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From the words “crowd” plus “outsourcing,” crowdsourcing is not new news (see PickyDomains or DoNanza). It has been around for a while, and given the many advantages (productivity, cost-effectiveness, timely results, etc.) it can bring, especially in this highly competitive technology-driven world, is here to stay.
Launched on November 20, 2012 at the Amazon AWS re:Invent conference, Alegion aims to provide large enterprises the ability to incorporate crowdsourced work into their complex business processes via its ground-breaking self-service crowdsourcing platform. According to Nathaniel Gates, Alegion’s co-founder and CEO, crowdsourcing hasn’t really taken off, no thanks to the fact that users stay away from crowdsourcing because of the perception that results are generally inaccurate and that there’s no surefire way to ensure the accuracy of such results.
Gates recognizes that the problem with crowdsourcing has nothing to do with the platform or the workers, but with the process. He also insists that when users – businesses or individuals – fail to generate the desired results from their crowdsourcing endeavors, it is because they are not asking the right questions or following proven best practices to guarantee accuracy.
Another reason enterprises aren’t taking advantage of the full gamut of benefits they can gain from crowdsourcing is the complicated nature of setting up a crowdsourcing infrastructure in-house, which normally takes up a lot of resources. With Alegion, continuous development and expensive business consultants are no longer needed as everything will now be made available. With Alegion, companies design their workflow processes to ensure work accuracy, including a scoring system that will allow them to build a workforce fit for certain tasks. Companies will also be able to see job-related data so they can perform their own analyses and find out what went well and what didn’t, and everything else they want to track.
What’s more remarkable about Alegion is job creators’ ability to interact with their workers, answer questions, provide rewards and bonuses, even categorize their workers into groups, like those who constantly provide outstanding work and those who might need some help.
Gates points out that if users treat crowdsourcing as a system – data in, data out – they are unlikely to find satisfaction with the results.
[Via - NicheGeek.Com]
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