Tuesday’s “Future of Crowdsourcing Summit”, orchestrated as a single event with simultaneous productions in San Francisco and Sydney linked by video and social media, was well executed and received positively as speakers, panelists and a highly engaged audience discussed the adoption, opportunities and consequences of crowdsourcing.

John Winsor, CEO of Victors & Spoils, opened with a keynote presentation on the transformational nature of crowdsourcing as a business model that will have a far-reaching effect on the global economy. The disruptive nature of crowdsourcing is evidenced by the fact that old tenets are being challenged: the best ideas can often come from outside your company; your customers are willing to help each other; and customer loyalty is more about an individual’s meaningful relationship with your brand.

Does crowdsourcing, however, have the potential to be truly transformational at a macroeconomic level?

Crowdsourcing is clearly challenging the way that things have been done in the past, but will lots of little changes at an Enterprise or small to medium business (SMB) level add up to fundamental transformation for the global economy? Live from Sydney, Matt Barrie, CEO of Freelancer.com, with an air of certainty, argued that the train has already left the station! I would argue that a different paradigm shift is occurring.

Crowdsourcing platforms, offering access to abundant affordable labor, are grabbing latent demand from SMB’s (to quote Matt, SMB’s equate to 95% of Freelancer.com’s business). They are not taking market share from the current $350b annual spend directed to existing providers of outsourcing services to large Enterprises. This is because the vast majority of this spend is allocated to complex SG&A processes and functions that on-demand labor pools don’t and may never be able to address.

Currently, the nature of the tasks that can be outsourced through crowdsourcing platforms is very simplistic and very narrow in scope. Companies such as CloudCrowd are only now working out how basic workflows can be defined and broken down into separate tasks which can be completed by different workers with results then being re-compiled. For example, they have defined a basic workflow for a straightforward translation task and decomposed it as seven independent steps that can be performed by different individual workers.

Alex Edelstein, CEO, explained to me that that the reason CloudCrowd can undercut the price traditional translation services by 50% or more is not due to the labor arbitrage play but due to the efficiency within the workflow by having the right skilled people working on the task elements that they are best qualified to work on in a manner that is highly efficient.  This also means they can compete the work in hours and not days.

Another interesting challenge facing labor-on-demand models is that the outsourcing industry has moved away from resource-based models that are based on inputs and moved to pricing models and metrics that are based on outputs.

I have spent many years watching the outsourcing and offshoring industry morph from when it was considered to be a groundbreaking new business model in the early 90’s. It was disruptive in terms of changing cost structures because for approximately ten years outsourcing and offshoring were mostly adopted as a staff augmentation models and a labor arbitrage play.

These models had characteristics that were associated with buying capacity. They were input based models – defined, monitored and managed in terms of what went into the arrangements. Pricing units included, for example, the number of full-time employees (FTE’s) at a given rate. Performance metrics or service level agreements (SLA’s) were volume based – for example, the service desk handling a given number of calls per hour. It took many years for the industry to learn that performance was not optimized by defining what went into an outsourcing or offshore contract but rather by what resulted from one. The industry now looks to define these arrangements from an “output” perspective – improved levels of user satisfaction because it takes less time to resolve a user’s problem – higher quality code written in less time – application availability being greater, etc. 

If the crowdsourcing labor models are going to scale beyond the SMB market and challenge performance based contracting models they will need to be super cheap, super fast and super high quality.

I do think that most of the growth from labor-on-demand models is a result of two things. Firstly, the labor arbitrage play is now available to smaller companies where scale and term of commitment (which drives utilization for firms that employ their own labor pools) are not factors that in crowdsourcing platforms determine rates which are more greatly influenced by the demographics and supply. Secondly, the labor pools are more accessible and cool web tools that manage the work distribution act as digital intermediaries that enable us to connect very easily with the new, globally distributed, talent pool. This means that this new pool of affordable and qualified talent is within the reach of SMB’s. This is both fueling the growth of these new crowdsourcing labor pools as much as it is helping the micro economy.

In my next post I will explore whether other applications of crowdsourcing, beyond labor arbitrage models, have the potential to be truly transformational?