Pareto Analysis
According to Vilfredo Pareto, an Italian economist from the 19th century, most wealth resides in the hands of a small number of people. Pareto's work rests on the principle that 80% of consequences arise from 20% of causes. It is also known as the 80/20 rule and the "Law of the Vital Few." While teaching at the University of Lausanne Switzerland, Pareto wrote about the 80/20 connection. Pareto showed in his work, Cours d'économie politique, that 20% of the population owned 80% of the land in Italy.
Dr. Joseph Juran
A quality expert named Joseph Juran coined "Vital Few and Trivial Many" after continuing Pareto's work on the 80/20 rule. Since it is universal, the idea can be applied to almost any situation. The majority of early deaths are caused by just a few diseases, according to mortality tables. According to sales analysis, a company's top 10% of customers account for more than half of its revenue. When studying late deliveries, a quality improvement team might discover that 85% of the delays are caused by 6% of its vendors. The benefit of having this information is obvious. When using Pareto analysis, quality efforts can be prioritized, focusing on those areas that can yield the most significant gains.
Pareto Analysis
Statistical decision-making techniques such as Pareto analysis are used to identify tasks that significantly affect a quality problem. Thus, the vital few factors can be identified and focused on. A Pareto diagram shows the vital few and the useful many by separating them visually. Determining probable causes and implementing corrective actions help organizations make critical decisions. Pareto charts also show the cumulative impact of sources from largest to smallest.
Pareto Chart
A Pareto chart visually represents the frequency or cost of different situations in descending order of length (see Figure 1). Using it, you can identify the most significant conditions by showing which factors contribute to most problems. Bars are arranged from highest to lowest frequency counts, and a line graph may also be included to show cumulative impact. Using a Pareto chart can help identify areas for improvement and prioritize actions.
Figure 1 - Deployment Frequency Over a 50 Day Period
Pareto Analysis Example
In this simple example, a team was formed to improve the quality of software delivery flow based on deployment frequency. The team looked at the DORA metric of Deployment Frequency of 10 weeks grouped by day (see Figure 2 - Pareto Table.) The table contains three columns. The first column is the day of the week. The second column shows that day's total number of deployments over the past ten weeks. The third column gives the cumulative percent of the incremental deployments. Typically the key to Pareto analysis is the cumulative percent column.
Figure 2 - Pareto Table
Then the quality team used a Pareto Chart to visualize the data (see Figure 3.)
Figure 3 - Pareto Chart
Although this is a simple example, the chart visualizes some key points. Most of the deployments occur on Fridays. The least amount of deployments happens on Monday, Tuesday, and Wednesday. With further analysis, the quality team found that although the development teams practiced DevOps and Agile principles, they were still in a waterfall regarding deployments. The majority of deployments happened on Fridays at the end of each sprint. In light of this new knowledge, development teams at this organization were encouraged not to deliver software at the end of each sprint.
