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Delivering Quality Management in Cloud Workforces


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March 02, 2012

Delivering Quality Management in Cloud Workforces

By Chris Freeburn, TMCnet Web Editor

When most people speak of cloud-based services, they refer to data storage or other technical services. But researchers at the Karlsruhe Institute of Technology (KIT) in Karlsruhe, Germany, have developed a quality monitoring solution for a different kind of cloud, one composed of outsourced workers -- a “people cloud,” as they term it.

In a people cloud, businesses can access workers distributed across different locations to perform needed work. Workers in a people cloud perform tasks that cannot be automated and can only be carried out by human operators. This includes creating documentation for products, technical writing, foreign language translation, video and image classification and indexing. Large assignments can be distributed among groups of workers communicating across the internet. Each worker performs a “microjob” and several “microjob” workers can work in parallel on a single project. KIT notes that this is often described as paid crowd sourcing. Web portals and the publishing industry have been deploying such workers for years in the form of freelancers. However, recently a number of web-based firms have begun creating organized pools of workers and making them available as outsourced workforces.

As with data storage or technical service clouds, people clouds are scalable to a business’s specific needs. Workers communicate and receive instructions and materials via the Internet. As with other cloud services, the flexibility and personnel cost savings of people clouds make them attractive to businesses. However, as information is disseminated across the internet and work is returned through multiple channels, it maintaining the quality of work produced, in many cases, far outside the business, becomes a significant challenge.

“Before the individual results of the microjobs executed are compiled again, it must be ensured that they comply with the quality standards required. This is a big challenge, as the contributions of the individual crowd workers in a crowd sourcing scenario can be controlled to a limited extent only,” says Robert Kern, a researcher at KIT in a release. “This is where our quality management system starts to work. Its approach: We combine the contributions of several crowd workers by means of statistical methods and derive the quality of the work rendered from the degree of the contributions’ agreement and, thus, ensure the required quality of the overall result.”

KIT says that is quality monitoring solution has been adopted by various companies that employ “people clouds” including crowd sourcing supplier

Edited by Rich Steeves

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