Gig Economy – future of workforce
The Gig Economy started as little (gig) works requiring very limited skills, like delivering food in the neighbourhood requiring very little resources (a bike would do) or fixing a rusty bannister … The person offering the services was doing that on his own schedule, would do that today but not tomorrow. No obligations beyond that specific task/time limited commitment.
Compare this with the (mutual) contractual obligations between an employer and an employee and you immediately perceive the difference. The contractual obligation ensures the employer to be able to deliver a service as needed by making sure of the availability of the needed resources (the employees) and provides the employee with a continuous wage.
Technology can bridge these two approaches creating platforms that decrease the cost for offer to meet demand and provide access to a pool of resources that, statistically, would ensure continuity of service: all people with the skill of fixing a rusting bannister can declare their availability at any given time and all people needing someone to fix that rusty bannister can get in touch with someone willing to take up that job. These platforms are the engines of the Gig Economy and each one is a company of its own.
Platforms decrease transaction cost, they make the whole process of delivering a service more efficient. This is not as good as it might seem at a first glance! A company creating a platform slash the cost of doing business, hence many more people will be able to offer their service using the platform: offer increases and, as in any competitive system, the price of the service is going to decrease, favouring the end customer. At the same time the alternative for someone wanting to offer their services outside of the platform is basically not existent, because of the efficiency provided by the platform (i.e. it will cost much more for the offer to meet demand). This creates an asymmetrical situation between the company owning/operating the platform and the people using it to offer their services. The company holds all the cards and can end up exploiting the ones that are actually delivering the service. We have seen the protest of riders claiming (with good reasons in general) to be exploited, underpaid, forced to work even if they are sick,… This is the result of the asymmetry and of the efficiency provided by the platform that in presence of an offer that exceeds demand leads to a compression of values (wages). The issue has become a sensitive one and organisations like Fairwork have identified a set of principles to evaluate these platforms (companies) using parameters like:
- fair pay: decent pay, based on the service provided that should be paid on time and cover all work completed;
- fair condition: appropriate work conditions should be enforced, decreasing occupational risks (the high competition often enforced by platforms push workers to cut corners and take risks);
- fair contracts: although there may not be a specific labour contract, the access to the platform and the way the work process is managed (distribution of demand, monitoring of activity, …) should be transparent;
- fair management: decisions affecting workers (like way of ranking and assessing quality) should be transparent;
- fair representation: although the relationship is between a gig worker and a platform, workers should have the right to self-organise and to appeal to decisions taken by the “platform/company”.
Working conditions have indeed worsened in several cases, as should be expected when the offer is high and the competition drives for more and more efficiency at the expense of the “offer”, i.e. the gig workers. It is the result of the basic economic rule that in every competitive systems the price of a product/service tends to the marginal cost and in this case the marginal cost is approaching zero (it cost nothing, but time and fatigue, to ride a bike to deliver a pizza). This is why some sort of regulation is sorely needed.
The problem is not felt in those situations where demand is high and offer is low. In this cases the gig workers are the ones having the upper hand, like in consultancy areas. Consider how much a company has to pay for a consultant service provided by a consulting firm. Quite a lot and the more skilled the consultant required (there are very few of them) the more the consulting firm is charging. By leveraging on a platform a consultant can access the demand directly and because the bridge takes place in the cyberspace a consultant will experience an increased demand, hence can charge more! This is not the case in delivering pizza, since this service is constrained by the location (a gig worker in LA cannot benefit from a demand in San Diego…) thus having a limited demand, and potentially a big number of “riders”
Notice that because of the efficiency introduced by the platform, both the consultant and the company using the consultancy are winning: a consultant that would make 200,000$ a year as an employee of a consulting firm gets payed, roughly 100$ per hour. As freelance consultant he can make at least 3 times as much, per hour. If you look at this from the company seeking the consulting service, it means that their cost is slashed. Rather than paying the consulting firm some 1,500$ for a spot consulting they will pay the consultant 300$, one fifth (these numbers are based on my real experience, in providing consultancy as freelance over a number of platforms. Figures change quite a bit depending on the type of consultancy but the concept is clear). So both the freelance consultant and the company using the service are gaining. Who is losing? The old style consulting companies that are seeing their way of doing business superseded by the shift to the Gig Economy. Indeed, most consulting companies have started to offer consultancy platform-based, as a new business proposition, keeping the “old” way for those consultancies that involve a long term effort.
There is now, and so it will be in this decade, a broad spectrum of working types in the gig economy as shown in the figure.
There are/will be platforms that manage demand and, based on a policy and resources availability, connect demand to offer, i.e. send the demand to one of the available resources (a freelance worker). The worker has no visibility on the demand landscape, just respond to a request. This is the case of the Amazon Mechanical Turk, a platform that manages, in principle, any type of offer connecting it to any type of demand (a work marketplace). It really looks like the Amazon marketplace where companies offering their product have no control over the demand. They are just told that someone is asking for their product and they will deliver. A similar situation is the one of the Uber platform where the offer of the service (transportation) is allocated by the platform to a specific demand (based on platform’s criteria, including the shortest time to pick up as well as the rating of the drivers in the area). In this second case, like in the previous one, the connection between offer and demand is still decided by the platform but it is fully integrated, whilst in the former case of the Mechanical Turk each connection is self-standing (no need for coordinating the offer).
Other platforms support the negotiation of the work by those who are controlling the offer. Hence, these platforms aggregate the demand side and let the offer side have the visibility on the demand allowing them to establish the connection and negotiate the deal. An example of “separate” offer is the one provided by Upwork, where the offer side can “show” their wares (skills and services that can be provided) and the demand side can enter in contact with the offer to start a negotiation. Other platforms are supporting negotiations but do that in an integrated way, like Twago. In this case the demand (the customer) explain the needs and the platform works out a possible offer that will then be negotiated by the customer directly with the freelancers involved.
As shown, there is a significant evolution ongoing in the Gig Economy and this is expected to characterise the work landscape in this decade (and the following ones). It is obvious the dramatic effect on work processes, on the workforce and on the work environment that this evolution implies.
It is also important to notice that the expansion of the Gig Economy is enabling the access to the offer of services by a multitude of people that before had no way to offer their skills. This is true both for the ones that using the cyberspace can offer their skills to the world market (a software developer in India can sell her skill to companies all around the world based on spot-demand) and for people offering their skills to a local area, like Go-Jek, that with a team of 200 engineers has set up and operates a platform managing 100 million order per month and coordinating over 2 million drives (in Indonesia). The amazing thing is that it basically created from scratch 2,000,000 + jobs in 10 years (the company was founded in 2009). By slashing transition cost these platforms enable a very effective connection of offer and demand increasing the marketplace, a crucial aspect in emerging economies.
At the same time the evolution of the Gig Economy towards high skill markets transforms single individuals in their own entrepreneurs. This is a very important evolution that is going to change, in a dramatic way, the work landscape in developed countries and that respond to the before mentioned evolution in distributed knowledge and human cloud. In a way we could say that the present evolution of the Gig Economy is a response (enabled by technology) to the increasing knowledge distribution, rapid obsolescence and human specialisation requiring access to a dynamically evolving human cloud.