Discussion Question:
Imagine you were asked to improve the design of the experiment that produced a dataset that showed significant improvement in predictability of the work performed over 10 iterations, comparing the predictability improvement over the first four iterations with the predictability improvement over the last six. After each iteration, a continuous improvement process was used to focus the participants on sources of variation and how they might be removed from the work.
It has been argued that a continuous-improvement method and the improved results from it could just be extraneous due to a possibly greater factor that was actually responsible for increasing the correlation over the last six iterations of the method. Maybe all one needed to do was practice and the skill improvement that comes with practice is the root of the increase in the correlation. Could it be that the work required during iterations 1 through 4 was inherently more unpredictable than the work in iterations 5 through 10?
How would you go about designing an experiment to reduce, if not eliminate these issues?
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