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Root cause analysis (RCA) is a class of problem solving methods aimed at identifying the root causes of problems or events.[1] The practice of RCA is predicated on the belief that problems are best solved by attempting to correct or eliminate root causes, as opposed to merely addressing the immediately obvious symptoms. By directing corrective measures at root causes, it is hoped that the likelihood of problem recurrence will be minimized. However, it is recognized that complete prevention of recurrence by a single intervention is not always possible. Thus, RCA is often considered to be an iterative process, and is frequently viewed as a tool of continuous improvement.

Root cause analysis is not a single, sharply-defined methodology; there are many different tools, processes, and philosophies of RCA in existence. However, most of these can be classed into five, very-broadly defined "schools" that are named here by their basic fields of origin: safety-based, production-based, process-based, failure-based, and systems-based.

Despite the seeming disparity in purpose and definition among the various schools of root cause analysis, there are some general principles that could be considered as universal. Similarly, it is possible to define a general process for performing RCA.

General principles of root cause analysis[]

  1. Aiming corrective measures at root causes is more effective than merely treating the symptoms of a problem.
  2. To be effective, RCA must be performed systematically, and conclusions must be backed up by evidence.
  3. There is usually more than one root cause for any given problem.

General process for performing root cause analysis[]

  1. Define the problem.
  2. Gather data/evidence.
  3. Identify issues that contributed to the problem.
  4. Find root causes.
  5. Develop solution recommendations.
  6. Implement the solutions.

Root Cause Analysis Tools[]

  1. 5 Whys
  2. Barrier Analysis
  3. Change Analysis
  4. Causal Factor Tree Analysis
  5. Failure mode and effects analysis
  6. Fish-Bone Diagram or Ishikawa diagram
  7. Pareto Analysis
  8. Fault Tree Analysis


  1. Wilson, Bill, Root Cause Analysis,, 2005.
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