Root Cause Analysis is an effective method for discovering the true source of a problem.
There are a number of different techniques for conducting a root cause analysis, each with its own strengths and weaknesses. In this post, we’ll review some of the most common root cause analysis tools to help you pick the right one for your needs.
What are Root Cause Analysis Tools?
Simply put, Root Cause Analysis tools are methods used in quality management and continuous improvement to identify and solve a given problem. While you can certainly take an ad hoc approach to problem solving, each of these tools help add structure and intention to your efforts. Some are visualization tools, helping you see root causes by presenting information in a new format. Others make sure you’re moving beyond causal factors to the true root cause. All of them help you dig beneath the surface and see your operations in a new light.
Types of Root Cause Analysis Tools
Here are five common Root Cause Analysis tools used by most manufacturing firms.
Pareto Charts are based on the Pareto Principle, which states that “80% of the effects come from 20% of the causes.” In practice, a Pareto chart is a bar chart combined with a line graph to illustrate a frequency distribution in relation to relative significance.
Pareto Charts make it possible to see the most common forms of error at a glance. By displaying the most common sources of defect in descending order, Pareto charts can help teams prioritize improvements for maximum impact.
Multiple analytics reports on a Tulip Dashboard, including a Pareto Chart (bottom left corner)
The 5 Whys
5 Whys is an investigative method used to drill down on a particular problem. It’s easy: you just ask “Why?” repeatedly until a core problem is identified. This Root Cause Analysis tool is best used when investigating rudimentary problems without the need for quantitative analytical methods. The 5 Whys can be used in conjunction with a Pareto Analysis, where the chart reveals an area that needs more attention.
This is a tool widely used to analyze complex problems. Also known as a Cause-and-Effect Diagram, groups potential causes of a particular problem into subcategories linking back to the main problem being investigated. Fishbone Diagrams are used when the root cause is entirely unknown.
Scatter Diagrams also known as Scatter Plots, are visual representations of a relationship between two sets of data. It is a simple quantitative method of testing correlation between variables.
To use this root cause analysis tool, you plot the independent variable (or suspected cause) on the x-axis while your dependent variable (the effect) is plotted on the y-axis. If the pattern shows a clear line or curve, you know the variables are correlated. If needed, you can continue to more sophisticated regression or correlation analyses.
Failure Mode and Effect Analysis (FMEA)
FMEA highlights failures within a particular system. You can use this tool at any particular phase — planning, designing, implementation, or inspection — and consists of two main components: Failure Mode and Effect Analysis.
Failure Mode involves identifying different ways, types (or modes) in which something can fail. While Effect Analysis consists of analyzing the effects and consequences of each of the failure modes. The two go hand in hand.
Root cause analysis tools can simplify the hard work of continuous improvement. Each of the tools outlined here are simple to learn and quick to apply.