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Root Cause Analysis

Root cause analysis (RCA) is the process of discovering the root causes of problems in order to identify appropriate solutions. RCA assumes that it is much more effective to systematically prevent and solve for underlying issues rather than just treating ad hoc symptoms and putting out fires.

How to Perform a Root Cause Analysis in 5 Steps

The Five Whys Technique:

The method is remarkably simple: when a problem occurs, you drill down to its root cause by asking "Why?" five times. Then, when a counter-measure becomes apparent, you follow it through to prevent the issue from recurring.

  1. Why did the cake burn?
  2. It burned because the temperature was too high. Why was the temperature too high?
  3. The temperature was too high because there was a misprint in the recipe calling for a very high temperature. Why was there a misprint in the recipe?
  4. There was a misprint in the recipe because it was handwritten first as 450 degrees, then a 3 was written on top of the 4 hoping to make it look like 350 but the 4 stood out. Why did the 4 stand out?
  5. The 4 stood out because it was larger than the 3 and written with darker ink.
Difference between correlation and causality

A correlation between variables does not automatically mean that the change in one variable is the cause of the change in the values of the other variable. Causation indicates that one event is the result of the occurrence of the other event; i.e. there is a causal relationship between the two events.

"Correlation is not causation" means that just because two things correlate does not necessarily mean that one causes the other. As a seasonal example, just because people tend to spend more in shops when it's cold and less when it's hot doesn't mean cold weather causes frenzied spending.

To establish causality you need to show three things–that X came before Y, that the observed relationship between X and Y didn't happen by chance alone, and that there is nothing else that accounts for the X -> Y relationship.

When we investigate we must look for what is actually causal. More mistakes are made in this area than anywhere else, mistaking correlation for causality..

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