Human-based electronic services (people services) provide a powerful way of outsourcing tasks to a large crowd of remote workers over the Internet. Because of the limited control over the workforce in a potentially globally distributed environment, efficient quality management mechanisms are a prerequisite for successful implementation of the people service concept in a business context. Research has shown that multiple redundant results delivered by different workers can be aggregated in order to achieve a reliable result. However, existing implementations of this approach are highly inefficient as they multiply the effort for task execution and are not able to guarantee a certain quality level. Our weighted majority vote (WMV) approach addresses this issue by dynamically adjusting the level of redundancy depending on the historical error rates of the involved workers and the level of agreement among them. A practical evaluation in an OCR scenario demonstrates that the approach is capable of gaining reliable results at significantly lower costs compared to existing procedures.