Introduction
While perhaps not described as such, ‘crowdsourcing’ has been around in various forms since the earliest stages of the World Wide Web.
Sites such as eBay and Wikipedia succeeded in large part because they harnessed ‘the power of the crowd’ and in both cases scalability was achieved because they established ‘self-policing communities’.
In one case it was through a feedback system that encouraged buyers and sellers to act responsibly in their dealings with other members. In the other it was through constant peer review, combined with the ability for community members to edit records where they saw a need for improvement.
Outsourcing vs Crowdsourcing
While they may appear similar, outsourcing and crowdsourcing are fundamentally different in both concept and application.
Outsourcing did not represent a paradigm shift in the way work was performed or organisations configured.
The general model for outsourcing was for a company in a high cost country to transfer a function to a comparatively low-cost location. However the organisational model was the same. (A call centre in Bangalore is run along very similar lines to a call centre in Boston).
While today a very large industry, outsourcing never scaled in the way that eBay and Wikipedia have, and the main reason is that outsourcing is not self-policing.
In order to manage risk the clients doing the outsourcing required companies such as Cap Gemini and Infosys to manage the staff or function being outsourced. As a result you had simply replicated the same organisational model in a lower cost country.
A Paradigm Shift
A couple of years ago I tried using the crowdsourcing community www.elance.com to have some work undertaken.
While it was clear that there were significant cost savings on offer, I found the process frustrating because of the lack of transparency as to the quality of the available contractors.
There just wasn’t a critical mass of demand and supply, and this impacted on the risk profile of the exercise.
(If you had tried to sell a high-value item such as a car or a boat on eBay 10 years ago you would have found the same issues with respect to liquidity and transparency).
A few months ago I repeated the exercise and noticed two fundamental changes had occurred:
• The volume of proposals (and the speed of response) had increased dramatically
• More importantly, this critical mass of supply and demand had generated transparency as to quality, since I could now see how much a particular contractor had earned in recent months, who they have been working for, and just as importantly what those clients had to say about them.
Just as eBay members are concerned about their feedback score, contractors on networks such as elance have become very concerned about their reputation.
This means that the risk profile of the transaction has changed:
• On the demand side operational risk has gone down (because of transparency)
• On the supply side reputational risk has gone up (again due to transparency, as well as the volume of available work)
This change in the risk profile of crowdsourcing has the potential to trigger a paradigm shift in the way many tasks are performed, and in so doing change the way many organisations are configured.
Unlike outsourcing, crowdsourcing has become a global, self-policing community to which increasingly complex tasks can be assigned with confidence, and at a fraction of the cost of traditional business models.
The Old Infrastructure of Work
The traditional infrastructure of work included not just an education, but physical infrastructure such as office space, mass transit facilities, sophisticated telecommunications networks and an industrial relations system to support employment relations at scale. However this model of work has come at a very high cost. In developed markets knowledge workers tend to be housed in large, expensive office buildings in CBD or metropolitan locations, and their employment conditions come with significant ‘on-costs’ which must be included in any business model to which their services are attached.
The New Infrastructure of Work
In terms of capital efficiency crowdsourcing is a world away from the above model. Work is undertaken in remote locations where ‘on-costs’ have largely evaporated, almost all work is performed on a per hour or fixed-price basis, and the concept of commuting might involve a 5 minute walk to the local café, not a cramped 1 hour train ride into town.
Similar advantages in terms of capital efficiency can be found in telecommunications infrastructure. In developing country markets the traditional fixed-line Internet has been bypassed in preference to wireless access at much lower cost. As a consequence over the next few years literally hundreds of millions of individuals will find themselves able to connect a low-cost laptop to the Internet via a 4G personal wi-fi hotspot run through their mobile phone, and in doing so expose themselves to a growing pool of ‘work’.
Labour Arbitrage at Scale
Per unit labour costs are significantly lower in the crowd.
While the absence of infrastructure costs contributes a proportion of this differential, it is largely due to the fact that ‘the crowd’ is a seamless, global marketplace for labour, and the very nature of crowdsourcing means that there is transparency to a ‘new global marginal cost’. Under these circumstances it is difficult to envisage any scenario other than migration of demand for those services that can be replicated in the crowd.
Redefining the Concept of an Organisation
It seems that we have two key trends intersecting:
• Changes in technology leading to a step-change in the global supply of labour
• At the same time networks are being established that provide a frictionless mechanism to link this supply with prospective demand.
Just as the network of computers called the Internet unleashed a period of ‘creative destruction’ in the late ‘90s, there is every chance that the ‘human cloud’ will unleash a similar period of change.
If that is the case the very concept of organisations will need to be revisited, from traditional, hierarchical entities with rigid structure, to fluid groups of individuals whose interests are loosely coupled but tightly aligned around the delivery of solutions to which some value has been attributed.
Threats and Opportunities in the Crowd
Just as cloud computing has changed the face of the hosting industry, it is not hard to find threats to incumbency in the crowd. The potential impact can be measured against two criteria:
• Geography
• Function
The geographic impact is likely to run along developed / developing country lines, with central business districts in locations such as the US and Europe more vulnerable because of their inherently higher cost structures.
In terms of function, the impact will depend on the nature of the work. Just as outsourcing was better suited to certain functions (call centres, payroll administration, helpdesk, etc) some tasks/functions lend themselves more readily to crowdsourcing than others, but generally speaking it will be knowledge workers who are most vulnerable (to the extent that their cost structure exceeds the new marginal cost).
The growth of crowdscourcing networks can be broken down into two types of platforms:
• Generic
• Vertical market focused
elance is a typical example of the generic model, with some 500,000 freelancers and US$150m worth of projects distributed in 2011. Others include odesk and freelancer.
Networks such as liveops represent an existential threat to the business model of incumbents in the IT helpdesk and call centre outsourcing space.
http://www.ft.com/intl/cms/s/2/1e12826e-270c-11e1-b9ec-00144feabdc0.html#axzz1ge3WapJz
Consulting firms (whose capital structure reflects all of the infrastructure costs described above) are also vulnerable, particularly where networks evolve to serve specific vertical markets on which they are focused. Kaggle recently raised US$11 million from a who’s who of US VCs, and has started to transform the data mining space.
Similar examples can be found in the graphic design space : 99designs, Design Crowd
But opportunities also exist for incumbents to leverage the power of the crowd to establish themselves as specialist clearing houses. Using such intermedia ries may become a common model for those clients who do not wish to develop the internal capabilities required to manage a distributed workforce.
