Second, gathering data and evidence, and classifying them along a timeline of events to the final problem, can be nontrivial. In telecommunications, for instance, distributed monitoring systems typically manage between a million and a billion events per day. Finding a few relevant events in such a mass of irrelevant events is asking to find the proverbial needle in a haystack. Third, there may be more than one root cause for a given problem, and this multiplicity can make the causal graph very difficult to establish. Fourth, causal graphs often have many levels, and root-cause analysis terminates at a level that is "root" to the eyes of the investigator. Looking again at the example above in industrial process control, a deeper investigation could reveal that the maintenance procedures at the plant included periodic inspection of the lubrication subsystem every two years, while the current lubrication subsystem vendor's product specified a 6-month period. Switching vendors may have been due to management's desire to save money, and a failure to consult with engineering staff on the implication of the change on maintenance procedures. Thus, while the "root cause" shown above may have prevented the quoted recurrence, it would not have prevented other perhaps more severe failures affecting other machines. See also Notes References External links "Root Cause Analysis and Monitoring Tools: A Perfect Match" by Irene Carrasco "Cause Mapping a visual explanation" "Sologic Root Cause Analysis Method" "Fundamentals of Root Cause Analysis" Quality control tools Problem solving