The red bead experiment is deceptively simple because it provides a powerful message that is difficult for many to grasp. In summary, the misconception that workers can be meaningfully ranked is based on two faulty assumptions. The first assumption is that each worker can control his or her performance. Deming (1986, 315) estimated that 94 percent of the variation in any system is attributable to the system, not to the people working in the system. The second assumption is that any system variation will be equally distributed across workers. Deming (1986, 353) taught that there is no basis for this assumption in real life experiences. The source of the confusion comes from statistical (probability) theory where random numbers are used to obtain samples from a known population. When random numbers are used in an experiment, there is only one source of variation, so the randomness tends to be equally distributed. This is because samples based on random numbers are not influenced by such things as the characteristics of the inputs and tools (e.g., size of the beads and depressions in the paddles) and other real world phenomena. However, in real life experiences, there are many identifiable causes of variation, as well as a great many others that are unknown. The interaction of these forces will produce unbelievably large differences between people (Deming 1986, 110) and there is no logical basis for assuming that these differences will be equally distributed.2
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I always liked Deming's Red Bead experiment.. http://maaw.info/DemingsRedbeads.htm
The red bead experiment is deceptively simple because it provides a powerful message that is difficult for many to grasp. In summary, the misconception that workers can be meaningfully ranked is based on two faulty assumptions. The first assumption is that each worker can control his or her performance. Deming (1986, 315) estimated that 94 percent of the variation in any system is attributable to the system, not to the people working in the system. The second assumption is that any system variation will be equally distributed across workers. Deming (1986, 353) taught that there is no basis for this assumption in real life experiences. The source of the confusion comes from statistical (probability) theory where random numbers are used to obtain samples from a known population. When random numbers are used in an experiment, there is only one source of variation, so the randomness tends to be equally distributed. This is because samples based on random numbers are not influenced by such things as the characteristics of the inputs and tools (e.g., size of the beads and depressions in the paddles) and other real world phenomena. However, in real life experiences, there are many identifiable causes of variation, as well as a great many others that are unknown. The interaction of these forces will produce unbelievably large differences between people (Deming 1986, 110) and there is no logical basis for assuming that these differences will be equally distributed.2