Root Cause Analysis Tools and Models (2022 Edition)






Root Cause Analysis (RCA) is a method of looking at a problem and eliminating it from the source, rather than simply treating the symptoms It’s a part of a more general problem-solving process and an integral part of continuous improvement.

ACR helps companies to prevent recurring problems and improve their products.

 • Emphasize the correction or elimination of root causes rather than symptoms.

• In many cases, symptoms need to be treated to obtain short-term relief.

• Multiple root causes may occur.

• Focus on WHY and HOW this issue happened, not WHO.

• Give detailed data to guide corrective actions.

• Plan how to prevent similar issues in the future.






There are tonnes of tools available to effectively perform root cause analysis. In this paper, we cited the 11 best tools and techniques used in industries ranging from manufacturing and information technology to telecommunications and health services.


We also listed a few RSA models that analysts can use to create a good problem statement, collect relevant data, effectively detect root causes and implement durable solutions. We'll begin with root cause analysis tools.




Pareto Analysis





Pareto Analysis is a decision-making technique for assessing a set of problems and measuring the impact of correcting them.

The Pareto Principle (also known as the 80–20 rule) is named after an Italian economist, Vilfredo Pareto. It indicates that for many results, approximately 80% of the consequences originate from 20% of the causes.

While ahead of its time, this principle was later found to apply in almost every field.

• 80% of all software bugs can be found in 20% of program modules

• 80% of defective parts are supplied by 20% of suppliers.

• 80% of the company’s revenue is generated by 20% of its products

• 80% of work in a business is performed by 20% of its employees.

The Pareto Analysis identifies the tasks or problem areas that will have the biggest payoff. Once the defective elements are addressed, the majority of cause for concern will be eliminated.

Pareto analysis is helpful when multiple causes are contributing to a single effect (a problem). It is used in various departments and different sectors of a business and organization.

The analysis involves assigning each problem a specific numerical score based on the level of impact on the business. The higher the score, the greater its impact. Companies can allocate resources to issues with higher scores to solve problems more efficiently.   (More information)


Fishbone Diagram



A Fishbone diagram can help in brainstorming to detect potential causes of a problem. It may also help you categorize your ideas into helpful categories. It’s a more structured method compared to other techniques available for brainstorming causes of a problem.

Fishbone diagrams were first created by Kaoru Ishikawa in the 1960s. They were used as a basic tool for quality control at the University of Tokyo. Today, they are widely used as a visual way to look at cause and effect. Common uses include product design and quality defect prevention.

In a pattern, the effect or problem is displayed in the mouth of the fish. Potential causes are added on the smaller “bones” under different cause categories. More specifically, each cause for defect is a source of variation. Causes are clustered into main categories to detect and classify these sources of variation.

This type of diagram can help you identify causes that might not otherwise be considered by looking at the categories and thinking of alternative causes. However, to achieve fruitful results, you must involve members who have detailed knowledge of the systems and processes involved in the event to be investigated.



  Limitations

While the diagram shows all causes simultaneously, it may become visually cumbersome when analyzing complex defects. In most cases, interrelationships between causes aren't easily identifiable.  (More information)

Fault Tree Analysis


Fault Tree Analysis is a graphical tool for identifying potential causes of system-level failures. It uses the concept of Boolean logic that creates a series of True/False instructions. When these statements are connected via a chain, they form a logic diagram of failure.

Events are arranged in sequences of parallel relationships (“OR”) or series relationships (“AND”). The outcomes of each event are displayed in an acyclic graph using logical symbols that show the dependencies between events.

This top-down approach can be used to analyze a specific accident in detail, highlight the logical relationship between faulty modules, and mitigate the risk before.
  (More information)


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