The template typically consists of two axes:
The resulting graph is a Pareto chart, which typically resembles a “staircase” with a few dominant factors at the top and many smaller ones at the bottom. The most important factors are those that fall along the diagonal line, indicating high frequency and high impact.
Here's how to use a Pareto Analysis Template:
Example:
Suppose you're analyzing a manufacturing process and want to identify the main causes of defects. You collect data on various factors such as machine malfunctions, operator errors, material defects, and inspection errors. After plotting the data on a Pareto chart, you find that:
In this case, you would focus your improvement efforts on addressing machine malfunctions first, as they have the greatest impact on defect rates.
By using a Pareto Analysis Template, you can efficiently identify the most critical factors affecting your process or product and allocate resources effectively to drive meaningful improvements.
Category | Frequency | Cumulative Frequency |
---|---|---|
[Category 1] | [Value] | [Cumulative Value] |
[Category 2] | [Value] | [Cumulative Value] |
[Category 3] | [Value] | [Cumulative Value] |
[Category 4] | [Value] | [Cumulative Value] |
[Category 5] | [Value] | [Cumulative Value] |
[Category 6] | [Value] | [Cumulative Value] |
Category | Frequency | Cumulative Frequency | Cumulative Percentage |
---|---|---|---|
[Category 1] | [Value] | [Cumulative Value] | [Cumulative %] |
[Category 2] | [Value] | [Cumulative Value] | [Cumulative %] |
[Category 3] | [Value] | [Cumulative Value] | [Cumulative %] |
[Category 4] | [Value] | [Cumulative Value] | [Cumulative %] |
[Category 5] | [Value] | [Cumulative Value] | [Cumulative %] |
[Category 6] | [Value] | [Cumulative Value] | [Cumulative %] |