The limitations of root cause analysis

Root cause analysis can only go so far, and it’s a lot harder than some make it out to be. Consider first all the ways to get to the root cause of a problem: you have the Ishikawa Diagram, Toyota’s “Five Whys” technique, and a host of other ways to determine what the common factor is in an issue. Next, consider how rigid a root cause has to be in order to be determined. Blog post author Lydia Bourne points out that project teams don’t have a single root cause: it often takes several different elements working together to cause a failure, not simply one. Complex failures, Bourne explains, are harder to determine and prove through root cause: This is a far more difficult undertaking that recognises complex systems have emergent behaviours, not resultant ones. There are several systemic accident models available including Hollnagel’s FRAM, Leveson’s STAMP that can help build a practical approach for learning lessons effectively. In the meantime, the next time you read or hear a report with a singular root cause, alarms should go off, particularly if the root cause is “human error”. If there is only a single root cause, someone has not dug deep enough! But beware; the desire for a simple wrong answer is deeply rooted. The tendency to look for singular root causes comes from the tenets of reductionism that are the basis of Newton physics, scientific management and project management. So consider this the next time you’re attempting root cause analysis: are you actually determining the series of events that lead to the error, or are you hand picking a single path that could work as the reason for the problem? There is a fundamental difference between the two.

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