Pareto charts are a useful tool for prioritizing your efforts. If you can't fix everything, what should you fix first? They are most commonly used to prioritize root causes, but they can also be used to prioritize problems. This concept was developed in the 19th century by an Italian economist Wilfredo Pareto. From this idea, came the 80/20 rule, you may have heard of that. This idea has been widely adopted and modified. Pareto studied wealth distribution in 19th century, Italy and found that 80% of the land was owned by 20% of the people. In business, we often apply this and say that 20% of your customer's account for 80% of your business, or 80% of your profit may come from 20% of your products. This concept was adapted for quality by Joseph Juran. He said that 80% of defects come from 20% of the causes. Juran recognized that most problems have many root causes. He said that a Pareto chart will help us to separate the vital few from the trivial many. Here is an example from a student survey on the cafeteria. The bars indicate the frequency or count of poor ratings for each category. The corresponding scale for the bar is on the left. The line indicates the cumulative percent from left to right. The corresponding scale for the cumulative percent line is on the right. The Pareto chart is always arranged by frequency, with the most frequent on the left. To create the chart, first collect the data. In this case, it's student dissatisfaction with various aspects of the cafeteria. When you have collected the counts, sort the data from largest to smallest. The largest bar is always on the left. You can tell at a glance that service efficiency is the biggest problem contributing to student dissatisfaction with the cafeteria. Using the 80/20 rule, the first two or three bars usually account for about 80% of the problem. If you can fix those root causes, you can make a significant improvement. Discrete data is a set of numbers where only certain values are possible. On a survey, you may be asked to write something one through five. There are no other possible values besides the whole numbers between one and five. You cannot rate it a three and a half. Continuous data is a set of numbers with all of the values in between. This might include one through five and all possible values between one and two, between two and three, etc. For discrete data, we just need to count the number of occurrences for each condition. Continuous data can be converted to discrete data by creating groups the same way we did for a histogram. Then we count the values that fall in each group. This is an example of a Pareto diagram of workplace injuries in a manufacturing facility. Data shown in the table in the upper-right was collected by type of injury. Hand injuries are easily the most common type of injury in manufacturing, followed by foot injuries. So if we wanted to reduce the number of injuries, we would probably focus on those. But what if the cost of injuries was the important thing? If we collect data on the cost of injuries by type, as shown in this table, we get a very different picture. The most costly injuries tend to be back injuries because of lost time. The point here is to think carefully about what you want to know and what you want to accomplish. Pareto diagrams are a useful tool for getting a visual picture of what your priorities might need to be. Pareto diagrams use discrete data, that is counts or frequencies. The data is arranged from the most frequent to the least frequent, so that the tallest bar is always on the left and the scales for the bars is on the left side of the chart. The line represents a cumulative percent and its scale is on the right side of the chart. Visually, it's easy to see where our efforts need to go for maximum effect.