In a recent blog post, “Assessing Variability for Quality Improvement,” I showed how measuring variability is as important as measuring the mean for a product or service in a quality improvement initiative. The mean, by itself, often tells an incomplete story. Additionally, quality management veterans know that controlling the variability is often more difficult than controlling the mean. If you want to change the mean, it often entails adjusting a manufacturing setting or target. However, reducing variability often requires new technology or procedures.

For example, in the image below, it’s generally easier to re-center the tightly clustered measurements on a target than it is to reduce the spread of the dots that are centered.

 …