A root cause is an initiating cause of a causal chain which leads to an outcome or effect of interest. Commonly, root cause is used to describe the depth in the causal chain where an intervention could reasonably be implemented to change performance and prevent an undesirable outcome.
The term root cause has been used in professional journals as early as 1905, but the lack of a widely accepted definition after all this time indicates that there are significantly different interpretations of exactly what constitutes a root cause.
The two biggest differences in viewpoint regard the possibility of an outcome having more than one root cause.
Effects have causes. The causes may be natural or man-made, active or passive, initiating or permitting, obvious or hidden. Those causes that lead immediately to the effect are often called direct or proximate causes (see proximate causation). The direct causes often result from another set of causes, which could be called intermediate causes, and these may be the result of still other causes. When a chain of cause and effect is followed from a known end-state, back to an origin or starting point, root causes are found. The process used to find root causes is called root cause analysis.
The usual purpose of attempting to find root causes is to solve a problem that has actually occurred, or to prevent a less serious problem from escalating to an unacceptable level (see Near miss (safety), for example). The basic concept is that solving a problem by addressing root causes is ultimately more effective than merely addressing symptoms or direct causes. Consider the following example, where root cause a leads to effect e, with a few intervening steps.
Assume each of these factors is as described below:
The effect, e, could be prevented by addressing any of the other factors. For example, attaching jumper cables from another car (addressing factor d) will probably allow the problem-car to be started. However, this solution is not likely to provide long-lasting relief from the undesired effect, as factor c will ensure that the car shuts down again in a very short period of time. Addressing factor c by repairing the alternator may solve the problem for a longer period, but factor b will eventually result in another age-related breakdown in the alternator. The alternator could be replaced with a new unit, addressing factor b, thus allowing the car to be driven for an extended period of time. However, factor a will eventually ensure that the car breaks down again for some other reason. Many peope stop the root-cause analysis here, arguing that the solution to the problem (and many other potential problems) is to maintain the car properly, which addresses factor a, the root cause.
One difficulty with root cause analysis is knowing when to stop. The above analysis stops with the following of procedures. The alternator was not maintained properly, so blame the people who were responsible for the maintenance: call that the root cause, find the people responsible and instruct them to do the required maintenance in the future. Experts in human-machine interaction would argue that this is an inappropriate stopping point. Failure to follow the maintenance procedure is still an intermediate cause of the problem. The root cause analysis should go even more deeply: Why wasn't the maintenance done? Would could be changed to ensure either that the maintenance was done when required or, better yet, that maintenance would not be required (or perhaps, required less frequently).
An issue closely related to solving an existing problem is to foster learning that will embed knowledge (within a person, group, or organization) that may help prevent similar problems from occurring in the future. Such knowledge is often referred to as lessons-learned. Gaining such knowledge, retaining it, and using it effectively is one of the goals of a learning organization engaged in continuous improvement.
Practitioners of root cause analysis often define what the phrase "root cause" means for a particular setting and application. The benefits of finding deeper layers of root cause tend to diminish after a certain point. The practical application of root cause analysis therefore often searches only as long as the benefit of answers outweighs the effort of the search.
e: car will not start
d: battery is dead
c: alternator does not function
b: alternator is well beyond its designed service life
a: car is not being maintained according to recommended service schedule