Everything You Need to Know About Pareto Charts
What Is a Pareto Chart?
In an increasingly data-driven world, getting savvy with analytics has become the best way to tackle HR problems. There are many ways to represent and analyze data collected to gain insight into company progress and identify factors that are hindering it. A simple yet effective way is to use a Pareto chart.
A Pareto chart is a diagram that combines a bar chart and a line graph to display frequency data. It is an analysis tool used to help assess quality control problems and identify areas needing improvement to reduce these problems. Pareto charts are widely used to analyze various scenarios.
The basic use of the chart derives from the Pareto principle, which states that roughly 80% of consequences result from 20% of causes. This is also known as the 80/20 rule, the principle of factor sparsity or the law of the vital few – where the vital few refers to the 20% of causes. Both the principle and the chart are named after famed Italian economist Vilfredo Pareto.
When to Use a Pareto chart
In line with the Pareto principle, the Pareto chart is used to:
Analyze frequency data to investigate the relationship between problems and causes in a process
Identify the highest frequency of problems and what the biggest causes are of these problems
Delve deeper and break down causes into specific components
Present your data for further discussion amongst your team, colleagues, or senior leadership.
Thus, a Pareto chart is the first step in solving many HR problems by identifying the main causes.
Pareto Chart Procedure
The steps to construct a Pareto chart are the following:
Determine if your nominal data can be grouped into categories that will be of interest to investigate.
Decide an appropriate measurement for the frequency of these categories, such as cost, time, or quantity.
Decide the period of time the Pareto chart will cover. This can be a day, a week, a month, a year, etc.
Collate the data you need or use data already at hand sort the data appropriately into these categories.
Tally up subtotals for each category frequency. If there are many categories with small frequencies, you can group them together as one category and label it “other.”
Determine a suitable scale by looking at the subtotal frequency range, with emphasis on the maximum and minimum frequency values. This is used for proportionality and labeling of a scale placed vertically on the left-hand side of the Pareto chart. This scale will measure frequency.
Divide the horizontal axis into segments of equal widths. The number of segments you need will be the same as the number of categories you have arranged your data into in step 4.
Place another appropriately proportioned scale on the right-hand side of the chart. It should correspond to the frequency scale and represent s percentage, from 0 to 100. The total frequency on the frequency scale should line up with the 100% mark on the percentage scale. This will ensure all other percentage points line up as well.
Label each segment of the horizontal axis with category names in descending order of frequency (highest frequency to lowest frequency), and draw bars to represent the frequency for each category. The heights of these bars should correspond to the frequency scale from step 6.
Calculate the percentage each category contributes to the total frequency by dividing each subtotal frequency by the total frequency.
Plot these frequency percentages for each category using the percentage scale, placing each point at the midpoint of the bar width for the corresponding category. The final percentage point for the last category is always 100%, as this is a cumulative frequency line graph.
Pareto Chart Examples
In this example, Pareto charts are used to analyze customer complaints data for the second quarter of 2005.
In Figure 1, the Pareto diagram shows customer complaint frequency data being split into five categories, each category being the reason for the complaint. It is easy to see that documents and product quality are the biggest causes of customer complaints as they have the highest frequencies. This is represented by these categories having the tallest bars.
We can then deduce that improving product quality and issues with documents would drastically reduce customer complaints. We can tackle document-related complaints with further Pareto analysis by breaking them down into subcategories and creating another Pareto chart for them. This is shown in Figure 2.
In Figure 2, we now know specifically which documents are causing the most complaints. A decision-maker can then implement solutions to target missing and erroneous Quality certificates.
It is also worth noting that the steeper the line graph is, the more these corresponding categories contribute to total customer complaints. Similarly, relatively horizontal line segments between percentage points would indicate a minimal contribution from the corresponding categories. From Figure 2, we can see that addressing Quality certificate problems will reduce document-related customer complaints by roughly 75%, meaning overall customer complaints can be reduced by a total of 30 complaints (75% of 40 document-related complaints).
As you can see, powerful graphical tools like the Pareto chart can help pinpoint problem areas that need improvement. Many daily business problems can be simplified and solved by analyzing data effectively. Thanks to technological advances, Pareto charts and other useful analytical tools can be created easily using HR software platforms like Lanteria.
Lanteria can save you time and effort by removing the need for manual chart construction, where accurate data visualizations can be generated instantly with a click of a button. Contact us today and arrange a free demo!