Root cause analysis

In science and engineering, root cause analysis (RCA) is a method of problem solving used for identifying the root causes of faults or problems. It is widely used in IT operations, manufacturing, telecommunications, industrial process control, accident analysis (e.g., in aviation, rail transport, or nuclear plants), medicine (for medical diagnosis), healthcare industry (e.g., for epidemiology), etc. Root cause analysis is a form of inductive (first create a theory [root] based on empirical evidence [causes]) and deductive (test the theory [underlying causal mechanisms] with empirical data) inference. RCA can be decomposed into four steps: Identify and describe the problem clearly Establish a timeline from the normal situation until the problem occurs Distinguish between the root cause and other causal factors (e.g., using event correlation) Establish a causal graph between the root cause and the problem RCA generally serves as input to a remediation process whereby corrective actions are taken to prevent the problem from recurring. The name of this process varies from one application domain to another. According to ISO/IEC 31010, RCA may include the techniques Five whys, Failure mode and effects analysis (FMEA), Fault tree analysis, Ishikawa diagram, and Pareto analysis. There are essentially two ways of repairing faults and solving problems in science and engineering. Reactive management consists of reacting quickly after the problem occurs, by treating the symptoms. This type of management is implemented by reactive systems, self-adaptive systems, self-organized systems, and complex adaptive systems. The goal here is to react quickly and alleviate the effects of the problem as soon as possible. Proactive management, conversely, consists of preventing problems from occurring. Many techniques can be used for this purpose, ranging from good practices in design to analyzing in detail problems that have already occurred and taking actions to make sure they never recur. Speed is not as important here as the accuracy and precision of the diagnosis.