
Donald Wheeler has over forty years of experience in the study, practice and collaboration in data analysis. In “Twenty Things You Need to Know”, he shares this experience in the form of questions and answers.
What are two mistakes in data analysis? Mistake one: “Interpreting the routine variation of noise as if it amounted to a signal of change in the underlying process, thereby sounding a false alarm” [1]. Mistake two: Thinking that a signal of change in the underlying process is merely the noise of routine variation and thereby missing a signal”[1].
“You need a technique that will:
- Allow you to learn from your process data
- Warn you when your process changes
- Help you to identify the causes of those changes; and
- Enable you to operate your process predictably and on target”[2]
Wheeler explains: think of a measurable product characteristic; list all the possible cause-and-effect relationships that have an impact upon the measured value of your characteristic; arrange these causes in descending order of impact.[p10] Shewhart called dominant uncontrolled causes Assignable Causes, and Deming called lesser uncontrolled causes Common Causes.[3]
Assignable Causes will be the source of most of the unexplained variation in the product, such as excess production costs and low quality.[4]
The Upper and Lower Natural Process Limits of the characteristic can be calculated from the measured characteristic’s average. “Whenever a point goes outside the Natural Process Limits, it identifies an…Assignable Cause of variation”[5]. Identifying these points on a Process Behaviour Chart provides a methodology for when to look for Assignable Causes. [6]

The above Process Behaviour Chart shows UK inflation as the UK came out of COVID as time series data, with an average running through it, an Upper Natural Process Limit above it and a Lower Natural Process Limit below it. Inflation goes above the Upper Natural Process Limit, and so has an Assignable Cause.
In Twenty Things You Need to Know, we learn about why process behaviour charts are created in the way they are, and that Wheeler tested process behaviour charts on 1143 probability models [7].
A friend of mine used the techniques in the book to understand the difference in the quality of output of two development teams by analysing the number of unit tests each team created each week. One team developed software with only a few bugs and created a similar number of unit tests each week. Its datapoints stayed within the Natural Process Limits. The second team’s software often contained bugs, and they created different numbers of unit tests each week. Their data points frequently went outside the Natural Process Limits. The process behaviour charts showed that the second team was not always creating unit tests as it developed code, which was an Assignable Cause of the bugs in their code.
Twenty Things You Need to Know is a companion book to Understanding Variation The Key to Managing Chaos.
I read this book with the Profound Book Club and would like to thank them for the insights I gained while reading it.
You can also use process behaviour charts to understand quality data by analysing your process data. Reading Understanding Variation The Key to Managing Chaos, and its companion book Twenty Things You Need to Know will help you do so.
References
[1] Twenty Things You Need to Know by Donald J. Wheeler (2009, p2)
[2] Twenty Things You Need to Know by Donald J. Wheeler (2009, p17)
[3] Twenty Things You Need to Know by Donald J. Wheeler (2009, p14)
[4] Twenty Things You Need to Know by Donald J. Wheeler (2009, p15)
[5] Twenty Things You Need to Know by Donald J. Wheeler (2009, p20)
[6] Twenty Things You Need to Know by Donald J. Wheeler (2009, p21)
[7] Twenty Things You Need to Know by Donald J. Wheeler (2009, p36)
Additional Resources:
Donald J. Wheeler’s Wikipedia page
Articles by Donald J. Wheeler SPC Press
Donald J. Wheeler QualityDigest
Control Charts Resources, including a spreadsheet template, from the American Association for Quality (process behaviour charts are also known as control charts)
A History of the Chart for Individual Values The ultimate in homogeneous subgroups by Donald J. Wheeler
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