Gig work platforms such as Urban Company, Ola, and Swiggy have frequently projected themselves as being crucial actors in India’s development agenda because they generate employment, increase labour force participation and offer opportunities for “upskilling”.
These workers are not employees – instead they are classified as partners who use the platforms to be connected to customers who want services such as beauty care and housekeeping, ride-hailing and delivery.
Still, even though this “gig work” is outside the purview of the traditional relationship between employers and employees, these platforms have a common motivation in investing in workers: this would improve their efficiency by reducing the time taken to deliver services and standardise customer experience.
To build their reputation as skill development actors, these platforms provide short-term training and certification to workers, either directly or through third parties.
Prominent platforms have partnered with the Ministry of Skill Development and Entrepreneurship and related state government programmes. They have also been advocating for an expanded role in the skill development policy through the inclusion of platform work itself as a skilling mechanism.
However, the extent to which these platforms actually contribute to skill development is a matter of discussion. The skill development records and career paths of the people who work for these platforms tell a different story. Further, business models and technological features developed by platforms are fundamentally inimical to meaningful skill development.
The primary route these companies have taken to integrate platform work into the skill development policy of India is by claiming to provide opportunities for “micro-entrepreneurship” or “self-employment”. Platform work is projected as an accessible way to build entrepreneurial skills. This is possible because platforms treat workers as independent contractors instead of employees, using terms such as professionals and partners.
Platforms have manufactured an identity for workers that is characterised by professionalism and entrepreneurialism, which is continually reinforced in contracts, training and general communication. This identity has the potential to increase the dignity and social value of platform work, but is far from an accurate description of the relationship between workers and platforms.
Platforms operate as asset-light businesses, shifting the onus of asset ownership to workers. But service delivery is strictly controlled by on-demand platforms and their value proposition hinges on the standardisation of services.
Unlike a true model of self-employment that offers autonomy and flexibility, platforms control all aspects of work including working conditions, task allocation and pay. Workers are subjected to the costs of being entrepreneurs and yet have little scope to acquire entrepreneurial skills.
In-depth interviews with workers show how this duality plays out in everyday work, where platforms standardise and control all aspects of their services and closely monitor workers at all stages of service delivery. I spoke with two workers – Mohit*, a hairstylist, and Yash*, who repairs air conditioners.
They have been working at the platform for the past two to four years, and were previously engaged in salaried and contract-based work. Conversations with Mohit and Yash revealed that platform control and standardisation is persistent across all aspects of work, right from recruitment.
The recruitment policy at the platform prioritises work experience and skill level, although these criteria are disregarded while determining the terms and nature of work.
Both Mohit and Yash developed their skills through prior work experience, on-the-job training, and vocational certifications. However, these skilling benefits have not been transferable to the work allocated to them due to the standardisation of the platform’s services.
Their work as well as working hours are largely determined by the incentive and disciplinary mechanisms of the platform. Earnings are closely linked to the number of tasks completed, putting undue pressure to maximise this output. To facilitate the maximisation of tasks, platforms have designed work in a way that routinises and fragments services for swift service delivery.
The design and organisation of platform work, characterised by a high division of labour, has been likened to a digital form of “Taylorism”, which involves breaking down work processes into small tasks. Services on platforms are broken down into short, specific, standardised tasks.
This manner of work is not conducive to skill development and dulls the individuality in the skills of workers. It is limiting for workers with higher skill levels, and also for those seeking upskilling opportunities.
Platforms exacerbate this mismatch by artificially segmenting workers into tiered service categories, largely to manage workforce flexibility and meet service demand. These classifications are arbitrary and based on the rating systems of platforms rather than actual work experience and skill levels.
Far from supporting skill development, these issues can have an opposite effect by pushing workers into performing repetitive tasks in short timeframes.
Further, even the off-the-job training provided by platforms is dictated by the nature of standardised work. Workers have criticised the training provided by platforms as unsuitable for the meaningful development of skills, because it focuses primarily on enhancing customer experience.
Ratings and algorithms
Performance evaluation, regular assessments and feedback are key to skill development programmes. In platform work, these components of management are outsourced to customers. To facilitate this outsourcing, platforms have commodified interpersonal and communication skills, which are key to customer service. Customers control the skill assessment of workers through a ratings and review system, which is reduced to five-point scales on most platforms.
Crucially, many workers are forced into (re)training, again determined by the ratings system instead of a training-needs assessment, where sessions are organised for workers whose ratings fall below a threshold decided by platforms.
Substituting customers for management is at odds with the established standards for skill assessment, such as the framework laid out by the National Skill Development Corporation. As an assessment tool, rating systems fail to meet standards of validity and reliability, and do not necessarily capture workers’ skills at all.
Rating systems are largely based on non-skill components such as behaviour, service delivery and response rate. By design, workers are evaluated on each instance of service delivery, rather than their overall performance over longer periods, as is usually the case for skill assessment.
A major drawback of the system is that customers are often unaware of the platforms’ standards and interpretations of ratings, which renders the process grossly unreliable. Customers provide ratings based on arbitrary criteria and in many cases, do not provide ratings at all or do so up to a month after the service has been fulfilled.
Mohit said that while his platform only considers a five-star rating as an indication of satisfactory service, customers gauge performance on a different scale, providing four to four-and-a-half stars for good service and five stars only for exceptional service delivery.
Moreover, customers also consider non-service aspects while determining their final rating, such as payment modes and product quality, which workers have no control over.
Customers are in a position of power over workers, and the entanglement of ratings with service quality forces workers to please customers no matter the cost, including undertaking tasks that they are not being paid for. Despite these glaring limitations, ratings continue to play a key role in performance evaluation for platforms.
Mohit and Yash said they are dependent on high ratings to continue working on the platform and prevent their accounts from being deactivated. As Mohit said, “wherever you work, you have to bow your head and nod along”, or run the risk of receiving low ratings and deactivation.
Managerial functions on platforms exclude any provisions for two-way feedback and planning with workers on their skilling needs. The workforce management is skeletal and only concerned with maintaining the efficiency of matching and service delivery.
Mohit said that the platform’s category managers – supervisors in specific service lines – are hardly accessible and are involved only in recruitment and handling on-the-job grievances of workers.
Managerial functions, both automated and human-led, are geared only towards monitoring and shaping performance in accordance with the platforms’ business development strategies.
On-demand platforms tightly control work processes facilitated by algorithmic management, wherein platforms use algorithms to manage workers end-to-end, including assigning work and tracking performance.
In essence, this process outsources the managerial responsibilities of an employer to algorithms. The algorithmic management, however, primarily functions as a disciplinary tool through intense surveillance and control.
The high degree of control exercised by platforms, and the near absence of middle management focused on skill management, foreclose the ability of workers to meaningfully acquire skills and develop their careers.
Gig work platforms have a surplus of labour and only offer short-term work – which means that workers are dispensable and chronically disadvantaged compared to platforms. Platforms capitalise on this skewed power advantage and disregard the skilling and career development goals of workers.
In fact, engaging in minimal skilling and training commitments is crucial to maintaining the platforms’ careful positioning as mere intermediaries.
As skill development policy looks to increasingly integrate industry actors for skilling through a public-private partnership model, both on and off-the-job training prospects through platforms contain major structural drawbacks to effectively contribute towards bridging India’s widening skill gap.
The effectiveness of an employer-led model of skilling depends on how work is organised and managed, the nature of the employment contract, the degree of autonomy workers have, and the extent to which they are involved in skilling and related decision-making.
So far, dominant platforms have shown no inclination towards altering their business models in ways that can lead to effective platform-led skill development.
*Names changed to protect identity
Chiara Furtado is a Research Assistant at the Centre for Internet and Society, India