most workers without any warning or explanation. During the lockdown, Swiggy too suddenly stopped paying its workers monthly incentives. All of this led to longer working hours. Workers had little ‘freedom’ or ‘flexibility’ but simply had to comply with the platform’s decision.

Akash, a former Zomato worker [...] identified incentives for what they actually are: a mechanism of worker exploitation.

Incentives are conditional upon adhering to a slew of requirements around log-in hours, weekend attendance, limit on cancelling orders, ratings and so on. But incentives are a significant component of income, and workers usually apportion this money towards fuel costs and other daily work-related expenses. Even after multiple cuts, Zomato’s daily incentives are roughly 30% of order earnings currently.

During a brief interview with a fleet manager at one of Swiggy’s Bangalore “hubs”, one of us asked him about workers being logged in for extremely long hours. (Swiggy’s mandatory “log-in shift” of 10 hours for full-time workers is much more than what is permitted by law.)

The manager, a young man in his early 30s, swivelled on his chair and casually remarked: “It is their choice to work so much [...] they work so much because they want incentives.”

This rhetoric of ‘choice’ was countered by Akash, a former Zomato worker whose ID was “terminated”—platform-speak for autocratically firing workers—for protesting the consistent lowering of rates in Bangalore. He identified incentives for what they actually are: a mechanism of worker exploitation.

They tie our hands through incentives. They know earnings from orders alone doesn’t work out for us if we do not earn incentives. They use this to play with our lives.

Imran’s experience is an example. A 42-year-old Swiggy delivery worker in Hyderabad, this primary earner for his family of four has found it difficult to earn even Rs 10,000 per month (after allowing for fuel expenses), despite working 13-15 hours a day. The Rs 3,000 monthly incentive money he used to earn went towards his children’s private school fees. “Because they don’t have school now, I’m somehow managing to run the house. If school starts again, I will not be able to send them to school with these [current] earnings.”

Surviving platform work

On-demand labour platforms label workers as ‘partners’ or ‘micro-entrepreneurs’ by claiming to offer them control and flexibility over work. These claims are misleading because platforms unilaterally control and dictate every aspect of work for their so-called partners. 

Flexibility, far from a luxury, is an imperative, a necessary trait workers must embody in order to survive the vicissitudes of platform work.

Workers have no participation in the decisions that directly impact the conditions of their work. Flexibility, far from a luxury, is an imperative, a necessary trait workers must embody in order to survive the vicissitudes of platform work. During our interviews, it was striking to find workers, both food delivery workers and drivers, speaking of 12-hour work days as the “minimum” they worked.

As remuneration decreased and other work opportunities looked bleak during the economic downturn (present even before the pandemic), workers had to be ‘flexible’ and stretch their already long working days to accommodate the whims of platforms. With worsening incentives, we saw screenshots of login hours stretching to 14, 15, and even 18 hours in order to sustain previous levels of incomes and meet the growing costs related to fuel, loan instalments, vehicle repairs, servicing costs, and expenses on accessories such as portable chargers and earphones.

Besides extending their work-hours to punishing levels, workers also resorted to borrowing money. Drivers speak of being in a debt spiral, trying to offset one debt with another, in a bid to keep up with EMI payments and prevent their vehicles from being taken back by the finance company for defaulting on repayments.

“It is shameful to have a car seized [...] and this is my only source of income. What will my family and I eat if they take away the car?” asks Suresh, an app-based driver. “To save the car,” he has resorted to borrowing from moneylenders and has also mortgaged his wife’s jewellery.

[Fintech] apps automatically deduct payments from workers’ earnings on the platforms, further binding workers to platforms.

Since Covid-19, this delicate process of ‘rolling’ debts, especially amongst drivers, has become ever more challenging to juggle. Appallingly, platforms like Swiggy, Zomato, Ola, and Uber refer workers to lending apps such as Avail and SuperMoney. These apps automatically deduct payments from workers’ earnings on the platforms, further binding workers to platforms and also creating a market for fin-tech start-ups. Moratoriums on loans announced by the government was not of much use to workers who were indebted to such fintech start-ups, as platforms kept deducting loan instalments from workers” accounts even during the pandemic.

With work hours easily reaching 10-15 hours per day for most platform workers, the impact on their health and the risks they pose to themselves and others on the roads is severe.4 Younger drivers often sleep in their cars and drive for 2 to 3 days at a stretch, resting between rides. It was distressing to hear youngsters in their mid-twenties and early thirties complain of health ailments as a result of working in platforms: insomnia, gastric trouble, piles, back pain, eye infections, chronic muscle aches and headaches. Rest and recreation are a luxury to workers who can hardly meet members of their family, who are usually asleep when they return home. With workers preoccupied with reaching “targets” arbitrarily set by platforms, stress is a constant feature in their lives every day.

These are the long-term impacts on the lives of workers that the accident insurance policies offered by platforms and the government do not compensate for.

As platforms continue to slash earnings and incentives, workers, especially youngsters who are savvy enough to compare platforms and exchange information about them, juggled work across several platforms, hoping to earn a few hundred rupees extra in a day. Workers who depended on a single platform even until early this year, have become forced to split their time between platforms in the hope of earning a livelihood, as other forms of employment opportunities look bleak. This transposes labour anthropologist Jan Breman’s (1994) 30-year old characterisation of rural “wage hunters and gatherers” to an urban, digitally mediated context in 2020.

The need to look beyond social security measures

The everyday realities that workers struggle with will remain unchanged even if “gig” and “platform” workers have access to a social security fund as proposed in the new labour code. The more pressing problems faced by workers are the frequent reductions in remuneration structures premised on an extremely exploitative piece-rate, target and incentive model; the lack of transparency in calculating the earnings of workers; dubious workings of supposedly neutral algorithms; the total lack of space for collective bargaining; and the blocking and terminating IDs of protesting workers. It is here that the state needs to intervene by enacting stringent regulations and laws.

Referring to workers as ‘partners’ is what allows platforms to remain lean and off-load the costs and risks of work to low-paid service workers.

Successive protests by platform based drivers in India have been demanding state intervention to bring platforms under state-level transport laws/regulations along with appealing to Uber and Ola to increase incentives and decrease commissions. Delivery workers have also been demanding that platforms end their exploitative ways by increasing pay-rates and have been demanding that state governments regulate this sector. However, these continue to be ignored and the excesses of platforms are further enabled by the apathy of governments in awe of the business model's “disruptive” potential.

The demand for employee status and benefits amongst app-based workers has been less unanimous in India, unlike in certain countries in Europe and in cities in the United States. This, however, does not mean that the ‘partner’ label that platforms force on workers should not be put to the test of law by examining the lived experiences of workers.  The labour codes make no attempt in bringing this exploitative labour relation under scrutiny. Referring to workers as partners is what allows platforms to remain lean and off-load the costs and risks of work to low-paid service workers. Consultants, funders, and founders of platform businesses have criticised the proposal to contribute towards workers' welfare, claiming such measures would "destroy the model", and are devising ways to pass on these costs to workers.

As the pandemic continues unabated and the economic vulnerabilities of people intensify, we may witness an increased demand for platform work. E-commerce is one of the few sectors which has had a steady rise in demand. The unemployment crisis in the country, the ongoing economic downturn, and the anti-farmer laws passed recently, all risk pulling growing numbers of rural migrants and urban unemployed towards such employment. As ever-flexible capital finds new ways to expand the platformisation of work across sectors, it becomes urgent to subject this industry to serious scrutiny.


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Breman, J. (1994). Wage Hunters and Gatherers: Search for Work in the Rural and Urban Economy of South Gujarat. New Delhi: Oxford University Press.

Choudary, S. Paul. (2018). The architecture of digital labour platforms: Policy recommendations on platform design for worker well-being. ILO Future of Work Research Paper Series.

Cushen, J., & P. Thompson (2016). 'Financialization and value: Why labour and the labour process still matter'. Work, Employment and Society 30(2), 352–365.

Doorn, N. van, & A. Badger. (2020). 'Platform Capitalism”s Hidden Abode: Producing Data Assets in the Gig Economy'. Antipode.

Kenney, M. & J Zysman. (2019). 'Unicorns, Cheshire cats, and the new dilemmas of entrepreneurial finance'. Venture Capital 21(1), 35–50.

Langley, P., & A. Leyshon. (2017). / capitalism: The intermediation and capitalization of digital economic circulation'. Finance and Society 3(1), 11–31.

  1. We deliberately use the term workers and not ‘partners’ throughout the article as an attempt to not normalise the usage of language that is misleading and the basis of worker exploitation.
  2. Seed funding and perhaps the first 2-4 years of funding. The timelines of various funding stages is contingent on several factors and therefore hard to define.
  3. Amazon has very recently entered the online food delivery sector in India in certain cities.
  4. See for a comprehensive report on the health impacts of platform based driving on Uber and Ola drivers.
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