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MIT Sloan research shows a learning curve for consistency

CAMBRIDGE, Mass., Aug. 6, 2020 /PRNewswire/ --A Learning curves show that experience improves average productivity. But is there a learning curve for consistency? With experience, does task performance become more consistent? Or is there still a wide variability in completion times, even if the times improve on average? In the first study to address the variance learning curve, MIT Sloan School of ManagementProf. JA?nas Oddur JA?nasson and his colleague Hessam Bavafa of the University of Wisconsin-Madison found that experience significantly improves consistency. Further, they showed that the benefits of learning curves in service systems are "substantially underestimated" when consistency effects are ignored.
MIT Sloan research shows a learning curve for consistency
"It's important to understand the impact of learning curves on consistency because the time it takes to complete a task is a signal of competency across most jobs. It also has practical implications for operational decisions such as staffing and scheduling," says JA?nasson. He points to surgeries as an example. "The more often a surgeon performs a routine procedure, the faster the average completion time. But does each procedure take one hour to complete, or do the procedures take anywhere from 15 minutes to two hours to complete? What is the spread around the average time? This is critical information not only for the patient, but also for the scheduling of operating rooms."A  In their study, the researchers collaborated with the London Ambulance Service to examine whether performance becomes more consistent due to a consistency learning curve. They looked at a decade of data to examine how experience affected the mean and variance of paramedic performance as they pick up patients and bring them to hospitals.
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