Obviously, reliable data is key in research on platform work. Given the drawbacks of the various methods applied for investigating this topic discussed in our previous post, platforms seem to be the source of the most reliable information on this topic. However, laying researcher’s hands on it is not that simple.
Companies in the tech sector - including online labour platforms discussed in these blog series - have built their businesses around data. Given that data is the key asset for income generation, competitiveness and innovation (which, of course, have brought substantial benefits to economies and societies in the past decades), the reluctance of platforms to share it with third parties can be easily explained by economic rationality. However, this has consequences not only for the potential competitors, but also for platform workers, researchers and policymakers.
For example, so far, no fully reliable data sources exist to estimate the number of people working through platforms. Researchers, as well as policymakers, would really benefit from this information. Understanding the real prevalence of different types of platform work would allow to prepare the necessary policy responses to this increasing and evolving phenomenon. After all, platform work is not limited to the tech sphere – it affects employment, labour and societal relations, skills development, consumer wellbeing and many other areas. However, platforms conveniently treat the numbers of workers (who, in their view are just a type of client of their services and tech products) as a commercially sensitive information. In many cases, this also concerns the information of worker profiles, pay levels and other aspects.
Such practices become even more problematic in the context of the ongoing debate on the labour market status of people working through online platforms. This especially concerns driving and delivery services organised though platforms, which have become virtually essential in the face of the pandemic. By conveniently not disclosing these numbers, many platforms may avoid legitimate questioning of their status as tech companies providing digital services to clients (as they like to position themselves), rather than employers in a subordination relationship with the workers.
Another key issue related to transfers of data is inter-platform portability of worker information. Currently, workers using digital platforms are unable to take their profile data, including the proof of skills and reputation data (i.e. ratings and feedback by clients) acquired using one platform, to any other platform or job market. This further creates lock-in effects on a specific platform by increasing worker switching costs. Clearly, the incumbent platforms may see this as a benefit from competition point of view. Besides that, data portability requires platform interoperability solutions. Introducing these functionalities, in turn, is costly, because it requires the development of common standards and revision of their back-end codes.
Given the economic rationality and absence of regulation, the protectiveness of platforms with regard to their data seems to be a natural response. New incentives, therefore, need to be introduced to change this current situation – whether by “sticks” (e.g., “hard” reporting obligations and mandated data portability) or “carrots” (e.g., endorsing and promoting the codes of conduct of “good” platforms). At the EU level, such policy discussions have already began. Hopefully, this cloak of secrecy will soon be lifted, opening new opportunities for exciting research into the topic.
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