DIGITAL SHIFT. Fix the chinks in sharing economy

The sharing economy is poised for change. Increasingly, the torchbearers of the peer economy are driving into discord, either with their partners or with the government. Last week matters reached a flashpoint in India between Ola and Uber and their drivers, who put the brakes on work, agitating over rates and incentives. Similar stories of drivers vs Uber conflict are pouring in from all over the world.

Meanwhile, regulators are waking up to address labour issues in a world where the workforce is outside the firm and managed by an algorithm. Their common concern: For all the talk of a sharing economy, there is not enough being ‘shared’ with the people who actually provide the service.

As unrest and litigation mounts, not just cab aggregators but all platform companies that use apps and data analytics to match customers with service providers will need to rethink their approach towards managing their pool of associates.

Over the last few years, a host of labour platforms have sprung up, such as Urban Clap, Housejoy, UrbanPro, that have spurred the growth of the gig economy.

In the current model, the platform owner has a nebulous relationship with the service provider, who is self-employed, and hence gets no guarantee of stability, health care or other benefits. But the provider is free to offer the same services to other rival platforms.

Things could change, however. Last October, an employment court in the UK ruled that Uber drivers should be considered as employees and be entitled to a national living wage. Of course, Uber went in for appeal.

As we move from managing labour within tightly controlled firms to dealing with loosely orchestrated ecosystems, community management will gain centrestage We already see this in the case of companies like Uber and Airbnb. But as more companies experiment with moving not just the technology but also their organisation onto the cloud, we will see structured processes getting into community management.

The origins of community management among Internet businesses can be traced to 10 to 12 years ago when social media led to the creation of digital communities. Initially, the community management function was an extension of the marketing function as the role was more about building a fraternity, and value-creation through these. But now, community management is rapidly becoming an extension of human resources management.

It’s already percolating into traditional organisations as well. Upwork, a platform for freelancers, for example, now allows any company to not just contract professionals but also run an entire organisation function on the cloud.

This is done by hiring managers on the cloud who manage these freelancers through the platform itself. As a result entire functions within organisations can be migrated from within the firm into the ecosystem.

As we go forward, and as digital technologies improve allowing platforms to move beyond just matching demand and supply to coordinating people, we will see this trend take greater hold among organisations. Already, specialised consultancies are coming up in this domain that help companies harness the power of communities digitally.

The basics of community management is incentivising people to perform based on how they are valued. Ecosystems in which service providers are treated as commodities and replaceable cogs will be much more difficult to manage. Uber is one such example. The taxi ride is very commoditised and this shows in the way the company treats its drivers.

In contrast, Airbnb treats its service providers as unique and differentiated individuals, relying on different forms of reputation for rewards. This is what allows the home-stay ecosystem to perform better, and also gives its service providers incentives to progress further.

A simple way of explaining this is by analysing the design of the rating system on these two platforms. In the case of Uber, the rating system is merely used to weed out the bad apples. In the case of Airbnb, the rating system is used to help the best hosts get more exposure on the platform. In one case, the rating system encourages career progression, while in the other it is merely a punishment mechanism.

It is important to understand that community management and governance are the sum of many different parts, and not just small initiatives to engage the ecosystem.

Most community management and governance mechanisms can be clubbed into three broad buckets: organisation driven, algorithm driven, and peer driven. Organisation-driven mechanisms involve a set of programs and initiatives by the company to manage the community, to reward the best, and weed out the worst.

Algorithm-driven mechanisms dig out data on the performance of ecosystem members; for example, the rating systems of Uber and Airbnb. Peer- driven mechanisms are more organic and arise from within the community. Traditionally, reactive peer-driven mechanisms take the form of unionising and striking work, such as in the case of Uber drivers.

But there are many positive peer-driven mechanisms as well where members share best practices with each other. Examples of this can be seen among design communities on platforms like Dribbble, artisan communities on platforms such as Etsy, and photography communities on platforms such as 500px.

Hence, to some extent, the kinds of community management mechanisms that can be used are dependent on the kinds of communities themselves.

One of the basic tenets of good ecosystem governance is that you should not bait and switch, the way Uber and Ola have done. When these platforms first launch in a city, they offer many incentives to drivers.

But as the platform scales, the payouts decrease. For the community of drivers, who buy new cars with hefty monthly EMIs on the assumption that favourable payouts will continue, the bait and switch policy comes as a rude shock. This is why we repeatedly see drivers unionising in protest.

Platform players need to lay out the costs and benefits to service providers upfront as well as outline the risks involved. If need be, an insurance mechanism to reduce risks could be worked out.

Aggregators also need to invest in training and skilling so that the service providers know how to best leverage the platform and reap more rewards.

Going forward, ensuring well-being of the community could also work towards the platform player’s advantage.

Paul Choudary is the author of Platform Scale and Platform Revolution and the founder of Platformation Labs. Narayanan is Editorial Consultant