The PARETO procedure creates Pareto charts, which display the relative frequency of quality-related problems in a process or operation. The frequencies are represented by bars that are ordered in decreasing magnitude. Thus, a Pareto chart can be used to decide which subset of problems should be solved first or which problem areas deserve the most attention.
Pareto charts provide a tool for visualizing the Pareto principle,[46] which states that a small subset of problems tend to occur much more frequently than the remaining problems. In Japanese industry, the Pareto chart is one of the “seven basic QC tools” heavily used by workers and engineers. Ishikawa (1976) discusses how to construct and interpret a Pareto diagram. Examples of Pareto diagrams are also given by Kume (1985) and Wadsworth, Stephens, and Godfrey (1986).
You can use the PARETO procedure to
construct Pareto charts from unsorted raw data (for instance, a set of quality problems that have not been classified into categories) or from a set of distinct categories and corresponding frequencies
construct Pareto charts based on the percentage of occurrence of each problem, the frequency (number of occurrences), or a weighted frequency (such as frequency weighted by the cost of each problem)
add a curve indicating the cumulative percentage across categories
construct side-by-side Pareto charts or stacked Pareto charts
construct comparative Pareto charts that enable you to compare the Pareto frequencies across levels of one or two classification variables. For example, you can compare the frequencies of problems encountered with three different machines for five consecutive days.
highlight the “vital few” and the “useful many”[47] categories by using different colors for bars corresponding to the n most frequently occurring categories or the m least frequently occurring categories.
create charts as traditional graphics, ODS Graphics output, or legacy line printer charts
create charts with bars oriented vertically or horizontally
highlight special categories by using different colors for specific bars
annotate traditional graphics charts
inset summary statistics in graphical output
save traditional graphics output in a graphics catalog for subsequent replay
display sample sizes on Pareto charts
display frequencies above the bars
save information associated with the categories (such as the frequencies) in an output data set
restrict the number of categories displayed to the n most frequently occurring categories
create variations on traditional Pareto charts, as described by Wilkinson (2006)
[46] Both the chart and the principle are named after Vilfredo Pareto (1848-1923), an Italian economist and sociologist. His first work, Cours d’Économie Politique (1895-1897), applied what is now termed the Pareto distribution to the study of income size.